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| Safety evaluation of a steel truss using mechanical Bayesian networks |
Jia-li TAN1( ),Sheng-en FANG1,2,*() |
1. School of Civil Engineering, Fuzhou University, Fuzhou 350108, China
2. National and Local Joint Engineering Research Center for Seismic and Disaster Informatization of Civil Engineering, Fuzhou University, Fuzhou 350108, China |
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Abstract A mechanical Bayesian network was used to express the logical relationship among truss members for safety evaluation of a truss structure. The network topology was established based on mechanical analysis, and the nodal variables included the maximum stress of all the members, the state of the discrete lower longitudinal girder, and the system state. The logical strength between two relevant member nodes was described by conditional probability. A mechanical Bayesian network was established based on numerical analysis and sampling. The four maximum member stresses of the steel truss structure model were input into the established Bayesian network as the known evidence. The maximum stresses of the other members, as well as the state probability of the system, were then deduced. Results show that the mechanical Bayesian network can be used to well estimate the maximum stress of the other nodes (truss members) when the maximum stresses of the monitoring members are known. The coefficient of determination, i,e., R2 = 0.9992, shows that the consistency between the evaluated stress of all elements and the observed data is strong. Simultaneously, the members closer to the known members are estimated in a more accurate way, which can be used as a reference for choosing monitoring members. Furthermore, the inferred state probability of truss system is consistent with the observed data. Thus, the failure probability can be used as an index for safety evaluation of truss structures.
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Received: 01 December 2020
Published: 05 November 2021
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| Fund: 国家自然科学基金资助项目（52178276）；福州大学“旗山学者”奖励支持计划资助项目（XRC-1688） |
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Corresponding Authors:
Sheng-en FANG
E-mail: M170510010@fzu.edu.cn;shengen.fang@fzu.edu.cn
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基于力学贝叶斯网络的钢桁架安全评估
为了评估桁架结构的安全性能，采用力学贝叶斯网络表示桁架各单元间的逻辑关系. 提出根据力学分析建立网络拓扑，网络节点变量包括连续型的桁架结构各单元最大应力、离散型的下平纵梁状态及体系状态；通过条件概率描述节点间的逻辑关系强度，基于数值分析和抽样实现参数学习，建立力学贝叶斯网络；以一榀钢桁架模型的4个单元最大应力作为已知证据输入建立的贝叶斯网络，推理其余单元的最大应力以及体系状态概率. 研究结果表明：在监测单元最大应力已知的情况下，利用力学贝叶斯网络可以估计其余各单元的最大应力值，评估的所有单元应力与观测值间的决定系数 ${R^2}$=0.9992，表现出较强一致性. 与此同时，更靠近已知单元的估计结果更为精确，可以为监测点的选取提供参考. 此外，推理的桁架体系状态概率与观测数据一致，可以为桁架结构体系安全评定提供参考.
关键词：
钢桁架,
结构安全评估,
力学贝叶斯网络,
条件概率分布,
贝叶斯网络拓扑
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