Efficient Robust Design Optimization by Variable Fidelity Kriging Model
Efficient Robust Design Optimization by Variable Fidelity Kriging Model
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DOI：
10.2514/6.2012-1926
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发表时间：
2012-04
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通讯作者：
Wataru Yamazaki
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作者：
Wataru Yamazaki
本文提出了一种基于变保真度Kriging模型的鲁棒设计优化框架。通过使用变保真克里格模型方法，可以通过高保真度函数的绝对值以及低保真度函数值获得的趋势有效地构建准确的代理模型。在这项研究中，通过利用不同的物理模型/计算网格来定义高保真度和低保真度。所获得的设计的鲁棒性进行了评估的Monte Carlo模拟上执行的可变保真度克里格模型。所开发的稳健设计优化方法的效率进行了调查的二维翼型阻力最小化问题。在该问题中，自由流马赫数和目标升力系数被假定为不确定参数。同时最小化阻力系数的均值和标准差，得到非支配鲁棒最优设计。所开发的稳健设计优化方法，通过可变保真度克里格模型被证明是有用的稳健翼型设计的有效搜索。标称值d C =阻力系数 * l C =目标升力系数p C =压力系数m M =自由流马赫数m =攻角[deg] m =平均值m =标准差
In this paper, a robust design optimization framework is proposed with a variable fidelity Kriging model. By the use of the variable fidelity Kriging model approach, an accurate surrogate model can be constructed efficiently by the absolute values of a highfidelity function as well as the trends obtained by low-fidelity function values. The high and low-fidelity levels are defined by utilizing different physical models/computational meshes in this study. The robustness of an obtained design is evaluated by a Monte Carlo simulation which is executed on the variable fidelity Kriging model. The efficiencies of the developed robust design optimization approaches are investigated by a 2D airfoil drag minimization problem. In this problem, free-stream Mach number as well as target lift coefficient are supposed as uncertain parameters. The mean and standard deviation of drag coefficient are simultaneously minimized to obtain non-dominated robust optimal designs. The developed robust design optimization approach via the variable fidelity Kriging model is shown to be useful for efficient search of robust airfoil designs. Nomenclature d C = drag coefficient * l C = target lift coefficient p C = pressure coefficient M = free-stream Mach number = angle of attack [deg] = mean = standard deviation