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A gradient-based nested Latin hypercube DOE for quadratic polynomials RSM in FEM simulation

机译:有限元模拟中基于二次多项式RSM的基于梯度的嵌套拉丁超立方体DOE

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摘要

A nested Latin hypercube DOE (Design Of Experiment) involves at least a low accuracy experiments and a high accuracy one in Finite Element Method (FEM) Simulation. How to use the information contained in the regression model of previous low accuracy experiments in the design of high accuracy one needs deeply study because such information may be ignored in evenly sampling method, leading to a imprecise regression model of high accuracy experiment. This paper employ the gradient of the regression model of low accuracy experiments as the index of the information distribution of tested object to adjust the DOE of high accuracy one. Thus more information of object can be obtained in those high accuracy experiments and a more precise quadratic polynomials RSM (Response Surface Method) model is built.
机译:嵌套的拉丁超立方体DOE(实验设计)至少涉及一个低精度实验和一个有限元方法(FEM)模拟中的高精度实验。在高精度设计中如何使用以前的低精度实验的回归模型中包含的信息需要深入研究,因为在均匀采样方法中可能会忽略这些信息,从而导致高精度实验的回归模型不精确。本文采用低精度实验的回归模型的梯度作为被测对象信息分布的指标来调整高精度DOE。因此,在那些高精度实验中可以获得更多的对象信息,并且建立了更精确的二次多项式RSM(响应表面方法)模型。

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