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An evaluation of simple techniques to model the variation in strain hardening behavior of steel
Linköping University, Department of Management and Engineering. Linköping University, Faculty of Science & Engineering. Painted Body and Closures, Volvo Car Corporation.
Linköping University, Department of Management and Engineering, Solid Mechanics. Linköping University, Faculty of Science & Engineering.
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. Vol. 55, no 3, p. 945-957
Keyword [en]
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: urn:nbn:se:liu:diva-133198DOI: 10.1007/s00158-016-1547-6ISI: 000398114200014OAI: oai:DiVA.org:liu-133198DiVA, id: diva2:1056189
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
In thesis
1. 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. 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: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

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