Surrogate Model Based Optimization Of Shaped Film Cooling Hole And Experimental Validation

Film cooling is an important external cooling method for modern gas turbine,and the design of film cooling hole is critical to film cooling performance.Numerical opti-mization plays an important role in film cooling hole design and optimization.Not only is it important to improve the efficiency and accuracy of numerical optimization meth-ods,but also it is necessary to take the real flow environment into consideration.Hence,in this current work we have developed a high-efficient film cooling hole optimization framework,which is separately applied in shaped film cooling hole design under flat plate environment and turbine endwall environment with transverse pressure gradient.In order to improve the efficiency of film cooling hole design optimization,firstly we developed a multi-fidelity surrogate model based optimization framework.Com-pared with traditional optimization works,this current work considers data fusion method,which allows to take other preliminary design methods such as empirical correlations into consideration apart from the common-used numerical simulation.The development of multi-fidelity model helps improve the construction efficiency of high-accurate surrogate model while maintains the prediction accuracy at the similar level.In the same time,we also developed an improved latin hypercubic sampling method based oncriteria.This sampling method provides better space-filling performance than normal latin hypercu-bic sampling,and hence helps improve the prediction accuracy of multi-fidelity model to some extent.We also investigated the influences of shaped film cooling hole parame-ters,i.e.,laidback angle,lateral angle and hole length-to-diameter ratio,on film cooling performance under flat plate environment.Furthermore,the shaped film cooling hole is optimized under flat plate environment using the multi-fidelity model based optimization framework.Generic algorithm and sequential quadratic programming is used as the op-timization method to make sure the global optimum point is determined.In the end,PSP measurement and 3D printing technology are used to verify the optimized hole design and the accuracy of multi-fidelity model.In order to improve the efficiency of Kriging model based optimization,an adaptive sampling method is developed in this work.It is found that the sampling method based on expected improvement?EI?can help improve the prediction accuracy in the region near the global optimum point,and in the same time reduce the whole sampling point number.In this current work,the geometric feature in turbine endwall is extracted as a curve channel,which aims to simulate the transverse pressure gradient in turbine endwall environment.The flow features in the curve channel are carefully investigated,and it is pointed out that the most obvious flow characteristic in flow curve under transverse pressure gradient is the cross flow inside the boundary layer.An optimization campaign is further carried out using the Kriging model based optimization framework,and the adaptive sampling method based on EI criteria is used to improve the optimization accuracy and efficiency.Three key hole design parameters are chosen for the optimization,which are laidback an-gle,lateral angle and compound angle.The optimization result indicated that the optimum hole design is not obtained with largest compound angle,which is against the traditional conclusion for compound angle in flat plate environment.In order to better explain this interesting phenomenon,a physical model is further proposed to illustrate the influences of endwall cross flow to kidney vortices with large compound angle in curve channel.In conclusion,the surrogate model based optimization framework helps improve the optimization efficiency and accuracy of film cooling hole design.It is also pointed out that we should consider the realistic operation condition during film cooling hole design,which might help the optimum hole design more feasible.