FILM COOLING PERFORMANCE IMPROVEMENT WITH OPTIMIZED HOLE ARRANGEMENT ON PRESSURE SIDE SURFACE OF NOZZLE GUIDE VANE - PART I: OPTIMIZATION & NUMERICAL INVESTIGATION

Although a plethora of high-performance film cooling hole configurations have been suggested, they are too complicated to manufacture and extremely difficult to maintain their original shapes during turbine operation. Thus, it is assumed that there is little room for further performance improvement by optimizing a single hole shape. However, optimization researches on the arrangement of the film cooling holes are still insufficient, so investigation of the possibility of the optimal hole array for improving film cooling performance is worth pursuing. In this study, to improve the film cooling performance of the pressure side surface of the nozzle guide vane, not a single film cooling hole shape, but an arrangement of the holes was considered. First, the optimum hole arrangements were determined by numerical optimization strategy, which contains newly suggested hole arrangement parameterization method and Efficient Global Optimization (EGO) method. Each array of the holes was parameterized by the shape function which consists of 5 design variables. This shape function is able to represent more general array shapes than the existing turbine film cooling hole array shape regardless of how many holes are included in a row. EGO method based on Kriging model is applied with Genetic Algorithm (GA), which yields superior optimization efficiency with minimum number of sampling points. Each sampling point obtained their fitness function by analyzing the nozzle with various array shape. Through this, the group of optimum hole arrangements, which greatly reduce the average wall temperature and the temperature deviation of the nozzle surface simultaneously were obtained. From the results, it is confirmed that the superior cooling performance was achieved when the array has smaller hole distances at the hub rather than at the shroud and when the array is disposed on the upstream position rather than on the downstream position. These optimization results were validated against experimental data, and it will be discussed in PART II.