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

Electronic Transactions on Numerical Analysis

article

Massimiliano Lupo Pasini¹  Simona Perotto² 

[1]Computational Sciences and Engineering Division, Oak Ridge National Laboratory

[2]MOX-Dipartimento di Matematica, Politecnico di Milano, Piazza L. da Vinci 32

关键词: hierarchical model reduction;    proper orthogonal decomposition;    parametric partial differential equations;    finite elements;    spectral methods;   

DOI  :  10.1553/etna_vol55s187

学科分类：数学（综合）

来源: Kent State University * Institute of Computational Mathematics

【 摘 要 】

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.

【 授权许可】

Unknown