线性动力系统灵敏度分析的最优随机强迫

IF 0.5 4区数学 Q4 MATHEMATICS, APPLIED

Russian Journal of Numerical Analysis and Mathematical Modelling Pub Date : 2022-04-01 DOI:10.1515/rnam-2022-0009

Y. Nechepurenko, G. Zasko

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引用次数: 0

摘要

摘要本文致力于构造最优随机强迫，以研究线性动力系统对外部扰动的敏感性。寻求最优强迫以使响应的Schatten范数最大化。作为一个例子，我们考虑了由分层湍流Couette流中的大型结构分析引起的线性动力系统的最优随机强迫的构造问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimal stochastic forcings for sensitivity analysis of linear dynamical systems

Abstract The paper is devoted to the construction of optimal stochastic forcings for studying the sensitivity of linear dynamical systems to external perturbations. The optimal forcings are sought to maximize the Schatten norms of the response. As an example,we consider the problem of constructing the optimal stochastic forcing for the linear dynamical system arising from the analysis of large-scale structures in a stratified turbulent Couette flow.

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来源期刊

Russian Journal of Numerical Analysis and Mathematical Modelling 数学-工程：综合

CiteScore

1.40

自引率

16.70%

发文量

审稿时长

>12 weeks

期刊介绍： The Russian Journal of Numerical Analysis and Mathematical Modelling, published bimonthly, provides English translations of selected new original Russian papers on the theoretical aspects of numerical analysis and the application of mathematical methods to simulation and modelling. The editorial board, consisting of the most prominent Russian scientists in numerical analysis and mathematical modelling, selects papers on the basis of their high scientific standard, innovative approach and topical interest. Topics: -numerical analysis- numerical linear algebra- finite element methods for PDEs- iterative methods- Monte-Carlo methods- mathematical modelling and numerical simulation in geophysical hydrodynamics, immunology and medicine, fluid mechanics and electrodynamics, geosciences.