Perfectly Parallel Optimization for Cutback Trailing Edges

Abstract

Previous attempts have been made to optimize the performance of film-cooling slots for cutback trailing edges, but these involved the use of steady calculation methods, which have been shown to be inappropriate for accurately capturing the behavior of this class of flows. Here, an unsteady method (large-eddy simulation on a coarse grid, or very large-eddy simulation) is used to compute the flow. To take advantage of the enormous parallel capacity of modern supercomputers and distributed computing nets, as well as the relatively low cost of very large-eddy simulation, while at the same time mitigating its lower scope for significant parallelization, a perfectly parallel evolutionary optimization process was undertaken. A relatively crude optimization target of maximizing the adiabatic wall film-cooling effectiveness averaged over the entire exposed cutback surface was used as a proof of concept. The optimizing heuristic then used an evolutionary approach to design a turbulator planform, subject to some imposed design restrictions. Six hundred large-eddy simulation type simulations were carried out over 12 generations, and the best performing designs from the last generation are examined. The optimized design showed a considerable improvement in the target metric over the previous experimental geometries. The influence of various geometric parameters on several of the metrics of film cooling is also explored by mining data from the populations generated over the course of the optimization. In a targeted optimization exercise, it is likely that these data could be used to steer the course of the evolution down favorable paths more quickly.