Multi-objective optimization of film-cooled turbine with source term method

A multi-objective genetic algorithm optimization procedure was demonstrated on the film cooled stator of the first high pressure stage of GE-E³ to decrease the temperature on the blade. Firstly, source term method was employed to simulate the effect of overall film cooling, considering it was cheap in term of CPU consumption and did not require any mesh adaption in the presence of cooling holes. The loss of momentum near the wall caused by the injected coolant could be observed from the simulated results, which agreed well with the experimental results. Secondly, multi-objective optimization method NSGA-II (Nondominated Sorting Genetic Algorithm II) was used to minimize the maximum temperature and average temperature of the blade. The inject angles and streamwise positions were varied in the design space. The results demonstrate that the temperature distribution on the blade has been improved, and the pressure side has better cooling effect compared with suction side.