This contribution focuses on the development of Model Order Reduction (MOR) for one-way coupled steady state linear thermo-mechanical problems in a finite element setting. We apply Proper Orthogonal Decomposition (POD) for the computation of reduced basis space. On the other hand, for the evaluation of the modal coefficients, we use two different methodologies: the one based on the Galerkin projection (G) and the other one based on Artificial Neural Network (ANN). We aim to compare POD-G and POD-ANN in terms of relevant features including errors and computational efficiency. In this context, both physical and geometrical parametrization are considered. We also carry out a validation of the Full Order Model (FOM) based on customized benchmarks in order to provide a complete computational pipeline. The framework proposed is applied to a relevant industrial problem related to the investigation of thermo-mechanical phenomena arising in blast furnace hearth walls.

Finite element based Model Order Reduction for parametrized one-way coupled steady state linear thermo-mechanical problems / Shah, Nirav Vasat; Girfoglio, Michele; Quintela, Peregrina; Rozza, Gianluigi; Lengomin, Alejandro; Ballarin, Francesco; Barral, Patricia. - In: FINITE ELEMENTS IN ANALYSIS AND DESIGN. - ISSN 0168-874X. - 212:(2022), pp. 1-33. [10.1016/j.finel.2022.103837]

Finite element based Model Order Reduction for parametrized one-way coupled steady state linear thermo-mechanical problems

Girfoglio, Michele;Rozza, Gianluigi
;
Lengomin, Alejandro;Ballarin, Francesco;
2022-01-01

Abstract

This contribution focuses on the development of Model Order Reduction (MOR) for one-way coupled steady state linear thermo-mechanical problems in a finite element setting. We apply Proper Orthogonal Decomposition (POD) for the computation of reduced basis space. On the other hand, for the evaluation of the modal coefficients, we use two different methodologies: the one based on the Galerkin projection (G) and the other one based on Artificial Neural Network (ANN). We aim to compare POD-G and POD-ANN in terms of relevant features including errors and computational efficiency. In this context, both physical and geometrical parametrization are considered. We also carry out a validation of the Full Order Model (FOM) based on customized benchmarks in order to provide a complete computational pipeline. The framework proposed is applied to a relevant industrial problem related to the investigation of thermo-mechanical phenomena arising in blast furnace hearth walls.
212
1
33
103837
www.sciencedirect.com/science/article/abs/pii/S0168874X2200110X
https://arxiv.org/abs/2111.08534
Shah, Nirav Vasat; Girfoglio, Michele; Quintela, Peregrina; Rozza, Gianluigi; Lengomin, Alejandro; Ballarin, Francesco; Barral, Patricia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/129331
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