Abstract

Numerous bridges are exposed to increasingly frequent and intense extreme events due to climate change, while serving more traffic than originally designed due to population growth. Thus, predictive maintenance of bridges is of paramount importance for securing structural safety and bridge network reliability. However, the application of predictive maintenance for networks of bridges, considering condition and criticality of bridges within the network, has not seen much attention in practice and literature. Presented herein is a maintenance prioritisation method for networks of bridges, based on: a deterioration model for individual components considering uncertainty; life-cycle cost analysis; grouping of components maintenance to reduce traffic interruption and setup cost; and criticality evaluation of bridges using a specifically tailored version of closeness vitality and traffic simulation. This method has been applied to a network of 21 bridges in Portugal, composed of several heterogeneous elements. It showed a substantial decrease in maintenance cost, compared to the Structures Investment Toolkit, and significant differences between criticality of bridges within a network. The proposed methodology can be applied to any networks of bridges or serve as the basis for updated maintenance decision support systems for infrastructure asset networks.

摘要

由于气候变化，许多桥梁面临着越来越频繁和激烈的极端事件，同时由于人口增长而服务于比最初设计更多的交通。因此，桥梁的预测性维护对于确保结构安全和桥梁网络可靠性至关重要。然而，考虑到网络内桥梁的状况和关键性，对桥梁网络进行预测性维护的应用在实践和文献中并未引起太多关注。本文介绍的是桥梁网络的维护优先级排序方法，基于： 考虑不确定性的单个组件的劣化模型；生命周期成本分析；组件维护分组，以减少流量中断和设置成本；使用专门定制的紧密度活力和交通模拟版本对桥梁进行关键性评估。该方法已应用于葡萄牙的 21 座桥梁网络，由多个异构元素组成。与结构投资工具包相比，它显示维护成本显着降低，并且网络中桥梁的关键程度存在显着差异。所提出的方法可以应用于任何桥梁网络或作为基础设施资产网络更新维护决策支持系统的基础。以及网络中桥梁的关键程度之间的显着差异。所提出的方法可以应用于任何桥梁网络或作为基础设施资产网络更新维护决策支持系统的基础。以及网络中桥梁的关键程度之间的显着差异。所提出的方法可以应用于任何桥梁网络或作为基础设施资产网络更新维护决策支持系统的基础。