Three-dimensional analysis of tunnelling effects on structures to develop design methods
The subject of this thesis is the verification of a three-dimensional numerical modelling approach for the prediction of settlement damage to masonry buildings due to tunnelling in soft ground. The modelling approach was developed by previous researchers at Oxford, and was applied to three sites, representative of a range of practical configurations. The first involved the excavation of a shaft close to the corner of an eighteenth century church in London. The second involved tunnelling with very low cover beneath the foundations of a terrace of cottages at Ramsgate, Kent. The third was the relatively well-known case of tunnelling beneath the Mansion House, London, for construction of the extension to the Docklands Light Railway in the late 1980’s. The overall conclusion of the project is that the modelling procedures are suitable for application to the detailed assessment of the response of buildings to tunnelling. Particular features of the procedures are that the building is modelled together with the ground and a representation of the tunnel excavation, and in three dimensions. It has been confirmed that all these features are necessary to model the building response, which may include a combination of shear deformation, arching and bending behaviour. Further lessons have been learned concerning the importance of the self-weight of the building in determining overall settlements, how to model openings such as doors and windows in façades, and whether it is necessary to model the building foundation. It has not proved possible, through lack of time, to model the advance of tunnels beneath buildings within this thesis. This, however, is observed to be an important effect in the field, particularly in causing damage to internal walls. It is recommended that further research be carried out in this area. This project made use of large-scale non-linear finite element analysis. The demand on computing resources was high, stimulating many enhancements to the software, the most important of which was parallelisation of the analysis program for use on the Oxford Supercomputer. To obtain optimum results, larger model sizes are required. The computing resources to enable this should become more commonly available within the next few years, enabling the modelling techniques to be used routinely.