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Integration algorithm for covariance nonstationary dynamic analysis using equivalent stochastic linearization

机译:等效随机线性化的协方差非平稳动态分析积分算法

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Deterministic mechanical systems subject to stochastic dynamic actions, such as wind or earthquakes, have to be properly evaluated using a stochastic approach. For nonlinear mechanical systems it is necessary to approximate solutions using mathematical tools, as the stochastic equivalent linearization. It is a simple approach from the theoretical point of view, but needs numerical techniques whose computational complexity increases in case of nonstationary excitations. In this paper a procedure to solve covariance analysis of stochastic linearized systems in the case of nonstationary excitation is proposed. The nonstationary Lyapunov differential matrix covariance equation for the linearized system is solved using a numerical algorithm which updates linearized system coefficient matrix at each step. The technique used is a predictor-corrector procedure based on backward Euler method. Accuracy and computational costs are analysed showing the efficiency of the proposed procedure.
机译:必须使用随机方法正确评估受随机动态作用(例如风或地震)影响的确定性机械系统。对于非线性机械系统,有必要使用数学工具来近似求解,如随机等效线性化。从理论的角度来看,这是一种简单的方法,但是需要数值技术,在非平稳激励的情况下,其计算复杂性会增加。提出了一种求解非平稳励磁随机线性系统协方差分析的方法。使用数值算法求解线性系统的非平稳Lyapunov微分矩阵协方差方程,该算法在每一步都会更新线性化系统系数矩阵。所使用的技术是基于反向欧拉方法的预测器-校正器过程。分析准确性和计算成本,表明所提出程序的效率。

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