PRODUCTS & TECHNOLOGY: OVERVIEW - Ansys · PRODUCTS & TECHNOLOGY: OVERVIEW ... or modest compute resources, ... and the new ANSYS Engineering Knowledge Manager

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PRODUCTS & TECHNOLOGY: OVERVIEW

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Engineering Simulationfor the 21st CenturyFive key principles guide the development of simulation products and technology at ANSYS.By Chris Reid, Vice President, Marketing, ANSYS, Inc.

Technology is the lifeblood of ANSYS, Inc., and the basisfor everything we offer our customers. For more than 35years, ANSYS has been a pioneer in the application of finiteelement methods to solve the engineering design challengesour customers face. During that time, the evolution of ourindustry, products and technology has been nothing short ofamazing. Fueled by a corresponding increase in the power-to-price ratio of the computing world, the problem size and complexity of simulations have grown to impressivedimensions. The net effect of this is evident in almost every

facet of life — from the cars we drive to the energy we use, theproducts we buy, the air we breathe and even the devices weinsert into our bodies to maintain our health.

How have we accomplished this near 40-year run ofgroundbreaking achievement in engineering simulation andmodeling? Staying true to our vision and strategy has certainly been a major factor. Unlike others, ANSYS has neverwavered from its core business of engineering simulationsoftware. Instrumental to that vision is our commitment toadvanced technology — the cornerstone of our business and

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value to our customers. After all, it is our products andtechnology that enable companies to create the mostinnovative and globally competitive products for their industry.

Also instrumental to our vision are five principlesthat guide the development of our products and tech-nologies. The first is unequalled depth. Simply stated,for each of the key areas of simulation and modelingtechnologies — whether it be mechanical, fluid flow,thermal, electromagnetics, meshing or others — weoffer a depth of capability that is second to none. Thisdepth has been created over time by reinvesting inthe research and development of new technologies,and supplemented by key acquisitions and partner-ships along the way. Today, the results speak forthemselves in the richness of what we offer our cus-tomers, regardless of their specific simulationrequirements.

The second guiding principle is unparalleledbreadth. In this regard, ANSYS has assembled a complete range of simulation capabilities — from pre-processing to multiple physics to knowledgemanagement. Our customers see this as a tremen-dous benefit, because they know we can provide asolution for each specific area of analysis and that weprovide rich depth across our entire portfolio of prod-ucts and technologies. Some companies, perhaps,can lay claim to this in one or two areas, but we offerthis depth and breadth for the full range of simulationand modeling techniques.

In offering both technological depth and breadth,our customers are able to run simulations that are more sophisticated, more complex and more representative of the real world. Utilizing such a comprehensive multiphysics approach — our thirdguiding principle — enables engineers to simulate andanalyze complete systems or subsystems using truevirtual prototyping. Increasingly, companies realize thata multiphysics approach is essential to attain the mostaccurate and realistic simulation of a new product orprocess design. At ANSYS, we not only provide the technologies to do this, but we make them all interoperable within the unified ANSYS Workbenchenvironment. Thus, the user can configure a multiphysics analysis and avoid the need for cumber-some file transfers or intermediate third-party software links. Our technology inherently provides the

infrastructure, saving implementation time whileproviding measurable benefits in speed and robustnessas well.

The old adage “one size fits all” is certainly not the case in the world of engineering simulation.Despite the common threads that appear everywheresimulation is used, there are also real differences.Some industries, such as automotive and aerospace,are mature in their use of these tools, while others,such as healthcare, are relative newcomers. Compa-nies within the same industry can be at markedlydifferent stages of adoption, and users within any onecompany may have vastly different needs or experi-ence with simulation tools. There is a need forflexibility. Customers must be able to adopt theappropriate level of simulation and know they willhave latitude in how they move forward.

At ANSYS, we call this engineered scalability —guiding principle number four. Why “engineered”?Our scalability is by design and is specifically engi-neered into the technology we have developed. Thedepth of our technology allows customers to choosethe appropriate level of technology for their needs yetscale upward as their requirements evolve and grow.If the customer is a small company with just a desktopor modest compute resources, or if it is large withhundreds of machines in large-scale compute clus-ters, our software runs efficiently and brings value. Ina similar vein, if the number of users is very small or inthe hundreds, scalable deployment has been factoredin. Likewise, if the customer is an infrequent user, adesigner who wants to perform a simple simulation oran expert analyst, we have the appropriate level oftool for each of those levels of experience. Underpin-ning this seamless range of capability — from theautomated to the most sophisticated and customiz-able — is the same advanced technology, scaled upor down accordingly.

Technology isn’t of much use to the customer if it’sextremely inflexible to apply, scalable or otherwise. Allof it must be usable in a way that makes sense for thecompany and its design and development processes,as well as alongside other programs it may haveselected for their engineering systems strategy. Thevision needs to be flexible and adaptive, not rigid andconstraining. In this regard, ANSYS adheres to a fun-damental tenet of adaptive architecture — the fifth

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guiding principle. We recognize the mission-criticalnature of what we provide and also how crucial it isthat our technology fits within the customer’s overallsystem. There can be CAD systems, selected third-party codes for niche applications, or legacy andin-house software, all of which remain critical compo-nents of the overall process. We need to coexist withthese and, in fact, enable them to be included in theoverall workflow as painlessly as possible.

Many companies are investing in product lifecyclemanagement (PLM) systems. These constitute a majorinvestment and require data exchange with the simulation software. The ANSYS Workbench platformand the new ANSYS Engineering Knowledge Manager(EKM) technology are designed to provide functionalcoexistence with PLM systems, which actuallyimproves their value to the customer. Adaptive architecture means what it says — ANSYS productsand technology can adapt to the customer’s specific

situation. We can be the backbone, coexist peer-to-peer or be a plug-in, whatever the need may be.

Five simple phrases — unequalled depth, unparal-leled breadth, comprehensive multiphysics, engineeredscalability and adaptive architecture. These five tenetsare what drive our product development strategy withevery dollar we invest. We also think they are the reasonthat 96 of the top 100 industrial companies on the FORTUNE Global 500 list, as well as another 13,000customers around the world, use technology fromANSYS. The ANSYS simulation community today is the world’s largest, and by continuing to pursue ourstrategy of Simulation Driven Product Development andadhering to these five guiding principles, we see no reason why our vision of placing simulation tools in thehands of every engineer shouldn’t become a reality inthe near future. ■

Images courtesy Tusas Engine Industries, Silesian University of Technology, Cummins,Inc., FluidDA nv, Modine Manufacturing Company and © 2008 Owens Corning Science & Technology, LLC and the Gas Technology Institute. Used with permission.

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PRODUCTS & TECHNOLOGY: DATA MANAGEMENT

The last three decades have witnessed the evolution ofcomputer-aided engineering (CAE) from a tool used by analysts in a research and development department to onethat is integral to the entire product design and lifecycleprocess. Companies around the world are making greateruse of upfront analysis and complex system simulation.With the ongoing integration of CAE into the designprocess, the focus is shifting from technology issues suchas improved simulation techniques, physics modeling andease-of-use to usage-focused questions such as “How do I better manage and share the voluminous data that is beinggenerated?” or “How do I better capture the engineeringexpertise that the simulation results represent?” The answerto these questions is often referred to as simulation processand data management (SPDM).

SPDM presents a whole new set of challenges to CAEpractitioners. The current focus centers on accessibility —that is, how do the right people get the right data at the righttime? More often than not, keeping track of this information isleft to the individual analyst or engineer who generated it, sotypically at the end of a project it is buried in obscurity some-where on a hard drive. According to a recent survey byCollaborative Product Development Associates (CPDA), 47percent of all simulation results are stored on the engineer’slocal workstation. This valuable intellectual property is usuallylost forever when individuals leave a team or company. Asanyone who has tried knows, tracking down old data files andanalysis models from past simulation projects is difficult or often impossible, even for the people who created them. Consequently, simulations are often redone from scratch —rather than by performing a simple modification to an existingcase or model. The result is a significant loss in time and productivity.

With rapid globalization now permeating all aspects ofmany companies’ operations, engineering groups located atdifferent locations around the world constitute virtual 24-hour-a-day development organizations. Effective collab-oration and communication are essential to support this global mode of operation. Ineffective communication hurtsthe entire team, from the engineer who is trying to explaindesign challenges and concerns to his or her manager, to theteams that need to consider external factors affecting theirdevelopment process and design. Using tools that can help

convey simulation results to all members of a team at everylevel across the enterprise — regardless of their technicalbackground — can dramatically boost the effectiveness ofthe team, the product development process and, finally, thequality and performance of the product.

Corporate knowledge is a key business asset in a com-pany’s quest for innovation and competitive advantage.Creating, capturing and managing a company’s simulation

Putting EngineeringKnowledge to WorkNew technology enables efficient sharing of rich simulationinformation and provides enterprise-wide benefits.By Michael Engelman, Vice President, Business Development, ANSYS, Inc.

Data management methods

Database andtemplates formost tasks

Database for somesimulation tasks*

Simulation datamanagement

CommercialPDM

Legacy databaseand in-house

solution*

User’s localmachine*

Other

Verbal and informal

exchange*

*Results in information loss

*Results in data loss

Other

Knowledge exchange methods


PRODUCTS & TECHNOLOGY: DATA MANAGEMENT

expertise is critical to enabling innovation. It empowers usersto build on previous experience and fosters continualimprovement and collaboration of the expert analysts anddesign engineers. Effective process management tools thatcapture simulation best practices, deploy managed simula-tion tasks and processes, and plug into internal applicationswithin a unified environment are essential to achieve thesegoals — though they must also require minimal effort andmaintenance costs.

Managing simulation data and processes within this context is a specialized subset of the broader product lifecycle management (PLM) vision. This discipline is based onthe digital management of all aspects of a product’s lifecycle,from concept and design through manufacture, deployment,maintenance and eventual disposal. Unfortunately, thoseneeds that are specific to simulation and SPDM are oftenoverlooked or poorly addressed by today’s PLM systems. Thisis a result of SPDM being more demanding than the file/document-centric approach of PLM and related product datamanagement (PDM) systems. Simulation data is richer, morecomplex and typically many orders of magnitude larger than

other types of product data. An SPDM system is comple-mentary to a PLM system and can add significant value whendesigned to work in close conjunction with PLM.

The ANSYS Engineering Knowledge Manager (EKM)technology, now in its initial release, is aimed at meeting thesechallenges with extensive capabilities: archiving and manage-ment of simulation data, traceability and audit trail, advancedsearch and retrieval, report generation and simulation com-parison, process/workflow automation, and capture anddeployment of best practices. It is a Web-based SPDMframework aimed at hosting all simulation data, workflowsand tools, whether in-house or commercial, while maintaininga tight connection between them. While providing seamlessintegration with simulation products from ANSYS — includingthe ability to automatically extract and organize extensiveinformation about ANSYS software–based simulation fileswhen they are uploaded into the repository — the ANSYSEKM tool is an open system that can manage any type of in-house or third-party simulation products, files or infor-mation as well. Moreover, it is a scalable solution that can beeffectively used by small workgroups, distributed teams ofengineers or the entire enterprise.

With tools and developers that have histories stretchingback to the formative years of simulation, ANSYS under-stands the complexity and challenges of simulation. ANSYSEKM technology was created with an appreciation thataccess to simulation; developing effective processes forincorporating simulation into individual, workgroup and enterprise-wide efforts; and managing simulation efforts within a larger development or industrial process is a compli-cated effort — one that can be made simpler. Having accessto the right tools, developed by a team that has devoted yearsto understanding the challenges of simulation, can streamlinethe incorporation of virtual product development efforts intotraditional workflows and environments. Adding ANSYS EKMtools to the capabilities of the family of products from ANSYSempowers organizations of all sizes to better achieve the goal of Simulation Driven Product Development. ■

Process workflows can be mapped out and displayed in diagram style, as shown here.Among other possibilities, each step may be customized by the user to include automated substeps, assign team members tasks and iterate to the next step.

Pressure data for airflow over an aircraft wing is extracted using ANSYS EKM data mining capabilities.

Comparison reports provide users, even those without a technical and simulation background, with the ability to examine simulation results.

Applying Six Sigmato Drive Down Product DefectsProbabilistic design and sensitivity analyses help engineers quickly arrive at near-zero product failures in the face of wide manufacturing variabilities and other uncertainties.By Andreas Vlahinos, President, Advanced Engineering Solutions, Colorado, U.S.A.

Companies often are focused primarily on time-to-market, but theadvantages of fast product introduc-tions may be quickly overshadowed bythe huge cost of poor quality, resultingin product recalls, rework, warrantypayments and lost business from negative brand image.

In many cases, such quality prob-lems are the result of variations infactors such as customer usage, manufacturing, suppliers, distribution,delivery, installation or degradationover the life of the product. In general,such variations are not taken into con-sideration as part of the developmentof the product. Rather, the integrity andreliability of a design is typically basedon an ideal set of assumptions thatmay be far removed from actual real-world circumstances. The result is adesign that may be theoretically soundbut riddled with defects once it is manufactured and in use.

ANSYS Mechanical parametric model of a gasket is automatically changed for each of the 10,000 DOE analyses performed.

Andreas Vlahinos

Design for Six Sigma (DFSS) is astatistical method for radically reducingthese defects by developing designsthat deliver a given target performancedespite these variations. The approachis a measure of quality represented asthe number of standard deviationsaway from a statistical mean of a targetperformance value. Operating at threesigma translates into about 67,000defects per million parts, performancetypical of most manufacturers. A ratingof six sigma equates to just 3.4 defectsper million, or virtually zero defects.

Achieving this level of qualityrequires a focused effort upfront in devel-opment, with design optimization drivenby integration of DFSS into the processand rigorous use of simulation. In suchDFSS efforts, ANSYS DesignXplorersoftware is a particularly valuable tool. Working from within the ANSYS Workbench platform and in conjunctionwith ANSYS Mechanical and other


PRODUCTS & TECHNOLOGY: DESIGN FOR SIX SIGMA



simulation software, the program per-forms Design of Experiments (DOE) anddevelops probabilistic design analysesfunctions to determine the extent towhich variabilities of key parametersimpact product performance.

The process is accomplished infour major phases: process automation,design exploration, design optimizationand robust design. Utilizing the ANSYSWorkbench environment, process auto-mation ensures that simulation tasksare well defined and flow automaticallyto extract and evaluate key perform-ance variables.

ANSYS DesignXplorer softwarethen performs the DOE, running numer-ous (usually thousands) analyses usingvarious combinations of these param-eters. The ability to quickly andeffortlessly execute such an extensivestudy on this wide range of parametersallows users to perform quick andaccurate what-if scenarios to testdesign ideas. In this way, design explo-ration — combined with knowledge,best practices and experience — is apowerful decision-making tool in theDFSS process.

Next, design optimization is per-formed with the ANSYS DesignXplorertool in order to select the alternativedesigns available within the acceptablerange of performance variables. Designparameters are set to analyze all possi-bilities — including those that mightpush the design past constraints andviolate design requirements. Finally,robust design is performed, arriving atthe best possible design that accountsfor variabilities and satisfactorily meetstarget performance requirements.

Throughout the process, ANSYSDesignXplorer software employs power-ful sampling functions and probabilisticdesign technology. It also provides valu-able output in the form of probabilitydesign functions, scatter plots andresponse surfaces that are critical inDFSS. Seamless interfaces with para-metric computer-aided design (CAD)programs — used to import geometry

for analysis and to set up parametricmodels in mechanical solutions fromANSYS — is essential for ANSYSDesignXplorer software to automaticallyperform numerous iterations in whichvarious design geometries are createdand analyzed. In this way, ANSYSDesignXplorer software is an effectivemeans of integrating DFSS into a com-pany’s product development process.The software provides individual engi-neers a unified package for quicklyperforming probabilistic design andsensitivity analyses on thousands ofdesign alternatives in a few hours; oth-erwise, this would take weeks of effortby separate statistics, simulation, DOEand CAD groups.

One recent project designed toimprove hyper-elastic gasket configu-rations in proton-exchange membrane(PEM) fuel cells illustrates the value ofthe ANSYS DesignXplorer tool in DFSSapplications. In this example, severalgaskets provide a sealing barrierbetween the cell and approximately200 bipolar cooling plates. In designingthe fuel cells for commercial use inharsh environments, the goal was tolower the failure rate of the gaskets,which tended to leak on occasion —even in a carefully controlled researchlab setting.

Probability density functions of parameters thatvary with each analysis iteration

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-2.400E-3

ANSYS DesignXplorer software generated a response surface showing sensitivity of each input variable to contact force.



Scatter plots of analysis results were generated, along with bell-shaped probability density functions,in arriving at a robust gasket design.

With the workflow captured in the ANSYS Workbench platform, the process is highly repeatable and can be efficientlyapplied in optimizing the design of other gaskets.

First, design variables were estab-lished — gasket profile, gasket groovedepth and the opposing plate’srecessed pocket groove depth — thatdetermined the overall compressiveforce of the gasket under a given boltload. These were considered to berandomly varying parameters withgiven mean and standard deviationsas determined through probabilitydensity functions generated by theANSYS DesignXplorer tool. The soft-ware then was set up to automaticallyperform a series of DOE analyses inorder to determine the gasket contactforce for 10,000 different combinationsof these variables. Variables were ran-domly selected by the software foreach round of analysis using the Latinhypercube sampling technique.

Using ANSYS Mechanical analy-sis, solutions were arrived at in which(1) nonlinear capabilities characterizethe hyper-elastic gasket materialproperties; (2) contact elements repre-sent contact between the gasket andplates; and (3) parametric featuresautomatically change the geometry of the gasket configuration for each ofthe 10,000 analyses.

Based on these analysis results,ANSYS DesignXplorer software generated a response surface of thecontact force per unit length of the gasket in terms of probabilisticinput variables. With the sensitivityestablished for each input variable onthe contact force, scatter plots of theanalysis results were generated alongwith bell-shaped probability densityfunctions, which were compared tothe upper and lower load limits of thefuel cell and cooler interfaces. Axialforces could not be so high as tobreak the plates, yet not so low as to cause leaking. From this data,the ANSYS DesignXplorer tool deter-mined the sigma quality level basedon the contact force target level.

The process succeeded in arriving at an optimal gasket shapethat exceeded the sigma qualitylevel, dropping the failure rate to animpressive three parts per million —

a tremendous improvement over the 20 percent failure rate that the gas-kets were experiencing previously.

The entire process — including creation of the mesh models and com-pletion of the 10,000 DOE analysiscycles — was completed in a matter ofdays by a single individual, as com-pared to months of effort thatotherwise would have been requiredby separate design, statistics andanalysis groups. Moreover, with theworkflow captured in the ANSYS

Workbench platform, the process now ishighly repeatable and can be efficientlyapplied in optimizing the design of othergaskets merely by changing the CADmodel and the upper/lower contactforce limits. ■

More detailed information on the DFSS gasketproject can be found in the ASME paper FuelCell 2006-97106 “Shape Optimization of FuelCell Molded-On Gaskets for Robust Sealing”by Vlahinos, Kelly, Mease and Stathopoulosfrom the International Conference on Fuel CellScience, Engineering and Technology, Irvine, CA,June 19–21, 2006.

Establish DesignVariables

Design of Experiments

ExperimentsParametric CAE Model

Probabilistic Response

Targets

Mean and StandardDeviation of Response

Variables

10K Random Experiments

Latin Hypercube SamplingMean and Standard Deviation

of Design Variables

Goodness of Fit

SigmaQuality Level

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a system of high-fidelity multidomain analysis tools to truly

enable SDPD. SDPD is centered on the highly adaptive ANSYS

Workbench architecture. The next major ANSYS Workbenchrelease will provide another big step toward this vision. It willbe the first release in which a number of the original FluentCFD products will be data-integrated into the ANSYS Workbench platform, and thus the tools will work togetherwith various other applications from ANSYS.

The ANSYS Workbench approach allows ANSYS to provide a large variety of software choices tailored tomeet individual needs while ensuring interoperability and aclear future upgrade path. This includes a very broad fluids product line with all tools falling into one of three categories: general-purpose fluid flow analysis, rapid flowmodeling and industry-specific products.

General-Purpose Fluids SolversThe well-known FLUENT and ANSYS CFX products are

the main general-purpose CFD tools from ANSYS. These twosolvers, developed independently over decades, have a lot ofthings in common but also some significant differences. Both are control volume–based for high accuracy and relyheavily on a pressure-based solution technique for broadapplicability. They differ mainly in the way they integrate thefluid flow equations and in their equation solution strategies.

The world of product engineering has come along way in its quest to advance analysis fromlaborious hand-drawn sketches and simplistic models to virtual computer-created models initiated at thetouch of a button. There has beena long evolutionary path from the inception of computationalfluid dynamics (CFD) to today’s integration of this technology intoSimulation Driven Product Develop-ment (SDPD) processes. Throughout itshistory, ANSYS, Inc. has been a technological championfor such commercial engineering simulation. The companyhas viewed simulation as the key to predicting how productswill perform; it has enabled the rapid comparison of manydifferent alternatives prior to making a design decision —well before customers might identify problems. ANSYS nowhas a fluids product line that is both broad and deep, alongwith a large commercial and academic user base that isreaping the benefits.

This CFD evolution has required, and continues todemand, that ANSYS go beyond merely providingadvanced mathematical flow solvers. ANSYS espouses amultiple physics approach to simulation in which fluid flowmodels integrate with other types of physics simulationtechnologies. The ANSYS vision is clear: to provide

The New Wave of Fluids TechnologyFluid flow simulation software from ANSYS provides a broad range of scalable solutions.By Paul Galpin, Director of Product Management

and André Bakker, Lead Product Manager, Fluids Business Unit, ANSYS, Inc.

Contours of temperatureon a car body calculatedin FLUENT software

ANSYS Advantage • Volume II, Issue 2, 2008

PRODUCTS & TECHNOLOGY: FLUIDS

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Contours of drug concentration in a stent and capillary wall

Airflow in a datacenter as simulated using ANSYS Airpak software

The ANSYS CFX solver uses finite elements (cell vertexnumerics) to discretize the domain, similar to those used inthe mechanical analysis side of the business. In contrast,the FLUENT product uses finite volumes (cell-centerednumerics). Ultimately, though, both approaches form “control volume” equations that ensure exact conservationof flow quantities, a vital property for accurate CFD simula-tions. ANSYS CFX software focuses on one approach tosolve the governing equations of motion (coupled algebraicmultigrid), while the FLUENT solver offers several solutionapproaches (density-, segregated- and coupled pressure-based methods). Both solvers contain a wealth of physicalmodeling capabilities to ensure that any fluids simulationhas all of the modeling fidelity required.

These two core CFD solvers represent more than 1,000person-years of research and development. This efforttranslates into the key benefits of fluid flow analysis soft-ware from ANSYS: experience, trust, depth and breadth.The fluids core solvers from ANSYS are trusted, used andrelied upon by companies worldwide.

Rapid Flow ModelingANSYS addresses the fluid flow analysis needs of

designers, who work on the front lines of their company’sproduct development process and often need to makeimportant design decisions quickly with no time to set up andsolve complex mathematical models. For these time-limitedengineers, ANSYS offers a choice of rapid flow modeling(RFM) products. RFM technology from ANSYS compressesthe overall time it takes to do a fluid flow analysis by providing a high level of automation and focusing on only themost robust physical models. Three RFM tools are available:FloWizard, ANSYS CFX-Flo and FLUENT for CATIA®

V5 software.FloWizard software integrates all steps in the fluids

process into one smooth interface. Computer-aided design(CAD) files can be sent to the FloWizard product, flow volumes extracted, models set up, calculations completedand HTML reports generated. FloWizard software is fullycompatible with the FLUENT product, making it a goodchoice for designers in companies that use FLUENT tech-nology in the analysis department.

The ANSYS CFX-Flo tool is a version of ANSYS CFXsoftware that limits the physics accessible by the user to themodels most commonly used by design engineers. It is com-patible with other applicable ANSYS Workbench add-ins.The reduced complexity and cost of ANSYS CFX-Flo make ita good choice for design departments in organizations thatalready use ANSYS CFX software or other products com-patible with the ANSYS Workbench environment.

The FLUENT for CATIA V5 product offers many of thesame benefits of FloWizard and ANSYS CFX-Flo software.Completely embedded into the CATIA V5 system, it is fullycompatible with the standard, full FLUENT solver. It is mostuseful for companies that use CATIA V5 in their designdepartments and FLUENT software in their analysis groups.

Industry-Specific Fluids Simulation ToolsFlexibility and generality are important, but sometimes

not required for specific applications. In addition to providinggeneral-purpose CFD and rapid flow modeling products,ANSYS makes fluids simulation even more accessible andfocused with its industry-specific analysis tools. These prod-ucts are often called vertical applications because of the waythey integrate all the steps for the analysis of a specific typeof system into one package. The technologies offer industry-specific functions as well as employ the language of theindustry in which they are used.

Turbomachinery is one of the world’s single most successful CFD vertical applications, due to the similarity ofthe geometry and physics across a broad range of rotating



Turbulence on a delta wing calculated by ANSYS CFX software

machinery sectors. The turbosystem technology fromANSYS includes custom geometry and meshing tools aswell as special modes within the general-purpose fluidssimulation tools.

The ANSYS Icepak product is a family of applicationsfocused on electronics design and packaging. In order toimprove the performance and durability of electronic boardsand other components for optimized cooling systems, the product calculates the flow field and temperatures inelectronics and computer systems.

ANSYS POLYFLOW software is focused on the needs of the materials industry, such as polymer processing,extrusion, filmcasting and glass production. It can modelthe flow of fluids with very complex behavior, such as viscoelastic fluids. The ANSYS POLYFLOW product offersunique features such as the ability to perform reverse calculations to determine the required die shapes in extrusion. It also can calculate the final wall thickness inblow-molding and thermoforming processes.

The ANSYS Airpak product is aimed at the design ofheating, ventilation and cooling systems in buildings, suchas offices, factories, stadiums and other large publicspaces. It accurately and easily models airflow, heattransfer, contaminant transport and thermal comfort in aventilation system.

Finally, end-users can create their own vertical applica-tions within the general-purpose fluids simulation products:ANSYS CFX software offers user-configurable setup wizards and expression language; FLUENT technology provides user-defined functions; and the FloWizard tooloffers Python scripts. All of these can be used to create custom vertical applications. It is not uncommon for ananalysis department to create such vertical applications fordeployment within a design department. The main benefit ofthis approach is to ensure repeatable simulation processcontrol, and hence quality control, for any CFD process.

The extrusion of a viscoelastic food material is simulated with ANSYS POLYFLOW software. The pressure drop between the inlet and the five outlets is shown. The outletshape is computed as part of the analysis.

FLUENT for CATIA V5 software works within the CATIA V5 PLM environment, as shownin this simulation of a heat exchanger.

The Future of Fluids Simulation from ANSYSTo help customers replace more and more of their

traditional capital-intensive design processes with a Simu-lation Driven Product Development method, ANSYS willcontinue to innovate and integrate.

In the very near future, users will see tremendousprogress toward the ANSYS integration vision, includingcommon geometry, meshing and post-processing tools for all users of CFD products from ANSYS. Many steps inthe fluids simulation process will be automatically recorded,enabling parametric simulations. Improvements in fluid–solid connectivity will be evident, enabling a number of newmultiphysics possibilities.

The upcoming ANSYS 12.0 release will lay a firm foundation for the future while carefully preserving andextending current software value. Over time, ANSYS plans toachieve the tightest possible integration of all its fluids tech-nologies as well as an intimate integration with ANSYSmechanical technologies. The goal is to combine the best ofthe best into a simulation system with unprecedented powerand flexibility. ■

Static mixer simulation in FloWizard software



PRODUCTS & TECHNOLOGY: MULTIBODY

Simpler is better — that’s whatwe’ve all been told. The more compli-cated something is, the more waysthere are for it to break. This seems logical and is something we shouldconsider as we invent new machines.The challenge is that simple machinesdo simple things and often can only do one thing well. A simple bottleopener, for instance, probably isn’tthe best tool for anything other thanopening bottles, but it does what it was designed to do. Complicatedmachines — both mechanical and bio-logical — have more parts, and oftencan be used to do more than one thing.As an example, the adult human bodytypically has 206 bones and can beused for all kinds of things from openingbottles to competing in triathlons.Inventing machines that can do a varietyof things requires that the machineshave multiple parts that work together,preferably without failing. Simulationtools in the product portfolio fromANSYS help make designing usefulmachines easier and faster, as well asmore fun.

JointsWhen machines were simpler,

there were fewer options, and multipleparts could be connected in mech-anical software from ANSYS only using shared nodes, beam elements,coupling, constraint equations andnode-to-node contact. These methods


Multibody Dynamics:Rigid, Flexible andEverything in BetweenAdvances in simulation solutions for machine features accommodate more complex designs.By Steve Pilz, Product Manager, ANSYS, Inc.

Images:motorcycle © iStockphoto.com/Paul Griffin bicycle © iStockphoto.com/Artsem Martysiok

As simulationcapabilities grow,an engineer’s ability to simulatemore complexmachines increases.

Joints were first releasedwith the COMBIN7 element,

which was used to model onlypinned, or revolute, joints. AtANSYS 10.0, major advances to jointtechnology were made via theMPC184 element, which could beused to model multiple joint types,such as those that are translational,cylindrical, spherical, slot, universal,general or fixed. Joint elements are particularly interesting to thoseinvolved with the design of multiple-part machines because they can beused to enable large rotations andtranslations between parts at a verylow computational expense. To illus-trate the potential computationalsavings of using joints, a metal hingeis used as an example. (Figure 1.)

were adequate formany years, buteventually generalsurface contact wasreleased to addressthe limitations. With thisnew functionality, parts undergoinglarge rotations, deformations, sticking, sliding and a host of other real-worldbehaviors could be modeled.

General surface contact becamepopular and widely used. It alsobecame more robust and efficient witheach successive ANSYS release formechanical applications and is nowconsidered mature, proven technology.One problem with the widespread useof general surface contact, however, is that sometimes it is more than isrequired. The relatively new capabilityto connect parts via joints has somepotentially huge advantages that canbe applied to many situations.


There are many ways to set up a model for a metal hinge, but thetwo used in this investigation are a traditional general surface contactapproach and a revolute joint approach (Figure 1). To simplify, the partsare set to be rigid so that problem size changes can be compared more easily. For each approach, a single CPU laptop is used to run the simulations.

In the general surface contact approach, to enable rotational free-doms but constrain all translationals except one, three contact surfacesare required (Figure 2) and one remote displacement, which rotates the hinge 90 degrees counter-clockwise. Using a few user-definedmesh specifications for surface contact size (body and edge sizing), theproblem consisted of 7,188 elements (Figure 3) and took 2,249 seconds to solve.

By changing from a general surface contact approach to a revolutejoint–based approach, there are three rigid parts and two joints connecting those parts to each other at the hinge: one revolute jointbetween the ear and the pin, and one fixed joint between the base and thepin. The pin could be suppressed since it won’t perform any function onceit is replaced with a revolute joint, but it is included in the model to makethe run-time comparison equivalent with the general surface contactapproach. The total problem size, as expected, is far smaller, uses only 14elements (Figure 4) and requires a solution time of only 1.625 seconds.

So what have we learned? First, if detailed contact information at the hinge pin is unimportant, it is a lot more efficient to replace thousands of contact elements with a single revolute joint element.

Doing that, the model can be solved in a fraction of the time it took tosolve without the use of joints. Second, as can be seen from the elementlisting in Figure 4, even in a model in which contact surfaces are notspecified, there are still contact elements — which come from use ofthe joint or MPC184 element — but far fewer of them.

TYPE NUMBER NAME

1 1 MASS21

2 1 MASS21 3 1 MASS21 4 1 CONTA176 5 1 TARGE170 6 180 CONTA174 8 1 TARGE170 9 178 CONTA174 10 180 CONTA174 11 178 TARGE170 12 576 CONTA174 13 1 CONTA176 14 1 TARGE170 15 832 CONTA174 16 1408 CONTA174 17 1408 TARGE170 18 288 CONTA174 19 832 CONTA174 20 288 CONTA174 21 832 TARGE170

TYPE NUMBER NAME

1 1 MASS21

2 1 MASS21

3 1 MASS21

4 1 CONTA176

5 1 TARGE170

6 2 CONTA176

7 1 TARGE170

8 1 CONTA176

9 1 TARGE170

10 2 CONTA176

11 1 TARGE170

12 1 MPC184

Figure 1. Hinge model Figure 2. For this hinge model, general surface contact joints are used in three locations.First, where the ear meets the base, frictionless surfaces prevent translation along the axis of the pin and still allow rotation of the ear and base against each other at the joint.Second, bonded surfaces between the pin and the base prevent the pin from spinning ortranslating relative to the base. Then lastly, frictionless surfaces between the ear and thepin allow the ear to rotate freely about the pin.

Figure 3. Element description for hingejoint modeled with general surface contact

Figure 4. Element description for hingejoint modeled with a revolute joint


Joints: General Surface Contact vs. Revolute Joint Approach

Pin

Base

Ear


ANSYS Rigid DynamicsThe ANSYS Rigid Dynamics

module, first released at Version 11.0,makes extensive use of joints for connecting parts. This is an ANSYSWorkbench add-on tool for users who have ANSYS Structural, ANSYSMechanical or ANSYS Multiphysicslicenses. The module enhances the

capability of those products by adding anexplicit solver that is tuned for solvingpurely rigid assemblies. As a result, it issignificantly faster than the implicit solverfor purely rigid transient dynamic simula-tions. The ANSYS Rigid Dynamicsmodule also has added interactive jointmanipulation and ANSYS WorkbenchSimulation interface options.

Interactive joint manipulation allowsthe user to solve a model essentially inreal time — the explicit solver producesa kinematic solution with part positionsand velocities — using the mouse todisplace the parts of the model. This tool is on the menu bar in the Con-nections folder. New Configure, Set andRevert buttons can be used to exercisea model that is connected via joints, seta configuration to use as a startingpoint or revert back to the original con-figuration as needed. In the case shownin Figure 5, before finding a solution, thehinge has been rotated a little morethan 46 degrees to verify that the jointis, in fact, behaving like a hinge.

The ANSYS Rigid Dynamics mod-ule is run using the same techniquesthat are used in ANSYS WorkbenchSimulation — attaching to the CAD orthe ANSYS DesignModeler model,using the model tree, populating theConnections folder and inserting NewAnalysis, for example.

The combination of the explicitRunge–Kutta time integration schemeand a dedicated rigid body formulationcreates a product that while limited toworking only with completely rigid parts,

Figure 5. Interactive joint manipulation is possible within the ANSYS Rigid Dynamics module, performed on a computerscreen by using the mouse to move the model.

Figure 6. Folding arms of John Deere agricultural sprayer model to be subjected to time–history loading Image courtesy Brenden L. Stephens, John Deere

www.ansys.comANSYS Advantage • Volume II, Issue 2, 20082222 www.ansys.com22

Angle=46.9715 Degrees


is extremely well suited to solvingmulti-jointed assemblies, such as thefolding arm agricultural assembly (Figure 6). This scheme is adept at handling complex time–history input(Figure 7) and is extremely fast com-pared to more traditional solvers. Solvetime, even for complex assemblies, istypically measured in seconds andminutes rather than in hours and days.One caveat worth mentioning is that,at release 11.0, parts need to beconnected with joints rather than contact when using the ANSYS RigidDynamics capability. If contact isrequired to accurately represent thepart interactions, flexible dynamicssimulation is required.

The ANSYS Rigid Dynamics toolshould be used first on any complex,multi–part assembly with connections.Fast solution times can help usersquickly find joint definition problems,inadequate boundary conditions, over-constraints and other problems. Withthe time saved, multiple design ideascan be analyzed in the same amount of

time that it previously would havetaken to simulate a single concept.

ANSYS Flexible DynamicsIs the ANSYS Rigid Dynamics

tool all that is needed to fully under-stand a prototype of a machine?What happens if the parts deform?Will they break? Will they fatigue andfail after a short time or only afterextreme use? If parts bend, twist andflex, will the machine still perform itsintended function?

The ANSYS Rigid Dynamicscapability, for all its strengths, doesn’t provide a complete pictureof a machine’s performance. In a thorough machine prototype inves-tigation, the next step is a flexibledynamics analysis, which allowssome or all of the machine’s parts tobehave as they would in the realworld — flexing, twisting and deform-ing. Flexible dynamics allows users toexamine parts to identify whetherthey are stiff and light, as they wouldbe if made from titanium, or heavy

and flexible, as they would be if madefrom rubber.

A more in-depth explanation of theuse of ANSYS Structural, ANSYSMechanical or ANSYS Multiphysicsproducts running flexible nonlineardynamics simulations is necessary todemonstrate the steps required to takean all-rigid dynamics model and turn itinto a partially or completely flexiblemodel. This translation from a rigid to aflexible model includes material assign-ment, meshing and solver setup.Without writing a spoiler to any futurearticles on this subject, this is remark-ably easy to do.

The simple machines have alreadybeen invented. We don’t really need amore efficient bottle opener. With theaddition of more realistic and fastermodeling solutions — achieved by com-bining the ANSYS Rigid Dynamicsmodule and ANSYS Structural, ANSYSMechanical or ANSYS Multiphysics software — complicated machines canbe less prone to failure and producefewer career-limiting disasters. ■

Figure 7. Time–history loading at six different geometric locations along the sprayer model in Figure 6Image courtesy of Brenden L. Stephens, John Deere


CH43 - Vert1 Displ FBK (Displacement)CH46 - Long1 Displ FBK (Displacement)

73.15

50.

25.

0.

-25.

-50.

-78.17

CH44 - Vert2 Displ FBK (Displacement)CH47 - Lat1 Displ FBK (Displacement)

CH45 - Vert3 Displ FBK (Displacement)CH48 - Lat2 Displ FBK (Displacement)

0. 11.5 23. 34.5 46. 57.5 69. 80.5 92. 103.5 115.

115.


PRODUCTS & TECHNOLOGY: NONLINEAR

24

In today’s competitive environment in which everyonestrives to develop the best design with the best perform-ance, durability and reliability, it is unrealistic to rely on linearanalysis alone. Analyses must be scaled from single partsand simplified assembly-level models to complete system-level models that involve multiple complex subassemblies.As more parts get added to a simulation model, it becomesmore difficult to ignore the nonlinear aspects of the physics,and, at the same time, expect realistic answers.

In some situations involving single- or multiple-part models, analysis with linear assumptions can be sufficient.However, for every assumption made, there is some sacrifice in the accuracy of the simulation. Ignoring nonlinear-ities in a model might lead to overly conservative or weakdesign in certain situations, or might result in the omission ofunexpected but valuable information about the design or per-formance of the model. It is essential to understand when andwhen not to account for nonlinearities. The following are some situations in which non-linearities are commonly encountered.

ContactCurrently, auto-contact detection

in ANSYS Workbench Simulationallows users to quickly set up con-tact (part interactions) betweenmultiple entity types (solids, sheets,beams). However, in cases in whichtwo parts interact with each other, theparts might stick or slide againsteach other instead of remainingstatic. Also, their stiffness mightchange depending upon whetherthey touch each other or not, as is seen with interference or snap-fit cases. Ignoring sliding may beacceptable for a large class of problems,

but for those with moving parts orthat involve friction, it is unwise tomake this assumption.

GeometryIn certain situations, the

deflections of a structure may belarge compared to its physicaldimensions. This usually results in a variation in the location and distribution of loads for that struc-ture. For example, consider afishing pole being bent or a largetower experiencing wind loads.The loading conditions over theentire body of the structure willchange as the structure deflects.

Also, in certain slender typesof structures, membrane stresses may cause

the structure to stiffen and, hence, reducedisplacements. One example of this is fuel

tanks used for satellite launchers andspacecraft. If accurate displacementsare to be computed, geometry non-linearities have to be considered.

MaterialMaterial factors become increas-

ingly important when a structure isrequired to function consistently andreliably in extreme environments —such as structures that must operateat high temperatures and pressures,provide earthquake resistance, or be impact-worthy or crash-worthy.Plastics, elastomers and compositesare being used as structural materials

Nonlinear SimulationProvides More Realistic ResultsWhen parts interact and experience large deflections and extreme conditions, nonlinear technology is required to simulate real-life situations.By Siddharth Shah, Product Manager, ANSYS, Inc.

Top-loading simulationof a plastic bottle

Frictional contact between the rotor and the brakepad in a brake assembly

resources and manpower. For many, thesoftware appeared cumbersome, chal-lenging and intimidating. It was acceptableand often preferable to get by with physical testing alone. That is not the case today,however. Nonlinear structural simulation isno longer an intimidating tool, but rather one that ANSYS has made available to allengineers by fusing its complex physicsinto an easy-to-use interface in the ANSYSWorkbench environment. ■

with increasing frequency. These materialsdo not follow the linear elastic assumption ofstress–strain relationships. Structures madewith these materials may undergo appre-ciable changes in geometric shape beforefailure. Without accounting for this materialbehavior, it can be impossible to extractmeaningful and accurate information fromtheir simulations.

In the past, nonlinear analysis was asso-ciated with heavy investment in training,

Medical check valve


“Through the ANSYS Workbench

platform, we have a tool that

allows us to increase the per-

formance of our products. Drastic

reductions in weights and inertia

of the couplings have been

achieved without compromising

the strength of the unit. Lateral

vibration of couplings is now

being estimated to a level of

confidence previously unattain-

able without days of computation

and cost.”— Ron Cooper, Technical Director

Bibby Transmission, U.K.

Turbomachinery Coupling Bibby Transmissions Group — a long-time ANSYS DesignSpace user — has

been a world leader for many years in the design and manufacture of couplingsfor use in industrial markets. The company’s high-speed disc couplings, designedby its TurboFlex division, have been a popular choice for transmission couplingsamong the power, chemical, steel and water treatment industries.

Engineers at Bibby found that with linear analysis assumptions, materialyielding occurred around clearance holes where the flexible coupling was mounted and also when the coupling was rotating near its operating speed.Knowing that they were not capturing material behaviors related to contact andpreloading conditions, engineers at Bibby felt a need to model the material plas-ticity and calculate plastic strains and deflection. This analysis was undertaken toensure that the loading-induced plasticity was localized and did not induce global failure for the coupling. The simulation required nonlinear modeling of con-tact in which the couplings used an interference fit, material behavior for the huband spacer, and bolt preloading for the couplings.

Bibby engineers successfully set up this model within the ANSYS WorkbenchSimulation tool using the previously mentioned nonlinearities and were able to accurately predict the observed behavior. In addition, they were able to identify operating speed — not torque as had been previously believed — as the dominant factor that influenced the observed plastic deformation. This valuableinformation could not have been obtained by physical testing alone.

Thanks to Wilde FEA Ltd. for assistance with this article.

The assembly model includes pretension boltedjoints and BISO material for the hub and spacer.

The von Mises stress exceeds the yieldlimit of 700 MPA, and yet it is localized.

PRODUCTS & TECHNOLOGY: NONLINEAR

25


CHEMICAL PROCESSINGPRODUCTS & TECHNOLOGY: MULTIPHYSICS

Thermoelectric coolers (TECs) serve as small heat pumps, utilizing semiconductors for the cooling action in an enclosedpackage without any moving parts. Because of their quiet opera-tion and small size, the devices are used extensively forspot-cooling electronics in aerospace, defense, medical, com-mercial, industrial and telecommunications equipment. In theextreme environments found in satellites and space telescopesapplications, TECs often are stacked on top of one another to achieve the required cold-side temperatures. The traditional multistage configuration is pyramidal in shape, with the unavoid-ably tall profile posing packaging problems in applications withlimited vertical space.

To address these issues, Marlow Industries developed aninnovative new planar multistage TEC (patent pending) thatreduces overall device height by arranging the thermoelectric elements side-by-side in a single plane, instead of stacking them.Because this configuration radically changed the structure, engineers used ANSYS Multiphysics software in evaluating thethermoelectric (TE) performance and thermomechanical stressesof the device, enabling the company to meet critical deadlines forlaunching the new product in a competitive market.

High Performance from MultiphysicsCoupled SimulationEngineers use ANSYS Multiphysics to study the mechanical strength and thermal performance of an innovative thermoelectric cooler design.By Robin McCarty, Senior Engineer for Product and Process R&D, Marlow Industries, Texas, U.S.A.

Thermoelectric coolers (TECs) are used extensively for thermal management inthe Hubble Space Telescope and other equipment operating in the extreme environment of outer spacePhoto courtesy STScI and NASA

Thermoelectric coolers serve as small heat pumps, utilizing semiconductors for thecooling action in an enclosed package without any moving parts.


PRODUCTS & TECHNOLOGY: MULTIPHYSICS

The company selected the ANSYS Multiphysics productbecause it is recognized as the only commercial finite element analysis package with the capability to model 3-Dthermoelectric effects with the required level of accuracy.Given the multiphysics capabilities of the software, a fullycoupled thermoelectric simulation could be performed, calculating the current densities and temperatures in the TECconsidering both Joule heating and the Peltier effect. Marlowengineers used the calculated temperatures from the thermo-electric analysis of the TECs to perform a static structuralanalysis, which then was used to predict thermal stresses inthe thermoelectric materials due to temperature differencesin the TEC assembly.

Structural analysis indicates the highest magnitude of stress on the cornerof the thermoelectric element where Marlow has historically seen cracking.

The objective of the thermoelectric simulation was todetermine temperature distribution throughout the device.For creating the analysis model, a constant temperature con-dition was applied to the bottom of the mounting solder, anda radiation boundary condition was applied to the cold-sideceramic. A heat load (simulating the heat-producing deviceto be cooled) was applied to the cold side of the TEC, and aDC current was applied to the TEC’s electrical terminals todrive the thermoelectric cooling. From this coupled-physicssimulation, the minimum cold-side temperature, temperatureuniformity of the top stage, voltage drop and electrical resistance of the TEC were determined.

Once the temperature distribution of the TEC assemblywas calculated from the thermoelectric model, it wasapplied to the TEC assembly in a static structural analysis.To mimic the TEC’s mounting conditions, the solder on the

How a Thermoelectric Cooler WorksA thermoelectric cooler operates based on a principle known as

the Peltier effect, in which cooling occurs when a small electric currentpasses through the junction of two dissimilar thermoelectric materials: a“p-type” positive semiconductor with a scarcity of electrons in its atomsand an “n-type” negative semiconductor with an abundance of electrons.Current is carried by conductors connected to the semiconductors,with heat exchanged through a set of ceramic plates that sandwich thematerials together.

When a small positive DC voltage is applied to the n-type thermoelement, electrons pass from the p- to the n-type material, and the cold-side temperature decreases as heat is absorbed. The heat absorption(cooling) is proportional to the current and the number of thermoelectriccouples. This heat is transferred to the hot side of the cooler, at whichpoint it is dissipated into the heat sink and surrounding environment.

P N

- +V

Heat absorbed from device being cooled

Heat dissipated into hot exchanger

DC power source

Heat sinkconnected tothis surface

Ceramicelectricalinsulator

Cold exchanger connectedto this surface

Ceramic

Conductor Conductor

Coupled-physics simulation determined the temperature distribution throughout thedevice (top). These results were applied to the TEC assembly to perform a static structural analysis of the structure (bottom).


PRODUCTS & TECHNOLOGY: MULTIPHYSICS

hot side of the device was fixed on the bottom surface.Maximum principal stress was used to evaluate and com-pare the TEC designs because it can be directly related tothe failure of a brittle material, such as bismuth telluride.

The testing team identified the thermoelectric elementwith the maximum stress and then refined the finite elementmesh in that area to ensure that stress convergence hadbeen obtained for the structural simulation. Using a plot of maximum principal stress distribution in a typical TE element, the engineering team found that the maximumstress occurs on the corner of the TE element, which correlated to where Marlow historically had seen cracking in thermoelectric elements that resulted in device failure.

To validate the new planar multistage designs, Marlow evaluated the mechanical stress levels for a thermoelectrically

equivalent traditional multistage device and a planar multistagedevice. Each device consisted of three stages equivalent withthermoelectric element dimensions and thermoelectric elementcount per stage. In the model, three different currents were eval-uated, and the maximum principal stress located in the mosthighly stressed thermoelectric element was noted.

Through these analyses, Marlow configured planardesigns with maximum principal stress levels comparable tothe traditional multistage devices. Thermal performance also was nearly equivalent. The correlation between the stress results for the traditional multistage and planar multi-stage devices provided confidence in the new planarmultistage design concepts. This type of evaluation would not have been possible without the multiphysics simulationcapabilities available in software from ANSYS. ■

In contrast to traditional multistage thermoelectric coolers with elements stacked in a pyramid shape (left), the new Marlow flat configuration (right, patent pending) arranges stagesside by side. The new design reduces the height of the device and also changes heat flow through the ceramic material (denoted by the purple arrow).

Package base

Heat-producing device

Package base

Traditional multistage design New planar multistage design

Cold ceramic

Cold ceramic

Solder

SolderHeat-producing device

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