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A Posteriori Error Estimation via Differences of Numerical Solutions
In this work we address the problem of the estimation of the approximation error that arise at a discretization of the partial differential equations. For this we take advantage of the ensemble of numerical solutions obtained by independent numerical algorithms. To obtain the approximation error, th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304713/ http://dx.doi.org/10.1007/978-3-030-50436-6_37 |
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author | Alekseev, Aleksey K. Bondarev, Alexander E. Kuvshinnikov, Artem E. |
author_facet | Alekseev, Aleksey K. Bondarev, Alexander E. Kuvshinnikov, Artem E. |
author_sort | Alekseev, Aleksey K. |
collection | PubMed |
description | In this work we address the problem of the estimation of the approximation error that arise at a discretization of the partial differential equations. For this we take advantage of the ensemble of numerical solutions obtained by independent numerical algorithms. To obtain the approximation error, the differences between numerical solutions are treated in the frame of the Inverse Problem that is posed in the variational statement with the zero order regularization. In this work we analyse the ensemble of numerical results that is obtained by five OpenFOAM solvers for the inviscid compressible flow around a cone at zero angle of attack. We present the comparison of approximation errors that are obtained by the Inverse Problem, and the exact error that is computed as the difference of numerical solutions and a high precision solution. |
format | Online Article Text |
id | pubmed-7304713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73047132020-06-22 A Posteriori Error Estimation via Differences of Numerical Solutions Alekseev, Aleksey K. Bondarev, Alexander E. Kuvshinnikov, Artem E. Computational Science – ICCS 2020 Article In this work we address the problem of the estimation of the approximation error that arise at a discretization of the partial differential equations. For this we take advantage of the ensemble of numerical solutions obtained by independent numerical algorithms. To obtain the approximation error, the differences between numerical solutions are treated in the frame of the Inverse Problem that is posed in the variational statement with the zero order regularization. In this work we analyse the ensemble of numerical results that is obtained by five OpenFOAM solvers for the inviscid compressible flow around a cone at zero angle of attack. We present the comparison of approximation errors that are obtained by the Inverse Problem, and the exact error that is computed as the difference of numerical solutions and a high precision solution. 2020-05-25 /pmc/articles/PMC7304713/ http://dx.doi.org/10.1007/978-3-030-50436-6_37 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Alekseev, Aleksey K. Bondarev, Alexander E. Kuvshinnikov, Artem E. A Posteriori Error Estimation via Differences of Numerical Solutions |
title | A Posteriori Error Estimation via Differences of Numerical Solutions |
title_full | A Posteriori Error Estimation via Differences of Numerical Solutions |
title_fullStr | A Posteriori Error Estimation via Differences of Numerical Solutions |
title_full_unstemmed | A Posteriori Error Estimation via Differences of Numerical Solutions |
title_short | A Posteriori Error Estimation via Differences of Numerical Solutions |
title_sort | posteriori error estimation via differences of numerical solutions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304713/ http://dx.doi.org/10.1007/978-3-030-50436-6_37 |
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