Year: 2024
Type: conference-paper
Abstract: The fluid modes generated using a proper orthogonal decomposition (POD) method were predicted for a fluidized bed and a power generation turbine. The POD-based reduced-order models were solved using either a Galerkin projection or a deep learning strategy. In both cases, as the number of the fluid modes increased, the modes appeared to fragment/bifurcate, indicating that these modes follow the constructal law.
DOI: 10.59277/clc.2024.39
Author: PAUL CIZMAS
Institution: Texas A&M University
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407045765