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Estimating flow fields with reduced order models
The estimation of fluid flows inside a centrifugal pump in realtime is a challenging task that cannot be achieved with long-established methods like CFD due to their computational demands. We use a projection-based reduced order model (ROM) instead. Based on this ROM, a realtime observer can be devi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623178/ https://www.ncbi.nlm.nih.gov/pubmed/37928036 http://dx.doi.org/10.1016/j.heliyon.2023.e20930 |
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author | Sommer, Kamil David Reineking, Lucas Ravichandran, Yogesh Parry Skoda, Romuald Mönnigmann, Martin |
author_facet | Sommer, Kamil David Reineking, Lucas Ravichandran, Yogesh Parry Skoda, Romuald Mönnigmann, Martin |
author_sort | Sommer, Kamil David |
collection | PubMed |
description | The estimation of fluid flows inside a centrifugal pump in realtime is a challenging task that cannot be achieved with long-established methods like CFD due to their computational demands. We use a projection-based reduced order model (ROM) instead. Based on this ROM, a realtime observer can be devised that estimates the temporally and spatially resolved velocity and pressure fields inside the pump. The entire fluid-solid domain is treated as a fluid in order to be able to consider moving rigid bodies in the reduction method. A greedy algorithm is introduced for finding suitable and as few measurement locations as possible. Robust observability is ensured with an extended Kalman filter, which is based on a time-variant observability matrix obtained from the nonlinear velocity ROM. We present the results of the velocity and pressure ROMs based on a unsteady Reynolds-averaged Navier-Stokes CFD simulation of a 2D centrifugal pump, as well as the results for the extended Kalman filter. |
format | Online Article Text |
id | pubmed-10623178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106231782023-11-04 Estimating flow fields with reduced order models Sommer, Kamil David Reineking, Lucas Ravichandran, Yogesh Parry Skoda, Romuald Mönnigmann, Martin Heliyon Research Article The estimation of fluid flows inside a centrifugal pump in realtime is a challenging task that cannot be achieved with long-established methods like CFD due to their computational demands. We use a projection-based reduced order model (ROM) instead. Based on this ROM, a realtime observer can be devised that estimates the temporally and spatially resolved velocity and pressure fields inside the pump. The entire fluid-solid domain is treated as a fluid in order to be able to consider moving rigid bodies in the reduction method. A greedy algorithm is introduced for finding suitable and as few measurement locations as possible. Robust observability is ensured with an extended Kalman filter, which is based on a time-variant observability matrix obtained from the nonlinear velocity ROM. We present the results of the velocity and pressure ROMs based on a unsteady Reynolds-averaged Navier-Stokes CFD simulation of a 2D centrifugal pump, as well as the results for the extended Kalman filter. Elsevier 2023-10-16 /pmc/articles/PMC10623178/ /pubmed/37928036 http://dx.doi.org/10.1016/j.heliyon.2023.e20930 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Sommer, Kamil David Reineking, Lucas Ravichandran, Yogesh Parry Skoda, Romuald Mönnigmann, Martin Estimating flow fields with reduced order models |
title | Estimating flow fields with reduced order models |
title_full | Estimating flow fields with reduced order models |
title_fullStr | Estimating flow fields with reduced order models |
title_full_unstemmed | Estimating flow fields with reduced order models |
title_short | Estimating flow fields with reduced order models |
title_sort | estimating flow fields with reduced order models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623178/ https://www.ncbi.nlm.nih.gov/pubmed/37928036 http://dx.doi.org/10.1016/j.heliyon.2023.e20930 |
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