Robust och Multidisciplinär Optimering av
Fordonsstrukturer
2009-00314
Fordons- och Trafiksäkerhet
Resultatkonferens - 2014
Project Partners
Principal applicant:
Volvo Car Corporation
Project partners:
Combitech AB
Altair Engineering
EnginSoft Nordic AB
Dynamore 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 reliabilitybased 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
Overall accomplishments
 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 FEbased 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
Sandeeep Shetty
Robust design procedure
Define problem
•
•
•
Inputs and outputs
Select Objectives
Uncertainties quantification
Optimisation strategy
Design evaluation
Estimation of the mean and
standard deviation
Select a optimum design
Meta model
Verification
DOE strategy
•
Design of experiments
Verification
‘
Sandeeep Shetty
Articles
Article -1
Article -2
Article -3
Robustness-analysis
Non-deterministic optimization
Efficient Reliability-based
optimization approach

Comparison between FE-based
and metamodel-based
robustness analysis

Comparative study of
deterministic and nondeterministic optimization

Validation of metamodels


New metamodelling approach to
handle discrete responses is
proposed
An approach to perform
optimization of large- scale
vehicle structural application is
presented
Conclusion
 Computational effort is
minimised significantly by using
meta models

Meta-model approach had
acceptable accuracy compared
to FE-based approach.
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
Sandeeep Shetty

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
Documented Results
Licentiate 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
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
MDO process
 Technical report
Comparison of
MDO methods
PhD courses
• single-level methods
• multi-level methods
• optimization courses
• solid mechanics courses
• etc
Conclusion:
 75.5 hp
A single-level method +
metamodels is often the
best choice
MDO studies
 Article 1
• different software
• different sizes
• different methods
• description
• demonstration on a
simple example
Conclusion:
The process is efficient,
flexible, and suitable for
common automotive
structural MDO applications.
The process fits existing
organizations and product
development processes.
etc.
 Article 2
 Experience
Ann-Britt Ryberg
Licentiate
thesis
MDO process
Application example
Front impact
Initiation
v
load case n
load case 1
Setup
Setup
…
Design of
experiments
Metamodel
creation
Screening
25  15, 7, 11, 12 variables
Design of
experiments
Step 3
Define DOE, run simulations,
and extract results.
DOE
Acceptable accuracy
 90, 42, 55, 48 simulations
Metamodel
creation
Step 4
Build, check, and compare
metamodels.
Metamodels
RBF neural networks +
Feedforward neural networks
Optimization
Verification
Verification
Setup
Minimize mass without degrading the
disciplinary performances.
Step 2
Find important design
variables.
Variable
screening
Variable
screening
Step 1
Define problem (load cases,
objectives, constraints, and
design variables).
Step 5
Find optimum solutions.
Step 6
Check results with detailed
model.
tx05_mid_front
intr_mid_front
Side impact
v
intr_upper_side
intr_lower_side
Roof crush
Optimization
Adaptive simulated annealing
Verification
RBFNN: 8% mass red. (1 constr. viol.)
FFNN: 12% mass red.
d
forc_3_roof
forc_max_roof
Modal analysis
Decision
freq_m1_modal
freq_m2_modal
Ann-Britt Ryberg
Publications
Licentiate thesis LIU-TEK-LIC-2013:1
Metamodel-based design optimization – A multidisciplinary approach for automotive structures
by A-B Ryberg
http://liu.diva-portal.org/smash/record.jsf;jsessionid=d0d8422fc5bf97e6f729a89c0b32?searchId=1&pid=diva2:601789
Technical report LIU-IEI-R-12/003
Metamodel-based multi-disciplinary design optimization for automotive applications
by A-B Ryberg, R D Bäckryd, L Nilsson
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-84701
Article 1
Multidisciplinary design optimization methods for automotive structures
by R D Bäckryd, A-B Ryberg, L Nilsson
Submitted
Article 2
A metamodel-based multi-disciplinary design optimization process for automotive structures
by A-B Ryberg, R D Bäckryd, L Nilsson
Under revision
Ann-Britt Ryberg
Futured work
Phase II accepted and started
Project number: 2014-01340
Aim:
• 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..