Railway track deterioration models: a review of the state of the art

Abstract

There has been a railway renaissance in Britain since the 1990s, with passenger kilometres approximately doubling between 1990 and 2019. Despite changing habits caused by the COVID-19 pandemic, the latest data show that passenger journeys are almost back to their 2019 levels. Without building new lines (HS2 being not yet open and recently downgraded in scope), increased use has led to increased rates of infrastructure deterioration and a need for more maintenance and renewal to create the capacity on the aged existing railway network to meet this demand. Against this background, there have been on-going efforts in the field of railway track deterioration modelling to limit component failures and prolong the remaining useful life of the infrastructure. Analysis and modelling techniques have become increasingly detailed owing to advances in real-time data-acquisition and computational methods and the emergence of ‘big data’ approaches to interpretation. However, previous studies have generally merely confirmed the complexity of modelling track deterioration. There are few if any systematic reviews of deterioration models aimed at informing infrastructure managers (IM) from a whole-life asset management perspective. This paper addresses this knowledge gap by building on previous research to present a systematic taxonomy of track deterioration models, and proposing a hierarchical classification based on level of detail and functionality.

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Identifiers

ORCID for Georgios Rempelos: orcid.org/0000-0002-7525-2718

ORCID for Giacomo Ognibene: orcid.org/0000-0003-4620-2399

ORCID for Louis Le Pen: orcid.org/0000-0002-4362-3895

ORCID for Simon Blainey: orcid.org/0000-0003-4249-8110

ORCID for John Preston: orcid.org/0000-0002-6866-049X

ORCID for William Powrie: orcid.org/0000-0002-2271-0826

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