NUMERICAL INVESTIGATION AND MULTI-OBJECTIVE STRUCTURE OPTIMIZATION OF TRANSPIRATION COOLING ON THE LEADING EDGE OF TURBINE BLADE

Transpiration cooling, utilizing the micro-hole channel of the porous matrix, is regarded as highly promising turbine blade cooling applications. This study comprehensively investigates the cooling performance of transpiration cooling on the leading edge of C3X turbine blade. The numerical investigation is conducted by comparing the uniform and gradient porous matrix. Various influence factors such as coolant mass rate, porosity and average pore diameter are taken into discussion. The simulation results suggest that the gradient porous matrix scheme can improve cooling efficiency by altering the permeability distribution and adjusting coolant flow accordingly. Additionally, the average total pressure loss coefficient is primarily influenced by the region directly facing the mainstream and the new structure can also reduce this coefficient. To optimize the transpiration cooling performance with a gradient design, a novel optimization process is proposed, which combines Computational Fluid Dynamics (CFD), Artificial Neural Network (ANN) and Multi-Objective Genetic Algorithm (MOGA). The optimization process is implemented through the coupling simulation of ANSYS FLUENT and MATLAB via Text User Interface (TUI) and User Defined Function (UDF). The configuration parameters of the porous matrix are set as design variables, with the average cooling efficiency and average total pressure loss coefficient serving as optimization objectives. The simulation results demonstrate an improvement in the former (increases by 11.35%) and a reduction in the latter (decreases by 36.23%) respectively compared with the uniform porous matrix. This optimization process provides a straightforward and reliable method for addressing a range of similar structural issues. Keywords: transpiration cooling, porous matrix, structure optimization, thermal protection