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Title: Soil parameters for modelling critical velocity effects of railways
Author: Duley, Alice
ISNI:       0000 0004 7972 0982
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2018
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In many countries high speed rail is playing a growing role in improving the capacity, availability and carbon cost of national infrastructure. Higher speeds require straighter railway alignments, which often means crossing areas of soft ground that have historically been avoided. Due to their low ground-borne surface wave speeds, there is a greater likelihood in such areas of the train passage resulting in critical velocity effects - a phenomenon in which excessive ground and track movement and vibration occurs. This can cause extensive damage, and may result in a forced reduction of train speeds. The aim of this research is to assess methods of determining appropriate soil parameters for use in simple elasticity-based models for the prediction of critical velocity effects on railways. After a review of existing knowledge, the research consists of field measurements, laboratory experiments and modelling. This research focuses around two case study sites on the UK rail network. Soil samples were extracted from each site, and tested in resonant column and triaxial equipment, to investigate their strain-dependent stiffness and damping. This involved testing on soil types for which there is little published data, including highly organic silts. The results are compared with measurements taken in situ, including seismic analysis and heavy probe tests. A linear elastic model, MOTIV, of train-induced vibration is used to investigate the key soil and model parameters required for critical velocity analysis, as well as to assess the importance of the non-linearity of soil stiffness and damping with strain. It is clear that the use of strain-degraded soil parameters, for example through the use of an equivalent linear model, is essential. Recommendations are made for the best methods to obtain the relevant data, from which reliable critical velocity predictions can be made using linear soil models.
Supervisor: Le Pen, Louis Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available