liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multiobjective reliability-based and robust design optimisation for crashworthiness of a vehicle side impact
Linköping University, Department of Management and Engineering, Solid Mechanics. Linköping University, The Institute of Technology. Painted Body and Closures, Volvo Car Corporation, Göteborg, Sweden.
Linköping University, Department of Management and Engineering, Solid Mechanics. Linköping University, The Institute of Technology.
2015 (English)In: International Journal of Vehicle Design, ISSN 0143-3369, E-ISSN 1741-5314, Vol. 67, no 4, 347-367 p.Article in journal (Refereed) Published
Abstract [en]

Optimisation of vehicle design is necessary to meet increased safety requirements, new emission regulations, and to deal with competition in the global market, etc. However, optimised design using classical optimisation techniques with deterministic models might not meet the desired performance level or might fail in extreme events in real life owing to uncertainties in the design parameters and loading conditions. Consequently, it is essential to account for uncertainties in a systematic manner to generate a robust and reliable design. In this paper, an approach to perform multiobjective, reliability-based, and robust design optimisation is presented using a vehicle side impact crashworthiness application. Metamodels have been used in the optimisation process to decrease computational effort. Variations in material properties, thicknesses, loading conditions, and B-pillar heat-affected zone material strength have been considered for the stochastic optimisation. A comparative study of deterministic, reliability-based, and robust optimisation approaches is performed.

Place, publisher, year, edition, pages
InderScience Publishers, 2015. Vol. 67, no 4, 347-367 p.
Keyword [en]
Multiobjective optimisation; robust optimisation; reliabilitybased optimisation; crashworthiness; Monte Carlo analysis; metamodel; boron steel; fracture risk factor
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-103691DOI: 10.1504/IJVD.2015.070410ISI: 000359461500002OAI: oai:DiVA.org:liu-103691DiVA: diva2:690292
Available from: 2014-01-23 Created: 2014-01-23 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Optimization of Vehicle Structures under Uncertainties
Open this publication in new window or tab >>Optimization of Vehicle Structures under Uncertainties
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

New emission targets, increased safety requirements and competition in the global market have led the automotive industry to focus more on developing efficient, optimised vehicle structures. Consequently, the use of simulation-based design in vehicle engineering has increased significantly in recent years. Advancements in computational power and efficient algorithms have made the simulation-based design process faster and more efficient and also made it possible to include structural optimisation. However, optimised design using classical (deterministic) optimisation techniques might not achieve the desired performance in real life due to uncertainties in input parameters such as variation in material properties, geometrical parameters, loading conditions, etc. Consequently it is necessary to consider these variations in the optimisation process in order to create a robust and reliable design. However, the incorporation of uncertainties into the design optimisation of a full-scale vehicle model tends to be computationally expensive so approximation models have often been utilised to minimise  computational effort.

In this thesis, different approaches to evaluate robustness and to perform non-deterministic optimisation have been studied. Primary focus was on robust design and reliability-based optimisation methods. These methods were verified using a complex vehicle engineering application. The first part of the study involves evaluation of robustness analysis methods and a comparative study has been performed between FE-based robustness analysis and metamodel-based robustness analysis. Furthermore, different metamodelling techniques were also compared with respect to performance. An approach to handle the fracture risk factors using metamodels is also presented. In the second part of the study, an approach to perform multiobjective reliability-based optimisation and robust design optimisation is presented and verified using a vehicle side impact crashworthiness application. The importance of a non-deterministic optimisation approach as compared to a deterministic approach is illustrated by comparing the results from non-deterministic optimisation with those from deterministic optimisation. The approaches presented in the study were found to be suitable for applications related to vehicle structures.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. 30 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1643
Keyword
Multiobjective optimisation; robustness analysis; robust design optimisation; reliability-based optimisation; crashworthiness; metamodel
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-103692 (URN)978-91-7519-420-2 (ISBN)
Supervisors
Available from: 2014-01-23 Created: 2014-01-23 Last updated: 2014-01-23Bibliographically approved
2. Optimization of Vehicle Structures under Uncertainties
Open this publication in new window or tab >>Optimization of Vehicle Structures under Uncertainties
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Advancements in simulation tools and computer power have made it possible to incorporate simulation-based structural optimization in the automotive product development process. However, deterministic optimization without considering uncertainties such as variations in material properties, geometry or loading conditions might result in unreliable optimum designs. 

In this thesis, the capability of some established approaches to perform design optimization under uncertainties is assessed, and new improved methods are developed. In particular, vehicle structural problems which involve computationally expensive Finite Element (FE) simulations, are addressed.

The first paper focuses on the evaluation of robustness, given some variation in input parameters, the capabilities of three well-known metamodels are evaluated. In the second paper, a comparative study of deterministic, reliability-based and robust design optimization approaches is performed. It is found that the overall accuracy of the single-stage (global) metamodels, which are used in the above study, is acceptable for deterministic optimization. However, the accuracy of performance variation prediction (local sensitivity) must be improved. In the third paper, a decoupled reliability-based design optimization (RBDO) approach is presented. In this approach, metamodels are employed for the deterministic optimization only while the uncertainty analysis is performed using FE simulations in order to ensure its accuracy.

In the fifth paper, two new sequential sampling strategies are introduced that aim to improve the accuracy of the metamodels efficiently in critical regions. The capabilities of the methods presented are illustrated using analytical examples and a vehicle structural application.

It is important to accurately represent physical variations in material properties since these might exert a major influence on the results. In previous work these variations have been treated in a simplified manner and the consequences of these simplifications have been poorly understood. In the fourth paper, the accuracy of several simple methods in representing the real material variation has been studied. It is shown that a scaling of the nominal stress-strain curve based on the Rm scatter is the best choice of the evaluated choices, when limited material data is available.

In this thesis work, new pragmatic methods for non-deterministic optimization of large scale vehicle structural problems have been developed. The RBDO methods developed are shown to be flexible, more efficient and reasonably accurate, which enables their implementation in the current automotive product development process.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. 44 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1809
National Category
Aerospace Engineering Applied Mechanics Production Engineering, Human Work Science and Ergonomics Vehicle Engineering Other Engineering and Technologies not elsewhere specified
Identifiers
urn:nbn:se:liu:diva-133199 (URN)10.3384/diss/diva-133199 (DOI)9789176856307 (ISBN)
Public defence
2017-01-20, C3, Hus C, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2016-12-14 Created: 2016-12-14 Last updated: 2017-01-09Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Shetty, SandeepNilsson, Larsgunnar

Search in DiVA

By author/editor
Shetty, SandeepNilsson, Larsgunnar
By organisation
Solid MechanicsThe Institute of Technology
In the same journal
International Journal of Vehicle Design
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 378 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf