Modélisation des incertitudes aléatoires en élastodynamique transitoire

Christian Soize
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引用次数: 2

Abstract

A new nonparametric probabilistic approach is presented for modeling random uncertainties in transient linear elastodynamics. The information used does not require a description of the local parameters of the mechanical model. The probability model is constructed in the generalized coordinates associated with the elastic eigenmodes. The available information is constituted of the algebraic properties of the generalized mass, damping and stiffness matrices which have to be positive-definite symmetric matrices, and the knowledge of these matrices for the mean reduced matrix model. The convergence of the stochastic solution with respect to the dimension of the random reduced matrix model is analysed.

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瞬态弹性动力学中的随机不确定性建模
提出了一种新的非参数概率方法来模拟瞬态线性弹性动力学中的随机不确定性。所使用的信息不需要描述力学模型的局部参数。在与弹性本征模态相关的广义坐标中构造了概率模型。可用的信息由广义质量、阻尼和刚度矩阵的代数性质组成,这些矩阵必须是正定对称矩阵,以及这些矩阵的知识对于平均约简矩阵模型。分析了随机解相对于随机约简矩阵模型维数的收敛性。
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