A data model for heat-related rail buckling: implications for operations, maintenance and long-term adaptation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Heat-related rail buckling is a significant operational and safety issue for the railways of Great Britain (GB). Although continuously-welded rail is pre-stressed to a stress-free temperature of 27°C, degradation and local topographic and microclimatic factors can lead to failures occurring at lower temperatures. These buckle events can cause widespread knock-on delays. As a common risk mitigation approach, speed restrictions are imposed for forecasted heat events, with these measures also being associated with non-trivial delays and disruption. The recently published UKCP18 climate projections indicate that the frequency, duration and magnitude of heat wave events will increase in the coming decades. This paper presents a data model to explain the occurrence of heat-related disruption incidents on GB's rail network. This model is built on historical delay data from Network Rail - the owner of GB's railway infrastructure, given explanatory variables for important meteorological and infrastructure features from published research in the literature. The model is implemented at two scales. Firstly at the national scale, including all Network Rail operational routes, and secondly for the South East of England (climatologically the warmest part of the country and hence at perceived greater risk) including the operational routes of Anglia, Wessex and South East.

Details

Original languageEnglish
Title of host publicationProceedings of the 12th World Congress on Railway Research
Publication statusAccepted/In press - 1 Aug 2019
EventWorld Congress on Railway Research: Railway Research to Enhance the Customer Experience - Tokyo International Forum, Tokyo, Japan
Duration: 28 Oct 20191 Nov 2019
Conference number: 12
https://wcrr2019.org

Conference

ConferenceWorld Congress on Railway Research
Abbreviated titleWCRR2019
CountryJapan
CityTokyo
Period28/10/191/11/19
Internet address

Keywords

  • Rail, High temperatures, Logistic regression, Resilience, Disruption