Acceleration of uncertainty updating in the description of transport processes in heterogeneous materials

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F12%3A00194172" target="_blank" >RIV/68407700:21110/12:00194172 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.cam.2012.02.003" target="_blank" >http://dx.doi.org/10.1016/j.cam.2012.02.003</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cam.2012.02.003" target="_blank" >10.1016/j.cam.2012.02.003</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Acceleration of uncertainty updating in the description of transport processes in heterogeneous materials

Popis výsledku v původním jazyce

The prediction of thermo-mechanical behaviour of heterogeneous materials such as heat and moisture transport is strongly influenced by the uncertainty in parameters. Such materials occur e.g., in historic buildings, and the durability assessment of thesetherefore needs a reliable and probabilistic simulation of transport processes, which is related to the suitable identification of material parameters. In order to include expert knowledge as well as experimental results, one can employ an updating procedure such as Bayesian inference. The classical probabilistic setting of the identification process in Bayes' form requires the solution of a stochastic forward problem via computationally expensive sampling techniques, which makes the method almost impractical. In this paper novel stochastic computational techniques such as the stochastic Galerkin method are applied in order to accelerate the updating procedure. The idea is to replace the computationally expensive forward simulation via

Název v anglickém jazyce

Acceleration of uncertainty updating in the description of transport processes in heterogeneous materials

Popis výsledku anglicky

The prediction of thermo-mechanical behaviour of heterogeneous materials such as heat and moisture transport is strongly influenced by the uncertainty in parameters. Such materials occur e.g., in historic buildings, and the durability assessment of thesetherefore needs a reliable and probabilistic simulation of transport processes, which is related to the suitable identification of material parameters. In order to include expert knowledge as well as experimental results, one can employ an updating procedure such as Bayesian inference. The classical probabilistic setting of the identification process in Bayes' form requires the solution of a stochastic forward problem via computationally expensive sampling techniques, which makes the method almost impractical. In this paper novel stochastic computational techniques such as the stochastic Galerkin method are applied in order to accelerate the updating procedure. The idea is to replace the computationally expensive forward simulation via

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Journal of Computational and Applied Mathematics

ISSN

0377-0427

e-ISSN

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Svazek periodika

18

Číslo periodika v rámci svazku

236

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

4862-4872

Kód UT WoS článku

000307425900025

EID výsledku v databázi Scopus

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