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Determination of Spatially Distributed Probability Density Functions for Parameter Estimation in Model Updating Procedures

机译:模型更新过程中用于参数估计的空间分布概率密度函数的确定

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The parameter estimation methods used in updating algorithms for finite element models (FE-models) of complex structures, depend on the choice of a priori to be determined weighting matrices. The weighting matrices are in most cases assumed by engineering judgement of the analyst carrying out the updating procedure and his assessment of uncertainty of parameters chosen and measured and calculated results. A more natural approach to cope with the uncertainties in parameters and results is a statistical one. The first problem here one is faced with is, that despite their statistical character most of the parameters are spatially distributed (thickness of plates and shells, material properties etc.) and they possess a kind of correlation to each other. The paper presents a method for addressing this problem and its limitations to get suitable statistical distribution.
机译:用于复杂结构的有限元模型(FE模型)的更新算法中使用的参数估计方法取决于要确定的加权矩阵的先验选择。在大多数情况下,加权矩阵是由执行更新程序的分析师的工程判断以及他对所选参数以及测量和计算结果的不确定性的评估所假定的。解决参数和结果不确定性的一种更自然的方法是统计学方法。这里面临的第一个问题是,尽管它们具有统计特性,但大多数参数还是在空间上分布的(板和壳的厚度,材料特性等),并且它们彼此之间具有某种相关性。本文提出了一种解决此问题的方法及其局限性,以获得适当的统计分布。

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