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

Hajisharifi, Arash
•
Romanò€, Francesco
•
Girfoglio, Michele
altro
Rozza, Gianluigi
2023
  • journal article

Periodico
JOURNAL OF COMPUTATIONAL PHYSICS
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.
DOI
10.1016/j.jcp.2023.112355
WOS
WOS:001050864000001
Archivio
https://hdl.handle.net/20.500.11767/133790
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85165512429
https://arxiv.org/abs/2302.12625
https://ricerca.unityfvg.it/handle/20.500.11767/133790
Diritti
metadata only access
Soggetti
  • CFD-DEM

  • Data-driven technique...

  • Fluidized bed

  • Proper orthogonal dec...

  • Reduced order model

  • Settore MAT/08 - Anal...

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