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Reliability Based Design Optimization Using a Single Constraint Approximation Point
KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.).
KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.).ORCID iD: 0000-0001-8068-2360
2011 (English)In: Journal of mechanical design (1990), ISSN 1050-0472, E-ISSN 1528-9001, Vol. 133, no 3, 031006- p.Article in journal (Refereed) Published
Abstract [en]

The computational effort for reliability based design optimization (RBDO) is no longer prohibitive even for detailed studies of mechanical integrity. The sequential approximation RBDO formulation and the use of surrogate models have greatly reduced the amount of computations necessary. In RBDO, the surrogate models need to be most accurate in the proximity of the most probable point. Thus, for multiply constrained problems, such as fatigue design problems, where each finite element (FE)-model node constitutes a constraint, the computational effort may still be considerable if separate experiments are used to fit each constraint surrogate model. This paper presents an RBDO algorithm that uses a single constraint approximation point (CAP) as a starting point for the experiments utilized to establish all surrogate models, thus reducing the computational effort to that of a single constraint problem. Examples of different complexities from solid mechanics applications are used to present the accuracy and versatility of the proposed method. In the studied examples, the ratio of the computational effort (in terms of FE-solver calls) between a conventional method and the single CAP algorithm was approximately equal to the number of constraints and the introduced error was small. Furthermore, the CAP-based RBDO is shown to be capable of handling over 10,000 constraints and even an intermittent remeshing. Also, the benefit of considering other objectives than volume (mass) is shown through a cost optimization of a truck component. In the optimization, fatigue-specific procedures, such as shot peening and machining to reduce surface roughness, are included in the cost as well as in the constraints.

Place, publisher, year, edition, pages
2011. Vol. 133, no 3, 031006- p.
National Category
Applied Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-32003DOI: 10.1115/1.4003410ISI: 000288390200008Scopus ID: 2-s2.0-79953059654OAI: oai:DiVA.org:kth-32003DiVA: diva2:409200
Note
QC 20110407Available from: 2011-04-07 Created: 2011-04-04 Last updated: 2017-12-11Bibliographically approved
In thesis
1. Methods for reliability based design optimization of structural components
Open this publication in new window or tab >>Methods for reliability based design optimization of structural components
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cost and quality are key properties of a product, possibly even the two most important. Onedefinition of quality is fitness for purpose. Load-bearing products, i.e. structural components,loose their fitness for purpose if they fail. Thus, the ability to withstand failure is a fundamentalmeasure of quality for structural components. Reliability based design optimization(RBDO) is an approach for development of structural components which aims to minimizethe cost while constraining the probability of failure. However, the computational effort ofan RBDO applied to large-scale engineering problems has prohibited it from employment inindustrial applications. This thesis presents methods for computationally efficient RBDO.A review of the work presented on RBDO algorithms reveals that three constituentsof an RBDO algorithm has rendered significant attention; i ) the solution strategy for andnumerical treatment of the probabilistic constraints, ii ) the surrogate model, and iii) theexperiment design. A surrogate model is ”a model of a model”, i.e. a computationally cheapapproximation of a physics-based but computationally expensive computer model. It is fittedto responses from the physics-motivated model obtained via a thought-through combinationof experiments called an experiment design.In Paper A, the general algorithm for RBDO employed in this work, including the sequentialapproximation procedure used to treat the probabilistic constraints, is laid out. A singleconstraint approximation point (CAP) is used to save computational effort with acceptablelosses in accuracy. The approach is used to optimize a truck component and incorporatesthe effect that production related design variables like machining and shot peening have onfatigue life.The focus in Paper B is on experiment design. An algorithm employed to construct anovel experiment design for problems with multiple constraints is presented. It is based onan initial screening and uses the specific problem structure to combine one-factor-at-a-timeexperiments to a several-factors-at-a-time experiment design which reduces computationaleffort.In Paper C, a surrogate model tailored for RBDO is introduced. It is motivated by appliedsolid mechanics considerations and the use of the first order reliability method to evaluate theprobabilistic constraint. An optimal CAP is furthermore deduced from the surrogate model.In Paper D, the paradigm to use sets of experiments rather than one experiment at atime is challenged. A new procedure called experiments on demand (EoD) is presented. TheEoD procedure utilizes the core of RBDO to quantify the demand for new experiments andaugments it by a D-optimality criterion for added robustness and numerical stability.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. 86 p.
Series
Trita-HFL. Report / Royal Institute of Technology, Solid mechanics, ISSN 1654-1472 ; 0520
Keyword
Reliability
National Category
Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-90753 (URN)
Public defence
2012-03-12, F3, Linstedtsvägen 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20120229

Available from: 2012-02-29 Created: 2012-02-28 Last updated: 2013-01-14Bibliographically approved

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