Abstract

Management of a large portfolio of infrastructure assets is a complex and demanding task for transport agencies. Although extensive research has been conducted on probabilistic models for asset management, in particular bridges, focus has been almost exclusively on deterioration modelling. The model being presented in this study tries to reunite a disjointed system by combining deterioration, inspection and maintenance models. A Petri-Net modelling approach is employed and the resulting model consists of a number of different modules each with its own source of data, calibration methodology and functionality. The modules interconnect providing a robust framework. The interaction between the modules can be used to provide meaningful outputs useful to railway bridge portfolio managers.

Highlights

  • Railway structures are integral to the efficient running of the transport network

  • The Severity Extent Rating (SevEx) states of medium conditions are of a medium risk and are recommended to be inspected no later than 6 year intervals

  • There are a wide variety of different systems, policies and practices that the model needs to encompass so a modelling approach that is very flexible was required

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Summary

Introduction

Railways are used for both industry and commuters so their use is critical from a social and economic perspective. Trains can carry very heavy loads and the schedules mean that the frequency of trains is relentless on supporting structures. A significant challenge is to be able to predict structural deterioration. Some defects are more or less likely to lead to other defects and knowing which defect an element suffers from and monitoring the defects development gives a great insight into predicting structural deterioration. This study uses concrete main girders as its exemplar element because concrete bridges are becoming increasingly more popular and the main girders are the elements that experience most. Structural loading and are critical to bridge safety. The techniques and methods used in this study can be applied to all railway bridges

Markov Based Models
Petri-Net Based Models
Petri-Nets
Coloured Petri-Nets
Condition States
Inspection Interval
Maintenance Actions
Data Source
Petri-Net Model
Quality of Fit of the Deterioration Module
Intervention Module
B2 B3 B4
Conclusion
Findings
Future Developments

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