Assessment of railway vibrations using an efficient scoping model
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 12 - Engineering
- Output identifier
- CIVIL-50
- Type
- D - Journal article
- DOI
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10.1016/j.soildyn.2013.12.003
- Title of journal
- Soil Dynamics and Earthquake Engineering
- Article number
- -
- First page
- 37
- Volume
- 58
- Issue
- -
- ISSN
- 0267-7261
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper outlines the first ever machine-learning-based method to predict railway ground-borne vibration levels. It has made it possible to account for the presence of variable soils during vibration scoping studies, which is one of the most important factors in vibration propagation. The approach is complementary to our other investigations (e.g. DOI:10.1016/j.soildyn.2018.07.046) and together, they were used by Ineco to inform vibration abatement measures on the Madrid-Barcelona high speed rail line in 2018. It is currently being directly applied in a Leverhulme prize research grant (PLP-2016-270).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
