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OnDemand Webinar Effizienzsteigerung durch multiphysikalische Simulation in der Materialverarbeitung Peter Jeszencsak Frei verwendbar @ Siemens 2019 Realize innovation.

OnDemand Webinar Effizienzsteigerung durch

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OnDemand WebinarEffizienzsteigerung durch multiphysikalische

Simulation in der Materialverarbeitung

Peter JeszencsakFrei verwendbar @ Siemens 2019 Realize innovation.

Frei verwendbar © Siemens 2019

28.11.2019Page 3 Siemens Digital Industries SoftwarePage 3

Raw Material

• Operating Conditions

• Catalyst

Energy

• Steam

• Heat

• Fuel

Value Added

Product

• Waste

• Pollution

• By-products

Profitability in the Metallurgy and Glass Production

Frei verwendbar © Siemens 2019

Page 4 Siemens Digital Industries SoftwarePage 4

Challenges

Energy Improve Efficiency

EnvironmentReduce, Reuse, Recycle

Source: https://www.nrcan.gc.ca/energy/efficiency/industry/technical-info/benchmarking/canadian-steel-industry/5183

Tremendous savings potentialOne of the most energy intensive industry

Frei verwendbar © Siemens 2019

Page 5 Siemens Digital Industries SoftwarePage 5

2020 Vision for Energy Intensive Processes: Heat & Steam

Burners in process boiler systems

• NOx <2 ppm, CO < 5ppm

• Multi-fuel capability

Burners in furnaces

• 90% reduction of pollutants

• CO2 per international agreements

• 20%-50% reduction in fuel consumption

• Multi-fuel capability

Office of industrial technologies, DOE Report DOE/GO102001-1213, Feb 2001

0

10

20

30

40

50

60

70

80

90

100

Aluminum Metals Glass Chemicals Steel Paper Petroleum

STEAM HEAT

Frei verwendbar © Siemens 2019

28.11.2019Page 6 Siemens Digital Industries SoftwarePage 6

Louis Sullivan

Wainwright Building, St. Louis, MO ca.1891

Frei verwendbar © Siemens 2019

28.11.2019Page 7 Siemens Digital Industries SoftwarePage 7

It is the pervading law of all things organic & inorganic,

of all things physical & metaphysical, human & superhuman,

of all true manifestations of the head, heart, & the soul,

that the life is recognizable in its expression,

that form ever follows function.

This is the law

Frei verwendbar © Siemens 2019

28.11.2019Page 8 Siemens Digital Industries SoftwarePage 8

Form = Design

Function = Performance

Frei verwendbar © Siemens 2019

28.11.2019Page 9 Siemens Digital Industries SoftwarePage 9

Base design or a “form” and performance indicator or a

“function”

•BUSINESS PROBLEM

Reduce

Emissions

Improve

Thermal

Performance Burner in a Ethylene Cracker Furnace

Frei verwendbar © Siemens 2019

28.11.2019Page 10 Siemens Digital Industries SoftwarePage 10

Iteratively Evolve the Design

To

Solve Business Problem

Frei verwendbar © Siemens 2019

Page 11 Siemens Digital Industries SoftwarePage 11

Frei verwendbar © Siemens 2019

28.11.2019Page 12 Siemens Digital Industries SoftwarePage 12

Genetic Algorithm

Smart Algorithm

Machine Learning

Artificial Intelligence

Natural Selection

Decision Tree

Evolution

Hybrid

Adaptive

Performance

Revolution

Design

Frei verwendbar © Siemens 2019

28.11.2019Page 13 Siemens Digital Industries SoftwarePage 13

13% Lower

NOx

5% Lower

CO

Optimized

Flame

Shape &

Volume

Frei verwendbar © Siemens 2019

Page 14 Siemens Digital Industries SoftwarePage 14

Simcenter STAR-CCM+

An integrated multiphysics solution for process efficiency

Realism with multiphysics

Fluid dynamics

Multiphase flows

Reacting flows

Solid mechanics

Particle flows

Rheology

Electrochemistry

Electromagnetics

Fluid-structure

interaction

Frei verwendbar © Siemens 2019

28.11.2019Page 15 Siemens Digital Industries SoftwarePage 15

• Optimum material distribution (coke and ore)

required for efficient use of fuel

• Siemens Simcenter STAR-CCM+ is

CAE (computer aided engineering) software that

can analyze performance using fundamental physics

• Phenomenon such burden structure, cohesive zone.

• Algorithms can be used to find optimum operating

conditions or design alternatives that can balance

complex parameters

Use Case: Reduce blast furnace operating costs

Blast Furnace Burden Structure

Unrestricted © Siemens AG 2019

Customer benefits

Reduce fuel costs

Energy savings (>100 K)

Increase operating efficiency

Frei verwendbar © Siemens 2019

28.11.2019Page 16 Siemens Digital Industries SoftwarePage 16

• Characterize of gas-liquid flow to optimize the mixing

efficiency of the Basic Oxygen Furnace (BOF)

• Siemens Simcenter STAR-CCM+ is

CAE (computer aided engineering) software that

can analyze performance using fundamental physics

• Phenomenon such burden structure, cohesive zone.

• Algorithms can be used to find optimum operating

conditions or design alternatives that can balance

complex parameters

Use Case: Improve mixing performance

Basic Oxygen Furnace Mixing

Unrestricted © Siemens AG 2019

Customer benefits

45% decrease in mixing time

Improve steel quality

Frei verwendbar © Siemens 2019

28.11.2019Page 17 Siemens Digital Industries SoftwarePage 17

• Evaluate stirring and mixing efficiency in ladle

• Siemens Simcenter STAR-CCM+ is

CAE (computer aided engineering) software that

can analyze performance using fundamental physics

• Phenomenon such gas injection or magnetic stirring

can be ealuated

• Algorithms can be used to find optimum operating

conditions or design alternatives that can balance

complex parameters

Use Case: Gas or Magnetic Stirring

Ladle Furnace

Unrestricted © Siemens AG 2019

Customer benefits

Improve stirring efficiency

Reduce cost of trial and error with a safer

method

Frei verwendbar © Siemens 2019

28.11.2019Page 18 Siemens Digital Industries SoftwarePage 18

• Effective method to evaluate and mitigate the risk

connected to confined hazardous releases

• Siemens Simcenter STAR-CCM+ is

CAE (computer aided engineering) software that

can analyze performance using fundamental physics

• Phenomenon such gas dispersion, explosive limits,

mean age of gas can be evaluated.

• Algorithms can be used to find optimum operating

conditions or design alternatives that can balance

complex parameters

Use Case: Gas dispersion and explosion limit evaluation

Coke Oven

Unrestricted © Siemens AG 2019

Customer benefits

Low Cost Safety and Risk Analysis

Accurate sizing of ventilation area & rate

Prevent human hazards and accidents

Frei verwendbar © Siemens 2019

Page 19 Siemens Digital Industries SoftwarePage 19

ArcelorMittal

Cutting plant maintenance costs with Simcenter STAR-CCM+

ArcelorMittal uses simulation

to troubleshoot excessive

equipment wear due to

erosion and extends plant

life

30%reduction in erosion

achieved in best design

Frei verwendbar © Siemens 2019

Page 20 Siemens Digital Industries SoftwarePage 20

Key Requirements

• Ability to import CAD from a variety of sources, including

directly from external CAD packages

• Tools to create, modify or repair complex geometry

Workflow Automation

Speed and Performance

Multiphysics Modelling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

Frei verwendbar © Siemens 2019

Page 21 Siemens Digital Industries SoftwarePage 21

Key Requirements

• Robust meshing to capture complex geometry features

• Adequate resolution of fluid and solid regions for accurate

conjugate heat transfer simulations

Workflow Automation

Speed and Performance

Multiphysics Modeling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

Frei verwendbar © Siemens 2019

Page 22 Siemens Digital Industries SoftwarePage 22

Key Requirements

• Ability to model liquid as well as gaseous fuels

• Conjugate heat transfer analysis for component durability

• Accurate prediction of emissions such as NOx and Soot

Workflow Automation

Speed and Performance

Multiphysics Modeling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

NOx in Flameless combustor (LES)

Green areas: NOx > 50 ppm

Blue: Fuel

Orange: Flame front

Frei verwendbar © Siemens 2019

Page 23 Siemens Digital Industries SoftwarePage 23

Engineer Innovation with Simcenter STAR-CCM+

Operational excellence for high temperature processes

FV Flow FE Flow DEM particle FE Stress

Comprehensive multiphysics

Multiple solvers in a single environment

• Choose the right numerical scheme for the physics

• Perform multidisciplinary analyses using one tool

Wide range of physics models in a single environment

• Use the right physics for the engineering problem

• Includes: multiphase, reactions, electromagnetics

Frei verwendbar © Siemens 2019

Page 24 Siemens Digital Industries SoftwarePage 24

Key Requirements

• Robust solvers for combustion simulations

• Excellent scalability for multiphysics simulations

Workflow Automation

Speed and Performance

Multiphysics Modeling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

0%

25%

50%

75%

100%

0

12.288

24.576

36.864

49.152

0 6.144 12.288 18.432 24.576 30.720 36.864 43.008 49.152S

PE

ED

UP

CORES

ColdHotIdeal (100% scaling)

Frei verwendbar © Siemens 2019

Page 25 Siemens Digital Industries SoftwarePage 25

Key Requirements

• Powerful, integrated post processing and visualization

• Tools to understand complex interdependencies

Workflow Automation

Speed and Performance

Multiphysics Modeling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

Frei verwendbar © Siemens 2019

Page 26 Siemens Digital Industries SoftwarePage 26

Key Requirements

• End-to-end pipelined workflow in one environment

• Workflow easily repeated with a few clicks enabling design

space exploration

Workflow Automation

Speed and Performance

Multiphysics Modeling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

CAD Solution AnalysisMesh

R1

R2

Frei verwendbar © Siemens 2019

Page 27 Siemens Digital Industries SoftwarePage 27

Key Requirements

• Intelligent search and design space exploration to improve

combustor performance

• Explore designs that help maximize fuel-air mixing, minimize

emissions, or maximize exit temperature uniformity

Workflow Automation

Speed and Performance

Multiphysics Modeling

Flexible and Robust Meshing

Powerful Data Analysis

Intelligent Design Exploration

Complex Geometry Handling

Frei verwendbar © Siemens 2019

Page 28 Siemens Digital Industries SoftwarePage 28

Simcenter STAR-CCM+ simulation of a generic flat flame burner

Burner Operation Requirements

• Flame Stability

• Acceptable flame pattern / length

• Flue gas patterns

• Avoid Flame impingement

• Avoid Flame-Flame interaction

• Maximize combustion efficiency

• Meet stringent emission standards

Design and Performance Objectives of Burners

CFD modeling of burners operating in their actual environment can

provide useful and detailed information that can be used to asses,

improve and optimize their performance

Frei verwendbar © Siemens 2019

Page 29 Siemens Digital Industries SoftwarePage 29

Design Space Exploration Case Study

Geometry Details:

• 4 Fuel ports

• Fuel and oxidizer at STP – Natural Gas burning in air

• Burner Heat Release = 0.88 MW

• Excess Air Supplied = 10%

Fuel flow rate

Air flow rate

D

Objective : Minimization of CO and NOx from

Baseline Flat Flame Burner Geometry

• Multi-objective optimization

• CO and NOx are competing objectives

Frei verwendbar © Siemens 2019

Page 30 Siemens Digital Industries SoftwarePage 30

Burner Design Variables

Primary injector Spacing

(range: 25mm – 250mm)

Side nozzle angle

(range: 1 to 30 deg, 10 steps)

Primary ports angle spacing

(range: 5 to 45 deg, 11 steps)

Primary nozzle angle

(range: 1 to 20 deg, 10 steps)

Burner tile angle

(range: 1 to 35 deg, 10 steps)

Side nozzle angle spacing

(range: -120 to 60 deg, 50 steps)

Frei verwendbar © Siemens 2019

Page 31 Siemens Digital Industries SoftwarePage 31

Burner Optimization Results

Fuel jet resolution using table

based refinement

14 million cells

Sym

me

try

pla

ne

Volume rendering of the flames

4,50E-05

4,51E-05

4,52E-05

4,53E-05

4,54E-05

4,55E-05

1,50E-04 1,90E-04 2,30E-04 2,70E-04 3,10E-04 3,50E-04

To

tal C

O a

t th

e E

xit (

kg

/s)

Total NOx at the Exit (kg/s)

Pareto Front and BaselineOptimization

Baseline

Best Design

Baseline

Lowest NOx and CO

• A total of 85 designs were run

• 13 designs did not meet the following constraints and were rejected:

• Constraint 1: Meet Flame Height Requirement

• Constraint 2: Meet average fire box temperature

• Best design minimizes CO by 0.5% and NOx by 13% from baseline

Frei verwendbar © Siemens 2019

28.11.2019Page 32 Siemens Digital Industries SoftwarePage 32

Form follows Function

Performance leads

Design