Journal article 1154 views 210 downloads
Solution of geometrically parametrised problems within a CAD environment via model order reduction
Computer Methods in Applied Mechanics and Engineering, Volume: 358, Start page: 112631
Swansea University Author: Rubén Sevilla
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© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
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DOI (Published version): 10.1016/j.cma.2019.112631
Abstract
The main objective of this work is to describe a general and original approach for computing an off-line solution for a set of parameters describing the geometry of the domain. That is, a solution able to include information for different geometrical parameter values and also allowing to compute rea...
Published in: | Computer Methods in Applied Mechanics and Engineering |
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ISSN: | 0045-7825 |
Published: |
2020
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa51756 |
Abstract: |
The main objective of this work is to describe a general and original approach for computing an off-line solution for a set of parameters describing the geometry of the domain. That is, a solution able to include information for different geometrical parameter values and also allowing to compute readily the sensitivities. Instead of problem dependent approaches, a general framework is presented for standard engineering environments where the geometry is defined by means of NURBS. The parameters controlling the geometry are now the control points characterising the NURBS curves or surfaces. The approach proposed here, valid for 2D and 3D scenarios, allows a seamless integration with CAD preprocessors. The proper generalised decomposition (PGD), which is applied here to compute explicit geometrically parametrised solutions, circumvents the curse of dimensionality. Moreover, optimal convergence rates are shown for PGD approximations of incompressible flows. |
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Keywords: |
Geometry parametrisation, Reduced order model, Computer-aided design (CAD), Proper generalised decomposition (PGD) |
Start Page: |
112631 |