Multi-Objective Reliability-Based Design Optimization utilizing an Adaptively Updated Surrogate Model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F15%3A00231265" target="_blank" >RIV/68407700:21110/15:00231265 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Objective Reliability-Based Design Optimization utilizing an Adaptively Updated Surrogate Model

Popis výsledku v původním jazyce

The goal of this paper is to formulate a methodology for the multi-objective reliability-based design optimization (RBDO) that is applicable for any type of simulation model. The double-loop RBDO formulation seems to be the most robust approach for any kind of a nonlinear limit state function, in which the reliability assessment is nested in the inner cycle corresponding to the optimized variables designed in the outer cycle. The applied asymptotic sampling as an adaptive sampling method for reliabilityassessment seems to be a good compromise between the costs and accuracy. The computational demands can be decreased by using a meta-model instead of the simulation model. Since the design variables change with every iteration and the meta-model is utilized for the reliability assessment, the meta-model is trained only in the vicinity of the relevant design variable which makes the meta-model computationally faster and more precise. Samples from the asymptotic sampling located close to t

Název v anglickém jazyce

Multi-Objective Reliability-Based Design Optimization utilizing an Adaptively Updated Surrogate Model

Popis výsledku anglicky

The goal of this paper is to formulate a methodology for the multi-objective reliability-based design optimization (RBDO) that is applicable for any type of simulation model. The double-loop RBDO formulation seems to be the most robust approach for any kind of a nonlinear limit state function, in which the reliability assessment is nested in the inner cycle corresponding to the optimized variables designed in the outer cycle. The applied asymptotic sampling as an adaptive sampling method for reliabilityassessment seems to be a good compromise between the costs and accuracy. The computational demands can be decreased by using a meta-model instead of the simulation model. Since the design variables change with every iteration and the meta-model is utilized for the reliability assessment, the meta-model is trained only in the vicinity of the relevant design variable which makes the meta-model computationally faster and more precise. Samples from the asymptotic sampling located close to t

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GA15-07299S" target="_blank" >GA15-07299S: Numerické nástroje pro návrh robustních a optimalizovaných experimentů</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering

ISBN

978-1-905088-64-5

ISSN

1759-3433

e-ISSN

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Počet stran výsledku

16

Strana od-do

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Název nakladatele

Civil-Comp Press Ltd

Místo vydání

Stirling

Místo konání akce

Praha

Datum konání akce

1. 9. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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