.png){kind=icon}
返回
Deep reinforcement learning-based sampling method for structural reliability assessment
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ress.2020.106901.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Surrogate model methods are widely used in structural reliability assessment, but conventional sampling methods require a large number of experimental points to construct a surrogate model. Inspired by the learning process of the AlphaGo, which is essentially optimization of sampling, we proposed a deep reinforcement learning (DRL)-based sampling method for structural reliability assessment. First, the sampling space and the existing samples are transformed into an array that is treated as the state in DRL. Second, a deep neural network is designed as the agent to observe the sampling space and select new experimental points, which are treated as actions. Finally, a reward function is proposed to guide the deep neural network to select experimental points along the limit state surface. Two numerical examples including a benchmark problem are employed to illustrate the sampling ability of the proposed method for structural reliability calculation. The simulation results demonstrate that the proposed method can learn to select experimental points along the limit state surface. Comparing with the direct Monte Carlo simulation, AK-MCS, Latin hypercube sampling, and subset simulation methods, the results show that the proposed DRL-based sampling method has an advantage in dealing with highly nonlinear problems.
Keyword:
Structural reliability
Deep reinforcement learning
Deep Neural Network
Surrogate model
Failure probability
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
R
IF:
11
论文数:
9.0K
被引数:
5.0W
机构
引用论文
Application of line sampling simulation method to reliability benchmark problems线抽样模拟法在可靠性基准问题中的应用.png)
STRUCTURAL SAFETY
STRUCTURAL SAFETYIF6.3
PREAI
分享收藏Study of bi-directional buck-boost converter topologies for application in electrical vehicle motor drives应用于电动汽车电机驱动的双向buck-boost变换器拓扑研究
PREAI
分享收藏Hamiltonian Monte Carlo methods for Subset Simulation in reliability analysis可靠性分析中子集模拟的哈密顿蒙特卡罗方法STRUCTURAL SAFETY
OAAI
STRUCTURAL SAFETYIF6.3
OAAI分享收藏分享收藏
查看更多内容