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Modelling screwpile installation using the MPM.

Wang, L. and Coombs, W.M. and Augarde, C.E. and Brown, M. and Knappett, J. and Brennan, A. and Richards, D. and Blake, A. (2017) 'Modelling screwpile installation using the MPM.', Procedia engineering., 175 . pp. 124-132.


Screwpiles are, as the name suggests, piled foundations which are screwed into the ground. They provide restraint to both upwards and downward loading directions and are commonly used for light structures subject to overturning or wind loading, such as sign gantries at the sides of motorways. An EPSRC-funded project led by University of Dundee has recently started, with Durham and Southampton as partners, in which the use of screwpiles (individual or in groups) for offshore foundations is under investigation. At Durham, a numerical modelling framework based on the material point method (MPM) is being developed for the installation phase of a screwpile. The aim is to use the model to provide an accurate representation of the in situ ground conditions once the pile is installed, as during installation the ground is disturbed and any model that “wishes in place” a screwpile may not provide representative long-term performance predictions. Following modelling of installation, the soil state will be transferred to a standard finite element package for the subsequent modelling of in-service performance (the MPM being considered unnecessary and computationally expensive for this phase of the life of a screwpile). In this preliminary work, we present the development of features of this numerical tool to simulate the screwpile installation. These features include a moving mesh concept (both translation and rotation) and interface elements. The effectiveness of the algorithm is illustrated through simple examples.

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Publisher statement:© 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (
Date accepted:05 December 2016
Date deposited:18 January 2017
Date of first online publication:27 February 2017
Date first made open access:No date available

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