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Lookup NU author(s): Dr Aleksandra Svalova, Dr Peter Helm, Dr Jordan Oakley
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Long linear infrastructure, e.g. highways and railways, includes large numbers of dispersed earthwork assets. Depending on their age and history, it can be practically impossible to constantly maintain up-to-date condition information. However, this data, and models using it, play a vital role in predicting earthwork behaviour and guiding intervention decision-making, which must take account of both the likelihood and consequences of asset failures. ACHILLES has developed novel surrogate models to help address uncertainty in earthwork assessment and make the most of limited data.
Author(s): Loveridge F, Svalova A, Helm PR, Armstrong A, Oakley J
Publication type: Report
Publication status: Published
Series Title:
Year: 2023
Print publication date: 24/11/2023
Online publication date: 15/12/2023
Acceptance date: 24/11/2023
Institution: Newcastle University
Place Published: Newcastle upon Tyne
URL: https://www.achilles-grant.org.uk/wp-content/uploads/2023/12/ACHILLES-Reading-Guide-SIX-V2_2023_12_13.pdf
