Uncertainty Quantification via Variable Fidelity Kriging Model
Uncertainty Quantification via Variable Fidelity Kriging Model
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DOI：
10.2322/jjsass.60.80
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发表时间：
2012-04
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影响因子：
--
通讯作者：
Wataru Yamazaki
中科院分区：
文献类型：
--
作者：
Wataru Yamazaki
本文将变保真度Kriging模型方法应用于二维翼型气动性能的气动数据建模和不确定性量化。该方法能够同时利用高、低保真度函数信息有效地构造精确的代理模型。在本研究中，低保真度函数是利用较粗糙的计算网格来定义的。不确定度量化通过代理模型上的蒙特-卡罗模拟来执行，这通常被称为廉价的蒙特-卡罗模拟方法。所开发的不确定性量化方法显示出与完全非线性蒙特-卡罗模拟结果相当的准确性，并且以低得多的计算成本执行。
In this paper, a variable fidelity Kriging model approach is applied to aerodynamic data modeling and uncertainty quantification of 2D airfoil aerodynamic performances. This approach enables to construct an accurate surrogate model efficiently by utilizing high and low fidelity function information simultaneously. The low fidelity functions are defined by utilizing coarser computational meshes in this research. The uncertainty quantification is executed by Monte-Carlo simulation on the surrogate model, which is often referred to as Inexpensive Monte-Carlo simulation approach. The developed uncertainty quantification approach showed comparable accuracy with full non-linear Monte-Carlo simulation results and was executed with much lower computational cost.