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Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization
Compressor characterization, either by running experiments in a turbocharger test rig or by detailed CFD modelling, can be expensive and time-consuming. In this work, a novel method is proposed which can be used to build a complete compressor map from a reduced number of measured operating points co...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641207/ https://www.ncbi.nlm.nih.gov/pubmed/36387523 http://dx.doi.org/10.1016/j.heliyon.2022.e11327 |
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author | Tiseira, Andrés Pla, Benjamín Bares, Pau Aramburu, Alexandra |
author_facet | Tiseira, Andrés Pla, Benjamín Bares, Pau Aramburu, Alexandra |
author_sort | Tiseira, Andrés |
collection | PubMed |
description | Compressor characterization, either by running experiments in a turbocharger test rig or by detailed CFD modelling, can be expensive and time-consuming. In this work, a novel method is proposed which can be used to build a complete compressor map from a reduced number of measured operating points combined with a previously collected database. The methodology is based on the application of the Singular Value Decomposition (SVD) method to acquire the orthonormal bases of a matrix which contains the information of previous compressor observations. These bases are used along with pivoted QR decomposition to obtain the minimum number of measurement points which are required to implement this technique as well as its optimal placement within the map. The reconstruction of two different compressor maps was made to validate the method. The results show a substantially better trade-off between number of testing points and accuracy compared to standard equidistributed sampling. |
format | Online Article Text |
id | pubmed-9641207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-96412072022-11-15 Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization Tiseira, Andrés Pla, Benjamín Bares, Pau Aramburu, Alexandra Heliyon Research Article Compressor characterization, either by running experiments in a turbocharger test rig or by detailed CFD modelling, can be expensive and time-consuming. In this work, a novel method is proposed which can be used to build a complete compressor map from a reduced number of measured operating points combined with a previously collected database. The methodology is based on the application of the Singular Value Decomposition (SVD) method to acquire the orthonormal bases of a matrix which contains the information of previous compressor observations. These bases are used along with pivoted QR decomposition to obtain the minimum number of measurement points which are required to implement this technique as well as its optimal placement within the map. The reconstruction of two different compressor maps was made to validate the method. The results show a substantially better trade-off between number of testing points and accuracy compared to standard equidistributed sampling. Elsevier 2022-10-28 /pmc/articles/PMC9641207/ /pubmed/36387523 http://dx.doi.org/10.1016/j.heliyon.2022.e11327 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Tiseira, Andrés Pla, Benjamín Bares, Pau Aramburu, Alexandra Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization |
title | Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization |
title_full | Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization |
title_fullStr | Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization |
title_full_unstemmed | Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization |
title_short | Application of the singular value and pivoted QR decompositions to reduce experimental efforts in compressor characterization |
title_sort | application of the singular value and pivoted qr decompositions to reduce experimental efforts in compressor characterization |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641207/ https://www.ncbi.nlm.nih.gov/pubmed/36387523 http://dx.doi.org/10.1016/j.heliyon.2022.e11327 |
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