Strain monitoring using embedded distributed fibre optic sensors in a sprayed concrete tunnel lining during the excavation of cross-passages
de, Battista N
Proceedings of the 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-7)
Politecnico di Torino
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de, B. N., Elshafie, M., Soga, K., Williamson, M., Hazelden, G., & Hsu, Y. (2015). Strain monitoring using embedded distributed fibre optic sensors in a sprayed concrete tunnel lining during the excavation of cross-passages. Proceedings of the 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-7) https://www.repository.cam.ac.uk/handle/1810/255405
The Crossrail project is currently the largest construction undertaking in Europe. It includes ten new rail stations, six of which are under central London, and 42 km of new rail tunnels weaving through the U.K. capital city’s congested sub-terrain. The underground stations typically consist of a concourse tunnel in between two platform tunnels, all linked with a number of cross-passages. The station tunnels are constructed using sprayed concrete lining (SCL) techniques. A distributed fibre optic sensor system was embedded within the SCL at Crossrail’s Liverpool Street Station to monitor the changes in strain within the tunnel lining, during the excavation of crosspassages. The monitoring system provided, for the first time ever, continuous strain profiles in the SCL during each stage of the cross-passage excavation. This field data is useful for calibrating SCL design models which, so far, have been purely analytical. The maximum recorded changes in tangential strains were 820 με in hoop compression and 567 με in longitudinal tension. The strain profiles indicate that the area of tunnel lining affected to any significant amount by the cross-passage excavation, is considerably smaller than the extent of the thickening SCL.
The authors would like to acknowledge funding from the UK Engineering and Physical Sciences Research Council (EPSRC) and Innovate UK, under EPSRC grant no. EP/I019308/1, under which this research was carried out.
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