htc2012 hyperstudy training
TRANSCRIPT
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Model Calibration usingAltair HyperStudy
Innovation Intelligence Fatma Koer
Altair Engineering
May, 2012
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
HyperStudy is:
Solver Neutral Design of Experiment, Multi-Disciplinary Optimization and Stochastic Simulation Engine.
Automates processes for parametric study, optimization and robustnessstudy, optimization and robustnessassessment
Integrated with HyperWorks thru HyperMesh, MotionView and direct solver interfaces
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
HyperStudy: Business Benefits
Design high-performance products
Reduce cost and development cycle
Increase the return on CAE investments
Cost effective and innovative licensing model
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
HyperStudy: User Benefits
Streamlined design exploration, study and optimization process Solver-neutral, multi-disciplinary Advanced data-mining capabilities State-of-the-art optimization engine HyperWorks integration: Morphing, Direct parametrization, Results Readers
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Unilever Corp. (UK)Optimal Comfort Softener Bottle Design
Challenge: Increase collapse load and stiffness of a softener bottle while minimizing the mass
Solution: DOE to screen design variables:
Fractional Factorial Method 7 design variables are selected
DOE to create Approximate Model: Box Behnken Method
Optimization using the Approximate Model: ARSM
Results: Buckling capacity increased over 20% Mass reduced over 5%
HyperStudy provides potential for reducing design cycle times, through facilitating definition of strong design concepts early in the design process, which require fewer down-stream modifications.
Richard McNabb, Design Analysis and Technology Manager, Lever Faberg, Unilever Corporation
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Capabilities Overview
Capabilities Overview
Next Generation
User InterfaceModel Calilbration
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
HyperStudy: Architecture Schema
StudyEngine:
Model
VariantVariantVariantVariant
Variant
SimulationSimulation
Creation
JobManagementEngine:
DOEFitOptimization Stochastics
ResultsResultsResultsResults
Results
SimulationSimulationSimulationSimulationSimulation
Study ResultsOptimal parameters
SensitivitiesModel Robustness
Management
Extraction
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Parameters Screening
HyperStudy: Study Types
DOE Approximation Optimization Stochastic
Parameters ScreeningSystem Performance StudyResponse Surface EvaluationOptimum DesignVariation AnalysisRobust DesignReliability Design
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
HyperStudy: Key Differentiators
Technology
State-of-the-art exploration,
approximation and optimization methods
Direct Results Access
Direct result access to most Solvers: Abaqus, Ansys, Madymo, etc.
DataMining
Correlations, SnakeView, PCA, RDA,
etc.
Direct Parameterization
Automatic transfer of modal parameters from
HyperMesh, MotionView, HyperForm
Shape Optimization
Seamless integration with HyperMorph
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Next Generation HyperStudy
Capabilities Overview
Next Generation
User InterfaceModel Calilbration
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Next Generation HyperStudy
Differentiators of HyperStudy are kept tree-based process navigation in the study pages
Changes in user interface data in tables extended edition features dedicated wizards
Enhanced Task Management orchestration live monitoring and control
Improved Post-Processing multiple plots richer charting
Reporting messaging study report
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Model Calibration using HyperStudy
Capabilities Overview
Next Generation
User InterfaceModel Calibration
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Background
We need to model 6063 T7 Aluminum material in Radioss for the first time. 6063 T7 Aluminum has an isotropic elastic-plastic behavior which can be reproduced by a Johnson-
Cook model without damage as:
In Radioss Johnson-Cook model can be defined using the Law2 material card as:
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Background
In this card, we do not know the values for five material properties: Youngs modulus, yield stress (a), hardening modulus (b), hardening exponent (n) , and maximum stress.
We have strain-stress curve from tensile testing of a a 6063 T7 Aluminum sample We have strain-stress curve from tensile testing of a a 6063 T7 Aluminum sample
Our objective is to find the five material property values of Radioss Law2 card such that Radioss simulation of the tensile test gives the same curve as the test. Then we can be confident in our material model for further simulations.
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Background
We can model the tensile testing in Radioss as a quarter of a standard tensile test and using symmetry conditions. A traction is applied to the specimen via an imposed velocity at the left-end.
Thickness = 2.0 mm
We can then calculate the engineering strains are by dividing the node 1 displacement by the reference length (75 mm), and engineering stresses by dividing the section 1 force by its initial surface (12 mm2).
Node 1
(displacement) Section 1
(force)
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Results from the Initial Radioss Simulation
Radioss simulation with initial guesses of Youngs modulus, yield stress (a), hardening modulus (b), hardening exponent (n) , and maximum stress values of 60400 MPa, 110 MPa, 120 MPa, 0.15, 280 MPa leads to significant differences between the test and simulation results as seen below
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
ObjectiveThe objective is to find the values for the five material properties so that the simulationresults match to tensile test results. We can achieve this if we minimized (ideally zero):1. difference between Radioss and experimental stress (141MPa) at Strain equal 0.022. difference between Radioss and experimental stress (148MPa) at Necking point3. difference between Radioss and experimental strain (0.08) at Necking point
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Method
We will use optimization to achieve this objective.
We will use a special optimization problem formulation called System Identification.
System identification minimizes the sum of normalized error-squared. Error is the difference between the target values and simulation results.
2
where fi(x) is the ith response obtained from analysis, Ti are the target value for the ith response.
Note that, in HyperStudy we do not need to enter this equation manually. We can simply enter the target values for each response and use the System Identification objective.
2
mini
ii
TTf
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Problem Formulation
where
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DemonstrationDemonstration
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DOE Results
32 Design Full Factorial
Youngs Modulus and SigMax are not significant so we will continue our study with three design variables.
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
First Optimization Results
Adaptive Response Surface Method (ARSM) is used for this case. In 5 iterations, we minimized the system identification objective function value from
0.158 to 0.06. In the optimum design, the DV values are: 99, 132, 0.165 The response values are: 140, 146, 0.06 (note that the targets were 141, 148 and 0.08;
initial design values were 147, 150, 0.05)
We observe that all three design variables are at their lower or upper bounds. If we can relax those bounds; we may be able to get closer to the target values. We started a new optimization from the best result of the first optimization and with
relaxed bounds.
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Second Optimization Results
ARSM is used for this case. In 10 iterations, we minimized the system identification objective function value from
0.06 to 0.0. In the optimum design, the DV values are: 93, 157, 0.2. The response values are: 140, 149, 0.08 (note that the targets were 141, 148 and 0.08)
First two objectives are off by 1.0 from the target and last one is on target
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Results
Initial Opt 1 Opt 2VariablesE 60400 60400 60400a 110 99
(99-121)93
(50-150)b 120 132 157
(108-132) (100-200)n 0.15 0.165
(0.135-0.165)0.19
(0.1-0.3)Sigma 280 280 280ResponsesObj1 147 (Target 141) 140 140Obj2 150 (Target 148) 146 149Obj3 0.05 (Target 0.08) 0.06 0.08
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Results
Radioss results for the Initial Design vs. Test Results: There are significant differences between the two curves.
Radioss results for the Optimum Design vs. Test Results: The two curves are almost identical.
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Conclusions
HyperStudy provides a user friendly GUI to easily set up design studiesincluding system identification.
Design Study methods in HyperStudy are efficient and effective in meetingdesign targets.
HyperStudy is solver independent and can also work with applicationsrunning other solvers such as LS-Dyna, Abaqus, Ansys, Adams, etc.
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Copyright 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Altair HyperStudy
Altair HyperStudy is a user-level, solver neutral, multi-disciplinary, exploration, study and optimization tool,
helping engineers to
HyperStudy enabled us to efficiently implement DOE and optimization methods. The new automatedprocess is able to cover different types of applications and can be used in various projects. Besides thetechnical advantages and the saved development time, Magna benefits from being an HyperWorks PartnerAlliance member and therefore can use the needed software at no additional costs.
Werner Reinalter, Teamleader, MBS Simulation, Magna Steyr
helping engineers to design high-performance products, reduce cost and development cycle, increase the return on CAE investments
with advanced optimization and data mining capabilities.