Review and application of Artificial Neural Networks models in reliability analysis of steel structures

A.A. Chojaczyk; A.P. Teixeira; L.C. Neves; J.B. Cardoso; C. Guedes Soares

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Review and application of Artificial Neural Networks models in reliability analysis of steel structures

机译：人工神经网络模型在钢结构可靠性分析中的回顾与应用

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This paper presents a survey on the development and use of Artificial Neural Network (ANN) models in structural reliability analysis. The survey identifies the different types of ANNs, the methods of structural reliability assessment that are typically used, the techniques proposed for ANN training set improvement and also some applications of ANN approximations to structural design and optimization problems. ANN models are then used in the reliability analysis of a ship stiffened panel subjected to uniaxial compression loads induced by hull girder vertical bending moment, for which the collapse strength is obtained by means of nonlinear finite element analysis (FEA). The approaches adopted combine the use of adaptive ANN models to approximate directly the limit state function with Monte Carlo simulation (MCS), first order reliability methods (FORM) and MCS with importance sampling (IS), for reliability assessment. A comprehensive comparison of the predictions of the different reliability methods with ANN based LSFs and classical LSF evaluation linked to the FEA is provided.

机译：本文就结构可靠性分析中人工神经网络（ANN）模型的开发和使用进行了概述。该调查确定了不同类型的人工神经网络，通常使用的结构可靠性评估方法，为人工神经网络训练集提出的改进技术，以及人工神经网络近似在结构设计和优化问题中的一些应用。然后，将人工神经网络模型用于承受船体梁垂直弯曲力矩引起的单轴压缩载荷的船用加劲肋板的可靠性分析，并通过非线性有限元分析（FEA）获得其崩溃强度。所采用的方法结合了自适应ANN模型的使用，以蒙特卡罗模拟（MCS），一阶可靠性方法（FORM）和带有重要度抽样（IS）的MCS直接逼近极限状态函数，以进行可靠性评估。提供了基于ANN的LSF和与FEA关联的经典LSF评估对不同可靠性方法的预测的全面比较。

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来源
《Structural Safety》 |2015年第2015期|78-89|共12页
作者
A.A. Chojaczyk; A.P. Teixeira; L.C. Neves; J.B. Cardoso; C. Guedes Soares;
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作者单位

Research Centre in Structures and Construction (UNIC), Department of Civil Engineering, Universidade Nova de Lisboa, Portugal;

Centre for Marine Technology and Engineering (CENTEC), Instituto Superior Tecnico, Universidade de Lisboa, Portugal;

Nottingham Transportation Engineering Centre (NTEC), Dept. of Civil Engineering, University of Nottingham, NG7 2RD Nottingham, United Kingdom;

Research and Development Unit for Mechanical and Industrial Engineering (UNIDEMI), Department of Mechanical and Industrial Engineering, Universidade Nova de Lisboa, Portugal;

Centre for Marine Technology and Engineering (CENTEC), Instituto Superior Tecnico, Universidade de Lisboa, Portugal;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Artificial Neural Networks; Structural reliability; Monte Carlo simulation; Importance sampling; First-order reliability methods; Finite element analysis; Ultimate strength; Stiffened plates;

机译：人工神经网络;结构可靠性;蒙特卡罗模拟;重要抽样;一阶可靠性方法;有限元分析;极限强度;加筋板;

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7. Review and application of Artificial Neural Networks models in reliability analysis of steel structures [O] . Chojaczyk, A.A., Teixeira, A.P., Neves, Luís C., 2015

机译：人工神经网络模型在钢结构可靠性分析中的回顾与应用

Review and application of Artificial Neural Networks models in reliability analysis of steel structures

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