Speakers
Description
This study presents an optimization model for forced convection problems, aiming to determine the optimal location and size of inlet and outlet ports in a cavity flow field. The proposed approach integrates the localized meshless method, the generalized finite difference method (GFDM) for spatial discretization, the projection method for stable and accurate simulation, and particle swarm optimization (PSO) for design optimization. Forced convection, driven by external sources such as fans, pumps, or air conditioning systems, enhances heat transfer and is governed by the Navier-Stokes equations and the energy equation. The projection method ensures stability in solving time-dependent incompressible fluid flow problems, while GFDM eliminates the need for mesh generation, numerical quadrature, and parameter determination, enabling efficient spatial discretization. The combination of these methods ensures stable, accurate, and computationally efficient numerical solutions. Integrating GFDM and the projection method with PSO, a robust metaheuristic algorithm, allows the model to effectively identify the optimal design parameters for inlet and outlet ports. Several examples demonstrate the effectiveness of the proposed simulation-optimization model, highlighting its potential to improve cooling system designs and solve complex forced convection problems.
