Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design
Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design
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DOI：
10.1080/0305215x.2017.1367391
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发表时间：
2018-01-01
影响因子：
2.7
通讯作者：
Kanazaki, Masahiro
中科院分区：
文献类型：
--
作者：
Ariyarit, Atthaphon;Sugiura, Masahiko;Kanazaki, Masahiro
研究了一种基于混合代理模型的多保真度全局优化方法。该模型使用克里金法构造局部偏差，使用径向基函数构造全局模型。计算预期的改进以决定可以改进模型的附加样本。该方法首先通过解决数学测试问题进行了研究。结果与普通克里金法和协同克里金法的优化结果进行了比较，所提出的方法产生了最佳的解决方案。将该方法应用于直升机桨叶的气动优化设计，以获得最大的桨叶效率。所提出的方法获得的最佳形状实现的性能几乎等同于使用高保真度，基于评估的单保真度优化。比较所有三种方法，所提出的方法需要最低的高保真评估运行总数，以获得收敛的解决方案。
A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.