Genetic Algorithm Optimization of an HPT Vane Pressure Side Film Cooling Array

Abstract

The following work is an in-depth investigation of the heat transfer characteristics and cooling effectiveness of a full-scale fully-cooled modern high-pressure turbine (HPT) vane as a result of genetic algorithm (GA) optimization, relative to the baseline cooling configuration. Individual designs were evaluated using 3-D Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) that modeled film cooling injection using a transpiration boundary condition. 1,800 total different film cooling arrays were assessed for fitness within the optimization where film cooling parameters such as axial and radial hole location, hole size, injection angle, compound angle, and custom-designed row patterns were varied in the design space. The GA was able to find a unique pressure side (PS) cooling array after only 13 generations. The fitness functions prescribed for the problem successfully lowered the PS average surface temperature, lowered the maximum temperature, and increased the average overall effectiveness. Results clearly show how the optimized design redistributed flow from over-cooled areas on the vane PS to under-cooled areas near the shroud. Methods used in substantially improving pressure side film cooling performance here are promising in terms of eliminating durability problem areas for individual HPT components in their proper operating environments as well as increasing the potential to use less air from the compressor for cooling purposes in a gas turbine engine.