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Lack-of-fit Tests to Indicate Material Model Improvement or Experimental Data Noise Reduction

机译:缺乏适合测试,以指示材料模型改进或实验数据降噪

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A lack-of-fit test can be used to determine whether a finite element (FE) material model, or experimental results should be the focus to improve overall model accuracy. The lack-of-fit test compares the unbiased estimate of variance to the estimated variance from noise within data. GSJ and Hart methods from literature are provided to estimate the noise within data, and a generalized lack-of-fit test is described. The variance estimators are compared and convergence is demonstrated on a simple regression problem. The lack-of-fit test is then applied to a material calibration problem using the FE method. The lack-of-fit test indicates that the shear component of a non-linear orthotropic material models could be improved, despite already being considered an excellent fit. Additionally the lack-of-fit test is used with a load-dependent Poisson's ratio to demonstrate that the variance in the experimental data should be reduced in order to improve the model.
机译:缺乏拟合测试可用于确定有限元(FE)材料模型,或实验结果应该是提高整体模型精度的重点。缺乏拟合测试将无偏见的差异估计与数据中的噪声中的估计方差的差异进行比较。提供来自文献的GSJ和HART方法来估计数据内的噪声,并且描述了广义缺乏拟合测试。比较方差估计器,并在简单的回归问题上证明了收敛性。然后使用Fe方法将缺乏的测试应用于材料校准问题。缺乏拟合测试表明,尽管已经被认为是优异的合适,但是可以改善非线性正交材料模型的剪切组分。另外,缺乏拟合测试与负载依赖的泊松比率一起使用,以证明应该减少实验数据的方差以改善模型。

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