Computational Fluid Dynamics Based Fuzzy Control Optimization of Heat Exchanger via Genetic Algorithm

This study evaluates the combination of computational fluid dynamics (CFD) and artificial intelligence (AI) algorithms in heat exchanger application. More specifically, fuzzy logic controller (FLC) is selected in the closed-loop control system. The sensor read by the FLC is based on the reading from the CFD meshing finite element method (FEM) discretization in order to solve the Navier-Stokes (N-S) equation. The controller output is the boundary condition of the CFD system (i.e heat flux). In this study, the CFD result will provide a predicted value approaching the set point. This system utilizes six rules for the controller. In order to evaluate the controller performance, several different set points are set. In addition, the genetic algorithm (GA) is set as the optimizer for the making of the sequence of the Mamdani triangular membership function. Finally, the GA is used to modify the membership function of the FLC. The total evaluation error for the FLC is 0.92 °C of the mean absolute error (MAE). Meanwhile, the GA-based FCL produces 0.78 °C of the MAE.