Abstract
It is well recognized that the axial pipe-soil shear friction is an essential controlling parameterin the prediction of subsea on-bottom pipeline behaviour. This PhD thesis presents the design,
assembly and application of a novel large-scale shear test apparatus to address some of the
challenges and uncertainties identified in the previous research on subsea pipeline design and
characterization of pipe-soil shear friction at low normal stress conditions. A series of largescale axial pipe-soil shear tests at low vertical load levels are conducted on this novel apparatus
on granular soil beds with a wide range of particle sizes from fine sands to cobbles. Influence
of main testing variables including the vertical loads, particle sizes, pipe surface roughness,
soil bed profile features and actual pipe-soil contact point numbers has been carefully
investigated. Additionally, the effects of pipe surface curvature and pipe embedment on overall
axial shear friction are estimated through the comparison with elements-scale planar interface
shear tests. The database of axial pipe-soil shear frictions on sands and coarser granular rocks
are integrated with the combined effect of local shear behaviour at each pipe-soil particle
contact and the total pipe-soil particle contact numbers, based on a specific analysis on the
actual pipe-soil contact conditions regarding to different soil bed profiles. Finally, a simplified
1D numerical model is proposed to predict the overall friction-displacement responses in axial
pipe-soil interaction with the element-scale test data, which is calibrated and validated by the
comparison with the large-scale test data in this study. The research presented in this thesis is
expected to reduce the uncertainties in subsea pipeline design by expanding the currently
limited database for pipe-soil shear friction and to deepen the understanding of the shear
behaviours at different scales
| Date of Award | 3 Oct 2023 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Supervisor | Andrea Diambra (Supervisor), Matt S Dietz (Supervisor) & George Mylonakis (Supervisor) |