Numerical simulation and structural optimization of transpiration cooling with gradient porous matrix in supersonic condition

Transpiration cooling with gradient porous matrix is employed to address the non-uniform distribution heat flux in the applied environment. The cooling characteristics in supersonic condition are analyzed by developing porous matrix with varied coolant mass rates, structure schemes and coolant injection methods. The simulation results indicate that temperature on the trailing edge changes less compared with the leading edge due to the film lifting outside the structure during coolant mass rate adjustment. Furthermore, it is discovered that the segment with greater permeability does indeed result in more coolant allocation, but it does not lead to a better cooling effect. Meanwhile, the coolant injection pressure is primarily influenced by the leading edge in the gradient porous matrix, despite its highest permeability. Based on the above analysis, a new optimization process combining Computational Fluid Dynamics (CFD), Artificial Neural Network (ANN) and Multi-Objective Genetic Algorithm (MOGA) is proposed. This optimization process is implemented through the coupled simulation of commercial software ANSYS FLUENT and MATLAB using User Defined Function (UDF). The configuration parameters are set as design variables, and cooling efficiency at the stagnation point and dimensionless injection pressure are selected as optimization objectives. The optimization results demonstrate an improvement of 8.77% in cooling efficiency and a reduction of 10.31% in dimensionless injection pressure compared to the original structure. This procedure provides a reliable and accessible reference for solving a series of similar optimization problems.