newsletter09-4

The first commercial software to allow Multi-ObjectiveOptimization applied to any engineering design area

SHOW US YOUR GREEN SIDEInternational modeFRONTIER Users’ Meeting 2010 goes green... ‘cause optimize means saving: time, resources, energy. And you? Are you ready to go green?27th - 28th May 2010 - Savoia Excelsior Palace - Trieste - Italy

To stay competitive and gain market share, companies are forced to continuosly improve the quality of the products. While this has been a longtime-held belief for most managers, only in recent years has it become clear that achieving higher quality is not necessarily at odds with efforts to reduce cost and time-to-market.

By attending the conference you will get a chance to learn how modeFRONTIER, the leading

multidisciplinary & multi-objective design optimization tool, is used globally by designers and managers in many industries to better understand their product development process, and achieve higher quality at reduced cost, allowing them to meet the challenge of producing better products faster.

2010 Come and attend, we are waiting for you!

online conference registration

http://um10.esteco.com

modeFRONTIER® is a registered product of ESTECO Srl. International modeFRONTIER Users’ Meeting is an initiative of ESTECO Srl

Newsletter EnginSoft Year 6 n°4 - 3

EnginSoft FlashSometimes challenging times in business

can leverage, cultivate and grow our

creativity and innovativeness. They

remind us on how important networking

really is to develop and realize new ideas

and visions and to get inspiration from

other people and their views.

In early 2010, we can see a new

understanding and new beginnings in

many areas. It is the engineering

profession that has always created jobs

and projects, engineers bring things

forward, they bridge many gaps and

realize technological advancements.

In the past year, EnginSoft has started several new

initiatives and strengthened existing ties between our

customers, partners, the academia, research and industry.

To us, networking has never been more important. During

my recent visit to Silicon Valley and the US, I have had

the opportunity to meet with representatives of BAIA, the

Business Association Italy America. BAIA is a political

business network that facilitates the open exchange of

knowledge and business opportunities. BAIA promotes a

culture of innovation by fostering entrepreneurial spirit

and principles, in the US and in Italy.

This edition of the Newsletter includes a review of my

encounters with BAIA, the University of California at

Berkeley, University of Stanford, and the University of

Santa Clara in October 2009.

Our readers also hear about SimNumerica, the University

Spin-Off EnginSoft has co-founded to support the

development of Digital Mechatronics by using Co-

Simulation. SimNumerica’s joint expertise is focused on

environments for the virtual prototyping of mechatronics

systems based on micro-controllers

We present the modeFRONTIER 4.1.2 highlights and the

successful application of the technology at Indesit

Company that recently has received the 2009 Ecohitech

Award for its state-of-the-art appliances. Volvo Car

Corporation tells us about robust design

optimization of a bumper system with

modeFRONTIER. The statistical capabilities of

the software, this time, are applied to the

modeling of the spread of a disease like swine

flu using relatively simple equations.

For those who are looking for first insights into

the field of optimization, we recommend the

article by EnginSoft Germany on optimization

in today’s product development.

Further software news feature Magma 5 for

Process Simulation and Forge 2009.

Another highlight of this issue is the article on ANSYS

simulation of carbon fiber and anisotropic materials in the

ATLAS Experiment and the Large Hadron Collider at CERN.

We also present R&D News, current research projects, the

EnginSoft Event Calendar and latest advancements in HPC

High Performance Computing, as well as our Japan Column

which features CADdoctor for accelerating reverse

engineering and an interview with Mr Sakae Morita and Mr

Kentaro Fukuta of ELYSIUM Co., Ltd. Japan, both speak

about their time at our International Conference in

Bergamo this year.

Akiko Kondoh, EnginSoft’s Consultant in Japan welcomes

us to Shogatsu, the New Year, with Osechi-ryori and best

wishes from the land of the rising sun and Monodukuri.

We hope that you will enjoy reading the many

contributions of this edition and that some will inspire

you for 2010. As always, we welcome any feedback and

ideas for future publications.

EnginSoft and the editorial team of the Newsletter would

like to take this opportunity to wish you and your families

a very Happy and Prosperous New Year!

Stefano Odorizzi

Editor in chief

Ing. Stefano OdorizziEnginSoft CEO and President

4 - Newsletter EnginSoft Year 6 n°4

Sommario - Contents

6 modeFRONTIER: release 4.1.2 highlights

7 MAGMA 5: le nuove frontiere della Simulazione di processo

10 FORGE 2009 Release notes - dicembre 2009

14 Elysium’s CADdoctor accelerating Reverse Engineering

17 Parametric FEM model optimization for a pyrolitic Indesit oven

21 Robust Design Optimization of a Bumper System at Volvo Cars using modeFRONTIER

25 Optimization in product development - An efficient approach to integrate single CAE Technologies up to theentire design chain

29 ANSYS simulation of carbon fiber and anisotropic materials

32 Aeronautical engines: reduction of emissions and consumptions with a process simulation study

35 Healing the swine flu with modeFRONTIER

39 New trends in High Performance Computing

43 Development of Digital Mechatronic Applications using Co-Simulation

45 About SimNumerica and EnginSoft

46 Innovation and EnginSoft in the USA

48 BENIMPACT Building’s ENvironmental IMPACT evaluator & optimizer

50 Continuing Higher Education on CAE: The TCN Consortium

51 Analizzare cinematica e dinamica dei meccanismi con le tecniche multibody: terminologia, ambiti di applicazione ed opportunità

The EnginSoft Newsletter editions contain references to the followingproducts which are trademarks or registered trademarks of their respec-tive owners:ANSYS, ANSYS Workbench, AUTODYN, CFX, FLUENT and any and all

ANSYS, Inc. brand, product, service and feature names, logos and slogans are

registered trademarks or trademarks of ANSYS, Inc. or its subsidiaries in the

United States or other countries. [ICEM CFD is a trademark used by ANSYS,

Inc. under license]. (www.ANSYS.com)

modeFRONTIER is a trademark of ESTECO EnginSoft Tecnologie per

l’Ottimizzazione srl. (www.esteco.com)

Flowmaster is a registered trademark of The Flowmaster Group BV in the

USA and Korea. (www.flowmaster.com)

MAGMASOFT is a trademark of MAGMA GmbH. (www.magmasoft.com)

ESAComp is a trademark of Componeering Inc.

(www.componeering.com)

Forge and Coldform are trademarks of Transvalor S.A.

(www.transvalor.com)

AdvantEdge is a trademark of Third Wave Systems .

(www.thirdwavesys.com)

LS-DYNA is a trademark of Livermore Software Technology Corporation.

(www.lstc.com)

SCULPTOR is a trademark of Optimal Solutions Software, LLC

(www.optimalsolutions.us)

The Diffpack Product Line is developed and marketed by inuTech GmbH

(www.diffpack.com)

LINFLOW is entirely a development of ANKER – ZEMER Engineering AB in

Karlskoga, Sweden. (www.linflow.com)

The AnyBody Modeling System is developed by AnyBody Technology A/S

(www.anybodytech.com)

WAON is a trademark of Cybernet Systems Co.,Ltd Japan

(www.cybernet.co.jp)

CADdoctor is a trademark of Elysium Co., Ltd. Japan

(http://www.elysiuminc.com)

For more information, please contact the Editorial Team

SOFTWARE UPDATE

CASE STUDIES

IN DEPTH STUDIES

CORPORATE NEWS

RESEARCH AND TECHNOLOGY TRANSFER

TRAINING

Newsletter EnginSoftYear 6 n°4 - Winter 2009If you want to receive a free copy of the next Enginsoft

Newsletters, please contact our Marketing office at:

[email protected]

All pictures are protected by copyright. Any reproduction

of these pictures in any media and by any means is for-

bidden unless written authorization by Enginsoft.

©Copyright EnginSoft Newsletter.

AdvertisementIf you want to purchase advertising spaces within our

newsletter, please contact the Marketing office at: Luisa

Cunico - [email protected]

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Tel. +39 0461 915391 • Fax +39 0461 979201

www.consorziotcn.it

EnginSoft GmbH - Germany

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EnginSoft France - France

EnginSoft Nordic - Sweden

Aperio Tecnologia en Ingenieria - Spain

www.enginsoft.com

ASSOCIATION INTERESTSNAFEMS International

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TechNet Alliance

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RESPONSIBLE DIRECTOR

Stefano Odorizzi - [email protected]

ART DIRECTOR

Luisa Cunico - [email protected]

PRINTING

Grafiche Dal Piaz - Trento

The EnginSoft NEWSLETTER is a quarterly magazine published by EnginSoft SpA


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52 Interview with Mr Sakae Morita, General Manager,Marketing and Mr Kentaro Fukuta of ELYSIUM Co., Ltd.Japan

53 New Year Greetings from Japan

54 Il mondo della forgiatura a stampi aperti, della laminazione piana e circolare, si è dato appuntamento aPadova per fare il punto sulle tecniche più avanzate diottimizzazione di processo/prodotto.

56 Il mondo dello stampaggio a freddo di viterie e minuteriemetalliche, si è dato appuntamento a Bergamo per fare ilpunto sulle tecniche più avanzate di ottimizzazione di processo/prodotto.

57 Bilancio del Ciclo di Workshop dedicati alla Simulazionedei Processi di Deformazione dei Metalli

58 EnginSoft Event Calendar

59 EnginSoft 2010 CAE Webinars

59 Optimization Crossword Puzzle

JAPAN CAE COLUMN

EVENTS

PAGE 21 OPTIMIZATION

OF A BUMPER

SYSTEM AT VOLVO CARS

PAGE 17 PARAMETRIC

FEM MODEL OPTIMIZATION FOR

A PYROLITIC INDESIT OVEN

GAMES

PAGE 32 AERONAUTICAL

ENGINES: REDUCTION

OF EMISSIONS AND

CONSUMPTIONS WITH

A PROCESS SIMULATION

STUDY


modeFRONTIER:release 4.1.2 highlightsESTECO is proud to announce the release of v4.1 of themulti-objective optimization and design environmentsoftware, modeFRONTIER. This state of-the-art PIDO tool,written to allow easy coupling to almost any Computer-Aided-Engineering (CAE) tool, is now even more powerfuland user-friendly than previous versions.

DOE AlgorithmsNew features have been added to the list of availablealgorithms in the DOE Sequence:• Incremental Space Filler• Inscribed Composite Design• Uniform Reducer• Dataset Reducer

Schedulers and OptimizersNew features have been added to the list of algorithmsavailable in the Scheduler and Optimizers:• Polynomial Chaos• Evolution Strategy• Lipschitz Sampling• Mixed Integer Programming Sequential Quadratic

Programming

Response Surface AlgorithmsEvolutionary Design is now available, which implements asymbolic regression technique based on GP (GeneticProgramming). The algorithm searches for the analyticalexpressions that are able to approximate the training dataset. The users select the operators to be used among thebasic mathematical functions (+,-,*,/,cos(),sin(),tg(),exp(),etc.) and the program evaluates the analytical expression.

Data MiningNew functions have been added to the Tools and Chartsavailable in order to make life easier for users when exploringand assessing the data available in the Design Space tables:

Auto-Reportpublishing results is just a few clicks away, thus the users cancreate automatic/custom report according to their needs.

Principal Component Analysis and Multi-DimensionalScalingPrincipal Component Analysis, designed to extract thesignificant latent variables out of a multi-dimension set ofdata and Multi-Dimensional Scaling, a powerful tool forexploring and analyzing sets of data have been added to theMulti-Variate Analysis Tool.

Distribution FittingDistribution Fitting chart has been designed for fittingunivariate distributions to sets of existing data

Multi-VectorMulti-Vector chart lets the users display vector data in asingle plot

The WorkflowNew features have been added to the list of CAD/CAE Nodesavailable in the Workflow library

Design Target NodeIt is now possible to easily assign an external vector astarget function, by importing from an external text file orpasting the data values from the clipboard. This feature,coupled with the Levenberg-Marquardt algorithm is ideallysuited for most of the common curve-fitting design problems.

For further information:Ing. Francesco Franchini - [email protected]

Flowmaster™ V7

LMS Virtual.Lab™

ANSA™

Moldflow MPI™

GT-SUITE™

MSC Adams/View™


MAGMA 5: le nuove frontiere della simulazione di processoCon il mese di Novembre 2009 è iniziata la consegna dellaversione 5.0 di MAGMASOFT, denominata MAGMA5, che co-pre i principali aspetti dei processi di colata in SABBIA perleghe ferrose e non ferrose.

MAGMA5 è molto più di una semplice nuova release: è unambiente totalmente nuovo, basato sulle più recenti tecno-logie software, che rivoluzionerà l'utilizzo della simulazione.Con questo nuovo strumento diventa molto più semplicecreare e gestire i modelli, impostare la simulazione e visua-lizzare in maniera efficiente i risultati.

Il nuovo ambiente CAD per la modellazione solida si inter-faccia con gli altri CAD commerciali, offrendo la possibilitàdi importare ed esportare file geometrici di vari formati: al-l’interfaccia STL si potrà affiancare il formato STEP per unperiodo di prova di un anno senza costi aggiuntivi, mentrediventano disponibili come opzioni attivabili anche le inter-facce CATIA V5 (solo per le piattaforme Windows) e Pro/E.

La manipolazione e la visualizzazione dei modelli geo-metrici cambia radicalmente: l’utente può scegliere dilavorare con più quadranti attivi fino ad un massimo di9; i quattro classici quadranti del preprocessore diMAGMASOFT rimangono come una delle possibili solu-zioni predefinite, anche se l’utilizzatore troverà moltocomodo e intuitivo disegnare visualizzando il modelloin un’unica finestra, dove i comandi di rotazione, tra-slazione, zoom e clipping sono utilizzabili in modo di-namico e interattivo come nell’attuale post-processore(fig1).

L’albero delle geometrie, disponibile a sinistra dell’am-biente CAD, restituisce con immediatezza la visualizza-zione dei volumi creati o importati. Operazioni quali lamodifica delle grandezze geometriche o dell’ordine dei

volumi, la selezione, il copia e incolla di geometrie esisten-ti sono rese semplici e veloci attraverso l’utilizzo del solomouse.Il nuovo comando “copy with reference” di volumi creati al-l’interno di MAGMA5 lega le copie al volume originario, inmodo che ogni modifica effettuata su quest’ultimo sia auto-maticamente applicata a tutte.

Nuove funzioni CAD sono state implementate per offrire lapossibilità di modellare più velocemente e in modo flessibi-le modelli complessi: geometrie estruse con sezione termi-

nale di forma differente rispetto a quella iniziale sono facil-mente ottenibili con il nuovo comando skin (fig2).

Inoltre, tutti i solidi possono essere dotati di raggi di rac-cordo semplicemente prevedendoli nel momento in cui si di-segna la sezione. Per esempio, attraverso la finestra di con-trollo, è possibile impostare le grandezze caratteristiche diuna sezione trapezoidale: altezza, dimensione della base

Fig.1: Esempi delle diverse modalità di visualizzazione dell’ambiente CAD

Fig.2: Il comando skin permette di estrudere volumi con sezione finale di formadiversa da quella iniziale


(maggiore e/o minore) e angolo di sformo sono completatidall’opzione del raggio di raccordo (fig.3).

Operazioni booleane sono permesse tra modelli importati daCAD esterni e geometrie create all’interno di MAGMA5. Unesempio classico è costituito dalla generazione di anime diforma complessa con le relative portate (fig.4).Al termine della progettazione, il modello CAD deve esseretradotto attraverso l’utilizzo della mesh in modello matema-tico. Dalla qualità della mesh dipende l’accuratezza dei ri-sultati e il corrispondente tempo di calcolo. MAGMA5 offrela possibilità di caratterizzare i volumi neces-sari alla simulazione, attraverso la generazio-ne del modello discretizzato, in un numero dilivelli di affinazione scelto dall’utente(fig.5), con il vantaggio di non rinunciare al-la qualità (visualizzandola istantaneamenteal termine della generazione) e di minimizza-re i tempi di calcolo.

Sui domini riconosciuti dalla mesh vengonorisolte le equazioni relative alla fluidodinami-ca, alla termica e alle tensioni residue. I cor-rispettivi solutori di calcolo sono arricchiti diulteriori modelli computazionali, come peresempio un nuovo modello di turbolenza perla simulazione del riempimento della cavitàche considera l’effetto della tensione superfi-

ciale, mentre un nuovo modello di plasticità vie-ne implementato per un calcolo delle tensioni re-sidue più accurato, con la possibilità di include-re l’effetto del contatto del pezzo con le paretidella forma di sabbia o anima. A completamento della previsione della qualitàdel getto, è possibile simulare qualsiasi tratta-mento termico. Per esempio, considerando ilclassico trattamento T6, il modello di calcolo de-gli stress residui valuterà il rilassamento delletensioni dopo colata durante la fase di solubiliz-zazione, l’insorgere di nuove eventuali tensioniresidue durante la fase di tempra e il successivostato di tensione generato dalla fase di invec-chiamento. Dal momento che le operazioni mec-caniche (come per es. la smaterozzatura) mutanoulteriormente la distribuzione delle tensioni resi-due presenti a seguito della colata, MAGMA5 of-

fre la possibilità di includerle nell’analisi di stress. La cono-scenza delle tensioni residue permette al progettista di va-lutare più accuratamente la resistenza in esercizio di uncomponente e qualora fosse di interesse, attraverso l’utiliz-zo di MAGMAlink, di utilizzare la loro distribuzione comestato iniziale in una simulazione strutturale.L'impostazione del processo di simulazione può ora essereelaborato in finestre parallele agli ambiente CAD, mesh epostprocessore. Nella finestra principale coesistono, infatti,diversi menù a tendina nei quali è possibile entrare con unsemplice “clic” per poter creare la geometria (fig.6a), visua-

Fig.3: Esempio di impostazione di un raggio di raccordo

Fig.4: Generazione di anime attraverso l’utilizzo di operazioni booleane

Fig.5: Pannello di generazione della mesh


lizzare la mesh, definire i parametri di processo (fig.6b) eanalizzare i risultati (fig.7.). Il veloce passaggio da una fi-nestra all’altra comporta un notevole miglioramento neitempi di impostazione della simulazione.L’analisi dei risultati viene agevolata dalla visualizzazione dipiù finestre contemporaneamente, in ognuna delle quali èpossibile analizzare un risultato diverso e usufruire dei clas-sici comandi di rotazione dinamica, traslazione, sezione eanimazione (fig.7).L’innovativo comando “picking” permette di rilevare il valo-re puntuale di qualsiasi risultato con un semplice “clic” nel-la zona di interesse. Una finestra informativa restituisce lecoordinate del punto selezionato eil corrispondente valore. Inoltre èpossibile salvare in formato graficol’evoluzione dei valori dei risultatifluidodinamici e termici dei puntiselezionati per l’intero arco di tem-po simulato (fig.8).

I settaggi, predisposti dall’utente(viste, sezioni, scale e risultati), peril salvataggio delle immagini dei ri-sultati vengono memorizzati nel fileMAGMASOFT.pdb che consente di ri-chiamare le stesse impostazioni an-che per le versioni successive, age-volando l’analisi di confronto di di-

verse simulazioni e di salvare leimmagini in background.La nuova modalità di visualizza-zione e i nuovi criteri (microporo-sità e proprietà meccaniche) delmodulo opzionale Non-ferrouspermettono metodi di verificadelle prestazioni del getto più ef-ficienti e immediati.Tale modulo restituisce, per le le-ghe di alluminio, la previsionedella microstruttura e delle pro-prietà meccaniche allo stato “as

cast”, calcolate sulla base della composizione chimica dellalega, della velocità di raffreddamento del sistema e dei trat-tamenti della lega eseguiti prima della colata (es degasag-gio).I moduli MAGMAhpdc, MAGMAlpdc e MAGMAPermanentmold, oltre MAGMAlink e MAGMAdisa, sono in fase di com-pletamento e verranno rilasciati con la versione 5.1, mentreMAGMAfrontier con la successiva 5.2.Nel periodo di transizione, MAGMA4.4. e MAGMA5 potrannocoesistere sullo stesso hardware, a condizione che il siste-ma operativo sia supportato per entrambe le versioni. MAGMA5 è stato sviluppato in linguaggio JAVA per sfrutta-re al meglio le potenzialità di Windows 64 bit, mentre ri-mangono supportate le piattaforme LINUX RedHat5 e SU-SE11 a 64 bit.

Per prendere visione degli hardware suggeriti e delle piatta-forme supportate dal nuovo software visitate la pagina:http://www.enginsoft.it/software/magmasoft/news/magma5.html

Le date dei corsi di formazione sono come di consueto pub-blicate alla pagina:http://www.enginsoft.it/formazione/corsi2010/processo/proc14.html

Per maggiori informazioni:Ing. Nicola Gramegna - [email protected]

Fig.6: Pannello di gestione: a) ambiente CAD,b) visualizzatore della mesh,c) settaggio della simulazione.

Fig.7: Previsione della qualità del getto attraverso la visualizzazione didifferenti risultati contemporaneamente.

Fig.8: Visualizzazione di valori puntuali e della corrispondente curva temperatura-tempo


FORGE 2009Release notes - dicembre 2009Nel mese di dicembre 2009 è stato rilasciato da Transvalor ilnuovo pacchetto di simulazione Forge 2009®, lo strumentoideale per la simulazione dell’intero processo di stampaggioa caldo o a freddo dei più svariati componenti (alberi, giun-ti, ingranaggi, flange, raccordi, cuscinetti, bulloni, viti, fa-steners, …). È possibile simulare la sequenza completa di unprocesso di forgiatura multistadio con una cinematica deglistampi anche molto complessa (stampi flottanti o pre-carica-ti), seguita da raffreddamenti, tranciatura bave e/o tratta-menti termici.Forge 2009® è la logica evoluzione di Forge2008® ed è unsoftware di simulazione FEM dedicato alla simulazione di pro-cessi assialsimmetrici (2D) e di qualsivoglia geometria (3D),che è stato sviluppato seguendo le indicazioni degli utilizza-tori.

Forge 2009 – ottimizzazione dei processi di forgiaturaLa principale novità introdotta nella nuova release è la pos-sibilità di effettuare una procedura automatica di ottimizza-zione per un determinato progetto in una o più operazioni.Già nelle versioni precedenti era stato introdotto il concetto

di “chaining”, checonsentiva di impo-stare una intera se-quenza di stampaggioe concatenare le sin-gole operazioni in ununico calcolo, trasfe-rendo in automatico irisultati tra le stazio-ni. Oggi è possibiledefinire delle variabiliin ingresso sulla pri-ma operazione, comead esempio le dimen-sioni caratteristichedella billetta o altri

parametri quali per esempio la corsa della pressa, chiedendoal software di ricavare i migliori risultati per degli obiettividefiniti dall’utente, come per esempio il migliore riempimen-to delle impronte nell’ultima operazione o la ri-chiesta di un pezzo privo di ripieghe o ancora laminimizzazione del carico pressa. Il modulo di ot-timizzazione effettua una serie di “run”, valutan-done i risultati e modificando le variabili in in-gresso, in modo da ottenere i migliori risultatipossibili. Le varie configurazioni sono classificatein funzione della combinazione di obiettivi rag-giunti, consentendo di individuare le configura-zioni migliori.

Il progettista, che in precedenza testava con Forge solo unnumero limitato di ipotesi, può limitarsi ora a definire, me-diante una interfaccia user-friendly, le variabili, i vincoli delprocesso e gli obiettivi da raggiungere, lasciando a Forge ilcompito di esplorare un numero decisamente maggiore diconfigurazioni: le migliori possono essere magari ipotesi cheil progettista non avrebbe considerato. Grazie all’esperienzamaturata utilizzando questo strumento, Transvalor, l’azienda

che sviluppa il softwa-re, intende aggiungerealtre variabili ed obiet-tivi che possono essere

gestiti dall’utente nelle versioni successive.In caso fosse necessario utilizzare uno strumento più flessi-bile ed in grado di consentire un’analisi più accurata dei ri-sultati, è possibile interfacciare il software con il softwaremodeFRONTIER prodotto da ESTECO e distribuito daEnginSoft; è possibile in questo caso sfruttare i nodi direttiverso i principali CAD e modificare le geometrie di pezzo ostampi, importandole quindi in Forge, per lanciare poi il cal-colo ed utilizzare gli strumenti avanzati del programma perl’analisi degli obiettivi.

Il processo di laminazione circolare – ring rollingL’esperienza accumulata grazie ai diversi utilizzatori del soft-ware per il processo di ring-rolling ha consentito a Transvalordi introdurre una serie di migliorie al modello utilizzato, chehanno portato ad un deciso miglioramento della qualità deirisultati, con una riduzione dei tempi di calcolo nell’ordinedel 30% rispetto alla versione precedente. Tra le novità piùsignificative, la possibilità di inserire la curva di laminazioneche normalmente viene impostata dall’operatore del lamina-toio, ed ottenere in automatico le curve di movimento di co-ni e mandrino per Forge. Per il mandrino, la velocità può an-che essere modulata in funzione della crescita del diametroesterno dell’anello. Il nuovo modello consente ora anche dirilevare la velocità di rotazione del mandrino folle per effet-to del contatto con il pezzo.Molto lavoro è stato dedicato al miglioramento delle routinedi calcolo: i nuovi algoritmi PETSC consentono di risolvere

profili anche molto complessi in tempimolto inferiori ai precedenti, con unaprecisione di risultati decisamentemaggiore grazie all’introduzione di nuo-ve funzioni di contatto.

Il processo di fucinatura – nuovi strumenti disponibiliIl processo di forgiatura/fucinatura ècaratterizzato da un numero molto ele-

Interfaccia di ottimizzazione

Simulazione processo di Ring-rolling

Newsletter EnginSoft Year 6 n°4 - 11vato di passate, ognuna con diversi colpi ed una movimenta-zione del pezzo anche complessa con dei tempi di attesa traogni colpo/passata. Il modello precedente, presente inForge2008, è stato ulteriormente arricchito di funzioni, tra lequali i tempi morti tra due colpi consecutivi, nel quali vienecalcolato il raffreddamento del pezzo, l’arresto del calcolouna volta che il pezzo è uscito dagli stampi, una migliore ge-stione degli scorrimenti del pezzo rispetto agli stampi grazieall’uso di manipolatori. Dal punto di vista operativo, la mi-glioria principale è una modifica e semplificazione delle mo-dalità di definizione delle passate, attraverso un nuovo for-mato di file generato in automatico dal programma.Le lavorazioni di fucinatura hanno l’obiettivo di chiudere leporosità, che sono causate dal processo di colata del lingot-to e che hanno una notevole influenza sulla qualità del pez-zo finito. Transvalor ha dedicato molte energie per imple-mentare questo aspetto in Forge: è stata aggiunta la possi-bilità di definire sul lingotto una distribuzione iniziale di po-rosità e tra i risultati la possibilità di visualizzare la chiusu-ra di tali porosità. La distribuzione iniziale di porosità puòessere ottenuta anche mediante l’uso di un altro software diTransvalor, Thercast, dedicato alla simulazione del processodi colata e raffreddamento in lingottiera ed in grado di cal-colare la formazione di porosità con il criterio di Yamanaka.I risultati calcolati da Thercast possono essere trasferiti di-rettamente in Forge, per ottenere una distribuzione moltorealistica delle porosità nel lingotto iniziale.

Altro aspetto fondamentale in questo tipo di processi è l’evo-luzione del grano cristallino funzione della ricristallizzazione.Forge da questa versione è in grado di seguire l’evoluzionedel grano cristallino per effetto della ricristallizzazione stati-ca e dinamica, basandosi sulle definizioni dei materiali pro-venienti da prove sperimentali e dal software JmatPro: sonodisponibili i dati di alcune leghe molto particolari e criticheper questi aspetti, quali: acciaio AISI316L, Inconel 718,Waspalloy ed alcuni acciai al manganese.

Stampaggio lamiere - anisotropiaNel campo dello stampaggio ed imbutitura delle lamiere glieffetti legati all’anisotropia del materiale sono rilevanti.

Nella nuova versione di Forge è stato introdotto un nuovomodello di materiale nel quale è possibile specificare i para-metri di anisotropia secondo il modello di Hill. Il solutore èstato quindi adeguato per tener conto di questa nuova defi-nizione e nel post-processore sono stati aggiunti dei risulta-ti in grado di consentire una migliore comprensione di que-sti effetti

Contatto materiale-materiale e ripiegheGrazie alle esperienze provenienti dagli utilizzatori, soprat-tutto nel campo dello stampaggio dei materiali non ferrosi(ottone ed alluminio), si è evidenziata la necessità di ripen-sare il modo nel quale il software evidenzia la formazione el’evoluzione delle ripieghe. Sono state quindi messe a puntodelle nuove funzioni di contatto in grado di gestire in manie-ra più efficiente le situazioni, ove il materiale ripiega su sestesso. Contemporaneamente è stato sviluppato un nuovoapproccio per la visualizzazione dei difetti nel post-processo-re: quando due lembi di materiale vengono in contatto tra lo-ro, si genera un tracciante, il cui movimento nel resto dellacorsa di stampaggio consente di valutare con una notevoleprecisione forma e dimensioni delle ripieghe. Oltre alla loca-lizzazione delle ripieghe, che era già presente nella preceden-te versione, il progettista è in grado di comprendere se, ef-

fettivamente, il difetto inte-ressa il pezzo e per che spes-sore o se esce verso le bave equindi non è critico per la qua-lità del pezzo. Effetti indottidi questi miglioramenti al mo-tore di calcolo sono stati unariduzione dei tempi di calcolostimabile mediamente dal 20%al 30% a seconda del numerodi nodi utilizzato e del tipo dicalcolo impostati, migliora-

mento riscontrato sia sulle configurazioni singolo processore,che sulle più potenti piattaforme cluster.

Un nuovo “wizard” per lo stampaggio a freddo Nella versione 2008 è stato introdotto il concetto di “wi-zard”, uno strumento in grado di guidare passo-passo l’uten-te nella creazione della singola operazione, utile soprattuttoper i neofiti, che possono creare con pochi parametri un pro-getto pronto per essere risolto. Nella versione 2009 è statoaggiunto un wizard per lo stampaggio a freddo.

Molte le migliorie introdotte nel pre- e nel post-processingPer Transvalor le linee di sviluppo del software sono sempreguidate dai suggerimenti degli utenti. Nella nuova versionediverse sono le migliorie apportate, che riassumiamo di se-guito.

1. Pre-processore e template di processoDiverse migliorie minori molto utili sono state introdotte nel-le finestre di impostazione dei progetti. Nel pre-processore

Calcolo delle porosità in Thercast e trasferimento in Forge

Tracciatura delle ripieghe

l’attenzione si è concentrata, in particolar modo, sul miglio-ramento di alcuni template di processo, i modelli che servo-no da base per l’impostazione di tipologie particolari di cal-colo. Per quanto riguarda il modello delle presse ad energia, pres-sa a vite e maglio, è stato riformulato invece il modello ingrado di tener conto dell’efficienza della macchina al proce-dere dei numero di colpi ed è stata aggiunta la possibilità diinserire un tempo di pausa prima dell’inizio dello stampag-gio, con il risultato che ora le temperature del pezzo all’ini-zio del processo sono molto più precise.Per quanto riguarda lo stampaggio di ottone, nelle configu-razioni di stampaggio a forare, ora è possibile introdurre car-relli inclinati, seguire lo stampaggio di più particolari (multiimpronta), valutare con precisione i carichi su ogni punzonein funzione della resistenza del cuscino. Sono in corso modi-fiche ancora più rilevanti per questo modello, con la possibi-lità di gestire configurazioni a forare più complesse o a cam-

pana. Sempre in tema di cinematiche molto complesse, sonostati messi a punto nuovi modelli di stampi flottanti in tra-slazione e rotazione, ma anche di stampi “slave” sia in tra-slazione, che in rotazione, collegabili al movimento di altristampi “master”. Per quanto riguarda la laminazione, sono stati sviluppati nuo-vi strumenti in grado di creare, per rivoluzione, il profilo deirulli a partire da un profilo 2D, la cui forma può essere mo-dificata direttamente nel pre-processor, muovendo o trasci-nando in nodi del profilo.Parlando poi delle funzioni comuni a tutti i progetti, è pro-seguito il miglioramento delle funzioni di meshatura da geo-metrie STL, con una qualità decisamente superiore rispettoalle versioni precedenti.

2. SolutoreL’evoluzione della parte del software relativa al calcolo ha se-guito due filoni principali. Le routine di calcolo sono statesensibilmente migliorate, ottenendo una migliore qualità del-la mesh, in grado di rispettare meglio la forma degli stampi,una maggiore stabilità del solutore soprattutto per configu-razioni multi-processore e/o multi-core e, di conseguenza,tempi di calcolo significativamente minori (-20-30% a secon-da dei casi) rispetto alla versione precedente. Il solutore èstato inoltre modificato per tener conto degli effetti di ani-

sotropia del materiale e tutta una serie di nuove opzioni im-postabili nei modelli dedicati ai singoli campi di applicazio-ne: per esempio i raffreddamenti prima dello stampaggio nelmodello della pressa a vite, nuove funzioni PETSC per la la-minazione circolare, nuove funzioni per il tracciamento delleripieghe. Per quanto riguarda il secondo aspetto, l’interfacciaper il lancio dei calcoli è stata ulteriormente evoluta e si pre-senta ora con delle nuove funzioni e scorciatoie per le ope-razioni più comuni.

3. Post-processoreLo sviluppo del post-processore, funzione delle richieste de-gli utilizzatori, ha riguardato diversi aspetti. Tra i più utili inevidenza la creazione di un cubo di navigazione, che rendeimmediata la rotazione del modello nelle viste ortogonali agliassi principali. Sempre nella direzione di una migliore gestio-ne del punto di vista scelto, è stata implementata la possi-bilità di salvare il “workspace”: l’utente carica i risultati di

interesse (scalari, vettoriali, plot) an-che per più progetti da confrontare,sceglie il punto di vista e le opzionigrafiche, carica eventuali animazioni esalva il “workspace”. Caricando questofile, vengono quindi ripristinate tuttele scelte dell’utente, opzione che con-sente un notevole risparmio di temponella fase di analisi dei risultati. La vista dei soli risultati in superficienon consente una valutazione di quan-to realmente succede all’interno delpezzo: per questo scopo si utilizzanodei piani di sezione. Tra le nuove fun-

zionalità introdotte per questo strumento, le più significati-ve sono la possibilità di muovere il piano attorno ad un as-se, la possibilità di selezionare dei punti sul piano, rilevan-done i valori calcolati, e la possibilità di ottenere un graficodell’area del piano in funzione della corsa impostata. Sempreper questo strumento risulta utile la possibilità di esportareil profilo del piano in formato dxf ed in coordinate XY, chepuò quindi essere utilizzato in qualsiasi CAD, ma anche lapossibilità di salvare, in un determinato istante della corsa,una animazione che mostri il piano di taglio che scorre attra-verso il pezzo in una determinata direzione, o secondo unarotazione attorno ad un asse. È così possibile valutare in unaunica animazione cosa accade nelle varie sezioni del pezzo.Sempre in termini di strumenti di interfaccia con strumentiCAD o FEM, da ri-cordare la possibili-tà di esportare informato .STL, sce-gliendo quali og-getti esportare e lapossibilità di gene-rare un file .UNV (I-deas universal file),che contiene sia laforma, ma anche


Stampaggio ottone con carrelli inclinati Bigorniatura anello in acciaio

Albero - Calcolo accoppiato tensione sugli stampi

tutti i risultati calcolati: è possibile quindi trasferire ad unaltro strumento FEM quanto calcolato in Forge, per effettua-re altri tipi di analisi, ad esempio del pezzo nelle condizionidi carico corrispondenti alla sua messa in opera.Degno di nota è inoltre il miglioramento dell’interfaccia diesportazione .vtf, che consente di esportare l’animazione diun risultato in una forma ove l’utente ha la possibilità dicambiare il punto di vista e/o lo zoom. Con il nuovo visua-lizzatore GlView Express, scaricabile gratuitamente, è orapossibile visualizzare nello stesso file più risultati, rendendodecisamente più agevole la comunicazione delle informazio-ni tra colleghi o verso l’esterno.

Miglioramento continuo del database dei materialiIl database dei materiali è sempre stato uno dei punti cardi-ne di Forge, con le curve di deformazione a caldo ed a fred-do, le caratteristiche elastiche e le proprietà termiche di ol-tre 800 leghe ferrose e non ferrose. In questa versione sono

stati aggiunti una se-rie di materiali prove-nienti dal programmaJmatPro, quali acciaial Boro, micro legati,acciai inox, superle-ghe (inconel718, ni-monic, waspalloy),leghe di Titanio, per iquali sono state cal-colate le curve reolo-giche e le caratteri-stiche fisiche da tem-peratura ambiente al-le temperature distampaggio a caldo.Da evidenziare comesiano stati introdottianche dei materialiche tengono conto

dell’evoluzione del grano cristallino causato dalla ricristalliz-zazione e del kinematic hardening.

Installazione – versioni disponibiliGià nella versione precedente era possibile impostare una ar-chitettura client-server, concentrando le operazioni di calco-lo sulla macchina più potente e demandando alle macchineclient la preparazione dei calcoli e l’analisi dei risultati. Il si-stema è stato ulteriormente evoluto, aggiungendo la possibi-lità di una licenza “floating”, che può essere attivata a tur-no su diverse macchine, aumentando la flessibilità di utiliz-zo in ambiente multiutente.La gamma di possibili installazio-ni di Forge è stata ampliata rispetto alla versione preceden-te. Oggi è possibile installare il software sia in sistema ope-rativo a 32 o 64 bit Windows XP, Server® 2003, Server® 2008,VISTA business, Linux Red Hat Enterprise o SLES 10 64bits. Intermini di piattaforme hardware, Forge sfrutta appieno la pa-rallelizzazione del calcolo, quindi è possibile utilizzare unamacchina con singolo processore 1-4core, con più processori

o sistemi cluster fino a 32 core, le cui code possono esseregestite anche mediante i software pbs v5, pbs v9, lsf e sge.Gli ultimi benchmark effettuati su piattaforme equipaggiatecon i nuovi processori Nehalem i7 (serie XEON 55**), con dueprocessori 4core, hanno mostrato una notevole efficienza,con tempi di calcolo paragonabili a quelli prima ottenibili so-lo con un cluster, con una semplicità di gestione decisamen-te maggiore. Questo rende ora possibile lanciare anche suqueste piattaforme analisi molto pesanti quali la laminazio-ne di anelli, mesh molto fini o analisi con molti incrementi.

ConclusioniSi può quindi affermare che Forge 2009® è un programmasempre in costante miglioramento, che ha raggiunto una no-tevole semplicità d’uso grazie al-l’esperienza accumulata con le ver-sioni precedenti e i suggerimentiprovenienti dagli utenti. Molte dellenovità introdotte portano la versio-

ne 2009 ad un livello diprecisione ed accuratezzadecisamente superiore al-la versione precedente.Dall’altra parte, la matu-rità raggiunta dal prodot-to consente sempre un

facile e rapido inserimento in qualsiasi ambiente tecnico, perla progettazione di prodotti ottenuti per stampaggio e l’otti-mizzazione dei relativi processi produttivi. Con Forge 2009 èquindi possibile migliorare rapidamente la qualità dei pezzi,ridurre gli sprechi di materiale e aumentare la durata deglistampi e delle macchine di stampaggio. È possibile inoltrevalutare in modo anticipato senza sorprese la stampabilità dinuove forme o di materiali poco conosciuti. EnginSoft, distributore in Italia del software Forge, grazie atecnici specializzati con oltre 10 anni di esperienza, offre al-le aziende del settore, formazione del personale ed avviamen-to all’uso oltre al supporto nell’installazione, nonché attivitàdi simulazione su commessa, con impostazione del caso, ana-lisi dei risultati e consulenza sull’ottimizzazione del processo.

Per maggiori informazioni:Ing. Marcello Gabrielli - Responsabile di prodotto [email protected]


Simulazione stampaggio a caldo fuso a snodo

Simulazione laminazione di prodotti lunghi

Stampaggio a freddo

Rollatura del filetto

Calcolo accoppiato vite,bullone e lamiera


Elysium’s CADdoctor acceleratingReverse Engineering1. 3D data utilization in Reverse EngineeringAs the noncontact 3D measuring machine has become sopopular, the digitalization of physical models is needed morethan ever. Traditionally, the main purpose of measuring physicalmodels was ”Inspection” to determine if the products weremanufactured following the original design by comparing CADdata and point cloud data measured by the contact measuringmachine. However applications in “Reverse Engineering” haverecently attracted a lot of attention. Typically, what we meanhere is the way how to use CAD data produced from the huge

number of point cloud and polygon data measured by thenoncontact measuring machine. The objective of creating a CADmodel from the point cloud and polygon data is either related todesign purposes or to simulation purposes.

Design purposes• Design: Creating CAD models from clay models and using

them for the design• Digitalization of CAD models from own products: Creating

CAD models only from physical models and usingthem for the design

• Mold building: Measuring existing die to producethe second die

Simulation purposes• Benchmark: Simulation of own products and

products developed by other companies• Simulation: e.g. Creating a CAD model of a golf

bag for the design of the luggage space

The key factor for effective Reverse Engineering isthe creation of a CAD model from measured point cloud andpolygon data. Generally, when a CAD model has been created forreverse engineering, the measured polygon data has beendivided into areas and a Brep surface was created for each area.In this process, it is important to translate the right CAD modelfor the purposes as the required CAD quality depends on theapplication of the translated CAD model. For example, if thepurpose is design, high quality CAD data of class A representingexact feature lines and curved surfaces are required as they willbe used for design and manufacturing later. However if the

purpose is simulation, the required quality is different. Indeed,very often, it is not necessary to have the same quality as fordesign. The created CAD model is meshed by using CAE and inmany cases, moderate quality is sufficient. (*)(*) When we consider CAE simulation, there is a tendency tothink that measured polygon data can be directly used formeshing and there is no need to create a CAD model. However,such polygon data is not sufficient for meshing and often leadsto low accuracy simulation results because of the noise involved.It is also a problem to increase the number of mesh elements.

Hence the translated CAD model is usually used formeshing before CAE simulation instead of using themeasured polygon data directly. Reverse Engineering performances have improvedthrough the years, but the huge amount of man-hours to create CAD models is still a relevant matter,in both areas of design and simulation. In fact, thereis no solution to create high quality CAD dataautomatically and efficiently enough for designpurposes. In recent years, another approach has

evolved, which consists in using original CAD data andtransforming it to fit with the polygon data, in order to producethe final CAD data of measured polygon data. However, this iscertainly not the best solution. When considering this approach,it would be better to transform the model by fitting the featurelines of the original CAD data to feature the lines of the polygondata. However, the current process is to use commercial softwarewhich only transforms by fitting the original shape to thenearest polygon. (See Figure 1).

For simulation purposes, usually the required CAD quality is notas high as for design purposes. Though, it would be muchappreciated to represent the position of the feature line todefine the right boundary condition. The reduction of thenumber of surfaces of the CAD model is also important for theeffective mesh generation, although it is not easy because theCAD model has lots of square surfaces created from polygondata. Besides, it is also important that the translated CAD modelcan be used in CAE. To solve these problems, the latest versionof CADdoctor has the fully-automated capability to create CAD

Figure1: Deformation to the nearest point (solid arrow) and the ideal deformation orientationconsidering feature line (dashed arrow)

Figure 2: Measured polygon data (left) and CAD data from polygon (right)The complicated surface including the internal opening section can be created automatically.

Newsletter EnginSoft Year 6 n°4 - 15model data from polygon data by reproducing the feature lineposition, which had to be done manually before and it was verytime-consuming. Using this capability, CADdoctor represents anextremely complex surface including an internal opening sectionas a face. Hence it also has the ability to produce the best modelfor the simulation. (See Figure 2)

2. Reverse Engineering capability in CADdoctor2-1 Automatic CAD data generation from point cloud andpolygon meshPoint cloud data and polygon data measured by a 3D measuringmachine representing physical products (prototype orcommercial product) can be translated into 3D CAD datagenerating NURBS surfaces automatically. Prior to creating CADdata from polygon data, the surface is segmented. For thesegmentation, the geometry of the polygon data is captured,

fillets are automatically detected, and the range of eachsegment is determined automatically to approximate the surfacecomposed in the CAD model. Planar, cylindrical, and conicsurfaces for analysis representation are recognized automaticallyallowing a segmentation based on the surface type. Ifprototyping in-house design and original CAD data are at hand,the edge from the original CAD data can be copied to polygonand used as parting line for segmentation. (See Figure 3)Segmentation is automatic, but there are cases where thesegmentation may not be adequate due to unevenness occurringfrom noise. Such areas can be edited to adequate segmentationby using the editing commands, such as part, merge and extend.Once the segmentation is complete, by clicking a button, NURBSsurfacing will complete on each segment and complete CAD datais automatically created. With CADdoctor, surfacing is alsopossible on a trim surface surrounded with complex edges,allowing creation of effective CAD data with a simple surfacebased on segmentation. Moreover, after the batch surfacegeneration, minor amendments, if required, can bemade without re-executing the process, since partialsegments can be repaired or surface types can beswitched. Time spent on repair is reduced. The advantage of the CADdoctor Reverse Engineeringcapability is that manual operation and data healingare at minimum and creating 3D data can be donenearly fully automatically. From Elysium’sindependent study, CADdoctor creates 3D CAD datafrom polygon data in 1/10 to 1/30 of the timeneeded for using other translation products.

2-2 Fitting original CAD data to polygon dataThe product design in 3D CAD data can be transformed to beconsistent with the polygon data taken from an actual productusing a 3D measuring machine. This is the powerful advantageof CADdoctor. This capability can be applied not only to thepolygon data, but also to the polygon from CAE. (See Figure 4)When deforming actual CAD data, the distance between the CADdata and the polygon data is recognized, however, polygon datafrom a measuring machine has a subtle difference from theactual geometry due to noises. By setting tolerances for thedifferences to avoid this impact, the target for deformation willbe faced larger than the tolerance, and faces smaller than thetolerance will be excluded from target.

The target face for deformation is consistently deformed withthe polygon. However, if the face is deformed simply to the

nearest point of the polygon data, the area of thefeature may be out of alignment, creating distortionon the surface after deformation and the fillet'sboundary line may be disrupted, affecting theadjacent planar surface. The Fit feature in CADdoctordetermines the transformation orientation withrespect to curvature change of both the CAD andpolygon data and maintains the correct position ofthe boundary line between the fillet and adjacentsurface, thus ensuring continuity between faces thatare maintained when deforming. For the specific area where the fitting is very

difficult due to the large difference, the Reverse Engineeringcapability can only be used to create CAD data from polygondata. In summary, the fitting is completed for the polygon dataand CAD data including the large difference area, by combiningthese methods.

For more information, please visit the ELYSIUM website:http://www.elysiuminc.comFor further information on CADdoctor in Italy, please contact:[email protected] article was written in collaboration with ELYSIUM Co,Ltd.

Akiko KondohConsultant for EnginSoft in Japan

EnginSoft partners with ELYSIUM Co.Ltd. Japan to promote CADdoctor in Italy

Figure 3: The original CAD data is copied to polygon (left); copied parting line (right)

Figure 4: Distance between the original CAD data and the measured polygon data (left);distance after fitting (right)


Parametric FEM model optimization fora pyrolitic Indesit oven

By examining only the internalglass of the pyrolitic ovenwhich consists of visco-elasticmaterial, the optimizationprocess obtained the minimumstress distribution and stressgradient.To successfully finalize the workand to deliver the best possibletechnical results insuringhighest quality standards aremet, the following analyseshave been performed by Indesitand EnginSoft:

1) Parametric FEM model creation with ANSYS2) Creation of workflow in modeFRONTIER and ANSYS

integration into Frontier’s loop3) Optimization of the clamping system by

an automated routine defined withinmodeFRONTIER

4) Results analysis and optimum designextraction according to the givenobjectives

The present device belongs to a new typeof the Indesit domestic oven range, calledPyrolitics.Indesit’s new technology allows a fastcleaning of oven cavity, by means of apyrolysis process that burns encrustationcaused by cooking. The Pyrolysis process starts attemperatures close to 500°C which are extremely high for atraditional device considering an external temperature of20°C. This environment produces an high thermal gradientwhich considerably deforms the glass.

The door structure of the oven is made of a triple-glasssystem, whereas each is separated by an air wall to guaranteerapid heat dissipation and to respect the safety regulationswhich limit the allowed external glass temperature to 60°C.Glass stresses are derived from the thermal gradient,established between its surfaces, and produce a consequentdeformation; an inappropriate glass clamping system wouldprobably increase internal stresses and cause rupture.From experimental tests, we have learned that the internalglass is exposed to the highest stresses; in fact, this is thecomponent with higher thermal gradients between its faces.The aim of this work was to develop a methodology that allowsto simulate the real working conditions of the glass and to

find an optimal glass clamping solution that minimizes thestresses.

2 Structure of the model2.1 Solid modelThe model provided by Indesit has been made of a 3D doormodel of the oven with the actual glass clamping system. Thedoor is composed of a 3 glass system, mounted on a specificstructure that keeps them parallel and separated in order toallow the passage of the air cooling flow. This model has beensimplified in order to obtain a complete glass clamp system toreproduce the real door-clamping solution.

The provided material included someelements, such as, chamfer and a non-functional fillet that have been deleted inorder to create a simplified model fareasier to analyze. Constraintscharacteristics and glass geometry havebeen maintained in order to produce asuitable approximated model.

2.2 Experimental measuresAfter some experimental measures, a seriesof grid-organized values of temperatures

on the internal glass of the oven, was provided by the user.These glass temperatures were obtained by somethermocouple probes on the point highlighted in picture2.2.1.

Many repeated tests were performed in order to minimize theerror of measure, and an average value of each measuringpoint was taken into account.In this verification, we have considered the maximummeasured values to reproduce the worst working condition.

3 Glass modeling3.1 Thermal modeling of the glassIn order to perform a FEM analysis, it was necessary to assignto each node its temperature, but we had only eight measuredpoints, that is why, the available value was modeled by usinga RSM application. In fact, we used the eight measuring pointsto build an opportune RSM that reproduces the glass-temperature distribution with a good approximation.

Picture 2.2.1 – Temperature measuring point on internal glass

2009 Ecohitech Award:Recently, Indesit Companyhas won the prestigiousEcohitech Award and thusearned itself an “eco-virtuousenterprise" status.


A Response Surface, also called meta-model, is a post-processing tool of modeFRONTIER; in this application anapproximate RSM was chosen, because all measuring pointsmay be affected by a measuring error, due to uncontrollablethermal effects (e.g.: radiation and convection).In picture 3.1.1, an approximate function and relativeapproximation error graph are shown.Apart from obtaining a continuous tool able to estimatetemperatures of all values including a variable spacedefinition, using modeFRONTIER allows to obtain an analyticalform of this surface.This expression will be used in the FEMmodeler (ANSYS) to assign temp value on each node.

The next step is the application of the analytical expression tothe FEM model. In picture 3.1.2 we observe the glass with theapplied temperature.

3.2 FEM Model During the FEM modeling process, free glass deformation wasevaluated firstly, or the maximum deformation reachedwithout any constraint.During the next step, a series of constraints was applied onthe glass, in order to compare the real glass deformation withthe simulation and to estimate the model reliability.

3.2.1 Free glass deformationBy using ANSYS Multiphysics as finite element solver, only acorner was bonded and thermal field was applied in order toallow any deformation due to the thermal gradient.The thermal gradient originates from a difference intemperatures between contiguous areas; to perform the

analysis we should know the values onboth glass sides.The door of the oven is composed ofthree glass sheets spaced by fewmillimeters to allow an air coolingpassage, this eliminates the installationof probes on the internal sides of theglass.To obtain all necessary temperaturevalues and to perform our analysis, wehad to model the whole multiple glasssystem, considering convecting effects;the known temperatures were from themeasured set on the first internal glassface and a reference temperature of 60°Cwas established.

Once the estimated necessary temperature values weredefined, we have modeled a single bond on an edge of theglass. We knew that this was an unfeasible solution but it wasnecessary to understand the entity of the maximum glassdeformation with this temperature field.By applying the calculated temperature function on the firstglass, simulating heat transfer from the oven cavity to theroom and calculating the thermal gradient on the component,we were able to obtain the maximum deformation of the glassin free conditions. The results show that the maximum deformation isconcentrated in the center of the glass, as expected. The valueof this deformation is aligned to the experimental results.

3.2.2 Constrained glass deformationThe initial complete model has been simplified in order tospeed up the simulation, as detailed in par. 2.1. The constraints applied to the internal glass for the simulationof the real condition are:

• Upper support• Side support• Back support• Lower support

Picture 3.1.2 illustrates the constraint system with andwithout glass. The upper support block YZ glass displacement,the side support block XZ displacement and the lower support

Picture 3.1.1 – Approximating function and error graph (relative and absolute errors respectively)

Picture 3.1.2 – Glass surface with the applied node-temperature

Picture 3.1.2 – Constraint system of the glass


block XY displacement. The constraint conditions have to beunderstood with a little tolerance in displacement. In fact,every constraint allows a clearance to avoid stressconcentration due to an over- constrained condition.Applying the temperature field to the modeled system asdescribed before, we continue with the structural simulationto calculate the stress on and the deformation of the examinedcomponent.

In order to avoid value distortion, due to mesh problems,instead of considering maximum and minimum values, wehave taken into account a mean value of this quantity closeto the glass constraints.

4 Optimization of the glass supportThe initial model described previously has been parametrizedto allow the management by modeFRONTIER; the describedparameters refer to the dimensions of the upper and lowerglass constraints. While we focused on these constraints, thedistances from the left and right glass edges and their widthwere parametrized.

The aim of this step was to define an optimum set-up of theconstraint system that minimizes the glass deformations inpyrolysis conditions.

4.1 Project set-up in modeFRONTIERVariables used in this first optimization sub-step are thereforefour and each couple refers to the dimension of a constraint.The constraints on the glass are four, symmetrical, and henceit is sufficient to modify the dimensions of only one to modifythe couple: these will be the variables of the optimization. Lower and upper bounds of all the variables were set accordingto the customer’s requirements.By using modeFRONTIER, we want to manage the entire FEM(ANSYS) process automatically, to obtain the desired results.To interface the FEM model with the optimizer, some macroswere built, or rather a series of pre- and post-processinginstructions to modify the geometry of the model during eachsimulation.During the set-up of the optimization, some factors, such astime for each calculation or maximum available time have tobe taken into account in order to define the best strategy. In this project, the time for each calculation was about 75minutes, not negligible; this made us choose a geneticalgorithm that has a good robustness to find the optimum. The objectives were:• Minimization SXZ shear stress;• Minimization SX normal stress;• Minimization SZ normal.The chosen algorithm was the MOGA (Multi Objective GeneticAlgorithm), starting from an initial random population (DOE)of the input variables domain.Simulation parameters:• MOGA iterations: 10• DOE dimensions: 12 - variables number multiplied for

objectivesWith these settings we have to do 120 runs for a total runtime of 150 hours

4.2 Optimization resultsAfter the optimization process, a good convergence of resultswas achieved: values of shear and stresses decreased up to40% with respect to the original configuration.Picture 4.2.1 shows an example of the history charts ofstresses SX.As this is a multi-objective optimization, optimum results aremore than one: in fact, we could have some designs whichachieve the first objective, but are very far from the otherobjectives. Hence we are looking for the best tradeoff!In this job, all three objective are very correlated, so theconvergence is parallel, which allows us to choose twooptimal designs.From the obtained results we can extract some importantinformation about the component behavior in real workingconditions, especially with regard to the glass constraintsdimension and their dispersion across the oven door:• Distance of the lower constraint from the edge of the

glass seems to have no influence on stresses;• Width of lower constraint should be bigger than original;• Distance of the upper constraint from the edge of the

glass seems to have no influence on stresses;• Width of upper constraint should be smaller than original;

Pict. 4.1.1 – modeFRONTIER’s workflow

Picture 4.2.1 – History chart SX


In summary, for an optimal solution, the constraints layoutshould encompass the upper constraint going more closewith the opposite behavior for the lower constraints. In thefollowing picture the optimal solution is graphicallyrepresented.

For the stresses, without having sufficient information aboutthe glass characteristics, it is more opportune to present thedeformation chart of the glass, during the pyrolysis phase.

5 ConclusionsThe provided model is composed of an assembled system ofthree glasses, mounted on a chassis that keeps themseparated to allow an air passage between them, inaccordance with the regulations for this appliance.Experimental tests performed by Indesit are focused ontemperature measurement of pre-determined points locatedon the internal side of the first glass, in pyrolysis conditions,when the internal temperature of the oven rises to 500°C.Punctual values of temperature, were computed withresponse surface modeling in modeFRONTIER in order toobtain a function that describes the temperature distributionon the entire glass, and assigns a relative value on each FEMmodel node.The built map is related to the hot side of the consideredglass. To calculate temperature distribution on the cold side,

the entire glass system was modeled by thermal analysis.Knowing the internal cavity temperature distribution, thesafety temperature on the external side of the outdoor glassand convex thermal coefficients, we were able to obtain thetemperature distribution on the coldest side of the moststressed glass and hence also the thermal gradient applied tothis component.

The focus of the first simulation was on examining the freeconstraint condition of the glass, or to verify the maximumdeformation of the glass, without constraint.In the subsequent simulations, the initial configuration, asdescribed in the initial 3D model, was modeled with the dualpurpose to validate the FEM model with experimental results,and to determine stress and deformation values of the initialconfiguration.

The aim of the optimization process was to find an optimallayout of the constraint system that minimizes stresses onthe internal glass. To achieve this result, the FEM model wasparametrized by means of a series of instructions named“macros”, to allow modeFRONTIER to manage the geometry ofthe model.

The task of modeFRONTIER is to modify the model geometryon each run and to drive the input variables to the best set.The modified parameters are referred to as the upper andlower glass constraints dimension, and in particular, thereciprocal distance and the width of each constraints areverified.

The results were the values of stress and deformation on themodel, due to the thermal gradient applied. Due toimperfections in the mesh, the mean value of stresses closeto constraints, was taken into account.Obviously, the selected area for the calculation of this mean,was related to the area affected by higher stress values, tobe precautionary.

The obtained results meet our expectations: a sensibledecrease of stresses was registered nearby 30-40% withrespect to the customer configuration, and a goodconversion of results was achieved, highlighting the goodquality of the work performed by modeFRONTIER.The deformations of the optimized configuration are biggerthan the original ones, which is an indication that theobtained design provides room for a better movement for theglass.

Finally, we are certain that the obtained results are sufficientand correct, and that this work has delivered furtherinformation and details about the system behavior to themodeFRONTIER users at Indesit Company.

For more information:Ing. Nicola [email protected]

Picture 4.2.2 – Displacement sum

Picture 4.2.3 – Elongation due to the shear SXZ


Robust Design Optimization of aBumper System at Volvo Cars usingmodeFRONTIER70% are low speed crashesAccording to a recent survey by VolvoCars Brand Experience Centre, lowspeed crashes represent over 70% ofthe crashes today. Typically crashesup to approximately 15 km/h arecategorized as low speed crashes andare often caused by accidents duringparking, queuing and brakingsituations.

The components of the rear part ofthe car are highly integrated, makingrepairs very expensive. Therefore,both customers and insurancecompanies require that the damage ofa low speed crash should be limitedto a few components which are easyto replace. In order to minimize thedamage to the car body, the rear bumper beam must bedesigned to absorb all the energy from a crash. Due to thecomplexity and cost of repairs, the optimization of thebumper system becomes a very important and challengingtopic.Ever since its establishment, Volvo Car Corporation has putsafety among its top priorities and recently a thesis work [1]on best practices for robust design optimization of a rearbumper beam was carried out.

Performance varies due to tolerances in productionUsing modern crash simulation software such as LS-DYNA, itis now possible to predict the behavior in a crash with goodaccuracy. However, everything that is manufactured has itstolerances on geometry, material properties etc which meansthat in practice a certain range of variation on theperformance parameters always exists. Any small deviation,even a random noise, could influence the real crash, but maynot be visible in the CAE analysis when nominal values are

used for simulation.

A robustness study looks into groups ofsimulations with different combinations of inputparameters, to see if they give similar responses ornot. Just as with the input parameters, it isimportant to identify the relevant and interestingoutput parameters which are then traced in therobustness study. The analysis will show how theperformance varies due to scatter in the inputparameters.

Evaluation of robustnessPerforming a robustness study is both complex andexpensive. Complex, since the crashworthiness isdetermined by variations in a large number ofparameters, such as material properties of differentparts, friction, impact angle and speed. Complexityincludes both choosing the most influentialparameters and implementing them for automaticevaluation. Expensive, since a single simulation

Figure 1: Low speed crashes represent more than 70% of the crashes and combined with very high costs forrepairs make robust design optimization extremely important. The study focuses on the bumper beam shownto the right.

Figure 2: Driving backwards into a fixed barrier at 15 km/h, i.e. the Allianz test, without damaging the carbody is one of the toughest requirements. The figure shows the CAE model built in ANSA. This model of afull vehicle was used for verification.

Figure 3: modeFRONTIER was used to automate the robustness study using LS-DYNA andMETApost. In order to save computational cost, a submodel instead of a full vehiclemodelwas used for the robustness and metamodel evaluations.


takes about 2 hours using parallel execution on 24 CPUs anda robustness study may need more than 100 evaluations.The selected input parameters in this study are: • Material properties of the bumper beam• Thickness of the bumper beam• Material properties of the parts behind the bumper beam• Barrier impact and tilt angle• Friction

The selected output parameters are:• Maximum plastic strain in all parts except bumper and

barrier• Mean plastic strain in all parts except bumper and barrier• Number of high plastic strain nodes in all parts except

bumper and barrier• Maximum deformation of the bumper beam • Kinetic and internal energy of the model• Maximum bumper beam internal energy• Section forces of the side member• Latch displacements

The preferred sampling method for this type of robustnessstudy is Latin Hypercube. A central question is how manysamples are needed for the chosen 10 variables in the study.A possible answer is to study the correlations between theinput variables as shown in figure 4. Figure 5 shows theabsolute max and arithmetic mean of the correlation versusthe number of designs. It can be seen that both valuesapproach the ideal correlation of 0 as the number of designs

grow. A correlation of 0.1 is regarded as acceptablewhich corresponds to about 75 to 100 samples. Inthe crashworthiness study, the complexity of theevaluated results as well as the number andcomplexity of significant interactions among theinput variables may require even more samples to beevaluated in order to reach converged stochasticresults.

In this study, convergence of the stochastic results ofthe initial sampling of 200 design points is verifiedby an additional 100 design points. The additional100 designs are also generated from Latin Hypercube,but from a different random seed. This means thatthe additional 100 designs differ from the original200 designs and the 300 designs as a whole stillfollow the Latin Hypercube space filler distribution.It is observed that there was not a big differencebetween the output correlations or the outputdistributions gained from the 200 and 300 designsets.

Results of the robustness studyOne result of the robustness study is a list of themain effects for each results quantity. Figure 6 showsthe effect of input parameters on the maximuminternal energy of the bumper beam, ranked frommost to least influential. It can be seen that the

maximum internal energy of the bumper beam is criticallyinfluenced by changes to the tilt and impact angle of thebarrier. In addition, an increase in the friction and a decreasein the bumper beam material strength could give higherenergy absorption.

Besides, the effect of each individual input parameterinteractions of several inputs can be significant. As it can beseen in table 1, the combination of material properties of therear side members and the impact angle have more effect onthe results than the single factors friction or materialproperties of the bumper beam.

The robustness study also uncovered a set of designs givingextreme results. A separate study on these outliers revealedthat they all had low values of friction. The root cause of theoutliers is related to the way LS-DYNA deals with friction. Asa result, 200 new FE simulations were performed with thefriction fixed at the nominal value. The ranking of main andinteraction effects was not affected while the output valuesand their distributions had to be updated. Table 2 shows how

Figure 4: Linear correlations between the 10 input variables for the Latin Hypercubesampling.

Figure 5: Correlation between input variables approach the ideal value of zero as thenumber of designs grows. A maximum correlation of 0.1 between two inputs is regardedas acceptable which corresponds to a requirement of approximately 75 to 100 samples.

Table 1: Comparison of main and interaction effects of the inputs onmaximum level of the bumper beam internal energy.

Newsletter EnginSoft Year 6 n°4 - 23the most important stochastic data changes whenfriction is removed as a stochastic input variable.The table also shows that the standard deviationof the internal energy is in the order of 5-10% ofthe nominal value. By comparison, the number ofdeformed elements, i.e. elements exceeding aspecified plastic strain, has a standard deviationexceeding 50% of the nominal value.

The correlation chart is a versatile tool and figure7 shows the original 10 input variables versus 4outputs. Marked boxes are regarded to have highvalues of correlation. Since the variables Tilt,Thickness, Impact Angle and Friction have manymarked boxes but only one box is marked for thematerial properties, it is concluded that variationsin material properties are of less importance thanvariations in the loading case.

Another important result is the correlationbetween the outputs. Figure 8 shows that an increase in themaximum internal energy of the bumper beam leads to adecrease in the number of deformed elements on the ringframe.

The necessity of metamodelsAs seen in the robustness study, the scatter ofthe results cannot be neglected in anoptimization. Furthermore, the computationalexpense makes it most desirable to find a fastreplacement for the FE simulation during theoptimization. In modeFRONTIER there are 7types of metamodels which aim to replace theunderlying simulation model with a very fastbut approximate function. The evaluation timeis in the order of 0.05 seconds, making itpossible to evaluate thousands of designcandidates in order to solve the robust designoptimization task. The process of using metamodels is divided into3 steps:• Training the metamodel • Evaluating the quality of the fit• Using of the metamodelIt was not obvious which metamodel woulddeliver the best fit so Kriging, Radial Basis

Function and Neural Networks were included and evaluated.Besides the previously mentioned robustness parameters, 3new geometry parameters, implemented through meshmorphing in ANSA, were introduced.

The training set consisted of 1000 FE simulations andanother 170 FE simulations were used to check the quality ofthe metamodels. Figure 9 shows the difference between theRadial Basis Function and the evaluation set for one of theresults. The mean residual values between the three methodswere close and the response looked similar to the samedesign IDs. As such, all three methods in this study areconsidered to give equally good results. In the end, theparameters given by the Neural Networks were chosen forfinal verification.

Figure 6: The main effects plot shows that the most influential parameter on the internalenergy of the bumper beam is the tilt of the barrier followed by the impact angle and friction.

Table 2: Variation of friction has a significant effect on some of thestochastic results. It is also clear that the robustness properties can hardlybe ignored when the maximum value in the study exceed the nominal valueby more than 5 times.

Figure 7: Correlation between input and output variables. The variation in crashworthiness due toscatter in material properties is small if compared to the scatter in the load case variables.


Robust Design OptimizationThe metamodels were used torun a multi-objective robustdesign optimization. A designfound through optimization onthe metamodels was thenselected and verified using realFE simulations. Table 3 showsresults for highly strainedelements and it is clear that theoptimized bumper beam is a bigimprovement over the original.Both the mean value andstandard deviation havedecreased. The comparison isalso done for the full car model,to confirm that results

calculated from the submodel can be applied tothe full car, cf. figures 10 and 11.The bumper which was optimized according tothe Allianz load case was also tested in other lowand high speed crashes. The results highlightedthe necessity to consider multiple load cases atthe same time during the optimization.

SummaryOverall the results were very promising, provingthe potential of running robust designoptimization on metamodels for crashsimulations. The initial robustness study alsoprovided great value and insight into thedominant parameters and considerationsregarding the FE simulations. The arithmeticmean and standard deviation for the stochasticssimulations were improved for all studiedoutputs, e.g. for the ringframe the results wereimproved by about 50% and 20% respectively.

Reference[1] Xin Li and Tolga Olpak, "Robustness andOptimization Study of a Rear Bumper BeamDuring a Low Speed Impact", M.Sc. Thesis atVolvo Car Corporation, Göteborg, Sweden,Department of Solid Mechanics at the RoyalInstitute of Technology (KTH), Stockholm, 2009

AuthorsDr. Anneli Högberg, CAE Crash Engineer, Volvo Car Corporation,[email protected]. Professor Martin Kroon, Department of Solid Mechanics,Royal Institute of Technology (KTH), [email protected] Li, CAE Engineer, FS Dynamics AB, [email protected] Olpak, CAE Engineer, Xdin Systems AB,[email protected]åkan Strandberg, Sales Manager, EnginSoft Nordic AB,[email protected]

Figure 8: Correlation between output and output variables. An increase in the internal energyis strongly correlated to fewer nodes with high strain in the ring frame.

Figure 9: The residual chart shows the difference between the forecasted value by the RadialBasis Function and the FE simulations for the evaluation set.

Table 3: The optimized bumper has been improved in all studied outputs.

Figure 10: a) shows the plastic strain on the ring frame (i.e. a rear part of car body) in the submodel with originalbumper beam. b) shows the plastic strain on the ring frame in the submodel with optimized bumper beam.

Figure 11: a) shows the plastic strain on the ring frame in the full car model with original bumper beam. b) showsthe plastic strain on the ring frame in the full car model with optimized bumper beam.


Optimization in product development -An efficient approach to integrate singleCAE Technologies up to the entiredesign chainOverviewIn today’s industrial production plants, state-of-the-artsoftware systems are used to analyze different loadingconditions in order to determine the performance anddurability of a product. Similarly, production companiesuse simulation for manufacturing processes, such ascasting and welding. Optimization techniques are widelyregarded and applied as the next logical step to perfectcompetencies in simulation for modern productdevelopment. Possible applications of optimizationtechniques range from local problems with singleapplications up to the mapping and optimization of alarge range of parameters of an entire productdevelopment process. Hence optimization can providesignificant time and resources savings, opportunities thatare illustrated in this article.

IntroductionSince the introduction of the computer, nearly all areas oflife have changed rapidly. This applies also, and inparticular, to the working environment and all professionalactivities of engineers.For example, engineeringdrawings are no longermade on a drawing boardusing 2D techniques; 3Dmodels are createdinstead on the screen.Thus necessaryadjustments to theproduct are realizedquickly, for example theweight or the moment ofinertia of complex

geometries can be determined – all in an automated way.Advances in computational mechanics, such as the FEAFinite-Element Method, have also made their way intomodern production facilities a long time ago. Again, clearadvantages of simulation are shortened productdevelopment cycles, improved assessments of productquality and, importantly, savings in experimental time andequipment.

Today’s status of simulation in product developmentcovers a number of standard analyses, including:• Strength and durability/fatigue analyses of mechanical

and/or thermally stressed devices in most diverseloading conditions (Figure 1),

• Computation of characteristic measures in CFDproblems as shown in Figure 2,

• Crash Simulations in the area of Safety Engineering and Figure 1: Stress analysis of a crank shaft

Figure 3 (a) Solidification stage of a casting simulation and (b) forging simulation of a crank shaft

Picture 2: CFD simulations for a turbine blade


• Vibration and dynamic analyses ofcomplex multi-body models.

Considering its industrial infrastructure, thearea of manufacturing process simulationcould be regarded as a separate domain ofcomputation. The attention here is notpurely focused on the product, as also therequired tools for the processes have to betaken into account. Those simulationmethods comprise among others:• Simulation of casting processes

including filling and solidificationprocesses, the resulting impacts on thematerial microstructure and thecorresponding local mechanicalproperties as well as the residualstresses (Figure 3a),

• Simulation of forging processes withforming simulations performed continuously or inseveral steps, including material and stress-strainanalyses of the device and the forging dies (Figure 3b),

• Injection-Molding Simulation of plastic-based devicesincluding filling and solidification processes as well asjoint formation,

• Simulation of machining processes including chip-forming analysis, thermo-mechanical analysis of thematerial removal rate of the workpiece and the tools aswell as of surface properties.

If we consider the structural trends in manufacturing andR&D industries as an example - the ever-growing globalcompetition, shorter development cycles and increasingdemands on product quality to name a few - it is evidentthat further efforts are necessary to reduce costs andimprove product quality. This is particularly important forcompanies whose operations are based in technologically

advanced countries, such as Germany. Here, the CAEapplication “Optimization” is a well-known commonpractice and among the primary goals of technicaldevelopments.

OptimizationOptimization is defined as the mathematical process forfinding optimal parameters of mostly complex systemswith regard to a single or multi-objective functions. It isimportant to understand the advantages of optimizationwhich are explained hereafter with the help of someexamples:• Target functions depend on individual problems and, in

reality, often conflict with each other. Therefore, theultimate objective of optimization is to find a solutionwhich represents the best compromise among thedifferent objective functions.

• Due to its mathematical background and its

Figure 4: Parameter Optimization of a bicycle frame

Picture 5: (a) The modeFRONTIER Workflow which integrates a FEA application for a strength calculation of a bicycle frame. (b) The results of the optimizationrun presented in a Bubble Chart with the highlighted Pareto Frontier.

Newsletter EnginSoft Year 6 n°4 - 27independency from respective applications,optimization is often regarded as a complex andindependent field of action. Thereby, commercial tools,such as modeFRONTIER, are readily available for usesince a long time. Such tools allow to setup, performand automate optimization analyses in an easy way.

• The optimization level (and, hence, potential savings)depends to some degree on the development status ofa company. On the one hand, it is possible to performoptimization on a relatively low level for the

parameters of a single product. On the other hand,optimization can be considered as a tool of processintegration and automation, hence, to enable themapping and simulation of the complete process anddesign chain.

Optimization of a bicycle frameFigure 4 illustrates an optimization of a bicycle frame withrelatively traditional optimization objectives in structuralmechanics: The goal here is to minimize the stressescaused by different loading conditions; at the same time,the weight of the frame should be minimized. Moreover,requirements regarding limits for maximum stresses(tensile strength and fatigue resistance) have to beobserved.

In this example, the available geometric optimizationvariables are some lengths, the thicknesses of the tubesand their radial dimensions. In fact, with modeFRONTIERthe present problem can be described in a single run andby integrating a single FEA application, as shown in Figure5. Here, after an automatic analysis of the problemstructure, modeFRONTIER recommends to run theoptimization with a certain algorithm - in the presentcase a Multi-Objective Genetic Algorithm MOGA-II, withan appropriately generated DOE.

The optimization run takes place automatically and allowsa systematic Illustration of the results as, for example, byusing a Bubble Chart as shown in Figure 5 (b). Here, theoptimal solutions on the Pareto Frontier are clearly visible.In this example, the automation enabled the engineer to

compute 300 designs within a few minutes time. Hence,the design time was shortened, instead of wasting timefor multiple manual variations. Additionally, theperformance of the bicycle frame with respect to stressescould be improved, while achieving significantly lowerweight conditions, which also led to lower material costs.

Design Chain OptimizationThe relatively simple optimization approach applied to thedesign of the bicycle frame already delivered significant

savings. This approach however is based on the (mostlyfeasible) assumption that existing residual stresses, σ0,inside the device can be neglected. These stresses derivefrom upstream manufacturing processes. With regard tothe bicycle frame, we could consider such stresses beingrelated to welding, heat treatment, and quasi-staticbending (straightening) processes of the frame. Ifavailable, this data could be used in a subsequent stressanalysis to take into account real initial stress conditionsand thus provide a far more accurate optimization. Thisway, we would obtain a process chain with four differentapplications which also can be mapped and optimized inmodeFRONTIER.

As another similar example, we can take a closer look at aroller support of a paper machine, as illustrated in Figure6. The roller support is manufactured by a casting process,the weight of the first design was 476 kg. Theoptimization goal here was to minimize the weight anddeformation at the same time. In addition, the castabilityof the final form had to be guaranteed.

In this example, the sole and initially performedoptimization of the geometry (variation of 13 parameters)with respect to the most extreme load-case delivered aweight reduction from 476 kg to 360 kg, while thedeformation was reduced slightly. The verification of thecastability was performed using the software toolMAGMASOFT (sand casting) in a second step afteroptimization.Analyzing the casting simulation, the results additionallyrevealed zones with non-homogeneous microstructure and

Figure 6: Optimization of a support roller of a paper machine


hardness due to different thicknesses and local coolingrates. Also, local zones with high residual peak stresseswere found, which have a decreasing effect on the fatiguelife of the roller support.

These results gave reason to consider performing a largelyextended optimization analysis that includes both thecasting simulation and load-case analyses. In a tool suchas modeFRONTIER, the complete process chain could besetup, in which results of the casting simulation aretransferred as initial conditions to the subsequent FEM-based load-case simulation. Hence, all following steps areincluded in this kind of optimization problem:• Casting simulation with MAGMASOFT to ensure the

quality of the materials, to avoid casting defects,determination of local material properties (for exampleYoung’s module, fatigue and yield stress limits), as wellas residual stresses on the different roller supportzones.

• Transfer of the results via MAGMAlink (residual stressesand material properties) as initial conditions to beused in ANSYS.

• Load case (stress-) analysis with ANSYS.

This procedure enables also the systematic optimization ofthe support roller geometry with respect to the load inoperating conditions, but including the consideration ofresidual stresses and the locally changed materialproperties from the casting manufacturing process. Thecastability could, therefore, be guaranteed reliably.Additionally, statements with respect to the fatigue life ofthe product could be obtained and coupled to theoptimization procedure as constraints.Figure 7 shows the original (traditional) load case analysis(left) and an excerpt of such a novel design chainapproach that considers the results from the castingsimulation (right). It is clearly seen that the stresses inthe roller support are in no way homogeneouslydistributed due to different pre-stress conditions and non-

homogeneous mechanical material properties. Similarly,peak stresses (van Mises) can be seen to be increased insome areas from approximately 30MPa to 50MPa (166%).Maximum principle stresses (not shown) even highlightincreased values from 60MPa to 228MPa (380%). Althoughthese values are yet far away from the materials tensileand fatigue stresses, they lead to significant reductions inthe fatigue life of the product.

ConclusionsThe ever growing competitive global market place will callfor more and more applications of optimization techniquesin various industrial sectors. In this article, we haveoutlined the following key points:• The optimization of real problems most often defines

solutions which are in conflict with each other. SuchMulti-Objective Optimization tasks can already besolved today with easy-to-use software, such asmodeFRONTIER.

• It is possible to perform automatic optimizationalready for simple development cases by linkingstandard tools from arbitrary areas (e.g. CAE tools).

• Optimization can be extended infinitely and, hence, beregarded as a tool for process integration andautomation. In this way, it is possible to setupsimulations of an entire process chain and, therefore,to systematically extend the optimization capabilitiesfrom single device parameters to the parameters of theentire design chain.

• There is potential for large savings. They may comprisein experimental costs and reduction of developmenttimes due to the automation of computations. Thereby,savings even go hand-in-hand with ensuring productquality.

Hans-Uwe Berger, EnginSoft GmbH, Frankfurt am Main25. Schmalkaldener Fachtagung/Conference: Die Digitale Fabrik–Module und Referenzlösungen/DigitalPlant – Modules and Solutions

Figure 7: Standard Optimization (left) in comparison with an Optimization which encompasses the entire process chain: at the critical points, the analysisthat considers casting simulation shows increased van Mises stress values.


ANSYS simulation of carbon fiber andanisotropic materialsIntroductionThe scope of this R&D is to develop a newsupport, with an integrated cooling system, forthe replacement of the inner layer of theSilicon Pixel Detector installed into the ATLASExperiment, working on the Large HadronCollider at CERN; for details, we ask our readersto visit: www.atlas.ch/pixel-detector.html. Thisreplacement will become necessary because ofthe radiation damage, with the detector beingvery close, about 50 mm, to the high-energyproton-proton interaction point.

The task of the support system is to hold thedetector modules in positions with highaccuracy, minimizing the deformation inducedby the cooling; this must be done with thelowest possible mass because there are tightrequirements in terms of material budget. Anevaporative boiling system to remove thepower dissipated by the sensors is incorporated in thesupport: thermal contact is made through a veryconductive light carbon foam to maintain the sensortemperature sufficiently low, to limit the leakage currentsand hence the thermal run-away. The coolant should be afluorocarbons blend or CO2. The worst case is imposing acooling pipe design pressure of 10 MPa. The number of

pipes could be 1 or 2 and the pipe material should becarbon fiber or titanium. The structural strength of the800 mm long support stave is given from a carbon fiber“omega” shaped laminate.

Summary of the workThe design is based on thermal, mechanical and thermo-structural analyses of assemblies made of carbon fibercomposites. Calculation of the Tsai-Hill safety factors andtransversal strains in theplies are required fortightness assessment ofthe pipe. Moreover, thepipe lay-up optimizationagainst the internalpressure has been madetogether with estimationsof the thermal expansioncoefficient of the pipeand omega laminates. Weused ANSYS andESAComp; input figuresfor the ply properties, starting from fiber and matrixvalues, are provided by a dedicated spreadsheet. Tovalidate the FEM simulations both Composite LaminateTheory hand-made calculations on cross-check simplemodels and experimental tests are used. Work is still inprogress to measure material characteristics and FEMresults: pull test on pipes performed with “braided”technology, burst pipe pressure, thermal transmission

The ATLAS Pixel Detector during construction. Here we can see one of the cylindrical shells ofPixel detectors formed by the longitudinal cooled supports called staves.

Prototype of a stave with 2 carbon fiber pipes integrated into the carbonfoam and attached to the structural omega shaped laminate.

Carbon fiber pipe production test usingbraiding technology, beforeimpregnation with resin


coefficient K of the carbon pipe, CTE and deformationsinduced by the cooling using a Coordinate MeasuringMachine.The R&D key element is the production of the CF pipe andof the relative joints versus the external connectingpiping, having suitable mechanical and tightnessproperties.

FEM of composite materialsSome assumptions are taken up in building the model andsome parameters needed to run the software should beguessed as they are absent in literature (i.e. ply out-of-plane moduli and Poisson coefficient). A major problemfound in building the models is the necessity to correctlyorient the layered elements for the composites whichturns out to be very time consuming. Moreover, in themulti-physics, during the switching from structural tothermal analysis automatically a different orientation ofthe thermal element coordinate systems is set; the use ofdedicated APDL macro routines can be useful to optimizethe FEM workflow. We used several meshing techniques:mapped mesh for composites materials and free mesh in

2D or extruded mesh in 3D for the anisotropic materials.Geometry of the anisotropic carbon foam has beencarefully conditioned in order to avoid degenerated shapeelements. We have chosen to assemble models, avoidingthe use of contact elements between the meshed parts inorder to obtain a practicable linear solution method,

merging the interfacing nodes and reducing both thenumber of elements and the run-time. Comparisonsbetween different sized meshes, with aspect ratioranging from 1 to 10, and between 2D cross sectionand 3D solutions have been judged for timeoptimization and control purposes.The use of brick elements for thin solids was driven byour specific multi-physics needs.

Note that the composite pipe produced by the“braiding” technology can only in first approximationbe simulated by the laminate multi-ply hypothesis,like those implemented in the layered elementsavailable at present. This could be an interestingANSYS product development. We are also in contactwith the DIGIMAT micro-mechanics developers tostudy the problem.

Cross section example of a finite element model. Note the mapped mesh for the laminate pipe and omega, whose one possible stacking sequence is showed.

Thermal solution example

Internal pressure and longitudinal stress applied to the pipe

Newsletter EnginSoft Year 6 n°4 - 31Thermal performanceThe thermal performances of the different configurationsproposed are studied with steady-state 2D simulations. Heatflux is applied while the BC is the temperature setting of thecooling pipes inner surface. We collected the resulting maxΔT across the staves in a table, using a performanceparameter obtained by dividing ΔT by the thermal power fluximposed as load.

Evaluation of the thermal expansion coefficientsLongitudinal CTE is calculated for the possibleconfigurations; the simulations are executed with the volumefiber percentage measured on the samples, ranging from 30%to 60%. The calculation procedure is to build a model andincrease the nodal temperature in order to have a ΔT: thenodal displacement is evaluated and the relative CTE is thencalculated. ESAComp has been used for cross check.

Pressurized pipe lay-up optimizationThe design of the pipe laminate should satisfy these criteria:withstanding a pressure test of 15 MPa, having a safetyfactor of 4 on the design pressure against a Tsai-Hill failurecriterion, matching the longitudinal CTE of the othermaterials, remaining tight under pressure with maximumtransversal ply strain ≤ 0.1%. This is the parameter thatcontrols the micro-cracks growth. Pipe is modelled using theelement layered-type Solid186. Pressurized vessel conditionsare simulated with axial force on the pipe extremities.Different pipe stacking sequences are considered for thesestructural simulations; for each ply longitudinal, transversaland shear stresses and strains are extracted for the result

analysis, used directly or combined in the failure criteria. Comparison between the stress values or Tsai-Hill indexresulting from the simulation and the corresponding rupturestress values of the ply is done. Lastly, the best lay-up,matching the requirements and including technologicalfeasibility, is [45/-45]s.

Deformations induced from gravity, cooling and pipepressurizationTo understand the thermo-mechanical effects, we firstperformed 3D thermal simulations using 20 node Solid90

elements, in order to determine the temperature fieldunder defined heat flux. The resulting nodal temperatureshave been imported, node to node, in the structuralenvironment, using Solid186 elements to determine thedeformations and stress of the stave components due tothe thermal induced deformation, related to the differentCTE values of the materials. Coefficients of thermalexpansion of the ply are calculated by the Schaperyformulas. In the following study the loads applied toanalyse the behavior of the stave are: 1) cooling-down: ΔT= -60°C, that is the ΔT between the assemblingtemperature and the minimum evaporation temperature;2) static gravity to evaluate the maximum deformationdue to the weight; 3) pressure 10 MPa inside the coolingpipe.

ConclusionsA number of considerations have been taken into accountin the frame of this collaboration with regard to all ANSYSsilmulation results and other parameters, such as theglobal radiation length, to optimize the assemblyproperties. The final choice to be made will also dependon the measurements in progress on the real prototypes.

The ANSYS software can be used as a useful tool for themodel analysis with composite and anisotropic materials.A lot of work has been devoted to understanding themethod, and then to building the required models in aproper way, for achieving the various simulation goals.The real measurement performed on a pipe prototype,actually the CTE of a CF pipe, provides a first positive

feedback from the R&D work which is still in progress.

AcknowledgmentsThanks to the colleagues of the INFN Milano MechanicalDesign and Workshop Department, in particular Mauro Monti,the responsible for the simulations and to Danilo Giugni andthe whole ATLAS Insertable B-Layer Collaboration.

Ing. Simone CoelliIstituto Nazionale di Fisica Nucleare

Sez. di Milano

Thermo-mechanical simulation results for a given configuration.


Motori Aeronautici: riduzionedelle emissioni e dei consumiattraverso lo studio dellesimulazioni di processo Il progetto Marborè, promosso dal Dipartimento diIngegneria Meccanica dell’Università degli Studi di Padova,ha lo scopo di mettere a disposizione degli allievi aerospa-ziali un motore aereonautico funzionante a banco, su cuipoter effettuare test e studi di ricerca volti a migliorare leprestazioni, come l’abbattimento delle emissioni inquinan-ti, quali NOx e COx, e la diminuzione dei consumi.

Visto il notevole sforzo, economico e tecnologico, che sa-rebbe stato necessario per la realizzazione ex-novo di unpropulsore su cui lavorare, si decise di utilizzare un turbo-jet già presente sul mercato. Verso la fine del 2006 viene re-cuperato e messo a disposizione dell’Università un turbo-getto di tipo Marborè VI-C, realizzato negli anni ’70 dallafrancese Turbomeca, smontato da un aereo bersaglioschiantatosi al suolo. A seguito dell’impatto, il propulsore èrisultato essere fortemente danneggiato, soprattutto nelcomparto anteriore, sede del compressore centrifugo. Il pro-getto prevede la completa modellazione del turbogetto, at-traverso software CAD, e la ricostruzione degli organi dan-neggiati.

The project “Marboré”,which is promoted by theDepartment of MechanicalEngineering of theUniversity of Padua, aimsat offering to aerospacestudents a trial aeronautical engine in order to carry outtests and researches. These studies are useful both toimprove the performances of turbojets according to stricterlaws for the reduction of CO2 and NOx emissions and toreduce fuel consumption.As the design of a new propeller involved many technicaland economical difficulties, the University decided to use aturbojet which was already available on the market.At the end of 2006, a Marboré VI-C turbojet, dismantledfrom a target plane which had crashed, was collected and

given to the University. The engine had been designed andproduced by the French company Turbomeca in the 70’s.After the impact, the propeller was heavily damaged, inparticular the front section, seat of the centrifugalcompressor. The project included the entire modelling of theturbojet with the help of a CAD software and thereconstruction of the damaged parts.At the end of 2007, the rotor was completed, while theintake casing, originally created with magnesium alloy, wasexcluded from any analysis, as this study required particularknowledge about the casting process. For this reason, it wasnecessary to carry out a specific study for this part with theaim to find out all the technological details to plan andperform the casting process.The first step was a careful CAD modelling which wasslightly modified from the original according to thedifferent use and then the project focused on the design ofthe casting system.

Aeronautical engines:reduction of emissions andconsumptions with aprocess simulation study

Newsletter EnginSoft Year 6 n°4 - 33Alla fine del 2007 i componenti rotorici sono stati comple-tati, mentre è rimasta esclusa da ogni tipo di analisi la boc-ca anteriore del motore, fusione monoblocco in lega di ma-gnesio, studio che richiede particolari conoscenze del pro-cesso produttivo.Si è quindi reso necessario realizzare un lavoro specifico perquesta parte, che approfondisse tutti i dettagli tecnologiciper la progettazione e la realizzazione per processo fusoriodel componente.Si è iniziata un’attenta modellazione CAD, con alcune lieviriprogettazioni dettate dalle diverse esigenze tra un compo-nente progettato per il volo da uno statico da banco, sof-fermandosi poi sulla progettazione del sistema di colata.Dopo un primo abbozzo nell’ambiente CAD, si è passati a la-vorare con il software MAGMASOFT, necessario per verifica-re e ottimizzare il processo di colata.Durante questa fase si è mantenuto un approccio di tipo ac-cademico: si è realizzata una serie di simulazioni applican-do di volta in volta alcune modifiche dettate dall’attentaanalisi dei risultati ottenuti, ponendosi come unico obietti-vo la realizzazione di un singolo prototipo di buona quali-tà, senza porsi limiti nei tempi e nei modi di elaborazione.Innanzitutto si sono implementate più versioni rappresen-tanti le varie configurazioni del sistema di colata inizial-mente progettate in accordo con le parti partecipanti alprogetto. Queste differivano nel sistema di raffreddamentoe nella disposizione dei filtri di colata.Nella prima versione era previsto un raffreddatore centraledi ghisa e tre maniche esotermiche, in corrispondenza del-le zone massicce. I risultati di solidificazione hanno eviden-ziato subito che tale disposizione era ottima per il suppor-to del cuscinetto, in quanto il raffreddamento repentino ga-rantisce caratteristiche meccaniche migliori, mentre perquanto riguarda la corona esterna erano presenti notevolizone di liquido isolate durante la solidificazione e quindiconseguenti proble-mi di porosità.La seconda versioneprevedeva, invece,di utilizzare esclusi-vamente manicheesotermiche, dispo-ste nella parte su-

After a first sketch ofthe casting systemusing CAD, thesoftware MAGMASOFTwas used to verify andoptimize the castingprocess. During thisstep an academic

approach permitted to carry out a series of simulationswhich modified the model as to a careful analysis of theresults. This enabled to obtain a single good qualityprototype without limits on time and elaboration methods.First of all, the simulations of the initial versions, whichwere created in agreement with the partners involved in theproject, were essential to choose among different possibleconfiguration methods. These versions differed both in thecooling system and in the filters placement.

The first version had a central cast iron chill and threeexothermic feeders on top of the component. Solidificationresults immediately showed that this type of placement wasperfect for the bearing support: as a matter of fact, a veryquick cooling improved the mechanical characteristics inthe most “significant” area of the component. At the sametime, isolated liquid bubbles on the external surface duringthe cooling caused feeding problems.


periore del getto. Anche in questo caso i risultati hannomesso in luce fattori positivi e negativi della configurazio-ne. Si è ottenuta infatti una maggiore omogeneità del flui-do in fase di solidificazione, peggiorando però le caratteri-stiche meccaniche, specialmente nel supporto centrale.Si è cercato quindi di unire le caratteristiche migliori delledue versioni, ottenendo un sistema ibrido che dalle simula-zioni è risultato decisamente superiore rispetto alle prece-denti disposizioni.Esso prevede l’utilizzo del raffreddatore in ghisa centrale eotto maniche esotermiche sulla corona esterna.Inoltre per garantire una maggiore omogeneità del flusso infase di riempimento, si è scelto di aumentare a sei il nume-ro di attacchi, in maniera tale da limitare i gradienti di tem-peratura presenti a fine colata nelle versioni con solo quat-tro ingressi.I risultati di riempimento e di solidificazione hanno sotto-lineato infatti che i difetti di microporosità sono diminuitirispetto alle versioni precedenti, raggiungendo la soglia diqualità ricercata. I difetti ottenuti possono essere ritenutitrascurabili per la cautelatività del software e la particolareaffinazione del processo produttivo.Si è quindi realizzata la forma attraverso tecniche di proto-tipazione rapida, utilizzando tecnologie SLS(Sinterizzazione Laser Selettiva). Compiuta la fusione in le-ga leggera, con una particolare attenzione alla fase di pre-parazione del metallo da colare, si sono fatte alcune anali-si radiografiche per verificare l’integrità del componente econfrontare quindi i dati delle simulazioni effettuate con idati reali.Diversamente da come avviene solitamente in contesto la-

vorativo, dove normalmente non si se-guono tutte le fasi progettuali e realiz-zative, in questo studio è stato possibi-le analizzare accuratamente ogni detta-glio e vedere un disegno CAD trasfor-marsi in un componente reale.Inoltre questo percorso ha evidenziatole potenzialità di questo processo chepermette di ottimizzare tutti i passaggiattraverso software specifici, riducendoal minimo i margini di errore.

In the second versionthere were onlyexothermic feeders onthe top. Just like theprevious version, thisnew one presented bothpros and cons during theanalysis of thesolidification results.The fluid temperaturewas more homogeneous

in the cooling but the cooling front on the bearing supportmoving upward and the longer time of solidification led toworse mechanical characteristics, especially on the centralpart.

Both configurations, which were initially designed, enabledto obtain a “hybrid” system and simulations showed thatthis version was definitely better. It was constituted by acentral cast iron chill and eight exo-feeders on the top ofthe component. In addition, the number of ingatesincreased up to six in order to improve the homogeneity ofthe input flow and to reduce the temperature gradients,which appeared at the end of the casting process in theprevious versions with only four ingates.

Filling and solidification results pointed out that feedingdefects decreased in comparison to the previous versions,hence the quality target was reached. Defects could beconsidered irrelevant due to the precautionary softwareapplied and the particular refining of the casting process.

The sand mold was therefore realized using SLS (SelectiveLaser Sintering) rapid prototyping techniques. Afterwards,light alloy casting was carried out taking into particularconsideration the preparation of the alloy. Finally, some X-ray analyses were performed to verify theintegrity of the component and tocompare the simulation results with realdata. This study enabled to analyse eachdetail accurately and to follow thetransformation from a CAD drawing to areal component. In addition, it pointedout the potentialities of this process,which is suitable both to optimize all thesteps using specific software and at thesame time, to minimize errors.


Healing the swine flu withmodeFRONTIEROne of the hot topics of the winter2009 that probably will be rememberedis the outbreak of the so-called “swineflu”. The new virus A-H1N1 capturedthe attention of the Italian media,which literally bombarded thepopulation with daily reports on thenumber of deaths, the severity of thisvirus and other alarms based on theopinion of some “epidemiologyexperts”, spreading in this way thefear within the population.During the first weeks of autumn somesentences such as “We will have anextraordinary peak of flu diffusion between Christmas andthe new year” or “we will be the victim of a new pandemiawith many deaths” were pronounced.How is it possible to predict such an “apocalyptic” scenarioso many weeks in advance? The truth is that it is extremelydifficult, especially when no previous knowledge on the virusbehavior is available. However, in epidemiology some simplemathematical models have been developed and used formany years; they are mainly based on ordinary differentialequations (shortly ODEs).Probably, the most known model is the so-called SIR model,where the population, which is supposed to be large andhomogeneous enough, is divided into three groups(Susceptible, Infected and Recovered), according to theirstatus (see [4]). Strong simplifications are present in thismodel which can be applied as scale level; in some cases itcould lead to poor results. For this reason, there is a varietyof SIR based models which remove some of these

simplifications in an attempt to be closer to reality. In thiswork, we suggest to add a new category to the standard SIRmodel in order to consider the fact that unfortunately, someinfected people may die. The resulting model can beexpressed as:

This is a non-linear system of firstorder ODEs; the four categories used toclassify the population are S =Susceptible, I = Infected, R =Recovered, D = Dead and they areexpressed in percentage terms. For thisreason the sum of all the categorieshas to be always equal to one. Theparameters β, ν and δ are constants

which determine the evolution of the disease. The resultsstrongly depend on the numerical values of these parameters.Specifically the peak value of the infected and the week of

the year when it will appear, whichare important information to havein advance, can be really difficult tocapture if there is not a rigorousestimation of the above mentionedparameters.Obviously, it is mandatory to knowthe initial conditions before solvingthe system: in other words we haveto know the number of susceptible,infected, recovered and deadpersons at time zero, when we wantto begin our simulation.The solution of such equations isalways done, excluding trivial cases,through numerical techniques whichhave been expressively defined totackle this kind of problem. To

A photo of the A-H1N1 virus (left) and a swine (right). They do not look so dangerous…

Figure 2: The solution of a classical SIR model: the three categories S, I and R are plotted versus time,expressed in weeks. It is clear that the disease has a peak between the first and the second week and that themaximum number of ill people is around 150 over 1000. In this case we adopted the following values for theparameters (β=10, ν=5 and the number of initial infected is 1.98 for 1000 persons).


obtain reliable solutions, the numerical strategies have toconsider the nature of the ODE to be solved; in general, ODEscan be really complicated and strongly nonlinear and theindependent functions could have sharp variations withintime.

For this reason, many techniques have been developed as itcan be easily seen in literature (see [5] and [6] just to havean idea), to minimize the difference between the numericaland the theoretical solution.The implementation of such techniques in general is not aneasy task for many engineers and scientists who probably aremore interested in obtaining a reliable solution for theirproblems rather than in spending time and money incompiling codes.

To partially mitigate this situation, we use a general-purposeand open source platform, Scilab (see [2]) which providesthe user with powerful numerical tools to manage differentproblems and to solve an ODEs system.In Figure 2 the three categories S, I and R (these quantitiesare measured with reference to a population of 1000 persons)have been plotted versus time (expressed in weeks). In thiscase a classical SIR model has been solved: it can be easilyseen that the number of infected personsamounts to a maximum of 150 out of 1000 andthat it falls between the first and the secondweek. The model parameters (β=10, ν=5 andthe number of initial infected is 1.98 for 1000persons) have been chosen in this casewithout any reference to a real disease.Unfortunately, the model parameters are notknown in advance but, usually, they have to

be estimated starting from some previously acquiredknowledge on the evolution of the disease. Once theseparameters have been estimated, it will be possible topredict the spread of the disease.This is a typical model tuning problem which could beformulated, for example, as a least square problem. Actually,if we knew the number of infected persons and the deathswhich can be ascribed to the flu during a given period, wecould try to find out the values for the model parameters inorder to best fit the known data. The result could give abetter insight into the flu evolution, and the possiblepredicting of the peak of the infection and hence a betterunderstanding of the general evolution of the disease.To this aim we decided to use the data reported in Table 1,which are provided by the ISS (Istituto Superiore di Sanità)and collected by the author from different Italian media (see[2]). It is obvious that they are not numerous, but they arethe only ones available at the end of the 46th week of theyear (November 15th). However we would like to predict theswine flu evolution in Italy for the following weeks.

As mentioned above, our aim is now to find out the bestvalues of β, ν and δ in such a way that our modified SIRmodel is able to best fit the data reported in Table 1. We are

building the modeFRONTIER project drawn inFigure 3: the four input variables are representedby the four green nodes in the upper part whilethe output variables, the number of the infectedand the deaths at different weeks, are extracteddirectly from Scilab through two output vectors(the blue nodes).Among the many available strategies to adoptfor the solution of this problem, we decided touse the following one, which has the desirablefeature to lead to a mono-objectiveminimization problem.We introduce a target node, involving thecomputed number of infected people, lookingfor the best fit:

and a constraint node, involving the number of actualdeaths:

For the solution of such a problem, usually, a Levenberg-Marquardt algorithm is recommended, in view of the nature

Table 1: The number of infected persons over 1000 (data source [2],November 15th) and the total deaths due to the swine flu (reported by theitalian media) in Italy are reported in this table for some weeks of the year.

Figure 3: The modeFRONTIER workflow used for the model tuning problem.

Table 2: A comparison between the best solutions found with the two optimization algorithmsadopted. It can be seen that the NLPQLP provides a better solution. C44, C45 and C46 representthe value of the constraint as defined in equation (2) expressed for the weeks 44, 45 and 46respectively.


of the function to be minimized. It is well known, however,that this algorithm adopts a penalty oriented approach tomanage constraints, which may not be the best in our case:we actually would like to have a very accurate fit also for thedeath rate, which is involved directly by the constraints.The NLPQLP algorithm, which has a completely differentapproach in the constraint management, has also beentested: it can be seen (from Table 2) that it provides betterresults than the Levenberg-Marquardt algorithm.The evolution of the flu is reported in Figure 4, as computedusing the best fit parameters by NLPQLP. It is evident thatthe peak falls between the 45th and 46th week and itconcerns about 13.5 persons out of 1000. Moreover, it pointsout that the flu should practically disappear before the newyear. The mortality rate can be estimated by looking at thenumber of deaths after a long period (let us say after oneyear from the beginning): in our model this value amounts to0.0028 out of 1000 persons, which means 0.03% (170 deathsin Italy approximately). This value appears to be very closeto analogous quantities computed for otherseasonal flues in the past, which usuallyrange between 0.02% and 0.04%. Finally, ithas to be mentioned that the deaths areslightly overestimated in our model.

However, if the reader visits the web sitegiven in [2], he/she can read that theproposed data could be affected by slightvariations, due to some delays in reporting bythe surveillance network. Probably, thenumber of infected persons will not be exactlythe same as those reported in Table 1, afterNovember 15th. Hence knowing that theavailable data at the end of the 46th weekmay not be accurate, we would like toestimate how our previsions reported above,could change. In other words, we want tounderstand what is the error rate of our

previsions, as the target data maybe affected by slight variations.

Here, the first step certainly is togive a probabilistic characterizationof the target values; we decided touse an exponential probabilitydensity function for each targetvalue of the infected persons. Thischoice has been driven by the factthat the true values of the infectedpersons are certainly higher thanthose reported in Table 1; actually,they are expected to grow. In Table3 the values of the location and thescale for the four exponentialprobability functions are collected.

These values have been arbitrarychosen (there is no information on the reliability of data wehave) in such a way that values lesser than those reported inthe last column of Table 3 have around 90% of probability toappear.

Five thousand simulations have been organized modifyingthe target values in accordance with the given probabilitydensity functions mentioned above and the correspondingpeak position, peak intensity and mortality have beencomputed.

Figure 4: The evolution of the swine flu in Italy according to our modified SIR model. Note that the logarithmicscale has been adopted for the persons ages. It can be seen that the flu peak falls between the 45th and 46thweek (blue curve)and that it concerns about 13.5 persons out of 1000. The flu should practically disappearbefore the new year. The triangles represent the fitted data, contained in Table 1: it immediately becomes clearthat the death rate is slightly overestimated.

Table 3: The location and the scale parameters of the exponential probabilityfunctions used to characterize the target values of the infected people atdifferent weeks.

Figure 5: The modeFRONTIER workflow used for the solution of the sensitivity problem. A Latin-Hypercube technique has been used to generate a DOE in accordance with the probability densityfunctions characterizing the targets. In the project shown in Figure 3, the model tuning problem issolved by modeFRONTIER with a batch call and a Scilab routine which are used to continuouslyextract the information about the disease.


To launch these simulations a new modeFRONTIER project hasbeen organized (see Figure 5): the Latin-Hypercubealgorithm has been set up to plan an appropriate DOE and abatch call to the project described before has been appliedin order to solve the model tuning problem. A Scilab routinefinally extracts the results in correspondence with the bestsolution found.In Figure 6 a bubble chart is shown: the peak value is plottedversus the peak position and the bubble color is used torepresent the expected mortality. It can be easily seen thatwe obtain three ranges of existence; we can say that thepeak position ranges between 45.29 and 45.60 weeks andthat the peak ranges between 13.19 and 13.24 infected forone thousand inhabitants. The mortality rate never passesthe 0.00347 over 1000 persons. It is interesting to observethat the resulting cloud of points is not uniformly norhomogeneously distributed, but it has important voids andregions with high densities.To understand how the probability of the couple peak andpeak position is distributed, we have built the diagramplotted in Figure 7. The cloud of points has been divided ina 20 x 20 cells regular array, and we have counted thenumber of designs inside each cell. These counts have beendivided by the total number of computed designs obtainingthe relative frequency, which can be reasonably associatedwith the probability. This plot allows to saythat peaks of around 13.35 infected fallingbetween the 45.43 and 45.44 week are themost probable ones. We can conclude that,even if considering uncertainties in thetarget values, it is possible to estimate thespread of the disease with a reasonableaccuracy: it is certainly possible to excludecatastrophic scenarious even if few data areavailable. During the next weeks we will seeif the model presented in this work hasbeen able to correctly predict the spread ofthe swine flu or, on the contrary, if aterrible outbreak will happen. Let's hope forthe best and be optimistic!

ConclusionsIn this work we have shown how it ispossible to model the natural spreadof a disease, within a population,with relatively simple equations. Ifsome observed or measured data areavailable it is possible to tune themodel and predict the evolution ofthe disease with sufficient accuracyat macro scale.

The Scilab platform has been used tonumerically solve the ODEs systemand modeFRONTIER to tune themodel and manage the uncertaintieson available information. We wouldlike to emphasize that the

methodology adopted in this work can be used in the sameway, also in other contexts, when a prevision is needed andexperimental data are affected by errors.

References[1] http://www.scilab.org/ to have more information on

Scilab.[2] http://www.iss.it/iflu/ to have more information on the

italian sentinel surveillance. The data relative to theinfected have been downloaded here.

[3] http://www.ministerosalute.it to have a completedescription of the swine flu.

[4] http://www.wikipedia.com to have more information onthe SIR model.

[5] P. Blanchard, R. L. Devaney, G. R. Hall, DifferentialEquations, (2006) Thomson Brooks/Cole, 3nd ed.

[6] K. S. Bhamra, O. R. Bala, Ordinary Differential Equations.An Introductory Treatment with Applications, (2003)Allied Publishers PVT. LTD.

For more information on this document please contact theauthor: Massimiliano Margonari - EnginSoft [email protected]

Figure 6: The peak is plotted versus the peak position. The bubble color is used to represent the mortality.The cloud of points summarizes the simulated scenarious. It can be easily seen that even the worst previsionsin terms of peak and mortality rate have nothing in common with a pandemia or a catastrophic outbreak.

Figure 7: The frequency of the couples peak and peak position. The most probable scenarios are thosecharacterized by a peak of around 13.35 infected falling around the 45.44 week of the year.


New trends in High PerformanceComputingNew hardware and software technologies can reduce costsand computational time very effectively. In order to haveproductive clusters, the right choice of operating system,computer hardware, interconnection and disk storage iscrucial. Moreover, also deployment and support forcomputational software installation must be taken intoaccount in order to have cost-effective solutions which willnot become a nightmare for users and administrators.

Operationg system and queue systemTwo worlds: Linux with Perceus project and Microsoft HPCServer 2008 are the leading edge technologies for developinga cluster solution.

PerceusPerceus is the next generation cluster and enterprise tool kitfor the deployment, provisioning, and management of groupsof servers. Employing the power of the Perceus OS andframework, the user can quickly suggest a machine out of thebox. Perceus truly makes the computer a commodity, allowingan organization to manage large quantities of machines in ascalable fashion.Perceus is developed and provided to the world under theGNU GPL by Infiscale.com.

HPC Server 2008Windows HPC Server 2008 provides a productive, cost-effective, and high-performance computing (HPC) solutionthat runs on x64-bit hardware. Windows HPC Server 2008 canbe deployed, managed, and extended using familiar tools andtechnologies. It enables broader adoption of HPC byproviding a rich and integrated end-userexperience, ranging from the desktopapplication to the clusters. A wide range ofsoftware vendors, in various verticals, havedesigned their applications to workseamlessly with Windows HPC Server 2008so that users can submit and monitor jobsfrom within familiar applications avoidingto learn new or complex user interfaces.

The queue system: the heart of a clusterThere are several points involved in a queuesystem:

HOSTS• Master host – The master host is central

to the overall cluster activity. Themaster host runs the master daemonsge_qmaster. This daemon controls all

Grid Engine system scheduling and components, such asqueues and jobs. The daemon maintains tables about thestatus of the components, user access permissions, etc.By default, the master host is also an administration hostand a submit host.

• Execution hosts – Execution hosts are systems allowed toexecute jobs. Therefore, queue instances are attached tothe execution hosts. Execution hosts run the executiondaemon.

When using the VGL Image Transport (formerly "Direct Mode"), the 3D rendering occurs on theapplication server, but the 2D rendering occurs on the client machine. VirtualGL compresses the rendered images from the 3D application and sends them as a video streamto the client, which decompresses and displays the video stream in real time.

Tipical High Performance cluster architecture


• Administration hosts –Administration hosts are hostsallowed to carry out any kind ofadministrative activity for theGrid system.

• Submit hosts – Submit hostsenable users to submit andcontrol batch jobs only. Inparticular, a user who is loggedin to a submit host can submitjobs with the qsub command,can monitor the job status withthe qstat command.

QUEUESA queue is a container for a class ofjobs allowed to run on one or morehosts concurrently. A queuedetermines certain job attributes,for example, whether the job can bemigrated. Throughout its lifetime, arunning job is associated with its queue. The associationwith a queue affects some of the things that can happen toa job. For example, if a queue is suspended, all jobsassociated with that queue are also suspended. Jobs do notneed to be submitted directly to a queue. If you submit a jobto a specified queue, the job is bound to this queue. As aresult, the Grid Engine system daemons are unable to selecta better-suited device or a device that has a lighter load.

You only need to specify the requirement profile of the job.A profile might include requirements such as memory,operating system, available software, and so forth. The GridEngine software automatically dispatches the job to asuitable queue and a suitable host with a light executionload.

A queue can reside on a single host or can extend amongmultiple hosts. For this reason, Grid Engine system queuesare also referred to as cluster queues. Cluster queues enableusers and administrators to work with a cluster of executionhosts by means of a single queueconfiguration. Each host that isattached to a cluster queuereceives its own queue instancefrom the cluster queue.

License managementMost commercial software useFLEXLM (tm) license managementsystem to distribute licenses. Thecombination of licensing systemwith queue system has become inthe past months a serious matterfor mass intensive optimizationcomputation, as well for usersand system administrators.

Available licenses are checked inonly when the job has alreadyentered the queue system, thus atthat point is too late to deny alicense because of no more licensesavailable.

This is very disappointing for userscoming back from weekend to findtheir optimization job basically notdone over time, just because someother batch jobs where launced byother departments, or becausenetwork delays. The control of thissituation needs a very deepunderstanding how queue systemswork and interactions between allsystem components: customizationmust be well engineered to avoidinterferences between the licensemanager and the cluster.

We develop lots of custom scripts for SunGridEngine (fullyplatform independent, portable to Microsoft cluster system)to solve this problem and to make queue jobs start at righttime, allocating the right licenses and sub-licenses.There will be a 0.1% of cases where this procedures will notwork, spawning job at the wrong time, but this is a sideeffect of communication among daemons (queue,system,cluster etc..) that could not be taken away.

Parallel applicationsThe development of parallel programs requires integrateddevelopment environments along with the support fordistributed computing standards. Visual Studio 2008 providesa comprehensive parallel programming environment forWindows HPC Server 2008. Besides supporting OpenMP, MPI,and Web Services, Windows HPC Server 2008 also supportsthird-party numerical library providers, performanceoptimizers, compilers, and a native parallel debugger fordeveloping and troubleshooting parallel programs.


Common bottleneck sourcesAs the CAE industry continues an aggressive platformmigration from proprietary Unix servers to commodity HPCclusters, CAE models are becoming more realistic, too,requiring clusters to handle ever-increasing volumes of I/Oand the movement of large files.As organizations rapidly expand their cluster deployments,many encounter I/O bottlenecks when using legacy networkattached storage (NAS) architectures.

Initially, these NAS systems offered advantages such as sharedstorage and simplified IT administration which reduced costs,but today a few of them provide the scalability required foreffective I/O performance in parallel CAE simulations.Recently, a new class of shared parallel storage technology hasdeveloped to remove serial bottlenecks and to improve i/operformances, therefore extending the overall scalability ofCAE simulations on clusters.

Parallel storage is the leading solution of parallelNAS and enables the most advanced and I/Odemanding CAE challenges to become practicalapplications. Some examples include the high-fidelity transient CFD, large eddy simulation(LES), aerocoustics, large DOF structural dynamicresponse, parameterized non-deterministic CAEsimulations for design optimization and thecoupling of CAE disciplines such as fluid-structureinteraction (FSI). CAE workflows areoverburdened with lost productivity whenengineers and scientists must wait for serial I/Ooperations and large file transfers to complete.Furthermore, as simulation and workflowperformance degrades, so does CAE analystefficiency and effective workgroup collaboration.A parallel storage eliminates the I/O bottleneckswith a cost-saving solution that restoresproductivity and drives analyst creativity.

The benefits of parallel I/O for transient CFD weredemonstrated with a production case of an ANSYSaerodynamics model of 111M cells, provided by

an industrial truck vehicle manufacturer. Figure 2 below,illustrates the I/O schematic of the performance tests thatwere conducted, which comprised a case file read, a computesolve of 5 time steps with 100 iterations and a write of thedata file. In a full transient simulation the solve and writetasks would be repeated to a much larger number of time stepsand iterations, and with roughly the same amount ofcomputational work for each of these repeatable tasks.

It is important to note that the performance of CFD solversand the numerical operations are not affected by the choice ofthe file system, which only performs I/O operations. That is, aCFD solver will perform the same on a given cluster regardlessof whether a parallel or serial NFS file system is used. Theadvantage of parallel I/O is best illustrated in a comparison ofthe computational profiles of each scheme. ANSYS CFD 12 onPanFS keeps the I/O percent of the total job time in the rangeof 3% at 64 cores to 8% at 256 cores, whereas 6.3 and NFSspend as much as 50% of the total job time in I/O.

Visualization and PostprocessingAnother relevant matter of large cluster is visualization andpost-processing of results on relatively slow networks. Aneffective solution is performing 3D renders with openGL insidethe cluster and giving the client the possibility of remoteDisplay.

VirtualGL is an open source package which gives any Unix orLinux remote display software the ability to run OpenGLapplications with full 3D hardware acceleration. Some remotedisplay software, such as VNC, lacks the ability to run OpenGLapplications at all.

Large model with non-linear material and deformations example solved on a64 nodes cluster system

Tipical cluster management system and visualization nodes


Other remote display software forces OpenGL applications touse a slow software-only OpenGL renderer, to the detriment ofperformance as well as compatibility. The traditional methodof displaying OpenGL applications to a remote X server(indirect rendering) supports a 3D hardware acceleration, butthis approach causes all of the OpenGL commands and 3D datato be sent over the network to be rendered on the clientmachine. This is not a tenable proposition unless the data isrelatively small and static, unless the network is very fast andunless the OpenGL application is specifically tuned for aremote X-Windows environment.

With VirtualGL the OpenGL commands and 3D data are insteadredirected to a 3D graphics accelerator on the applicationserver and only the rendered 3D images are sent to the clientmachine. Thus VirtualGL "virtualizes" 3D graphics hardwareallowing it to be placed in the "cold room" with compute andstorage resources. VirtualGL also allows the 3D graphicshardware to be shared among multiple users and provides"workstation-like" levels of performance even on the mostmodest of networks. This makes it possible for large, noisy, hot3D workstations to be replaced with laptops or even thinnerclients. More importantly, however, it is the fact that VirtualGLeliminates the workstation and the network as barriers to thedata size. Users can now visualize gigabytes and gigabytes ofdata in real time without needing to copy any of the data overthe network or sitting in front of the machine that is renderingthe data.Usually, a Unix OpenGL application would send all of itsdrawing commands and data, both 2D and 3D, to an X-Windows server which may be located across the network fromthe application server. VirtualGL, however, employs a

technique called "split rendering" to force the 3D commandsfrom the application to go to a 3D graphics card in theapplication server. VGL performs this by pre-loading a dynamicshared object (DSO) into the application at run time. This DSOintercepts a handful of GLX, OpenGL, and X11 commands thatare necessary to perform the split rendering. Whenever awindow is created by the application, VirtualGL creates acorresponding 3D pixel buffer ("Pbuffer") on a 3D graphicscard in the application server. Whenever the application requests that an OpenGL renderingcontext have to be created for the window, VirtualGLintercepts the request and creates the context on thecorresponding Pbuffer instead. Whenever the applicationswaps or flushes the drawing buffer to indicate that it hasfinished rendering a frame VirtualGL reads back the Pbufferand sends the rendered 3D image to the client.

For further information:Ing. Gino Perna - ICT [email protected]

An example of a mesh generation for a reactor pressure vessel, 11 million nodes and 35 million DOFs.

Enginsoft provides all ranges of HPC solutions: from readyto use systems to dedicated HPC setup for specific needsin the simulation market.Enginsoft expertize ranges from system configuration,queue control, monitoring tools, licensing integration andetherogeneous systems building to maintain clusterefficiency along time.Also integration with parallel file systems and remotegraphic system is under continuous monitoring to provideour customers with the best of class solutions.


Development of Digital MechatronicApplications using Co-SimulationThe ever decreasing size and cost of embeddedmicrocontrollers have brought digital electronic equipmentto be used in almost every physical process or machine. Inthe real world, the software that runs on the microcontrollersactually implements the logic, the decision making and thecontrol functionality of industrial processes, transportation

systems, machine tools and electrical appliances in general.Moreover, the availability of low-cost sensors and actuatorsthat provide a multitude of physical quantities in variousfields to the electrical pins of a microcontroller, has madeembedded electronics a crosswise pervasive ingredient tomany engineering applications.

In this context, a computer program (usually written in Clanguage) becomes effectively a component of theengineering application. Therefore, it must be designed,optimized and verified like any other physical component.Moreover, these engineering steps have to be performedtaking into account also the fine scale interactions that thisrunning software develops with the physical components. Infact, the validation of a system governed by microcontrollerscannot be approached without taking into consideration theembedded control firmware and, on the other hand, thevalidation of the firmware cannot be performed withoutconsidering its embedding physical system.

Therefore, the development of a digital mechatronicsapplication is a tricky mixture of physical and abstractphenomena, since the physics of the software execution aremostly unobservable in a physical experiment. In a computersimulation, instead, the execution of the microcontrollersoftware can be replicated exactly. Moreover, by adding amodel for the simulation of the physical system (such asthose commonly used in the FE-based design), a detailedevaluation of the interaction between the embedded softwareand the physical system becomes possible.

SimNumerica s.r.l. is targeted at the exploitation of muLab,the Microcontrolled Systems Simulation Laboratory, aprototype of which has been developed and widely tested atthe University of Padua by a team of experts in numericalmathematics, electronics and software. muLab has been

tested in a variety of pilot projects, which have alreadyclearly demonstrated the advantages offered by muLabcompared to general purpose platforms for the developmentof numerical algorithms and the hardware-in-the-loopapproach.

muLab performs the co-simulation of the embedded softwaredirectly in the binary format which is executable by themicrocontroller. In this way, the production software can bedesigned and tested well before the hardware prototype isavailable. Moreover, when the final product is available, amuch larger set of functional tests can be performed in theco-simulation model, with respect to those feasible in aphysical laboratory.

With muLab, firmware people and mechanical engineersbecome aware of their mutual responsibilities concerning thefinal performance of their design activity. This is importantsince, in principle, software components are notunderstandable to mechanical engineers and, vice versa,electronics engineers often are not adequately familiar withmechanical components.

FEA and muLabFinite Element Analysis and the co-simulation implementedin muLab have the same DNA in common: they reveal thedetails of physical phenomena occurring at various space andtime scales. In this way, they allow to observe theinteractions between a software running on a microcontrollerand its embedding physical system, with an approximationlevel decided by the user.

In the same digital mechatronics application, the time-scalesinvolved may be quite distant from each other, e.g. firmwareinstructions are executed in microseconds or less, digitalelectronics signals present a milliseconds time base,kinematic/dynamic variables evolve in centesimal fractions ofseconds and thermal variables evolve in several seconds.

For this reason, we use the term Computational DigitalMechatronics when we refer to this type of co-simulation. Itinherits all the numerical engineering aspects ofcomputational mechanics, plus:• the co-simulation of a multiphysical engineering system

and of the digital embedded hardware/software thatinteracts with this system;

• the numerical analysis of the algorithms implemented inthe embedded microcontroller software (firmware), thatruns within the numerical simulation model of the wholesystem.

SimNumerica s.r.l. and his FE partnerEnginSoft s.r.l. outline their approach to thevirtual prototyping of systems where anembedded microcontroller controls amultiphysical process or a machine.


muLab is a fundamental tool for a large variety ofapplications designed with FEA. Indeed, even in simplemechatronics applications, such as the temperature controlof an air-conditioned railroad car (Figure 1), the algorithmicfunctionality implemented in a microcontroller may be quitecomplex. In general, it has to:• read the temperature sensors and filter/compensate

electrical disturbances and physical deficiencies of thesensor (nonlinearities, thermal inertia, condensed vapour,etc);

• infer the temperature at the user site; this is usually anindirect measurement, since the sensor can only beplaced in hidden locations, which is performed by analgorithm that uses a numerical model of the process topredict the unknown quantity; the numerical model musttypically have low computational cost and it is built byusing emerging numerical methods in engineering, suchas model order reduction, system identification, machinelearning.

• implement the logical behaviour required by the machinedesign; this is usually a rather complex set of functionsand procedures that covers machine initialization andconfiguration, manual or self-diagnosis, differentoperational modes, failure recognition and safe reaction,etc.

• control the actuators according to the specifications; thisusually involves algorithms to safely operate, optimizeand monitor the physical actions performed by actuatorsand related subsystems.

These algorithmic functionalities are easy to implement andverify in muLab, especially when they require the support ofa numerical model. In particular, system identification andmachine learning, which are based on the comparisonbetween model predictions and experimental data, will bealgorithmically supported explicitly in the near future.

MuLab: the software toolThe main feature of the software tool muLab is thesimulation-based prototyping and validation of algorithmsthat should run on the microcontrollers embedded in avariety of digital mechatronics systems. The approachfollowed by muLab is hardware software co-design.A main ingredient is the ability to monitor the functional

behaviour of the system up to the finest scale detail. To dothis efficiently, muLab offers to the user the possibility towrite a multi-level ensemble of debug procedures (Figure 2)that renders this monitor activity fully automatic during thesimulation. This is very important because the user typicallywants the computer to do hundreds of simulations during thenight. The language used to write the debug procedures is aslight customization of the simplest programming languagesactually used in computer programming.

Moreover, muLab is a collaborative design tool: thedevelopment of physical models becomes visible tothe firmware designer and the firmware behaviourbecomes visible to the mechanical engineer (Figure3). As a consequence, the firmware developmenttakes place in parallel with the hardwareconstruction and fits to it.At the same time, the physical system structure andorganization can be cheaply modified until theexpected performance appears to be adequate.

The environment includes also a source codedebugger (Figure 4) that works both for the

numerical models of the physical components and for theembedded software (firmware). The possibility to set abreakpoint during the simulation of a mechatronic systemallows a deep understanding of the interactions between thefirmware and its embedding physical system.

It allows the numerical analysis of algorithms that run onembedded microcontrollers, i.e. running in a non-sequentialmode. This is usually much more difficult than it is for FEnumerical methods. In fact, their execution is intrinsicallynon-sequential and may actually involve several subtasksexecuted by routines which are activated by interruptscaused by non-deterministic (and sometimes only looselypredictable) events.

Last but not least, muLab uses Standard and open languagesand data formats:• component model equations may be written in Python.• model structures and user procedures are coded in XML.

Figure 1

Figure 2


Advantages: reduced experimentation costs anddevelopment timemuLab enhances firmware debugging and simulation-basedrobust design. This is accomplished through the specificationof detailed Test Sequences (Figure 5) by which the user can:• specify complex test sequences;• track and identify firmware fault conditions;• Implement failure mode analysis (FMEA) of the hardware

components.

The automation of test sequences allows the user to verifythe application functionality in a large variety of situations,much larger than what is physically possible. Moreover, • the experimental test phase can take place selectively

and on a relatively mature firmware, where a large numberof bugs has already been removed;

• the quality and value of the firmware verificationprocedure increases, while the debugging time decreases.

Thus, time, energy and money can be saved. Practical issues concerning the multi-level debugging of thefirmware:

• one advantage of the numerical simulation compared to acorresponding physical experiment is that the former isdeterministic, and hence repeatable, while the latter isnot;

• the methodology implemented in muLab supports a user-defined ensemble of debug procedures that monitor thenumerical simulation: if something is suspect, a debugprocedure can restart the simulation with increasinglevels of diagnosis. In this way, following the diagnostictree, the details of a wrong behaviour of the system canbe traced at affordable time and computational cost.

Future DevelopmentIn a future release, additional parallel computing capabilitieswill be integrated in the software package. In particular,multi-core platforms and graphical processors (GPGPU) willbe supported. The target is an efficient co-simulation ofcomputational intensive models, such as large-scale dynamicFEM models, and of large firmware codes, in particular theones involving the control of processes whose durationextends to relatively large time-scales. The combined use ofmulti-core CPUs and GPUs makes computational digitalmechatronics affordable to small industrial engineeringteams, even for quite complex applications.

ContactFabio Marcuzzi, PhD - Simone Buso, PhDSimNumerica s.r.l., Pordenone - Italyemail: [email protected]

Figure 3

Figure 4

About SimNumerica and EnginSoftSimNumerica was founded by a dedicated research team, allexperts with broad experiences in numerical mathematics,electronics and software design, of University of Padua –Italy. SimNumerca’s industrial partner and co-founderEnginSoft is an international CAE Computer-AidedEngineering Consulting company with uniquemultidisciplinary competencies in virtual prototyping.SimNumerica’s joint expertise is focused on environments forthe virtual prototyping of mechatronics systems based onmicro-controllers.

Figure 5


Innovation and EnginSoft in the USASUNNYVALE, California – December 10, 2009 - StefanoOdorizzi, CEO of EnginSoft, has recently returned from a tripto the USA and has reported that recruitment, sales, andexpansion plans are moving forward rapidly.

EnginSoft CEO strengths connections with the US marketEnginSoft is continuously strengthening its connections andnetwork in the US market. Stefano Odorizzi visited the UnitedStates in the last week of October to view and developEnginSoft's local initiatives further. He met and interactedwith several existing clients, and thus gained insights intohow EnginSoft's services have benefited their businessmodels.During his visit, Stefano wanted to discuss with US customerstheir visions for future product development, their concernsand existing alternatives to develop efficient workingmethodologies between clients and the EnginSoft teams. Hemanaged to share EnginSoft's philosophy and business modelwith all the people he met during his short visit, and stated,"I am pleased to report that our initiatives in California aremoving forward and that there has been an incredibleamount of interest and enthusiasm shown by the localmarket. I had the pleasure of reviewing our operations andmeeting with our management staff to discuss the nextphases of our operations”.During this trip, Stefano met with some of the leadingexperts in the areas of Electronic Design Automation (EDA),Computational Fluid Dynamics (CFD), and DesignOptimization. Stefano emphasized the positive results whichcould be achieved to date in the American market despite thetough economic situation. He visited some of the world's topacademic institutions, namely University of California atBerkeley, University of Stanford, and the University of SantaClara. These relations will support the company to furtherdevelop its future technologies and strategies. Stefano's visitwas very successful and is a milestone inEnginSoft's roadmap. The outcomes will be incorporated in the company’spartners' network and business sectors.

EnginSoft at UC Berkeley - Prof. Stefano Odorizzi meetswith Prof. Alberto Sangiovanni VincentelliDuring his visit at the University of California at Berkeley, theEnginSoft CEO met with Professor Alberto Sangiovanni

Vincentelli, a worldwide renowned expert and cofounder ofCadence and Synopsys.The talk was a starting point for interaction and exchange ofCAE, EDA, and VP knowledge, development and application

results. The two experts sharedtheir visions for the future ofengineering simulation inindustry with a very positiveoutlook for the upcomingyears. With its highlyinnovative engineering andtechnology organization and network, EnginSoft wants tobecome an important player in the Global Computer AidedEngineering market fueling its growth also through closecollaborations with top academic institutions.

Prof. Alberto Sangiovanni Vincentelliholds the Edgar L. and Harold H. ButtnerChair of Electrical Engineering andComputer Sciences at the University ofCalifornia at Berkeley. Moreover, he is aco-founder of Cadence and Synopsys,the two leading companies in the areaof Electronic Design Automation. He is

the Chief Technology Adviser of Cadence, and a member ofthe Board of Directors of Cadence and the Chair of itsTechnology Committee, UPEK.

The University of California at Berkeley and itsflagship campus were founded in 1868.Berkeley ranks first nationally in the numberof graduate programs in their espective fields.Among its active faculty are 7 NobelLaureates, 28 MacArthur Fellows, and 4 Pulitzer Prizewinners. Today it is the world's premier public university anda wellspring of innovation.

EnginSoft special guest at the Business Association ItalyAmerica - BAIAIn this successful networking event organized by BAIA, Prof.Stefano Odorizzi presented and discussed the capabilities of

Newsletter EnginSoft Year 6 n°4 - 47leading edge technologies used to provide improvedengineering designs across various innovative applications.

Stefano shared the key factors that have led to his success asan Italian entrepreneur building a US and Global business, as

well as the crucial role played by global partnerships withboth companies and universities. This talk turned out to bea great opportunity to mix and mingle with young andseasoned professionals, entrepreneurs, students, and all theextended BAIA community, while enjoying Italian wine anddelicious appetizers.Stefano participated in an animated and dynamic roundtablediscussion with students of the Fulbright BEST grouppursuing the Certificate of the Technology Entrepreneurshipprogram offered by the Center for Innovation &Entrepreneurship (CIE) of Santa Clara.

BAIA is an independent,nonprofit, open, apoliticalbusiness network that offers aplace (physical and virtual) tofacilitate the open exchange of

knowledge and information, business opportunities,relationships and to promote a culture of innovation throughentrepreneurial spirit and principles for Entrepreneurs,managers, professionals and interested individuals in theUnited States and in Italy. For more information, please visithttp://www.baia-network.org/

EnginSoft at Stanford - Several Points in CommonStefano also met with Prof. Gianluca Iaccarino of StanfordUniversity. The meeting turned out to be a pleasant talkbetween two people who share an enthusiasm for innovationand excellence. EnginSoft and Stanford both act aslaboratories for technology transfer to industry. They stronglyinvest in the next generation of engineering and technologyexperts, to foster their growth and dynamism, a perfectcombination for a future collaboration. The obvious synergybetween Stanford and EnginSoft will provide our customerswith even more innovative solutions to meet industrialchallenges, such as increasing quality and reducing projecttimes.EnginSoft provide access to a range of services related to thecalculation and optimization of thermo-fluids, unmatched to

date by any other European or American CAE company.Prof. Iaccarino and Prof. Odorizzi discovered that they havea lot of interests and business objectives in common. A partfrom the high technological content of their meeting andtalks, both are aware that great networking opportunities are

indispensable to realize innovative visions.Please stay tuned for upcoming news in the NewsletterEditions of 2010 and on www.enginsoft.com

Stefano Odorizzi also met with Stanford Professor BernardWidrow. In fact, the first statement of Professor Widrowwas: “Optimization is everywhere," certainly a great startfor a sparkling conversation! The two gurus exchanged

ideas about the use of optimization techniques applied tohuman-like memory computers while enjoying tea. Prof.Widrow underlined its outstanding ability and talent fordescribing his most complex research at Stanford with simplewords.Silicon Valley represents a unique blend of knowledge,advanced research, remarkablecapital investments, and expertise. All this makes SiliconValley an ideal and unique place to do business.

Prof. Gianluca Iaccarino is an AssistantProfessor at the Mechanical EngineeringInstitute for Computational MathematicalEngineering at Stanford University withmany years of experience in fluid dynamics,physical modeling and advanced computersimulations.

Prof. Bernard Widrow'sresearch at Stanfordfocuses on adaptivesignal processing,adaptive control systems,adaptive neural networks,human memory, andhuman-like memory forcomputers. He is thecoinventor of the Widrow-Hoff Least mean squares filter(LMS) adaptive algorithm with the doctoral student Ted Hoff.The LMS algorithm led to the ADALINE and MADALINEartificial neural networks and to the back propagationtechnique. He has more than 21 patents under his name.

Stanford University is located between San Francisco and SanJose, in the heart of Silicon Valley, it is world-known for itsmultidisciplinary research within its schools anddepartments, as well as its independent laboratories, centersand institutes. There are currently more than 4,500 externallysponsored projects throughout the university,

with a total budget for sponsoredprojects of $1.060 billion during2008-09, including the SLACNational Linear Laboratory(SLAC).


BENIMPACTBuilding’s ENvironmental IMPACT evaluator & optimizerBENIMPACT is a research project co-funded by the autonomousProvince of Trento (Northern Italy) by means of the ERDF(European Regional Development Fund), whose prioritiesinclude research, innovation, environmental protection andrisk prevention. The duration of the research activities isforeseen to be a couple of years.BENIMPACT mainly aims at the development of methodologies(and of a related prototypical software platform) to supportarchitects and engineers in the design of eco-sustainablebuildings. The methodology shall be used to optimize thedesign of green buildings and will allow to identify theoptimal trade-off between costs and environmentalperformances of the buildings.The research activities will be carried out by EnginSoft and abunch of authoritative partners: the Department of Civil andEnvironmental Engineering of the University of Trento,DTTNhabitech and the Trentino Institute for Social Housing.EnginSoft has carefully chosen the partners on the basis oftheir specific knowledge and their contribution to the researchactivities: the University of Trento will share its long-timeexperiences related to energy modeling tools andmethodologies; DTTN-habitech, a consortium of more than 300

companies operating in the green-building trade, will supplythe required linkage with the market and their deep knowledgein green building rating tools (such as LEED, Green Star,BREEAM, etc.). The Trentino Institute for Social Housing, thepublic organization of the Province of Trento that managesand develops public residential housing projects, will bring tothe project group also the views of today'sbuilding designers.

The design methodology which will be definedduring BENIMPACT, will allow to carry out anintegrated building design process: all the stepsrequired to achieve the design of a green buildingwill be contemporary realized by meansof a bunch of analysis tools reciprocallyintegrated into each other. This approach willsignificantly innovate traditional ones: in fact,nowadays,each different building design topic iscompleted independently by differentprofessionals andin different design stages, thus leading to thedefinition of the building design parameters by

means of subsequent steps and to buildings that are notoptimal in relation to all the required objectives.However, now with BENIMPACT, the use of the advancedmodeFRONTIER technology will allow to build a suite ofintegrated applications (the BENIMPACT suite), that interactin a typical design chain process. Figure 1 shows the foreseenarchitecture of the design suite that will be implemented (ina prototypical release) in BENIMPACT. The shown architectureforesees the cooperation of core modules, databases andservice modules (green design solutions and targets settingmodules).In particular, the core modules are the embedded applicationsof the suite in charge of carrying out the whole calculationsand analyses. The multi-objective optimization module isactually the kernel of the whole suite: thanks to themodeFRONTIER functionalities, it will lead the search for theoptimal design features of the building, supplying a designenvironment where all the other applications are integrated.The geometric modeling module will translate the geometry ofthe building into a parametric model, able to storeinformation related both to the building shape and materials,components and systems that will constitute the buildingconstruction. The energy modeling module will evaluate theenergetic consumption of the designed building, taking intoaccount the thermal loads required in order to guaranteepredefined indoor comfort levels. The LCA (Life CycleAssessment) modeling module will calculate the environmental

EnginSoft al METEF2010Anche quest’anno EnginSoftprenderà parte alla Metef-Foundeq, l’ottava edizionedell’expo internazionale di riferimento dell’alluminio e deimetalli tecnologici in parallelo a Foundeq Europe expointernazionale degli impianti, attrezzature e prodotti dellafonderia metalli. La manifestazione con cadenza biennale, a cuiEnginSoft ha sempre partecipato, è in programma al CentroFiera del Garda, a Montichiari, in provincia di Brescia, dal 14 al17 aprile 2010.

EnginSoft presenzierà all’evento con uno proprio standall’interno dell’area fieristica. In questa edizione verrannopresentate le nuove releases di MAGMA, FORGE e ADVANTEDGE.

Nella scorsa edizione, nel 2008, la fiera ha registrato lapresenza di 568 aziende espositrici (di cui 396 italiane e 172estere), inoltre la cifra dei visitatori, provenienti sia dall’Italiache dall’estero, ha raggiunto quasi quota 19000.

Si preannuncia quindi un evento di grande successo, arricchitoda interessanti appuntamenti quali: • una tavola rotonda a cura del Comitato Laminazione nella

prima giornata denominata: “Il futuro della laminazionedopo la crisi: l'innovazione come chiave per vincere le sfidedel mercato”,

• la presentazione del nuovo "Manuale di difettologia"intitolato “Difettologia dei presso colati” organizzato daAIM – Associazione Italiana di Metallurgia, Centro StudiPressocolata

• la presentazione dei risultati del progetto europeo NADIA"New Automotive components Designed for a manufacturedby Intelligent processing of light Alloys" coordinato daEnginSoft

• una conferenza internazionale organizzata da ITmetal.it eda CSMT Centro Servizi Multisettoriale e Tecnologicointitolata “ICT e settore dell’alluminio: quali formule per ilsuccesso”.

Sito della manifestazione: www.metef.com

Newsletter EnginSoft Year 6 n°4 - 49impact of the building during its entire life, and hence alsoconsider the impacts that arise from resources extraction,manufacturing, on-site construction, occupancy/maintenance,demolition and recycling/reuse/disposal. The LCC (Life CycleCosting) modeling module will evaluate the costs of thebuilding, totaling up in a unique value the complete costs forthe building construction, its maintenance, occupancy (i.e. thecosts for energy consumption) and demolition.It is important to note that all the core modules will be softwareapplications (customized or implemented by means of ad-hocwritten codes) that will work also in a stand-alone modality inorder to allow the validation of each single application.Furthermore, it is possible that, for some particular applications,such as energy modeling, some existing codes will offer therequired functionalities: In such cases, freeware tools and open-source codes will be preferred to commercial ones, in order toallow further implementations and improvements by the wholecommunity of practice.The databases included in the BENIMPACT suite will supply therequired input data to all the applications involved. They willstore data related to the systems and components of thebuilding constructions and to the energy production systemsnormally used in buildings (such as boilers, solar andphotovoltaic panels, geothermal heat exchangers, etc.). Theywill also supply technical constraints, derived by the currentbuilding laws, and the required meteorological data.The service modules' green design solutions and target settingswill supply border information to the analysis: the former,operating as an expert system, will suggest solutions for thegreen building design (such as green roofs, natural ventilation,externally ventilated façade, etc.), while the latter will translate,in an engineering format, the design objectives set by the user(for example, the design objective of low energy consumptionshould be translated, for the sake of the numerical analysis, intoa defined value of Watts required per square meter of thebuilding).EnginSoft strongly believes that the activities which will becarried out in the framework of the BENIMPACT research projectwill bring benefits to the building trade, thanks to the tuning ofbrand-new CAE tools that will eventually improve the greenbuilding design. Moreover, BENIMPACT will help to protect theenvironment, it will allow and promote the diffusion of eco-sustainable buildings based on the definition, during the designphase, of the building features that guarantee low-environmental impacts and, at the same time, low life-cyclecosts of the building. Last but not least, EnginSoft itself willtake advantage of the BENIMPACT research activities: enhancingits knowledge related to green building techniques, the companywill be able to expand its market to this emerging sector,offering its engineering consultancy services, specific softwareand educational program to new clients in in the eco-sustainablebusiness, that seems to be thriving and not suffer fromeconomic downturns.

For futher information, please contact:Ing. Angelo Messina - R&D [email protected]


Continuing Higher Education on CAE:The TCN ConsortiumBorn in 2001, TCN Consortium is a private Italian companywhich organizes higher education activities in theengineering and CAE (Computer-Aided Engineering) fields.

The specific objective of TCN is to train the key resources,that ensure competitiveness to companies in eachtechnological sectors fundamental to process and productinnovation. The TCN motto – “training innovation leader” -embodies this objective.

The TCN Consortium has been working for many years in aprofessional and reliable way; moreover, it supports theentrepreneurship and the training managers in projectingand distributing customized training trails. The TCN efficientand agile approach is based on surveyingenterprises’ real educational needs to beconverted into customized training trails:TCN Faculty, teamed by professors inItalian and foreign Universities togetherwith experienced researchers andengineers, represents the key to achievethis goal.

TCN helps the enterprises to face theinnovation challenges, enabling them toface an ever-changing industrial andtechnological landscape, transferring thenecessary knowledge to create highly qualified humanresources, that will immediately work in the industrialenvironment.

TCN Consortium offers courses from the catalogue and on-demand courses for entrepreneurship. In particular, TCNoffers:

• Short Courses (1 to 5 days)• MiniMaster (intensive training over two non-consecutive

weeks)• On-demand training via the Internet• Publishing of manuals for the industry (TCN SBE&S Series)

TCN maintains a strong European and international identity:every two years it organizes “TCN CAE International

Conference on Simulation BasedEngineering and Sciences”, aninternational conference based on theCAE technologies in the industry.Furthermore, TCN takes actively part inEurope to pilot projects aimed atdesigning innovative higher educationcontents and training trails for theindustry.

On the website www.consorziotcn.it it ispossible to consult the up-to-date TCNcourses catalogue for the 2010, which is

constantly enlarged and updated on the entrepreneursdemand. Nevertheless, this is just a general view of the TCNtraining offer.

For further information and requests, please contact: TCN Consortium organizing secretary Mirella PrestiniPh. +39 035 368711 – [email protected]


Analizzare cinematica e dinamica deimeccanismi con le tecniche multibody:terminologia, ambiti di applicazione edopportunità

Le scuole di progettazionepiù tradizionali portano aconsiderare con maggiorfrequenza problematiche ditipo strutturale (incluse fa-tica ed acustica), fluidodi-namico, o di processo. Glistrumenti di simulazionenumerica offrono, in tuttiquesti ambiti, un aiuto for-midabile ed efficace, bennoto alla grande maggio-ranza degli utenti che han-no una cultura ingegneristi-ca moderna orientata all’ef-ficienza.

La progettazione meccanica è tuttavia un contesto dove pos-sono diventare decisivi i fattori non analizzabili dalle suddet-te branche della simulazione. Si pensi, per esempio, alle ca-ratteristiche di guidabilità di un veicolo, alla stabilità diuna lavatrice, alla precisione di un cambio da bicicletta, perrestare su applicazioni che riguardano la quotidianità. Allostesso modo potremmo citare la velocità delle macchine perla produzione e la lavorazione su larga scala di qualsiasi pro-dotto “consumer” (per esempio tessile, carta, alimentari, se-milavorati), senza dimenticare i complessi sincronismi na-scosti all’interno di qualsiasi mezzo di trasporto (per esem-pio auto, treni, aerei).Tutte queste applicazioni sono accomunate da requisiti eprestazioni che non sono esclusivamente di tipo struttu-rale. La disciplina che fornisce questo tipo di risposte è lameccanica applicata, che studia la cinematica e la dinamicadi sistemi di corpi variamente interconnessi. Cinematica eDinamica sono termini di uso comune, ma sono spesso uti-lizzati in modo poco corretto. Senza addentrarci in eccessiviformalismi, precisiamo che l’analisi cinematica determina ilmodo in cui si muovono i corpi di un sistema (posizioni, ve-locità, accelerazioni) in relazione agli azionamenti (motori,camme) e ai vincoli. Viceversa, l’analisi dinamica determinale forze e le coppie che sono causa e/o effetto del movimen-to. In alcuni problemi è sufficiente limitare lo studio alla par-te cinematica (ad esempio per la verifica di sincronismi e/odi possibili interferenze), mentre nei casi più generali è ne-cessario completare le indagini con la determinazione delleforze in gioco (ad es. per trasmetterle allo strutturista o perscegliere componenti da catalogo).

Gli strumenti di simulazione adatti a condurre queste parti-colari analisi sono i cosiddetti software multibody.All’interno di un ambiente multibody l’utente assembla vir-tualmente il sistema meccanico e procede con l’analisi dellarisposta nel dominio del tempo e/o delle frequenze. I codicicommerciali offrono la possibilità di interagire direttamentecon le geometrie CAD, a vantaggio dei tempi di modellazio-ne e della qualità di visualizzazione. Per applicazioni di nic-chia e per scopi di ricerca si utilizzano, tuttavia, efficace-mente anche approcci prettamente analitici, con i quali ilmodello viene definito attraverso scrittura diretta delle equa-zioni di moto.Indipendentemente dallo strumento utilizzato, il passaggiofondamentale per giungere a risultati corretti ed affidabilinella simulazione multibody è rappresentato dalla fase di“virtualizzazione” del modello fisico. Con “virtualizzazione”si intende l’approssimazione di un sistema meccanico reale(infinitamente complesso), con una collezione di oggetti nu-merici pensati per riprodurne moto e proprietà.La schematizzazione virtuale può avvenire in modo più o me-no raffinato, con conseguenze dirette sull’efficacia della si-mulazione. È compito del modellista scegliere le dimensioni,il grado di complessità e i dettagli del modello che vuolecreare, considerando simultaneamente gli obiettivi da rag-giungere, onere computazionale e il tempo a disposizione. Ilmiglior modello non è quello più dettagliato, ma quello cherisponde in modo più veloce ed esauriente alle esigenze.Questa regola, che vale in generale per tutte le dimensionidel CAE, assume un ruolo decisivo nella simulazionemultibody. Per queste ragioni è indispensabile provvedere aduna formazione teorico-pratica specifica per l’analista mecca-nico.EnginSoft propone un corso di modellistica multibody del-la durata di 2 giorni (2-3 Febbraio 2010, sede di Padova), ri-volto a tutti i progettisti che affrontano problemi di cinema-tica e dinamica. Il corso è pensato e strutturato in modo datrasmettere in tempi brevi le nozioni per poter poi in segui-to intraprendere le scelte per la modellazione multibody. Ilcorso sarà tenuto dal prof. Roberto Lot dell’Università diPadova in collaborazione con l’ing. Fabiano Maggio diEnginSoft.

Per informazioni sui contenuti consultare il sito del consor-zio TCN www.consorziotcn.itPer iscrizioni e informazioni generali consultare la sig.raMirella Prestini della segreteria del consorzio. E-mail: [email protected] - Tel: +39 035 368711

Automobile di Leonardo da Vinci (Codice Atlantico, f. 812r del 1478)


Interview with Mr Sakae Morita, GeneralManager, Marketing and Mr KentaroFukuta of ELYSIUM Co., Ltd. JapanWhat are your impressions of the EnginSoft InternationalConference 2009?Mr. Morita: Indeed, we brought back many new discoveriesfrom our first participation in the EnginSoft Conference. Ithas been particularly interesting to see that there are manyjoint efforts and activities between industry and theacademia and that lots of successes are actually linked tothese collaborations. Although we can see similar efforts inJapan, there is still a huge gap between industry and theuniversities. The attitude and openness in Italy and in thesurrounding countries in Europe seem to be very good.

Mr.Fukuta: Our time at the Conference in Bergamo was anextremely significant experience, more than I had anticipatedbefore our trip to Europe. Much to our surprise, we met manyparticipants from all over the world. This is one of thedifferences compared to CAE conferences in Japan. It’s greatto have the opportunity to actively exchange technicalinformation between organizations from different countries.

Mr.Morita: From Professor Stefano Odorizzi’s keynote speechand my personal conversation with him, I was particularlyimpressed by the fact that EnginSoft is expanding itsbusiness not only in Italy but also internationally and this inharsh economic times. At Elysium, we are keen to establish alongterm relationship with EnginSoft.

Apart from the Conference, did you have time to exploreItaly a bit?Mr.Morita: Luckily, we had enough time to stroll around in theold city of Bergamo and in Milan after the conference. Whatreally moved me is the deep history and the beautifulharmony between the past and modernity. These arememories I brought back from looking at the oldarchitectures and from our visits to some museums.

Mr.Fukuta: I will remember my first visit to Italy for along time to come. I was fascinated by the beautifullandscape of Bergamo and the wonderful dinner wehave enjoyed in a restaurant on one of the surroundinghills of the city.

Would you say that your presence, also as anexhibitor, at the Conference was effective?Mr.Morita: Certainly yes. There were quite a fewpositive discussions about our products and we couldgenerate some leads for our future business in Europe.I am really grateful to Ms. Barbara Leichtenstern forher deep considerations and to everybody at EnginSoft.

Mr.Fukuta: Thank you for all your support and for givingus such a good opportunity to meet the people ofEnginSoft and the audience of the InternationalConference.

This interview was conducted by Ms Akiko KondohConsultant for EnginSoft in Japan

Bergamo’s medieval Città Alta - Impressions photographed by Mr. Morita / Mr Fukuta inOctober 2009

Elysium Booth in the exhibition area


New Year Greetings fromJapan with best wishes from Akiko Kondoh

It has been a great pleasure to launchthe Japan Column in 2009. Sometimesinspiration is needed for productdesign and manufacturing. The sameis true for CAE. I hope that the newencounter in the EnginSoft Newsletter, between Japanese andEuropean (CAE) cultures, creates inspiration and motivation for2010.

In the New Year, Shogatsu is generally celebrated on the first3 days of January. In Japan, this is the most important periodto spend with family. Osechi-ryori are special side dishes whichwe enjoy on the first 3 days of the year. Osechi-ryori consist oftraditional ingredients in Japanese cuisine, all of them havespecial meanings. For example, sea bream (tai) should bringluck (medetai), herring roe (kazunoko) sends out “a wish forprosperity to our descendants”, and sea tangle roll (kobumaki)means “happiness” (yorokobu).

This Osechi-ryoriare arranged onthe Urushi, aJapanese lacquertiered box. Urushiis the coatingmaterial madefrom refined andprocessed lacquertree sap. Urushihas been used for

the last thousands of years. Indeed, Japanese lacqueringtechniques had improved rapidly at a time more than 1500years ago. The black shining Urushi became a traditional craftand nowadays it is widely used for tableware, fine furniture andmusical instruments. Urushi is resistant to humidity, heat, acidand alkali, but becomes depleted under extreme ultravioletirradiation or desiccation. This is why Urushi was not muchused for industrial products in the past. However, in recentyears, Urushi has attracted people’s attention not only in Japanbut around the world because of its unique glazing style andexcellent characteristics. Today, Urushi is applied to brand newareas of MONODUKURI*, for example for the interior of cars andairplanes and the exterior of various electrical products bycombining Urushi material characteristics and specificlacquering techniques.

*MONODUKURI: Japanese for manufacturing and Japan’s spiritfor excellence in manufacturing

modeFRONTIER at the 2009MADYMO Users Meeting inMelbourne

EnginSoft's partner inAustralia, ADVEAEngineering, hosted theirsemi-annual event “The2009 MADYMO UsersMeeting” in Melbourne,Australia on the 23rd &24th of November.The event attracted a wide-

range of engineers from the Asia Pacific region with a focus onautomotive active/passive safety, biomechanics, pedestriansafety and DOE/optimization.

Maciej Mazur, a University Student at the School of Aerospace,Mechanical and Manufacturing Engineering at RMIT, The RoyalMelbourne Institute of Technology, one of Australia’s originaland leading educational institutions, presented a DOE and anoptimization study of a cast-aluminium servo motor housing. In his presentation, Maciej detailed how he coupledsuccessfully modeFRONTIER with Catia and Abaqus for Catia tooptimize the housing for weight and stiffness.

For more information about this presentation and aboutmodeFRONTIER and CAE in Australia, feel free to contact Mr.Ryan Adams, email: [email protected], Manager ADVEAEngineering. www.advea.com

Optimization Training Star-CCM+ AND modeFRONTIERin Göteborg, February 23In cooperation with CD-adapco and FS Dynamics,EnginSoft Nordic willpresent a one-day hands-ontraining on optimizationwith modeFRONTIER andStar-CCM+. This training, tobe held in Göteborg onFebruary 23rd 2010, willteach how to automate and perform scripting of Star-CCM+analyses, and how to setup an optimization together withmodeFRONTIER. After an introduction and demonstration,training participants will be given a complete workshop towork through on their own. As such, they are expected to bringa laptop with Star-CCM+ for the exercises. After the workshop,the training will conclude with a discussion and a Q&A session.

For more information, please contact Adam Thorp at [email protected] or visit http://nordic.enginsoft.com


Il mondo della forgiatura a stampi aperti, della laminazione piana e circolare, si è datoappuntamento a Padova per fare il puntosulle tecniche più avanzate di ottimizzazionedi processo/prodotto.

Dopo il successo dei primi due appuntamenti di Lecco, il3 aprile, dedicato allo stampaggio a caldo di acciaio, e diBergamo, il 7 maggio, dedicato allo stampaggio a caldo dinon ferrosi (ottone ed alluminio), EnginSoft ha voluto de-dicare un pomeriggio al mondo della forgiatura a stampiaperti, della laminazione di prodotti lunghi e della lami-nazione circolare.

L’invito è stato accolto da quasi una cinquantina di rap-presentanti delle aziende più importanti in Italia che sioccupano di trasformazione di acciaio a stampi aperti oper laminazione, desiderosi di conoscere le più avanzate

tecniche di ottimizzazione di pro-cesso e prodotto.A fare gli onori di casa è stato PieroParona, Sales Manager di EnginSoft,con una descrizione delle moltepliciattività di EnginSoft nel campo del-la prototipazione virtuale e dellastrategicità dell’uso di queste tecni-che nell’ottica di riduzione dei co-sti.Si è entrati quindi nel vivo dell’ar-gomento con gli interventi dell’ing. Marcello Gabrielli,sempre di EnginSoft, che hanno riguardato le tecniche disimulazione numerica dei processi di stampaggio a stampiaperti e laminazione con il software Forge di Transvalor. Apartire da una analisi del modo attuale di progettare le se-quenze di stampaggio, si è costruito un percorso innova-tivo dove, grazie alla simulazione applicata ad esempi rea-li su particolari noti ai presenti, si sono evidenziati tutti ivantaggi concreti ottenibili. Le recenti modifiche apporta-te al software grazie ad EnginSoft ed agli utilizzatori ita-liani, consentono ora di simulare per lo stampaggio astampi aperti cicli anche molto complessi, con rotazioni

relative di pezzo e\omazze. Sono stati mo-strati esempi concreti diforgiatura, ricalcatura inchiodaia e con mazze,blumatura, compattazio-ne, sbozzatura, segnatu-ra, bigornatura, eviden-ziando per ciascuno di essi i risultati più significativi for-niti dall’approccio virtuale. Per un caso di riscaldo di unlingotto poligonale è stato mostrato un approccio di otti-mizzazione, ottenuto mediante l’integrazione conmodeFRONTIER, che ha consentito un risparmio di 4 ore dipermanenza in forno, garantendo comunque il riscaldo acuore del lingotto. Altrettanto significativi i risultati otte-nuti grazie alla simulazione del processo di tempra, in ter-mini di previsione delle fasi, durezza e distorsioni.

L’ing. Carlo Contri di Hydromec (www.hydromec.it) haquindi mostrato le novità dei propri impianti per la forgia-tura e la laminazione circolare, sottolineando come graziea Forge, utilizzato attraverso la collaborazione con

EnginSoft, per alcuni propri clienti,è stato fornito un servizio di co-design che ha consentito sia di va-lutare a priori se una macchina è ingrado di produrre un certo partico-lare, sia di ridurre significativa-mente i sovrametalli, fornendoquindi un servizio “chiavi in mano”ai propri clienti.

L’ing. Stefano Fongaro di FICEP(www.ficep.it) ha quindi mostrato come ha affrontato e ri-solto il problema del taglio delle barre mediante nuove se-gatrici ad alta velocità per barre fino a 800mm di diame-tro.

Ritornando a tematiche relative alla simulazione di pro-cesso, la parte relativa alla simulazione della laminazionedi prodotti lunghi è stata affidata alla testimonianza di unutilizzatore, la AFV Beltrame SpA (www.beltrame.it) diVicenza. A partire dai risultati della simulazione della sin-gola gabbia di laminazione, utili per una prima valutazio-ne della deformazione del materiale, si è passati all’anali-

Grande successo per il pomeriggiotecnologico - Forgiatura, Laminazione aCaldo di Prodotti Lunghi e LaminazioneCircolare: Simulazione dei Processi: NuoviSviluppi, Vantaggi e Prospettive –organizzato il 24 giugno a Padova daEnginSoft, con la presenza di AFV Beltrame,Hydromec, FICEP e DIMEG – Università diPadova.

Newsletter EnginSoft Year 6 n°4 - 55si di un treno completo di quattro gab-bie di laminazione per l’ottenimento diun profilo IPE. I risultati ottenuti perquesto particolare e per altri profili mo-strati (bulbo, cingolo, T80) hanno dimo-strato come la simulazione ha effettiva-mente consentito di valutare a priori lecorrette calibrature delle gabbie.Si è passati infine all’analisi del proces-si di laminazione circolare, per il qualesono state analizzate le fasi di forgiatu-ra e tranciatura dell’anello, risolte intempi molto rapidi grazie all’approccio 2D, e quindi la si-mulazione della laminazione vera e propria. Particolaritàdi questo processo è la moltitudine di cinematiche adot-tate per laminare (a rack assiale fermo o mobile, con conifermi o mobili, con rullo ad asse verticale o inclinato, fer-mo o mobile) ed inoltre le cinematiche stesse sono funzio-ne della crescita dell’anello. Nella pratica si definisconodelle curve di laminazione nel software del laminatoio edi tool si muovono di conseguenza. Grazie alla flessibilitàdi Forge nella definizione delle cinematiche, si è mostratocome forge riesca a replicare in modo molto accuratoquanto avviene nella realtà, aspetto questo dimostratocon esempi partici di laminazione di anelli di geometriadalla più semplice, rettangolare, alle più complesse, peranelli profilati, sagomati, flange e rulli. Non meno interes-sante è stato l’intervento del dott. Andrea Ghiotti del DI-MEG – Università di Padova (www.dimeg.unipd.it) che hamostrato le attività del DIMEG nella simulazione, tramite

Forge ed un approccio a reti neurali, della distorsione de-gli anelli nelle fasi di raffreddamento.A completare la sezione tecnica, una dimostrazione dal vi-vo di utilizzo di Forge, curata dall’ing. Andrea Pallara diEnginSoft, che ha impostato il caso di una sequenza di fu-cinatura e stampo aperto ed una laminazione di un anelloa sezione rettangolare. La demo live ha evidenziato comequesti strumenti siano ormai molto facili da utilizzare, sianella fase di preparazione delle simulazioni, che nella fa-se di interpretazione dei risultati.

Un appuntamento importante, dicevamo, dove alle presen-tazioni previste in agenda è seguito un partecipato dibat-tito tra i relatori ed il pubblico, dal quale è emerso comelo strumento sia già molto maturo per quanto riguarda letematiche di forgiatura. Per quanto riguarda la laminazio-ne circolare, l’aspetto critico sembra essere la precisione

con la quale si riescono a modellare le curve di laminazio-ne reali, in modo da prevedere comportamenti anomali delmateriale durante il processo. Forge è stato migliorato inmodo importante per questi aspetti specifici, grazie allacollaborazione con dei produttori di laminatoi.Volendo sintetizzare, quanto mostrato nel workshop ha di-mostrato come questi strumenti siano realmente in gradodi dare una maggior coscienza del proprio modo di produr-re e come le esperienze fatte con Forge siano utili sia a farcrescere molto rapidamente chi si avvicina a questo mon-do, e a far diventare “patrimonio aziendale” le proceduredi stampaggio ottimizzate in tal modo. Ultimo aspettonon meno importante è il fatto che, grazie ai concreti van-taggi ottenibili, è possibile ammortizzare l’investimentoin tempi molto rapidi.

In questo momento di difficoltà legata alla congiunturaeconomica, è necessario cogliere l’occasione per investirein metodologie innovative, in grado di dare maggiorecompetenza e conoscenza del proprio processo ai repartidi progettazione e produzione, di ridurre i costi, e di pro-muovere la propria immagine aziendale aumentando lepossibilità di co-design nei confronti dei propri clienti.

Per maggiori informazioni:Ing. Marcello Gabrielli - [email protected]

EnginSoft sponsorizza losport in trentinoSquadra di calcio femminile di serie A2 ACF TRENTO.www.calciotrento.it


Il mondo dello stampaggio a freddo di viteriee minuterie metalliche, si è dato appuntamento a Bergamo per fare il puntosulle tecniche più avanzate di ottimizzazionedi processo/prodotto.Il 25/10 a Bergamo si è tenuto l’ultimo appuntamento del2009 sulla simulazione dei processi di stampaggio dei metal-li, dedicato questa volta al mondo dello stampaggio a fred-do.

L’invito è stato accolto da una quarantina di rappresentantidelle aziende più importanti in Italia che si occupano distampaggio a freddo di acciaio nei campi della viteria e bul-loneria, della minuteria metallica e di altri particolati otte-nuti per stampaggio, desiderosi di fare il punto sui vantaggiofferti dagli strumenti di simulazione nel miglioramento deiprocessi/prodotti.

A rompere il ghiaccio, come di consueto, è stato PieroParona, Sales Manager di EnginSoft, con una descrizione del-le molteplici attività di EnginSoft nel campo della prototipa-zione virtuale e della strategicità dell’uso di queste tecnichenell’ottica di riduzione dei costi.

L’intervento successivo, a cura dell’ing. Marcello Gabrielli,sempre di EnginSoft, ha riguardato le tecniche di simulazio-ne numerica dei processi di stampaggio a freddo con il soft-ware ColdForm di Transvalor. Attraverso esempi reali si è ana-lizzato come il software sia un valido supporto alle decisioni

che i tecnici devonoprendere nella messa apunto del processo pro-duttivo, per ogni opera-zione di stampaggio. Si èpartiti dal processo distampaggio da filo, trat-tando alcune sequenze diformatura per dei particolari di minuteria e viteria e mostran-do come l’analisi dei contatti, del flusso di materiale e delleripieghe possa aiutare ad individuare i problemi e mostrare lavia per risolverli. Si è passati quindi all’analisi delle solleci-tazioni sugli stampi, mostrando come intervenire per ridurnel’usura e migliorarne la vita utile, una volta individuate le zo-ne di massima sollecitazione. Per alcune configurazioni si èaffrontata una messa a punto delle condizioni di interferen-za (blindaggio) per garantire il corretto precarico alle matri-ci. Si è quindi accennato ai risultati ottenibili nell’analisidella tranciatura e della rollatura dei filetti.

Sono stati quindi analizzati dei casi di stampaggio e trancia-tura di lamiere, con cenni relativi all’influenza dell’anisotro-pia sul risultato dell’imbutitura ed è stato mostrato un ap-proccio differente, con i software della FTI(www.forming.com) per i casi di stampaggio di lamiera sot-tile, per la quale vengono calcolati gli spessori, le zone di ce-dimento e di grinzatura.

In conclusione, sono stati mostrati esempi di messa in ope-ra di rivetti e viti, dove il software ha consentito di valutarele resistenza degli accoppiamenti all’applicazione di condi-zioni di sollecitazione assiali e tangenziali.

Ha quindi preso la parola L’ing. Brigatti dellaSACMA Limbiate (http://www.sacmalimbiate.it),riferimento per le macchine automatiche per lostampaggio a freddo, che ha mostrato quali so-no le tecnologie che vengono adottate per mi-gliorare precisione e prestazioni, quali ad esem-pio la slitta a guida conica, il sistema di cambiorapido degli stampi ed i sistemi di microregola-zione degli aggiustamenti. Si è quindi sofferma-to sugli ultimi sviluppi nel campo dello stam-paggio a tiepido, evidenziando i vantaggi diquesta tecnologia.

Grande successo per il pomeriggiotecnologico - Stampaggio a Freddo di Viteriee Minuterie Metalliche: Simulazione deiProcessi: Nuovi Sviluppi, Vantaggi eProspettive – organizzato il 25 ottobre aBergamo da EnginSoft, con la presenza diSACMA Limbiate, Panzeri, Omega Ifs.

Newsletter EnginSoft Year 6 n°4 - 57Lo spazio dedicato alle testimonianze degli utilizzatori si èaperto con la presentazione dell’ing. Giussani della Panzeri(http://www.panzerionline.com), che ha mostrato comeColdform può essere utilizzato per la verifica e la messa apunto del processo di tranciatura di rondelle. Interessante lostudio effettuato con la collaborazione di EnginSoft edell’Università di Trento, mediante il quale Panzeri è ora ingrado di caratterizzare i materiali per la simulazione numeri-ca, ma anche di certificarne la qualità per la produzione.

Si è passati infine alla presentazione dell’ing. Wegner di OME-GA IfS (http://www.omegaifs.it), che ha mostrato l’utilizzodel software in tre casi particolari: un perno, dove la forma-tura del profilo superiore dell’ingranaggio portatava alla for-mazione di bave, una doppia estrusione, dove è stato usatoColdform per valutare la forma della superficie libera ed unaforcella, per la quale le analisi hanno consentito di rimedia-re ad una rottura delle matrici.

A completare la sezione tecnica, una dimostrazione dal vivodi utilizzo di ColdForm, curata dall’ing. Andrea Pallara diEnginSoft, che ha impostato il caso di una sequenza di for-matura di una vita a partire dallo spezzone di filo, passandoper l’estrusione del gambo, la formatura della testa e la crea-zione dell’impronta. La demo live ha evidenziato come questistrumenti siano ormai molto facili da utilizzare, sia nella fa-se di preparazione delle simulazioni, che nella fase di inter-pretazione dei risultati.

Al termine delle presentazioni i presenti hanno avuto lo spa-zio per porre delle domande ed ottenere degli approfondi-

menti da tutti i relatori presenti. Volendo sintetizzare, quan-to mostrato nel workshop ha dimostrato come questi stru-menti siano realmente in grado di dare una maggior coscien-za del proprio modo di produrre e come le esperienze fattecon ColdForm siano utili sia a far crescere molto rapidamen-te chi si avvicina a questo mondo, e a far diventare “patri-monio aziendale” le procedure di stampaggio ottimizzate intal modo. Ultimo aspetto non meno importante è il fatto che,grazie ai concreti vantaggi ottenibili, è possibile ammortiz-zare l’investimento in tempi molto rapidi.

In questo momento di difficoltà legata alla congiuntura eco-nomica, è necessario cogliere l’occasione per investire in me-todologie innovative, in grado di dare maggiore competenzae conoscenza del proprio processo ai reparti di progettazionee produzione, di ridurre i costi, e di promuovere la propria im-magine aziendale aumentando le possibilità di co-design neiconfronti dei propri clienti.

Per maggiori informazioni:Ing. Marcello Gabrielli - [email protected]

Bilancio del Ciclo di Workshopdedicati alla Simulazione deiProcessi di Deformazione deiMetalli Con l’appuntamento del 25/10 a Bergamo si è quindichiuso il ciclo di workshop dedicati alla simulazione deiprocessi di deformazione dei metalli: il 03/04 a Leccoper lo stampaggio a caldo di acciaio, il 07/05 a Bergamoper lo stampaggio dei non ferrosi, il 24/06 a Padova perla forgiatura, la laminazione a caldo di prodotti lunghi ela laminazione circolare.Volendo fare un bilancio dell’in-tero ciclo, la partecipazione di oltre 180 persone di qua-si 90 aziende ha decretato il pieno successo di questainiziativa e con diverse delle aziende presenti si sta ini-ziando un percorso per l’introduzione di questi strumentinella pratica progettuale quotidiana. Probabilmente ledifficoltà economiche legate alla crisi hanno impedito adaltri di partecipare.

Questo ci ha spinto, perl’anno 2010, ad organiz-zare degli eventi simili,

però avvalendoci di webinar che sfruttano la rete internetper proporre gli stessi contenuti, senza obbligare le per-sone ad effettuare delle trasferte. Rimanete sintonizzatisul nostro sito www.enginsoft.it per le date di questieventi o contattateci per degli incontri specifici presso lavostra sede. Le date sono: 11 Febbraio - 12 Marzo - 15 Aprile - 13 Maggio www.enginsoft.it/webinar

ITALY

14-17 April - METEF 2010 - International aluminium andfoundry exhibition. Visit the EnginSoft Booth where wepresent news on process simulation technologies relatedto MAGMA, Forge, Coldform, AdvantEdge…www.metef.com

14-15 April 2010 - Affidabilità e Tecnologie 2010Meet EnginSoft in the exhibition and learn from ourSeminar on Innovation in industry through VirtualPrototyping! www.affidabilita.eu

27-28 May - International modeFRONTIER Users’ Meeting2010. Starhotel Savoia Excelsior Palace, TriesteLearn how modeFRONTIER, the leading multidisciplinary &multi-objective design optimization tool, is used globallyin many industries to better understand productdevelopment processes, and achieve higher quality atreduced cost, allowing them to meet the challenge ofproducing better products faster! www.esteco.com

Fall 2010 – EnginSoft International CAE Conference 2010Exact dates and venue will be announced soon!www.caeconference.com

FRANCE

17-18 Mars 2010 - Micado : Etats Généraux Micado : "Lacontribution de l’ingénierie numérique à l’ECO conception" Evry (91). Edition exceptionnelle en partenariat avec laChambre de Commerce de l'Essonne sur le thème: "Lacontribution de l'Ingénierie Numérique à l'ECOConception". www.af-micado.com

EnginSoft France 2010 Journées porte ouverte. Dans noslocaux à Paris et dans d’autres villes de France et deBelgique, en collaboration avec nos partenaires. Prochaineévénement: Journées de présentation modeFRONTIER

2010 Séminaires Simulation de Process et Optimisation EnginSoft France Boulogne Billancourt – Paris.S eminarshosted by EnginSoft France and EnginSoft Italy. Veuillezcontacter Marjorie Sexto, [email protected], pour plusd'information ou visitez : www.enginsoft-fr.com

21-23 June – ASMDO 2010 3rd International Conferenceon Multidisciplinary Design Optimization and Applications- Co-sponsored by ISSMO, ESTP, EnginSoft, and NAFEMSParis. ASMDO 2010 will bring together scientists andpractitioners working in different areas of engineeringoptimization! www.asmdo.com

GERMANY

Please stay tuned to www.enginsoft-de.com and contactStephanie Koch at: [email protected] for moreinformation.

Seminars Process Product Integration. EnginSoft GmbH,Frankfurt Office. How to innovate and improve yourproduction processes! Seminars hosted by EnginSoftGermany and EnginSoft Italy. Dates will be announced inearly 2010.

modeFRONTIER Seminars 2010. EnginSoft GmbH, Frankfurtam Main: 26 January, 16 February, 9 March, 30 March, 20April, 18 May, 15 June

UKPlease stay tuned to www.enginsoft-uk.com and contactBipin Patel at: [email protected] for more information.

modeFRONTIER Workshops at Warwick Digital LabPlease check www.enginsoft-uk.com for next dates!

25th February - Technical Seminar on ManufacturingProcess Simulation Cranfield University

Attend EnginSoft UK’s FREE Seminar and learn how state-of-the-art simulation tools can help reduce developmenttime and drastically cut costs in manufacturing processes. The seminar will provide an interesting and effectiveoverview of the most modern CAE technologies availabletoday and how they can enhance your design productionprocesses when combined with world-class expertise.To register online, please visit: www.enginsoft-uk.com

SPAIN

24 - 27 February - 9th International Symposium onComputer Methods in Biomechanics and BiomedicalEngineering. Valencia. For more information and toarrange a meeting with Gino Duffett, APERIO Tecnología,please contact: [email protected], www.aperiotec.es

SWEDEN

23 February - Optimization Training Star-CCM+ andmodeFRONTIER. Goeteborg. In cooperation with CD-adapco and FS Dynamics, Esteco EnginSoft Nordic willpresent a one-day hands-on training on optimization withmodeFRONTIER and Star-CCM+

modeFRONTIER Courses scheduled so far for 2010:Esteco EnginSoft Nordic Office, Lund


EnginSoft Event Calendar


Optimization Crossword PuzzleSearch the words linked to modeFRONTIER® in the puzzle on the left, then put together the remaining letters starting fromtop: You will discover a nice message from EnginSoft!

O B R E T U P M O C E SB P S T A T I S T I C SJ T T W I M C D M T S IE S C I N H C E T A H MC I L E M T O O L M O UT M U G N I L E D O M LI P S S F R Z T R T E AV L T E M O G A O U D TE E E D M G E R T A N OG X R O I L N E S I O RF T T N I A R T S N O CK R I G I N G I S E D N

SOLUTION

_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

ALGORITHM

AUTOMATIC

CLUSTER

COMPUTER

CONSTRAINT

DEMO

DESIGN

ITERATE

KRIGING

MCDM

MODELING

MOGA

NODE

OBJECTIVE

OPTIMIZATION

SIMPLEX

SIMULATOR

STATISTICS

TECHNICS

TOOL

• 21-22 January - Introduction to modeFRONTIER• 9-10 February - Introduction to modeFRONTIER• 11 February - Robust Design with modeFRONTIER

For further information, please contact Adam Thorp at:[email protected]

USACourses on: Design Optimization with modeFRONTIEROzen Engineering, Sunnyvale – Silicon Valley, CALearn about Optimization coupled with ANSYS. OZEN caneasily help you out automating the search for the optimaldesign. The primary audience for this course includesANSYS Classic and Workbench users as well as newmodeFRONTIER users who want to have a completeoverview to all software capabilities. Stay tuned to our USpartner’s website for the next events in the USA:www.ozeninc.com - [email protected]

EUROPE, VARIOUS LOCATIONS

modeFRONTIER Academic Training Please note: These Courses are for Academic users only.The Courses provide Academic Specialists with the fastestroute to being fully proficient and productive in the use ofmodeFRONTIER for their research activities. The coursescombine modeFRONTIER Fundamentals and AdvancedOptimization Techniques. For more information, pleasecontact Rita Podzuna, [email protected]

To meet with EnginSoft at any of the above events, please contact us: [email protected]

EnginSoft CAE Webinars in 2010

EnginSoft's engineering team will conduct a new series ofCAE webinars in 2010. A variety of CAE topics will becovered by our experts based on EnginSoftmultidisciplinary expertise and tradition.The CAE webinars will demonstrate the best ways toinnovate industrial processes using Virtual Prototyping.

Stay tuned on webinars calendar: www.enginsoft.it/webinar

Key partner in Design Process Innovation

NUOVO LIBRETTO - NEW PUBBLICATION

SOFTWARE TRAINING COURSES 2010

CORSI DI ADDESTRAMENTO SOFTWARE 2010

Training Center EnginSoft

• un modulo relativo al solutore ANSYS POLYFLOW dedicato allostudio di processi quali l' estrusione, la termoformatura, il soffiaggiodi polimeri o del vetro;

• in campo fluidodinamico è da rimarcare l' introduzione, accanto aicorsi classici tradizionalmente erogati, di corsi specifici per ilsolutoreANSYS-FLUENT.

Sono stati inoltre rivisti ed aggiornati i corsi relativi a tutti gli altrisoftware sostenuti da EnginSoft per adeguarli allo stato attuale dellerelative distribuzioni.

Dal punto di vista organizzativo nel 2010 tutte le cinque sedi EnginSoftsaranno impegnate nella formazione, dando la possibilità agli utenti discegliere la location a loro più conveniente in termini di vicinanzageografica alla propria società.

Tutto questo a riprova dell'impegno nella formazione che, perEnginSoft, è e rimane un punto fondamentale della politica aziendale,un impegno costante verso l'eccellenza, un servizio per fare crescere inostri clienti e, se lo desiderano, crescere con loro.

EnginSoft è la società italiana di maggior consistenza e tradizione nelsettore del CAE ove, grazie alla multidisciplinarietà delle competenze,è in grado di proporsi come partner unico per le aziende.L'attività di formazione rappresenta da sempre uno dei tre maggioriobiettivi di EnginSoft accanto alla distribuzione ed assistenza delsoftware ed ai servizi di consulenza e progettazione.Per ciascuno dei possibili livelli cui la richiesta di formazione può porsi(quella del progettista, dello specialista o del responsabile diprogettazione), EnginSoft mette a disposizione la propria esperienzaper accelerare i tempi del completo apprendimento degli strumentinecessari con una gamma completa di corsi differenziati sia per livello(di base o specialistico), che per profilo professionale dei destinatari(progettisti, neofiti od analisti esperti).

La finalità è sempre di tipo pratico: condurre rapidamente all'utilizzocorretto del codice, sviluppando nell'utente la capacità di gestireanalisi complesse attraverso l'uso consapevole del codice di calcolo.Per questo motivo ogni corso è diviso in sessioni dedicate allapresentazione degli argomenti teorici alternate a sessioni 'hands on',in cui i partecipanti sono invitati ad utilizzare attivamente il codice dicalcolo eseguendo applicazioni guidate od abbozzando, con isuggerimenti del trainer, soluzioni per i problemi di proprio interesse, ediscutendone impostazioni e risultati.

Anche nel 2010 EnginSoft propone una serie completa di corsi checoprono le necessità di formazione all'uso dei diversi softwarecommercializzati.Le novità proposte sono diverse, a conferma che l'idea che EnginSoftha della formazione non è una realtà statica che si ripropone uguale ase stessa di anno in anno, ma è un divenire, guidato dall'esperienzaaccumulata negli anni, dall'evoluzione del software e dalle esigenzedelle società che si affidano a noi per la formazione del propriopersonale.

L'offerta dei corsi ANSYS è stata ridefinita per adeguarsi siaall'evoluzione del software ed alle caratteristiche della recentissimaversione 12.1 che all' introduzione di nuovi moduli e solutorirecentemente resi disponibili.

In tale senso si segnalano:• il corso dedicato allo studio con ANSYS delle strutture in materiale

composito, in particolare attraverso l'utilizzo del modulo dedicatoACP;

• il corso per il solutore esplicito ANSYS WORKBENCHEPLICIT/STR integrato nell' ambiente WorkBench e quello per ilsolutore esplicito generalizzatoAUTODYN;

• i nuovi corsi, relativi alle applicazioni specializzate per laprogettazione offshore, AQWA (codice per lo studio dell'idrodinamica di strutture galleggianti) ed ASAS (codicespecializzato per la verifica di strutture OffShore);

• in campo elettromagnetico viene introdotto un corso per ANSOFT-MAXWELL, software che rappresenta il riferimento nel settore delleanalisi elettromagnetiche in bassa frequenza; www.enginsoft.it/corsi

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