Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems

Journal Article · 16 December 2021 · Electronic Transactions on Numerical Analysis

DOI: https://doi.org/10.1553/etna_vol55s187 · OSTI ID:1837417

Lupo Pasini, Massimiliano  ^[1]; Perotto, Simona  ^[2]

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1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2. Politecnico di Milano (Italy)

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE; European Union (EU)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1837417
• Journal Information: Electronic Transactions on Numerical Analysis, Journal Name: Electronic Transactions on Numerical Analysis Journal Issue: 1 Vol. 55; ISSN 1068-9613
• Publisher: Kent State University - Johann Radon Institute for Computational and Applied Mathematics (RICAM)Copyright Statement
• Country of Publication: United States
• Language: English