Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Optimization of Vehicle Structures under Uncertainties
Linköping University, Department of Management and Engineering. Linköping University, Faculty of Science & Engineering.
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. , p. 44
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: urn:nbn:se:liu:diva-133199DOI: 10.3384/diss/diva-133199ISBN: 9789176856307 (print)OAI: oai:DiVA.org:liu-133199DiVA, id: diva2:1056300
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
List of papers
1. Robustness study of a hat profile beam made of boron steel subjected to three point bending
Open this publication in new window or tab >>Robustness study of a hat profile beam made of boron steel subjected to three point bending
2016 (English)In: International Journal of Vehicle Systems Modelling and Testing, ISSN 1745-6436, E-ISSN 1745-6444, no 3, p. 252-270Article in journal (Refereed) Published
Abstract [en]

It is essential to account for variations in the manufacturing process and in loading conditions when improving the robustness and reliability of a product’s design. A finite element study of the robustness of a hat profile beam made from boron steel subjected to a three point bending load is presented, and an approach to incorporate the variations investigated is demonstrated. Fracture risk factors and the maximum deflection of the beam are the measured responses. Spatial variation of the sheet thickness is considered in the forming simulations, along with other input variations. Stress-strain relations from tensile tests have been used in the robustness analyses to represent the variation in material properties. Furthermore, validations of four metamodels have been performed. Both the responses measured were found to be sensitive to input variations. Separate metamodels were created for each risk prone zone in order to improve the performance of the metamodels for risk factor responses.

Place, publisher, year, edition, pages
Bucks: InderScience Publishers, 2016
Keywords
Robustness analysis; Monte Carlo analysis; metamodel; boron steel; fracture risk factor
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-103690 (URN)10.1504/IJVSMT.2016.080880 (DOI)
Available from: 2014-01-23 Created: 2014-01-23 Last updated: 2017-12-06Bibliographically approved
2. Multiobjective reliability-based and robust design optimisation for crashworthiness of a vehicle side impact
Open this publication in new window or tab >>Multiobjective reliability-based and robust design optimisation for crashworthiness of a vehicle side impact
2015 (English)In: International Journal of Vehicle Design, ISSN 0143-3369, E-ISSN 1741-5314, Vol. 67, no 4, p. 347-367Article 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
Keywords
Multiobjective optimisation; robust optimisation; reliabilitybased optimisation; crashworthiness; Monte Carlo analysis; metamodel; boron steel; fracture risk factor
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-103691 (URN)10.1504/IJVD.2015.070410 (DOI)000359461500002 ()
Available from: 2014-01-23 Created: 2014-01-23 Last updated: 2017-12-06Bibliographically approved
3. Efficient reliability-based optimization using a combined metamodel and FE-based strategy
Open this publication in new window or tab >>Efficient reliability-based optimization using a combined metamodel and FE-based strategy
2014 (English)In: Engineering Optimization IV - Proceedings of the 4th International Conference on Engineering Optimization, ENGOPT 2014 / [ed] Rodrigues H.C., Herskovits J., Soares C.M.M., Guedes J.M., Araujo A.L., Folgado J.O., Moleiro F., Madeira J.F.A., Leiden, The Netherlands: CRC Press, 2014, p. 471-478Conference paper, Published paper (Refereed)
Abstract [en]

It is essential to consider the uncertainties in design variables of an optimization process in order to create a reliable design. The computational effort required to perform reliability-based optimization of complex engineering problems is very high and most recent studies have used metamodels in order to reduce the computational effort.An efficient decoupled sequential reliability-based optimization using the combination of metamodel-based strategy and FE-based strategy is presented in this paper. Optimization loop and stochastic analysis loops are completely decoupled. Stochastic analysis is performed at the end of each optimization iteration and at the beginning of the first iteration only. In each optimization iteration, the standard deviation of constraint functions from the previous iteration is used. The stochastic analysis is performed using an FE-based Monte Carlo method,whereas metamodels have been utilized for the optimization. This approach is demonstrated using two engineering examples.

Place, publisher, year, edition, pages
Leiden, The Netherlands: CRC Press, 2014
National Category
Control Engineering Computational Mathematics Communication Systems Telecommunications Computer Engineering
Identifiers
urn:nbn:se:liu:diva-133197 (URN)2-s2.0-84941985436 (Scopus ID)
Conference
ENGOPT 2014 - 4th International Conference on Engineering optimization, 8-11 September, Instituto Superioe Tecnico, Lissabon, Portugal
Available from: 2016-12-14 Created: 2016-12-14 Last updated: 2018-01-13Bibliographically approved
4. An evaluation of simple techniques to model the variation in strain hardening behavior of steel
Open this publication in new window or tab >>An evaluation of simple techniques to model the variation in strain hardening behavior of steel
2017 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 55, no 3, p. 945-957Article in journal (Refereed) Published
Abstract [en]

It is important to consider variations in material parameters in the design of automotive structures in order to obtain a robust and reliable design. However, expensive tests are required to gain complete knowledge of the material behavior and its associated variation. Consequently, due to time and cost constraints, simplified material scatter modeling techniques based on scatter data of typical material properties provided by the material suppliers are used at early design stages in simulation-based robustness studies. The aim of this paper is to study the accuracy of the simplified scatter modeling methods in representing the real material variation. The simplified scatter modeling methods are evaluated by comparing the material scatter obtained by them to the scatter obtained by complete tensile tests, which are obtained after detailed timeconsuming experimental investigations. Furthermore, an accuracy assessment is carried out based on selected responses from an axially-crushed, square tube made from DP600 steel.

Place, publisher, year, edition, pages
Bonn: Springer, 2017
Keywords
Flow curve, Material scatter, Stochastic simulation, Tensile test
National Category
Aerospace Engineering Building Technologies Composite Science and Engineering Applied Mechanics Other Materials Engineering
Identifiers
urn:nbn:se:liu:diva-133198 (URN)10.1007/s00158-016-1547-6 (DOI)000398114200014 ()
Note

Funding agencies: Robust and multidisciplinary optimization of automotive structures Project - Vinnova FFI; Volvo Car Corporation

Available from: 2016-12-14 Created: 2016-12-14 Last updated: 2017-04-20Bibliographically approved

Open Access in DiVA

fulltext(629 kB)215 downloads
File information
File name FULLTEXT01.pdfFile size 629 kBChecksum SHA-512
5a35d4163ac40ab09145f82f417585142e033dfb272178d5a6542aefc8301d3e1312c8169567f79d9d2518988eafc2c259ad9d6e4cb510c34f834fa8f00b9674
Type fulltextMimetype application/pdf
fulltext(1166 kB)78 downloads
File information
File name FULLTEXT02.pdfFile size 1166 kBChecksum SHA-512
32be27ad26ce9c1383cd182eef32deaa33ed26345bb6827420c6d270323102b6fdf4af1c40d7b5472e9c988d1cb5705180b3cc728c8fd549939a518d9c49fe1e
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Shetty, Sandeep
By organisation
Department of Management and EngineeringFaculty of Science & Engineering
Aerospace EngineeringApplied MechanicsProduction Engineering, Human Work Science and ErgonomicsVehicle EngineeringOther Engineering and Technologies not elsewhere specified

Search outside of DiVA

GoogleGoogle Scholar
Total: 293 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 1417 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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