Abaqus2004 Morpher Isight


Published on

Published in: Technology
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Abaqus2004 Morpher Isight

  1. 1. MESH MORPHING BASED SHAPE OPTIMIZATION OF A CLUTCH LEVER Abaqus Global User Conference, 2004 Presented by: Ramesh Padmanaban, Ragavendran Vasudevan, , g , Radha Krishnan Detroit Engineered Products, Inc. Yogesh Wadhera – New Venture Gear Mike Sheh – Engineous Inc.
  2. 2. Recent Trends in the CAE Industry Significant improvements in computing hardware: High speed processors Networked/distributed computing etc. Significant improvements in Solvers: Reduction in analysis execution time Parallel processing Availabililty of process integration & automation tools: Ability to automate a routine CAE p y process Creation of automated workflows
  3. 3. Recent Trends in the CAE Industry Availability of general purpose optimization programs: Conduct i l C d t single and multi-discipline optimization studies that d lti di i li ti i ti t di th t utilize the automated workflows Create higher level ‘quick turn-around’ response surface models Availability of Morphing & Parametrization Tools: Ability to remove a key bottle neck in the optimization process, i.e, CAD dependency Rapid FE & CFD model generation – in a fraction of time taken by conventional methods b on entional
  4. 4. Role of Design Exploration & Optimization With these trends, the CAE engineer is best positioned for: Conducting DOE studies Conduct Optimization studies Perform design exploration Perform DFSS (Design for Six Sigma) studies Clear move from ‘single point design study to design single study’ exploration Good positioning of the CAE engineers to truly lead p g g y the design process
  6. 6. Different Shape Optimization Approaches Explicit definition of nodal movement as design variables: Rather cumbersome to set up Limited to small shape changes Shape optimization with CAD in the loop: OPTIMIZER New values of design parameters ANALYSIS SOLVER PARAMETRIC CAD SYSTEM NO Is it OPTIMUM ? Regenerated CAD model (new design) YES FE PRE-PROCESSOR PRE PROCESSOR (Auto-meshing) STOP FE model of the new design
  7. 7. Different Shape Optimization Approaches Remeshing from CAD data not fully automatable If FE model is an assembly comprising of different components and different types of elements remeshing elements, almost impossible May be limited to only shape parameters Mesh Morphing based shape optimization process OPTIMIZER New values of d i N l f design parameters MORPHER (FE/CFD Parametrization tool) Analysis ready FE model of new design ANALYSIS SOLVER NO Is it OPTIMUM ? YES STOP
  8. 8. Different Shape Optimization Approaches In this process CAD model generation is completely eliminated from the optimization process Models generated by the Morpher are analysis ready Process inherently robust Large shape changes are possible
  9. 9. Important stages in the Morpher based shape optimization process Parametrization of the FE (or CFD) model Analysis Process Automation Optimization
  10. 10. Parametrization: High Level Description Linear Static Analysis Model Non-linear Static Model MESHWORKS/MORPHER Parametrized V3.0 Model Data Noise & Base Morphing and Vibrations model Vib ti d l Parametrization Tool Crash Model CFD Model
  11. 11. Types of Design Parameters SHAPE FEATURE STRUCTURAL GENERAL PARAMETERS PARAMETERS PARAMETERS PARAMETERS Cross-section of A- Automated stiffener Thickness of Air bag firing time pillar (bead) creation shell structures (stiffness/frequency) Friction coefficient Number of stiffener Cross-sectional Vent Opening width of Column stroke beads and their properties of Passenger Air Bag spacing beam members Stiffness curve (occupant safety) Automated Etc. Etc. Front hood angle punching of holes (external and slots aerodynamics) Etc. Rail width & height (crashworthiness) Tether length & connection location Etc.
  12. 12. Parametrizing FE/CFD models Parametrization of the FE/CFD Model / Use Morpher to parametrize existing FE/CFD models Introduce shape, structural, feature and general parameters FE/CFD models become INTELLIGENT PARAMETRIC FE/CFD models
  13. 13. Creating a Design Design A Design B Design Design Design parameter A parameter B parameter C Morph Set A Morph Set B Morph Set C Control Zone Deformation Zone Fixed Zone
  14. 14. Concept of Parametric FE model (contd.) DP3 DP1 – Length design variable L th d i i bl DP2 – Height design variable DP3 – Width design variable DP2 DP4 – Radius design variable DP4 DP1 DP1 – 3.5 DP2 – 4.0 40 Design 1 g DP3 – 1.2 DP4 – 2.0 Parametrized FE model DP1 – 4.0 DP2 – 5.0 DP3 – 2.0 Design 2 DP4 – 2.5
  15. 15. Optimization loop Design 1 DP1 Design 2 DP2 Design 3 g P met i ed FE model Parametrized DP3 DP4 Design n OPTIMUM Loop 1 Loop 2 Loop 3 Loop n
  16. 16. Analysis Process Automation Use an analysis process automation tool such as Isight to automate typical analysis process steps executed by the CAE engineer These steps would typically include: Submission f h S b i i of the model for analysis to Abaqus d lf l i Ab From the results generated, extract the specific output parameters such as maximum deflection, maximum stress, contact pressure etc etc. Compute sensitivities of output parameters with respect to design variables Based on sensitivities, generate new values for design variables sensitivities Execute Morpher to generate analysis model of new design Proceed with the next loop Analysis t ti i A l i process automation is essential for automated ti l f t t d optimization process
  17. 17. Optimization Methodology Optimization p FEA Run time Resource & Project calendar time Number of Design Parameters Design Space – Linear & Non-linear A t t d Automated Model Response Surface M d l R S f
  18. 18. Analysis Process Automation & Optimization set up Meshworks/Morpher Parametrization & shape change engine g Analysis ready FE/CFD iSIGHT (Design model with new shape parameter values generation) Abaqus analysis q y FE / CFD Analysis iSIGHT NO output Parsing Conve r- Results extraction gence YES optimum
  19. 19. Optimization Loop (iSIGHT) Batch Morpher Shape change Abaqus Translation Remote execution of Abaqus iSIGHT waiting for Abaqus results Results extraction Remote deletion of old files
  20. 20. iSIGHT integration with Morpher – Design Parameter file iSIGHT modifies the values of each design parameter in DP file. A sample file is shown above. The logical way of automatically modifying the design parameter is using an optimization algorithm.
  21. 21. Results Extraction iSIGHT extracts the results from the text output file ( from analysis ). A sample file is shown above
  22. 22. Presentation of actual case study – optimization of clutch lever Objective function : Minimize D fl ti i th l t h l Mi i i Deflection in the clutch lever Constraints : Maximum stress < baseline maximum M i b li i stress t Design Variables: Shape of diffe ent feat es of the cl tch le e different features clutch lever Range of the design variables: Range based on manufacturability, package space and manufacturability element quality constraints
  23. 23. Lever - Loads and BC Two points are rigidly constrained g y except for the rotation about y axis z axis translation is constrained 2.86KN 2 86KN X axis 5.65KN Z axis Material = Cast Iron
  24. 24. Design Variables of the Clutch lever Thickness of ribs Width of web Thickness of web Height of ribs
  25. 25. Optimization – Design Space
  26. 26. Results Review - Mass history plot X 1000kg
  27. 27. Results Review - Maximum Von Mises stress history plot MPa
  28. 28. Optimization Statistics Multi-genetic global optimization scheme used Optimum obtained after 80 loops Total completion time for Abaqus analysis, results extraction & morphing in each loop = 30 min. HPJ6700 machine used for analysis After obtaining optimum for maximum stiffness, a separate optimization was carried out to minimize mass Results are presented in the subsequent slides
  29. 29. Results of Optimization Stiffness was improved about 25% Stress levels were maintained below the target of the material yield strength There was marginal increase in weight
  30. 30. Results of Optimization for maximizing stiffness Shape change from original to Optimal design Baseline design Optimized design
  31. 31. Results of Optimization for minimizing mass Shape change from original to Optimal design DV2 Baseline Optimum DV5 & DV7 Baseline Optimum DV4 Baseline Optimum Optimized design Baseline design DV5 & DV7 DV9 Baseline Baseline Optimum Optimum
  32. 32. Baseline to Optimum
  33. 33. Conclusions A robust mesh morphing based shape optimization process has been demonstrated It can be effectively used on components with complex geometries Significant shape change has been effected in a robust manner using this process The process can be successfully implemented on large system level models with multi-disciplinary constraints The ti i d d l b Th optimized model can be exported out in stereo-lithography (STL) t d ti t lith h file format, that can be imported into any CAD system, using which a detailed geometry can be built Using hi U i this process, the CAE engineer can truly lead the design process h i l l d h d i