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Reliability-based topology optimization of uncertain building systems subject to stochastic excitation

机译:随机激励下不确定建筑系统的基于可靠性的拓扑优化

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Topology optimization has traditionally been developed in a deterministic setting, notwithstanding the considerable uncertainties that generally affect both the system as well as the excitation. Therefore, the development of methods that are capable of describing the performance of uncertain systems in a fully probabilistic setting would represent an important step forward. In particular, the ability to consider reliability constraints written in terms of first excursion probabilities posed on systems driven by general stochastic excitation would allow a wide variety of important design scenarios to be modeled. This paper is focused on proposing a simulation -centered reliability-based topology optimization framework to this end. In particular, an approach is developed based on defining, from the argumentation of the simulation process, an optimization sub-problem that not only approximately decouples the probabilistic analysis from the optimization loop, but takes a form that can be extremely efficiently solved. By solving a limited sequence of sub-problems, solutions are found that rigorously meet the first excursion constraints of the original problem. A series of case studies are presented illustrating the potential of the proposed framework. (C) 2017 Elsevier Ltd. All rights reserved.
机译:传统上,拓扑优化是在确定性的环境中开发的,尽管不确定性通常会影响系统以及激励。因此,开发能够描述完全概率环境中不确定系统性能的方法将代表向前迈出的重要一步。特别地,考虑根据由一般随机激励驱动的系统所构成的第一偏移概率而写的可靠性约束的能力将允许对各种重要的设计方案进行建模。为此,本文着重提出了一个以仿真为中心的基于可靠性的拓扑优化框架。特别地,基于从仿真过程的论点定义优化子问题而开发的方法,该优化子问题不仅使概率分析与优化循环近似解耦,而且采取可以极其有效地解决的形式。通过解决有限的子问题序列,可以找到严格满足原始问题的第一个偏移约束的解决方案。提出了一系列案例研究,说明了拟议框架的潜力。 (C)2017 Elsevier Ltd.保留所有权利。

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