An integrated system for bridge management using probabilistic and mechanistic deterioration models: Application to bridge decks

Abstract

This paper presents a system for the maintenance management of aging highway bridges that integrates two different approaches for deterioration modeling. Probabilistic state-based/time-based models are used to predict the macro-response of bridge components for network level analysis, while reliability-based mechanistic models are used to predict the micro-response of bridge components for project level analysis. Probabilistic state-based/time-based models are developed using qualitative performance indicators (condition ratings) that are determined through visual inspections to identify the overall condition of damaged components in a bridge network. Reliability-based mechanistic models are developed using quantitative performance indicators (physical parameters) that are determined through detailed condition surveys, analytical assessments, and empirical investigations to identify the extent and severity of specific deterioration mechanisms for safety critical structures and/or highly damaged components. The condition rating data obtained from the Ministére des Transports du Québec database and the condition assessment of the Dickson Bridge in Montreal, Canada were used to demonstrate the two approaches for predicting the deterioration of concrete bridge decks at the two levels of management of the integrated system.

A Petri-Net-based modelling approach to railway bridge asset management

“…Frangopol et al (2004) states that it would be better to model deterioration in terms of a time-dependent stochastic process. Morcous et al (2010) reports from Ditlevsen (1984) that structural deterioration is a complex process and there is a considerable amount of uncertainty in the structures "micro-response" which means that stochastic models offer practicality and reliability.…”

Assessment railway bridges over the river Waal near Zaltbommmel

“…Frangopol, Kallen, & van Noortwijk 2004 state that structural deterioration is inherently stochastic by nature and therefore a stochastic modelling approach is most appropriate. Similarly, Morcous, Lounis, & Cho 2010 state that structural deterioration is a complex process which involves much uncertainty in the "micro-response" of the structure. Therefore a stochastic model offers a more robust approach that will more closely mimic the real-world process.…”

Bridge Assessment, Management and Life Cycle Analysis

“…An accurate description of the the life-cycle information management practice of Shanghai Yangtze River Tunnel and Bridge Project is in Tian et al (2012); while delaing with an approach considering bridge management and GIS instruments, the study dealing with management information system of road and bridge infrastructure based on ArcGIS engine (Xiaofang et al, 2012) is very interesting. A relative contemporary problem is faced in the study of the analysis and design of urban bridge safety early-warning management system by Rong et al (2010) generally approaching the problematic of early warning systems, while a more focused article consider an integrated system for bridge management using probabilistic and mechanistic deterioration models, with specific application to bridge decks by Morcous et al (2010); the scheduled maintenance and management actions, considering the residual life evaluation of railway infrastructures is described in , while in Pellegrino et al (2011b) a simplified management procedure for bridge network maintenance is deepen and applied; if a more deep approach on the risk modelling is requested, the advanced deterioration in bridge management systems by Thompson et al (2013) should be of interest; while a very useful and interesting application of the integration of SHM into bridge management systems, with a case study, is presented in Figueiredo et al (2011). As a fact, the economical aspects involving bridge management are increasingly important, so a stakeholder probability-based optimization approach for cost-effective bridge management under financial constraints by Orcesi and Frangopol (2011) should be a necessary lecture for these types of problems; and if a more complicated tools is desired, the multiobjective optimization for project selection in network-level bridge management incorporating decision-maker's preference using the concept of holism (Qiang et al, 2013) is very useful.…”