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HS2 railway embankment monitoring : effect of soil condition on underground signals
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Qiu, Song, Mias, Christos, Guo, Weisi and Geng, Xueyu (2019) HS2 railway embankment monitoring : effect of soil condition on underground signals. SN Applied Sciences, 1 . 537. doi:10.1007/s42452-019-0552-y ISSN 2523-3963.
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WRAP-HS2-railway-embankment-monitoring-effect-soil-condition-underground-signals-Guo-2019.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (2382Kb) |
Official URL: https://doi.org/10.1007/s42452-019-0552-y
Abstract
High speed rail demands precision structural health monitoring in shallow underground environments near embankments. Traditional low frequency wireless channels can communicate with underground sensors, but its large antenna elements are prone to damage from geological stress. In this case study paper, we design a higher frequency compact system and experimentally characterize its performance in-situ, in different soil and moisture conditions that are representative of UK soil conditions near the planned HS2 rail site and weather conditions. Accurate 3D electromagnetic simulation results are also shown to support experimental results and a pathloss model sensitive to soil conditions is developed to inform upcoming high speed rail embankment monitoring deployment. The multi-disciplinary findings presented will also directly inform the depth and data reliability of current high speed rail sensor deployment.
Item Type: | Journal Article | ||||||||||||
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TC Hydraulic engineering. Ocean engineering T Technology > TE Highway engineering. Roads and pavements T Technology > TF Railroad engineering and operation T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||||
Library of Congress Subject Headings (LCSH): | Embankments , High speed trains, Sensor networks , Soils -- Testing | ||||||||||||
Journal or Publication Title: | SN Applied Sciences | ||||||||||||
Publisher: | Springer | ||||||||||||
ISSN: | 2523-3963 | ||||||||||||
Official Date: | June 2019 | ||||||||||||
Dates: |
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Volume: | 1 | ||||||||||||
Article Number: | 537 | ||||||||||||
DOI: | 10.1007/s42452-019-0552-y | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
Date of first compliant deposit: | 29 April 2019 | ||||||||||||
Date of first compliant Open Access: | 23 May 2019 | ||||||||||||
RIOXX Funder/Project Grant: |
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