Solution of Inverse Problems using Bayesian Approach with Application to Estimation of Material Parameters in Darcy Flow

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68145535%3A_____%2F17%3A00482833" target="_blank" >RIV/68145535:_____/17:00482833 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/17:10237745 RIV/61989100:27740/17:10237745

Výsledek na webu

<a href="http://advances.utc.sk/index.php/AEEE/article/view/2236" target="_blank" >http://advances.utc.sk/index.php/AEEE/article/view/2236</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15598/aeee.v15i2.2236" target="_blank" >10.15598/aeee.v15i2.2236</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Solution of Inverse Problems using Bayesian Approach with Application to Estimation of Material Parameters in Darcy Flow

Popis výsledku v původním jazyce

Standard numerical methods for solving inverse problems in partial differential equations do not reflect a possible inaccuracy in observed data. However, in real engineering applications we cannot avoid uncertainties caused by measurement errors. In the Bayesian approach every unknown or inaccurate value is treated as a random variable. This paper presents an application of the Bayesian inverse approach to the reconstruction of a porosity field as a parameter of the Darcy flow problem. However, this framework can be applied to a wide range of problems that involve some amount of uncertainty. Here the material field is modeled as a Gaussian random field, which is expressed as a function of several random variables. The information about these random variables is given by the resulting posterior distribution, which is then studied using the Cross-Entropy method and samples are generated using the Metropolis-Hastings algorithm.

Název v anglickém jazyce

Solution of Inverse Problems using Bayesian Approach with Application to Estimation of Material Parameters in Darcy Flow

Popis výsledku anglicky

Standard numerical methods for solving inverse problems in partial differential equations do not reflect a possible inaccuracy in observed data. However, in real engineering applications we cannot avoid uncertainties caused by measurement errors. In the Bayesian approach every unknown or inaccurate value is treated as a random variable. This paper presents an application of the Bayesian inverse approach to the reconstruction of a porosity field as a parameter of the Darcy flow problem. However, this framework can be applied to a wide range of problems that involve some amount of uncertainty. Here the material field is modeled as a Gaussian random field, which is expressed as a function of several random variables. The information about these random variables is given by the resulting posterior distribution, which is then studied using the Cross-Entropy method and samples are generated using the Metropolis-Hastings algorithm.

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

9

Strana od-do

258-266

Kód UT WoS článku

000409044400017

EID výsledku v databázi Scopus

2-s2.0-85025665571