Polynomial Chaos Construction for Structural Reliability Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F15%3A00231262" target="_blank" >RIV/68407700:21110/15:00231262 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.4203/ccp.109.9" target="_blank" >http://dx.doi.org/10.4203/ccp.109.9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.4203/ccp.109.9" target="_blank" >10.4203/ccp.109.9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Polynomial Chaos Construction for Structural Reliability Analysis

Popis výsledku v původním jazyce

Regarding the structural reliability many important factors such as the environmental conditions as well as structural properties have to be taken into account in designing of structures. As aresult of the growth of powerful computing technology, recently developed procedures in the field of stochastic mechanics have become applicable to realistic engineering systems. This paper focuses on employing a surrogate model based on polynomial chaos expansion in uncertainty quantification for structural reliability analysis. The aim of the paper is to review and compare several approaches such as the stochastic Galerkin method, the stochastic collocation method or linear regression based on Latin hypercube sampling for construction of the polynomial chaos-based approximation of a model response. The advantages and disadvantages of these methods are demonstrated within the comparison with the traditional Monte Carlo method on a simple illustrative example of a frame structure.

Název v anglickém jazyce

Polynomial Chaos Construction for Structural Reliability Analysis

Popis výsledku anglicky

Regarding the structural reliability many important factors such as the environmental conditions as well as structural properties have to be taken into account in designing of structures. As aresult of the growth of powerful computing technology, recently developed procedures in the field of stochastic mechanics have become applicable to realistic engineering systems. This paper focuses on employing a surrogate model based on polynomial chaos expansion in uncertainty quantification for structural reliability analysis. The aim of the paper is to review and compare several approaches such as the stochastic Galerkin method, the stochastic collocation method or linear regression based on Latin hypercube sampling for construction of the polynomial chaos-based approximation of a model response. The advantages and disadvantages of these methods are demonstrated within the comparison with the traditional Monte Carlo method on a simple illustrative example of a frame structure.

Druh

D - Stať ve sborníku

CEP obor

JM - Inženýrské stavitelství

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

19

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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