A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain

Qian Fu; David Jaroszweski; John Easton

doi:10.1049/cp.2018.0071

A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we present a prototype model based on logistic regression analysis, with the aim to understand better the impact of temperature on heat-related incidents on the rail network in Britain. The work draws support from climatic, geographical, and vegetation data resources, and investigates ways in which these data may be used to predict when and where heat-related incidents will most likely occur, thus enabling us to gain a deeper understanding of the conditions that prevail in sites at risk of heat-related disruption events on the rail network in Great Britain. The method is demonstrated using historical records of heat-related incidents within the Anglia area between 2006/07 and 2014/15. By considering a selection of variables, the initial results show that the prototype has good overall performance in terms of both understanding as well as prediction of heat-related incident occurrence.

Original language	English
Title of host publication	Proceedings of the 8th International Conference on Railway Engineering (ICRE 2018)
Publisher	Institution of Engineering and Technology
Number of pages	6
ISBN (Electronic)	9781785618468
DOIs	https://doi.org/10.1049/cp.2018.0071
Publication status	Published - 25 Jun 2018
Event	8th International Conference on Railway Engineering (ICRE 2018) - IET Savoy Place, London, United Kingdom Duration: 16 May 2018 → 17 May 2018 Conference number: CP742

Conference

Conference	8th International Conference on Railway Engineering (ICRE 2018)
Abbreviated title	ICRE 2018
Country/Territory	United Kingdom
City	London
Period	16/05/18 → 17/05/18

Keywords

Rail
High temperature
Heat-related incident
Logistic regression

Access to Document

10.1049/cp.2018.0071Licence: None: All rights reserved

http://digital-library.theiet.org/content/conferences/10.1049/cp.2018.0071Licence: None: All rights reserved

3 Software
2 Conference contribution
1 Paper
1 Article
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Open Access
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A data model for heat-related rail buckling: implications for operations, maintenance and long-term adaptation
Jaroszweski, D., Fu, Q. & Easton, J., 1 Aug 2019, (Accepted/In press) Proceedings of the 12th World Congress on Railway Research. 6 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
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A data model for prediction of weather-related rail incidents: a case-study example of wind-related incidents on the rail network in Great Britain
Fu, Q. & Easton, J., 5 Jan 2018. 12 p.
Research output: Contribution to conference (unpublished) › Paper › peer-review
Prediction of weather-related incidents on the rail network: prototype data model for wind-related delays in Great Britain
Fu, Q. & Easton, J., Sept 2018, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 4, 3, 12 p., 04018027.
Research output: Contribution to journal › Article › peer-review

Open Access
File
3 Citations (Scopus)

447 Downloads (Pure)

1 Guest lecture or Invited talk

Understanding and predicting weather-related incidents on the rail network: Case studies of wind- and heat-related incidents in GB context
Fu, Q. (Invited speaker) & Ye, H. (Host)
8 Jan 2019
Activity: Academic and Industrial events › Guest lecture or Invited talk

Cite this

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title = "A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain",

abstract = "In this paper, we present a prototype model based on logistic regression analysis, with the aim to understand better the impact of temperature on heat-related incidents on the rail network in Britain. The work draws support from climatic, geographical, and vegetation data resources, and investigates ways in which these data may be used to predict when and where heat-related incidents will most likely occur, thus enabling us to gain a deeper understanding of the conditions that prevail in sites at risk of heat-related disruption events on the rail network in Great Britain. The method is demonstrated using historical records of heat-related incidents within the Anglia area between 2006/07 and 2014/15. By considering a selection of variables, the initial results show that the prototype has good overall performance in terms of both understanding as well as prediction of heat-related incident occurrence.",

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Fu, Q , Jaroszweski, D & Easton, J 2018, A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain. in Proceedings of the 8th International Conference on Railway Engineering (ICRE 2018). Institution of Engineering and Technology, 8th International Conference on Railway Engineering (ICRE 2018), London, United Kingdom, 16/05/18. https://doi.org/10.1049/cp.2018.0071

A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain. / Fu, Qian ; Jaroszweski, David; Easton, John.
Proceedings of the 8th International Conference on Railway Engineering (ICRE 2018). Institution of Engineering and Technology, 2018.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - In this paper, we present a prototype model based on logistic regression analysis, with the aim to understand better the impact of temperature on heat-related incidents on the rail network in Britain. The work draws support from climatic, geographical, and vegetation data resources, and investigates ways in which these data may be used to predict when and where heat-related incidents will most likely occur, thus enabling us to gain a deeper understanding of the conditions that prevail in sites at risk of heat-related disruption events on the rail network in Great Britain. The method is demonstrated using historical records of heat-related incidents within the Anglia area between 2006/07 and 2014/15. By considering a selection of variables, the initial results show that the prototype has good overall performance in terms of both understanding as well as prediction of heat-related incident occurrence.

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KW - High temperature

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A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain

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Cite this