Abstract

Vulnerability analysis has become a recent concern for bridge administration authorities. This paper presents a Bayesian network-based vulnerability evaluation methodology for a large-scale national highway (NH) bridge network, using the improved ORDER-II-Dijkstra algorithm. The NH bridge network consists of 1772 bridges, and includes their spatial locations, types, completion years, and assessment states. The network vulnerability was defined by combining edge failure and its influence on network connectivity. Using the equivalent bridge concept for simplicity, the edge failure probability was determined by a series system composed of all bridges in the same edge, where the failure probability for one bridge could be calculated by incorporating its assessment state and design load. The large-scale bridge network connectivity probability was approximately evaluated using the Bayesian network. To avoid the NP-hard problem, the ORDER-II algorithm evaluated the most probable state combinations of equivalent bridges, by adding or deleting ordered state combinations to the minimum heap. The improved Dijkstra’s algorithm was chosen to determine the network connectivity under each state combination by seeking the shortest paths between node pairs. The application of vulnerability to the bridge network illustrates the effectiveness and accuracy of this method, and can provide guidance for decision-making.

摘要

漏洞分析已成为桥梁管理机构最近关注的问题。本文使用改进的ORDER-II-Dijkstra算法，为大型国家公路（NH）桥梁网络提出了一种基于贝叶斯网络的脆弱性评估方法。NH桥网络由1772座桥梁组成，并包括其空间位置，类型，完工年份和评估状态。通过结合边缘故障及其对网络连接的影响来定义网络漏洞。为简化起见，使用等效桥的概念，边缘失效概率由一个系统组成，该系统由同一条边缘中的所有桥梁组成，其中一个桥梁的失效概率可以通过合并其评估状态和设计负荷来计算。使用贝叶斯网络近似评估了大型桥梁网络的连通性概率。为了避免NP难题，ORDER-II算法通过在最小堆中添加或删除有序状态组合来评估等效桥的最可能状态组合。选择改进的Dijkstra算法，通过寻找节点对之间的最短路径来确定每种状态组合下的网络连通性。漏洞在桥接网络中的应用说明了该方法的有效性和准确性，并可以为决策提供指导。通过向最小堆中添加或删除有序状态组合。选择改进的Dijkstra算法，通过寻找节点对之间的最短路径来确定每种状态组合下的网络连通性。漏洞在桥接网络中的应用说明了该方法的有效性和准确性，并可以为决策提供指导。通过向最小堆中添加或删除有序状态组合。选择改进的Dijkstra算法，通过寻找节点对之间的最短路径来确定每种状态组合下的网络连通性。漏洞在桥接网络中的应用说明了该方法的有效性和准确性，并可以为决策提供指导。