It has been known that in previous optimization problems, surrogate models are widely used to improve the optimization efficiency. The optimization result depends heavily on the accuracy of surrogate model, while it also costs a lot to construct a high-accurate surrogate model. In order to obtain the optimal design of a shaped film cooling hole which is already well-designed, an optimization framework based on multi-fidelity model is proposed in this article. The characteristic of the multi-fidelity model in this work is that it combines the experimental design information and numerical simulation together. The optimization efficiency can be greatly improved by 64.5% with multi-fidelity model and furthermore the prediction accuracy is maintained with a high level. In this work, three geometry parameters are selected as design variables, which are lateral angle, laidback angle and hole length. A combined optimization method which includes GA (generic algorithm) and SQP (sequential quadratic programming) algorithm is used in the optimization process. A validation experiment is further conducted to validate the optimized hole design using PSP (pressure sensitive paint) and 3D printing technology. The optimization results have shown that the overall film cooling performance is 39% higher compared with baseline design. This work shows the merits of multi-fidelity model in high-efficiency optimization film cooling holes and it may provide further guide for other relative works.
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