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

Yianni, Panayioti C.; Rama, Dovile; Neves, Luís; Andrews, John; Castlo, David

doi:10.1080/15732479.2016.1157826

Cited by 30 publications

(24 citation statements)

References 26 publications

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“…This model can support maintenance decision-making by identifying the most appropriate strategy Le and Andrews (2016). However, a comprehensive understanding of the complex deterioration process should be acquired before the calibration of the model Yianni et al (2017).…”

Section: Resultsmentioning

confidence: 99%

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A Modeling Framework for Efficacy Assessment and Preventive Maintenance of Torrential Protection Works

Chahrour¹,

Hariri²,

Tacnet³

et al. 2019

Proceedings of the 29th European Safety and Reliability Conference (ESREL)

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Natural phenomena in mountains put people and assets at risk. Risk reduction measures can be either structural (protection works) or non-structural (risk zoning maps). In torrential watersheds of the French mountains, many checkdams have been built since the 19 th century. As any civil engineered structure, those dams age and their failures may have severe effects on protected areas. Thus, preserving their level of efficacy is of a high interest. In a context of decreasing public budgets, it is necessary to assess their structural, functional and economic efficacy in order to quantify the residual risk and to choose the best maintenance strategies. Recent global approach has been proposed to integrate safety and reliability analysis, multicriteria decision-making methods, and information imperfection processing. However, it does not help in choosing the best strategy to maintain protection devices. It does not cover all aspects related to protection works management making the balance between investment, preventive maintenance costs, and risk evolution. This paper develops a contribution addressing all those issues and proposes a new modeling approach based on Petri nets, whose main steps are: 1) to describe multi-scale protection works systems interaction between both natural and technological systems' components; 2) to analyze structural and functional failure modes; 3) to develop a Petri net model for deterioration and maintenance modeling; 4) to compare different maintenance strategies under different hypothesis on degradation and damage processes.

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Section: Resultsmentioning

confidence: 99%

“…SPNs follow probabilistic models on transitions based on historical records and data used for dependability modeling. Stochastic models are superior to other modeling techniques because they offer practicality and reliability Yianni et al (2017).…”

Section: Stochastic Petri Nets Spnsmentioning

confidence: 99%

A Modeling Framework for Efficacy Assessment and Preventive Maintenance of Torrential Protection Works

Chahrour¹,

Hariri²,

Tacnet³

et al. 2019

Proceedings of the 29th European Safety and Reliability Conference (ESREL)

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“…Hence, elements such as decks, piers, abutments, girder, and stay cables are classified as critical elements. These critical elements relatively have more significant effects on the BHI [22][23][24][25]. Identification, proper monitoring, and adequate maintenance of critical elements can help reduce elevated risks in bridges [26,27].…”

Section: Literature Reviewmentioning

confidence: 99%

Co-Active Prioritization by Means of Contingency Tables for Analyzing Element-level Bridge Inspection Results and Optimizing Returns

Oyegbile¹,

Chorzepa²

2020

Infrastructures

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An efficient prioritization of bridge actions such as preventive maintenance, rehabilitation, or replacement (MRR) that accounts for inter-element interactions will optimize a long-term return on investments (ROI) in terms of service life extension. What enables this return is the assignment of “Co-Active” elements. This study develops a methodology based on the concept of “Co-Active elements”. The word, “Co-Active”, is used to represent a small group of elements that act together to improve the Bridge Health Index (BHI). The Co-Active parameters for three major bridge groups in Georgia are presented. To illustrate how the Co-Active model works, 1439 in-service bridges’ Element-Level Bridge Inspection results from the state of Georgia in U.S.A., representing a concrete bridge group with six Co-Active elements, are studied. The analysis results indicate that the overall BHI improves by 20% over the subsequent 20 years when expansion joints are replaced. The effects of Co-Active elements on the BHI predictions are quantifiable and depend on factors such as the timing of MRR, the condition of bridge elements as well as the type of MRR. Furthermore, it is concluded that inter-dependent relationships among Co-Active elements are highly affected by Co-Active coefficients. They increase when the degree of dependency among elements increases. Finally, the proposed bridge Co-Active prioritization analysis accounts for a performance target and associated gaps and thus is able to identify critical elements that affect bridge service life the most.

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“…or this reason alternative models to the classic Markov such as Hidden-Markov Chains and Semi-Markov Chains have been proposed. Recently, and with applications to fields like railway bridges, Petri Net models have demonstrated the appropriateness to model the infrastructure performance (Yianni et al 2017). Other options of performance modeling, as remarked in section 3, rely on artificial intelligence based on neural networks.…”

Section: Performance Indicators and Modelsmentioning

confidence: 99%

Lifecycle Management, Monitoring and Assessment for Safe Large-Scale Infrastructures: Challenges and Needs

Limongelli

Previtali

Cantini

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Many European infrastructures dating back to '50 and '60 of the last century like bridges and viaducts are approaching the end of their design lifetime. In most European countries costs related to maintenance of infrastructures reach a quite high percentage of the construction budget and additional costs in terms of traffic delay are due to downtime related to the inspection and maintenance interventions. In the last 30 years, the rate of deterioration of these infrastructures has increased due to increased traffic loads, climate change related events and man-made hazards. A sustainable approach to infrastructures management over their lifecycle plays a key role in reducing the impact of mobility on safety (over 50 000 fatalities in EU per year) and the impact of greenhouse gases emission related to fossil fuels. The events related to the recent collapse of the Morandi bridge in Italy tragically highlighted the sheer need to improve resilience of aging transport infrastructures, in order to increase the safety for people and goods and to reduce losses of functionality and the related consequences. In this focus Structural Health Monitoring (SHM) is one of the key strategies with a great potential to provide a new approach to performance assessment and maintenance over the life cycle for an efficient, safe, resilient and sustainable management of the infrastructures. In this paper research efforts, needs and challenges in terms of performance monitoring, assessment and standardization are described and discussed.

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

Cited by 30 publications

References 26 publications

A Modeling Framework for Efficacy Assessment and Preventive Maintenance of Torrential Protection Works

A Modeling Framework for Efficacy Assessment and Preventive Maintenance of Torrential Protection Works

Co-Active Prioritization by Means of Contingency Tables for Analyzing Element-level Bridge Inspection Results and Optimizing Returns

Lifecycle Management, Monitoring and Assessment for Safe Large-Scale Infrastructures: Challenges and Needs

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