FLUID MODES, DEEP LEARNING, AND CONSTRUCTAL LAW

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.