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Solution of Inverse Problems using Bayesian Approach with Application to Estimation of Material Parameters in Darcy Flow
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SYSNO ASEP 0482833 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Solution of Inverse Problems using Bayesian Approach with Application to Estimation of Material Parameters in Darcy Flow Author(s) Domesová, Simona (UGN-S) ORCID, SAI, RID
Beres, Michal (UGN-S)Number of authors 2 Source Title Advances in Electrical and Electronic Engineering - ISSN 1336-1376
Roč. 15, č. 2 (2017), s. 258-266Number of pages 9 s. Publication form Online - E Language eng - English Country SK - Slovakia Keywords Bayesian statistics ; Cross-Entropy method ; Darcy flow ; Gaussian random field ; inverse problem Subject RIV BA - General Mathematics OECD category Applied mathematics R&D Projects LQ1602 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Institutional support UGN-S - RVO:68145535 UT WOS 000409044400017 EID SCOPUS 85025665571 DOI 10.15598/aeee.v15i2.2236 Annotation 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. Workplace Institute of Geonics Contact Lucie Gurková, lucie.gurkova@ugn.cas.cz, Tel.: 596 979 354 Year of Publishing 2018 Electronic address http://advances.utc.sk/index.php/AEEE/article/view/2236
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