The investigation of fluid-solid systems is very important in a lot of industrial processes. From a computational point of view, the simulation of such systems is very expensive, especially when a huge number of parametric configurations needs to be studied. In this context, we develop a non-intrusive data-driven reduced order model (ROM) built using the proper orthogonal decomposition with interpolation (PODI) method for Computational Fluid Dynamics (CFD) - Discrete Element Method (DEM) simulations. The main novelties of the proposed approach rely in (i) the combination of ROM and FV methods, (ii) a numerical sensitivity analysis of the ROM accuracy with respect to the number of POD modes and to the cardinality of the training set and (iii) a parametric study with respect to the Stokes number. We test our ROM on the fluidized bed benchmark problem. The accuracy of the ROM is assessed against results obtained with the FOM both for Eulerian (the fluid volume fraction) and Lagrangian (position and velocity of the particles) quantities. We also discuss the efficiency of our ROM approach.

A non-intrusive data-driven reduced order model for parametrized CFD-DEM numerical simulations / Hajisharifi, Arash; Romanò, Francesco; Girfoglio, Michele; Beccari, Andrea; Bonanni, Domenico; Rozza, Gianluigi. - In: JOURNAL OF COMPUTATIONAL PHYSICS. - ISSN 0021-9991. - 491:(2023). [10.1016/j.jcp.2023.112355]

A non-intrusive data-driven reduced order model for parametrized CFD-DEM numerical simulations

Hajisharifi, Arash;Girfoglio, Michele;Rozza, Gianluigi
2023-01-01

Abstract

The investigation of fluid-solid systems is very important in a lot of industrial processes. From a computational point of view, the simulation of such systems is very expensive, especially when a huge number of parametric configurations needs to be studied. In this context, we develop a non-intrusive data-driven reduced order model (ROM) built using the proper orthogonal decomposition with interpolation (PODI) method for Computational Fluid Dynamics (CFD) - Discrete Element Method (DEM) simulations. The main novelties of the proposed approach rely in (i) the combination of ROM and FV methods, (ii) a numerical sensitivity analysis of the ROM accuracy with respect to the number of POD modes and to the cardinality of the training set and (iii) a parametric study with respect to the Stokes number. We test our ROM on the fluidized bed benchmark problem. The accuracy of the ROM is assessed against results obtained with the FOM both for Eulerian (the fluid volume fraction) and Lagrangian (position and velocity of the particles) quantities. We also discuss the efficiency of our ROM approach.
2023
491
112355
https://arxiv.org/abs/2302.12625
Hajisharifi, Arash; Romanò, Francesco; Girfoglio, Michele; Beccari, Andrea; Bonanni, Domenico; Rozza, Gianluigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/133790
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