Structural Optimization Design of Sinusoidal Wavy Plate Fin Heat Sink with Crosscut by Bayesian Optimization

The optimal structure of a sinusoidal wavy plate fin heat sink with crosscut ( SWHS-WC) is determined by an efficient intelligent optimization method based on the Bayesian Optimization (BO) algorithm. The comprehensive thermal performance factor (TPF) is the objective function to associate with the heat transfer and the pressure drop. The parametric modeling, meshing and numerical calculation are integrated to optimize three structure parameters, including the fin amplitude, period, and phase shift angle of the heat sink, in an iterative and automated way. The result shows that the TPF of the SWHS-WC with the optimized structure is increased by 17.6%, due to the significant reduction in the pressure drop penalty, and the corresponding synergy angle between the pressure and the velocity fields decreases by about 6.2°. Compared to the evolutionary algorithms, the BO algorithm demonstrates great advantage in calculation efficiency, which can be used to find the global optimum by much smaller computational cost