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Robust och Multidisciplinär Optimering av Fordonsstrukturer
2009-00314
Fordons- och Trafiksäkerhet Resultatkonferens - 2014
Project Partners
Principal applicant: Volvo Car Corporation
Project partners: Combitech ABAltair EngineeringEnginSoft Nordic ABDynamore Nordic AB
Academic partner: Linköpings Tekniska Högskola
Overall Project Objective
Find suitable methods for implementing robust and multidisciplinary design optimization in automotive product development process
Sandeeep Shetty
Robust design optimization
Scope Develop efficient methodologies to perform multiobjective robust and reliability-
based design optimization of large-scale vehicle structures
Investigation of approximate modelling techniques to reduce the computational effort of the optimization process
Implementation of developed methodologies into the existing product development process
Sandeeep Shetty
Different approaches to evaluate robustness and to perform non-deterministic optimisation have been studied
An approach to perform multiobjective reliability-based optimization and robust design optimization is presented and verified using a vehicle side impact crashworthiness application
An efficient reliability-based optimization using a combined metamodel and FE-based strategy is proposed and illustrated using industrial examples
Comparison between FE-based and metamodel-based robustness analysis has been performed
An approach to handle the discrete responses using metamodels is also presented
PhD courses – 60hp
Overall accomplishments
Sandeeep Shetty
Define problem
• Inputs and outputs• Select Objectives• Uncertainties quantification
DOE strategy
• Design of experiments Verification
Robust design procedure
Optimisation strategy
Estimation of the mean and standard deviation
Meta model
‘
Design evaluation
Select a optimum design
Verification
Sandeeep Shetty
Article -1Robustness-analysis
Comparison between FE-based and metamodel-based robustness analysis
Validation of metamodels
New metamodelling approach to handle discrete responses is proposed
Conclusion Computational effort is
minimised significantly by using meta models
Meta-model approach had acceptable accuracy compared to FE-based approach.
Article -2Non-deterministic optimization
Comparative study of deterministic and non- deterministic optimization
An approach to perform optimization of large- scale vehicle structural application is presented
Conclusion Presented metamodel-based
approach was found to be suitable for large-scale deterministic optimization
Further improvement in the presented approach is required in the case of non-deterministic optimization
Article -3Efficient Reliability-based optimization approach
An efficient reliability-based optimization method is proposed and validated using industrial examples
Conclusion Proposed method has better
accuracy and the method is computationally efficient
Articles
Sandeeep Shetty
Documented ResultsLicentiate thesis
S.shetty: Optimization of Vehicle Structures under Uncertainties, Licentiate thesis, Linköping university, Thesis No. 1643
Journal Papers
S. Shetty and L. Nilsson: Multiobjective reliability-based and robust design optimisation for crashworthiness of a vehicle side impact, accepted for publication in the international journal of vehicle design. S. Shetty and L. Nilsson: Robustness study of a hat profile beam made of boron steel subjected to three point bending, Submitted for publication.
Conference Paper
S.shetty: Efficient reliability-based optimization using a combined metamodel and FE-based strategy. published in proceedings of 4th International Conference on engineering optimization (EngOpt2014)
Sandeeep Shetty
Ann-Britt Ryberg
Multidisciplinary design optimization of automotive structures
Scope
Find an efficient MDO process for large-scale applications that takes the special characteristics of automotive structural applications into account considers aspects related to implementation within an organization and product development
process
Outcome
Description and demonstration of an MDO process that is simpler than multi-level methods fits existing organizations better than sequential response surface methods (SRSM) and direct
optimization often more computationally efficient than direct optimization, SRSM and multi-level methods
Ann-Britt Ryberg
Work performed
Literature survey• MDO methods• metamodel-based
optimization
Technical report
PhD courses• optimization courses• solid mechanics courses• etc
75.5 hp
Comparison ofMDO methods• single-level methods• multi-level methods
Conclusion:
A single-level method + metamodels is often the best choice
Article 1
MDO process• description• demonstration on a
simple example
Conclusion:
The process is efficient,flexible, and suitable forcommon automotivestructural MDO applications.
The process fits existingorganizations and productdevelopment processes.
etc.
Article 2
MDO studies• different software• different sizes• different methods
Experience
Licentiate thesis
Ann-Britt Ryberg
MDO process Application example
Decision
Initiation
Design of experiments
Variable screening
Metamodel creation
Setup
Verification
load case 1
Design of experiments
Variable screening
Metamodel creation
Setup
Verification
load case n
…
Optimization
Step 1Define problem (load cases, objectives, constraints, and design variables).
Step 2Find important design variables.
Step 3Define DOE, run simulations, and extract results.
Step 4Build, check, and compare metamodels.
Step 5Find optimum solutions.
Step 6Check results with detailed model.
Modal analysis
freq_m1_modalfreq_m2_modal
Front impactv
tx05_mid_frontintr_mid_front
Roof crush d
forc_3_roofforc_max_roof
Side impact
v
intr_upper_sideintr_lower_side
SetupMinimize mass without degrading the disciplinary performances.
Screening25 15, 7, 11, 12 variables
DOEAcceptable accuracy 90, 42, 55, 48 simulations
MetamodelsRBF neural networks +Feedforward neural networks
OptimizationAdaptive simulated annealing
VerificationRBFNN: 8% mass red. (1 constr. viol.)FFNN: 12% mass red.
Ann-Britt Ryberg
Publications
Licentiate thesis LIU-TEK-LIC-2013:1Metamodel-based design optimization – A multidisciplinary approach for automotive structuresby A-B Ryberghttp://liu.diva-portal.org/smash/record.jsf;jsessionid=d0d8422fc5bf97e6f729a89c0b32?searchId=1&pid=diva2:601789
Technical report LIU-IEI-R-12/003Metamodel-based multi-disciplinary design optimization for automotive applicationsby A-B Ryberg, R D Bäckryd, L Nilssonhttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-84701
Article 1Multidisciplinary design optimization methods for automotive structuresby R D Bäckryd, A-B Ryberg, L NilssonSubmitted
Article 2A metamodel-based multi-disciplinary design optimization process for automotive structuresby A-B Ryberg, R D Bäckryd, L NilssonUnder revision
Phase II accepted and started Project number: 2014-01340Aim:• Take researcher from licentiate to PhD.• Continue development of models for industrial problems.• Industrial implementation of the result from earlier project.• Couple the two areas in a combined study and paper..
Futured work