首页> 外文期刊>Computers & mathematics with applications >Time-domain formulation in computational dynamics for linear viscoelastic media with model uncertainties and stochastic excitation
【24h】

Time-domain formulation in computational dynamics for linear viscoelastic media with model uncertainties and stochastic excitation

机译:具有模型不确定性和随机激励的线性粘弹性介质计算动力学的时域公式化

获取原文
获取原文并翻译 | 示例

摘要

The paper is devoted to the computational time-domain formulation of linear viscoelastic systems submitted to a nonstationary stochastic excitation and in the presence of model uncertainties which are modeled in the framework of the probability theory. The objective is to introduce and to develop an adapted and complete formulation of such a problem in the context of computational mechanics. A reduced-order model in the time domain with stochastic excitation is derived from the computational model. For the reduced-order model, the stochastic modeling of both computational model-parameter uncertainties and modeling errors is carried out using the nonparametric probabilistic approach and the random matrix theory. We present a new formulation of model uncertainties to construct the random operators for viscoelastic media. We then obtained a linear Stochastic Integra-Differential Equation (SIDE) with random operators and with a stochastic nonhomogeneous part (stochastic excitation). A time discretization of this SIDE is proposed. In a first step, the SIDE is transformed to a linear It6 Stochastic Differential Equation (ISDE) with random operators. Then the ISDE is discretized using an extension of the Stormer-Verlet scheme which is a particularly well adapted algorithm for long-time good behavior of the numerical solution. Finally, for the stochastic solver and statistical estimations of the random responses, we propose to use the Monte Carlo simulation for Gaussian and non-Gaussian excitations.
机译:本文致力于线性粘弹性系统的计算时域公式化,该系统适用于非平稳随机激励,并且存在在概率论框架下建模的模型不确定性。目的是在计算力学的背景下引入和开发这种问题的适应和完整的表述。从计算模型中导出了具有随机激励的时域降阶模型。对于降阶模型,使用非参数概率方法和随机矩阵理论对计算模型参数不确定性和建模误差进行了随机建模。我们提出了一种新的模型不确定性公式,以构造粘弹性介质的随机算子。然后,我们获得了带有随机算子和随机非均质部分(随机激励)的线性随机积分微分方程(SIDE)。提出了该SIDE的时间离散化。第一步,将SIDE转换为带有随机算子的线性It6随机微分方程(ISDE)。然后,使用Stormer-Verlet方案的扩展离散化ISDE,Storm-Verlet方案是一种特别合适的算法,可长期有效地求解数值解。最后,对于随机响应的随机求解器和统计估计,我们建议对高斯和非高斯激励使用蒙特卡罗模拟。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号