Analysis and prediction of tram track degradation

Elkhoury, N 2018, Analysis and prediction of tram track degradation, Masters by Research, Engineering, RMIT University.

Document type: Thesis
Collection: Theses

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Title Analysis and prediction of tram track degradation
Author(s) Elkhoury, N
Year 2018
Abstract Transportation is the means to carry people and goods from one place to another, and has been very important in each stage of human civilization. Therefore, engineers have developed the transportation network day-by-day, aiming to provide for people’s comfort, needs and safety in the most sustainable way possible.

In the past, transport organisations generally concentrated on the construction and expansion of transport networks, but they have gradually moved from a focus on expansion to intelligently maintaining the existing assets in recent years. For this reason, degradation models have been developed in many transport management systems, with the aim of assisting track maintenance planning and reducing the costs of asset management.

Melbourne has the largest operating tram network in the world with 250 kilometers of double track (Yarra Trams, 2017a). Melbourne’s tram network is operated by the Yarra Trams organisation under franchise from the government of Victoria, Australia (Yarra Trams, 2017a). Yarra Trams organises the news, maps, timetables, service changes, real-time tram arrival information, and the construction and maintenance of the tram infrastructure.

Many variables are involved in ensuring that Melbourne tram system operates to safe and best practice standards. One of the main elements influencing the tram system is the track infrastructure. The condition of the track infrastructure affects network operations either directly or indirectly. In order to keep the track infrastructure in its best condition over the longest possible time period, a maintenance plan is required. This plan is essential for such a large network as it can help in recovering the serviceability of tram tracks from faults and damage and prevent further wear of the tracks.

Currently, manual inspections are still used to identify track maintenance activities across the network. These inspections identify the status of the tram tracks, whether the tracks need maintenance, the required level of maintenance and the time period needed to maintain the damaged tracks. Since the inspections are done by a number of maintenance teams, human errors are likely to occur. In addition, inaccurate prediction of the maintenance time frame and mistakes in the inspection and detection of track defects may occur. Therefore, prioritisation of the maintenance activities is a substantial challenge. High maintenance and operational costs may be the result of poorly planned maintenance schedules. In other words, very early or late maintenance of the tram tracks are very costly, as are unnecessary maintenance or replacement of tracks.

In order to solve this problem, this research investigates degradation models for tram tracks in Melbourne. The models are rigorously reviewed in order to determine the most appropriate model in terms of sustainability, safety, accuracy and long-term behaviour. A time-series stochastic model is developed using MATLAB software to predict the degradation of tram tracks. A regression model is also developed using SPSS software for comparison with the time-series model. The models are developed for straight and curves sections of the tram network.

The models were developed after analysing tram track variables over a period of time to find the relationship between the variables and track degradation. The variables include asset data variables (such as construction material, track surface, rail profile) and operational variables (such as annual rail usage, number of trips, route location). In this research, the annual rail usage (in million gross tons (MGTs)) is found to be the main variable affecting rail degradation using the gauge parameter of rails for curves and straight sections of the tram network.

Based on the developed prediction models, the maintenance activities of degraded rail tracks are identified within a specified time period. This will help to reduce the maintenance costs, save time and prevent occasional unnecessary maintenance activities. In addition, it will reduce interruptions to traffic and delays experienced by passengers.
Degree Masters by Research
Institution RMIT University
School, Department or Centre Engineering
Subjects Infrastructure Engineering and Asset Management
Civil Engineering not elsewhere classified
Transport Engineering
Keyword(s) Degradation
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Created: Fri, 20 Jul 2018, 11:08:48 EST by Denise Paciocco
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