This study aims to improve the outlet temperature performance of a pneumatic heat-generating blower and investigate the influence of turbulence on the outlet temperature. Based on the heat generation mechanism and structural principle, mathematical models are developed for key components including the impeller and flow channel. The Kriging surrogate model and NSGA-II multi-objective genetic algorithm are adopted to optimize the aerodynamic performance responses of the impeller structural parameters. After comprehensive analysis, an optimal parameter combination is selected from the Pareto solution set for CFD numerical simulation. The results show that the optimization effectively improves the outlet temperature and turbulent kinetic energy distribution. The numerical results agree well with the optimization outcomes, verifying the reliability and accuracy of the proposed method. These findings provide a reference for the multi-physics coupled optimal design of blower blades.
Huangfu et al. (Mon,) studied this question.