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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >An efficient Kriging based method for time-dependent reliability based robust design optimization via evolutionary algorithm
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An efficient Kriging based method for time-dependent reliability based robust design optimization via evolutionary algorithm

机译：基于高效的基于Kriging的基于时间依赖性可靠性的鲁棒设计优化方法，通过进化算法

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摘要

Uncertainty inadvertently exists in various stages of engineering system design, development, and operating conditions. During the system design and development stages, a design engineer encounters the reliability and robustness measures of a dynamic uncertain system. Due to the existence of dynamic uncertainties, incorporating the time-dependent reliability of an engineering system in reliability based robust design optimization (RBRDO) is crucial. However, the time-dependent and highly non-linear performance functions present a new challenge to the RBRDO problem. This paper presents a multiobjective integrated framework and corresponding algorithms to handle a time-dependent RBRDO problem. The mean and coefficient of variation of the cost function are taken as a multiobjective problem that needs to be optimized to maximize the robustness without destabilizing the system performance. An evolutionary algorithm is employed to find the optimal design points. The performance functions used to estimate the time-dependent reliability are taken as dynamic probabilistic constraints. The dynamic probabilistic constraints are then converted into deterministic constraints by predicting the corresponding time dependent reliability. A transfer learning based method integrated with the Kriging surrogate models is proposed to predict the time-dependent reliability for a given time interval. Various examples are used to demonstrate the effectiveness of the proposed approach. (C) 2020 Elsevier B.V. All rights reserved.
机译：在工程系统设计，开发和操作条件的各个阶段无意中无意中无意中存在。在系统设计和开发阶段，设计工程师遇到动态不确定系统的可靠性和稳健性测量。由于存在动态的不确定性，包括基于可靠性的鲁棒设计优化（RBRDO）在可靠性中的工程系统的时间依赖性可靠性至关重要。然而，时间依赖性和高度线性的性能功能对RBRDO问题带来了新的挑战。本文介绍了一个多目标集成框架和相应的算法，以处理时间依赖的RBRDO问题。成本函数的变化的平均值和系数被视为需要优化的多目标问题，以最大化鲁棒性而不稳定地稳定系统性能。采用进化算法来查找最佳设计点。用于估计时间依赖性可靠性的性能函数被视为动态概率约束。然后通过预测相应的时间相关的可靠性，将动态概率约束转换为确定性约束。提出了一种与Kriging代理模型集成的基于转移的方法，以预测给定时间间隔的时间依赖性可靠性。各种例子用于证明所提出的方法的有效性。 （c）2020 Elsevier B.v.保留所有权利。

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