Film cooling improvement analysis in gas turbine blades by swirling coolant flow using a numerical study and an RBF artificial neural network

Background: A numerical simulation is carried out to assess the film cooling improvement of the gas turbine blades using proposed hole shapes. The manipulation of the hole shapes is only conducted on the suction and pressure side. The study follows having converging round-to-slot holes and making the coolant flow to be swirled by considering the screwed holes’ wall or inserting a twisted tape, with different rotation angles or the tape's widths, in the film-cooling holes. 

Methods: Using the numerical simulation results, total and individual coolant mass flow rates, bulk-averaged blowing ratio, energy loss, and averaged adiabatic coolant effectiveness are computed. A post-processing method is used for calculating the parameters. The numerical results are also fed to an artificial neural network to evaluate its ability to predict. 

Significant findings: Considering an overall comprehensive evaluation, the swirling patterns can be beneficial, as they lead to 11% higher adiabatic cooling effectiveness and 4% lower energy loss, compared to the traditional cylindrical holes. Further, inserting twisted tape in the holes requires a 33% lower coolant mass flow rate compared to cylindrical holes. RBF neural network shows a powerful tool to predict mass flow rates.