Multi-objective optimization of 3D film cooling configuration with thermal barrier coating in a high pressure vane based on CFD-ANN-GA loop

Abstract

In this paper, the optimum parameters of a row of cylindrical film cooling holes have been investigated using a multi-objective evolutionary approach so as to achieve a compromise between film cooling effectiveness and coolant mass flow rate which are in opposite directions and compete with each other. For this purpose, chord-wise position of film holes as well as diameter and injection angles and holes spacing were chosen as design parameters. Forty samples were generated as database through CFD runs; artificial neural network (ANN) method was used to construct the surrogate model to approximate the optimization targets as functions of design parameters and genetic algorithm (GA) was used as optimizer. Design iterations were repeated seven times through the mentioned CFD-ANN-AG loop and optimum configuration, including film holes spacing, diameter, injection position and angle, based on objective function values was found. However, added row imposed an excess amount of coolant mass flow rate through the vane cavity which had a negative impact on the engine performance. Therefore, at last part of this work a thermal barrier coating layer was applied on external surfaces of the vane in order to assess the possibility of decreasing coolant mass flow rate with no additional increase on its exerted thermal loads.