Polynomial chaos in evaluating failure probability: A comparative study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F18%3A00326096" target="_blank" >RIV/68407700:21110/18:00326096 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.21136/AM.2018.0335-17" target="_blank" >http://dx.doi.org/10.21136/AM.2018.0335-17</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21136/AM.2018.0335-17" target="_blank" >10.21136/AM.2018.0335-17</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Polynomial chaos in evaluating failure probability: A comparative study

Popis výsledku v původním jazyce

Recent developments in the field of stochastic mechanics and particularly regarding the stochastic finite element method allow to model uncertain behaviours for more complex engineering structures. In reliability analysis, polynomial chaos expansion is a useful tool because it helps to avoid thousands of time-consuming finite element model simulations for structures with uncertain parameters. The aim of this paper is to review and compare available techniques for both the construction of polynomial chaos and its use in computing failure probability. In particular, we compare results for the stochastic Galerkin method, stochastic collocation, and the regression method based on Latin hypercube sampling with predictions obtained by crude Monte Carlo sampling. As an illustrative engineering example, we consider a simple frame structure with uncertain parameters in loading and geometry with prescribed distributions defined by realistic histograms.

Název v anglickém jazyce

Polynomial chaos in evaluating failure probability: A comparative study

Popis výsledku anglicky

Recent developments in the field of stochastic mechanics and particularly regarding the stochastic finite element method allow to model uncertain behaviours for more complex engineering structures. In reliability analysis, polynomial chaos expansion is a useful tool because it helps to avoid thousands of time-consuming finite element model simulations for structures with uncertain parameters. The aim of this paper is to review and compare available techniques for both the construction of polynomial chaos and its use in computing failure probability. In particular, we compare results for the stochastic Galerkin method, stochastic collocation, and the regression method based on Latin hypercube sampling with predictions obtained by crude Monte Carlo sampling. As an illustrative engineering example, we consider a simple frame structure with uncertain parameters in loading and geometry with prescribed distributions defined by realistic histograms.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20101 - Civil engineering

Projekt

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

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Applications of mathematics

ISSN

0862-7940

e-ISSN

1572-9109

Svazek periodika

63

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

25

Strana od-do

713-737

Kód UT WoS článku

000453844300007

EID výsledku v databázi Scopus

2-s2.0-85059002866