Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems
This work combines the Hierarchical Model (HiMod) reduction technique with a standard Proper Orthogonal Decomposition (POD) to solve parametrized partial differential equations for the modeling of advection-diffusion-reaction phenomena in elongated domains (e.g., pipes). This combination leads to wh...
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Veröffentlicht in: | Electronic transactions on numerical analysis 2022-01, Vol.55 (1), p.187-212 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This work combines the Hierarchical Model (HiMod) reduction technique with a standard Proper Orthogonal Decomposition (POD) to solve parametrized partial differential equations for the modeling of advection-diffusion-reaction phenomena in elongated domains (e.g., pipes). This combination leads to what we define as HiPOD model reduction, which merges the reliability of HiMod reduction with the computational efficiency of POD. Two HiPOD techniques are presented and assessed by an extensive numerical verification. Key words. hierarchical model reduction, proper orthogonal decomposition, parametric partial differential equations, finite elements, spectral methods AMS subject classifications. 65N30, 65N35, 65T40 |
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ISSN: | 1068-9613 1097-4067 1068-9613 |
DOI: | 10.1553/etna_vol55s187 |