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Variability response functions for stochastic systems under dynamic excitations

机译:动态激励下随机系统的变异响应函数

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摘要

The concept of variability response functions {VRFs) is extended in this work to linear stochastic systems under dynamic excitations. An integral form for the variance of the dynamic response of stochastic systems is considered, involving a Dynamic VRF (DVRF) and the spectral density function of the stochastic field modeling the uncertain system properties. As in the case of linear stochastic systems under static loads, the independence of the DVRF to the spectral density and the marginal probability density function of the stochastic field modeling the uncertain parameters is assumed. This assumption is here validated with brute-force Monte Carlo simulations. The uncertain system property considered is the inverse of the elastic modulus (flexibility). The same integral expression can be used to calculate the mean response of a dynamic system using a Dynamic Mean Response Function (DMRF) which is a function similar to the DVRF. These integral forms can be used to efficiently compute the mean and variance of the transient system response together with time dependent spectral-distribution-free upper bounds. They also provide an insight into the mechanisms controlling the dynamic mean and variability system response.
机译:可变性响应函数(VRF)的概念在这项工作中扩展到动态激励下的线性随机系统。考虑了随机系统动态响应方差的积分形式,其中包括动态VRF(DVRF)和模拟不确定系统属性的随机场的频谱密度函数。与静态负载下的线性随机系统一样,假定DVRF与频谱密度的独立性以及对不确定参数建模的随机场的边际概率密度函数的影响。此假设在此已通过蛮力蒙特卡洛模拟得到了验证。所考虑的不确定的系统特性是弹性模量(柔韧性)的倒数。可以使用与DVRF类似的动态均值响应函数(DMRF),使用相同的积分表达式来计算动态系统的均值响应。这些积分形式可用于有效地计算瞬态系统响应的均值和方差以及与时间相关的无频谱分布上限。他们还提供了控制动态均值和变异性系统响应的机制的见解。

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