The Stochastic Galerkin Method for Darcy Flow Problem with Log-Normal Random

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68145535%3A_____%2F17%3A00482834" target="_blank" >RIV/68145535:_____/17:00482834 - isvavai.cz</a>

Výsledek na webu

<a href="http://advances.utc.sk/index.php/AEEE/article/view/2280" target="_blank" >http://advances.utc.sk/index.php/AEEE/article/view/2280</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15598/aeee.v15i2.2280" target="_blank" >10.15598/aeee.v15i2.2280</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Stochastic Galerkin Method for Darcy Flow Problem with Log-Normal Random

Popis výsledku v původním jazyce

This article presents a study of the Stochastic Galerkin Method (SGM) applied to the Darcy flow problem with a log-normally distributed random material field given by a mean value and an autocovariance function. We divide the solution of the problem into two parts. The first one is the decomposition of a random field into a sum of products of a random vector and a function of spatial coordinates, this can be achieved using the Karhunen-Loeve expansion. The second part is the solution of the problem using SGM. SGM is a simple extension of the Galerkin method in which the random variables represent additional problem dimensions. For the discretization of the problem, we use a finite element basis for spatial variables and a polynomial chaos discretization for random variables. The results of SGM can be utilised for the analysis of the problem, such as the examination of the average flow, or as a tool for the Bayesian approach to inverse problems.

Název v anglickém jazyce

The Stochastic Galerkin Method for Darcy Flow Problem with Log-Normal Random

Popis výsledku anglicky

This article presents a study of the Stochastic Galerkin Method (SGM) applied to the Darcy flow problem with a log-normally distributed random material field given by a mean value and an autocovariance function. We divide the solution of the problem into two parts. The first one is the decomposition of a random field into a sum of products of a random vector and a function of spatial coordinates, this can be achieved using the Karhunen-Loeve expansion. The second part is the solution of the problem using SGM. SGM is a simple extension of the Galerkin method in which the random variables represent additional problem dimensions. For the discretization of the problem, we use a finite element basis for spatial variables and a polynomial chaos discretization for random variables. The results of SGM can be utilised for the analysis of the problem, such as the examination of the average flow, or as a tool for the Bayesian approach to inverse problems.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Advances in Electrical and Electronic Engineering

ISSN

1336-1376

e-ISSN

—

Svazek periodika

15

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

13

Strana od-do

267-279

Kód UT WoS článku

000409044400018

EID výsledku v databázi Scopus

2-s2.0-85025595208