Assessment of reduced-order modeling strategies for convective heat transfer

Author(s)

Zucatti, Victor ^[1] ; Lui, Hugo F. S. ^[1] ; Pitz, Diogo B. ^{[1, 2]} ; Wolf, William R. ^[1]

Affiliation

^[1] Univ Estadual Campinas, Sch Mech Engn, BR-13083970 Campinas, SP - Brazil

^[2] Univ Fed Parana, Dept Mech Engn, Curitiba, Parana - Brazil

• Document type: Journal article
• Source: NUMERICAL HEAT TRANSFER PART A-APPLICATIONS; v. 77, n. 7, p. 702-729, APR 2 2020.
• Web of Science Citations: 4

Abstract

An assessment of physics-based and data-driven reduced-order models (ROMs) is presented for the study of convective heat transfer in a rectangular cavity. Despite the simple geometrical configuration, the current setup offers increasingly rich dynamics as the thermal forcing is increased, thus making it a suitable candidate to evaluate the performance of ROMs. First, flow simulations are performed using a high-order spectral element method that will feed the ROMs with well-resolved temporal and spatial information. Proper orthogonal decomposition (POD) is applied to reduce the problem dimensionality for all models. The class of tested physics-based models include the Galerkin and least-squares Petrov-Galerkin (LSPG) methods that rely on projection of the Navier-Stokes and energy equations being solved. On the other hand, the data-driven methods applied in this work rely on regression of the governing equations, which are treated as a nonlinear dynamical system. The data-driven methods tested here include the sparse identification of nonlinear dynamics (SINDy) approach and a method recently proposed in literature based on deep neural networks (DNNs). All ROMs are able to represent the periodical temporal dynamics of a low Rayleigh number flow. However, the physics-based approaches demonstrate a better performance for a moderate Rayleigh number case with more complex flow dynamics, when several frequencies are excited in a non-periodical fashion. (AU)

• FAPESP's process: 18/11410-9 - On the application of principal component analysis for the construction of reduced order models
• Grantee: Victor Zucatti da Silva
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
• Grantee: Francisco Louzada Neto
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 13/08293-7 - CCES - Center for Computational Engineering and Sciences
• Grantee: Munir Salomao Skaf
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 19/18809-7 - Reduced order modeling strategies for simulation of unsteady flows
• Grantee: Victor Zucatti da Silva
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree