Toggle Main Menu Toggle Search

Open Access padlockePrints

Probabilistic capacity analysis of suction caissons in spatially variable clay

Lookup NU author(s): Dr Tom CharltonORCiD, Dr Mohamed Rouainia

Downloads


Licence

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

Suction caissons are increasingly used in offshore energy production to moor floating facilities in deepwater. The holding capacity of a suction caisson is dependent on the angle of the mooring line and is oftendescribed in terms of a vertical-horizontal (VH) load interaction diagram, or failure envelope. Theseenvelopes have commonly been defined by numerical methods using deterministic soil parameters,ignoring the natural spatial variability of seabed sediments. In this paper, spatial variability is modelledusing a random field and coupled with finite element analysis to obtain a probabilistic characterisation ofholding capacity. The increase of strength with depth that is characteristic of a marine clay is taken intoaccount. A non-parametric approach using kernel density estimation is presented for constructing probabilistic VH failure envelopes that allow an appropriate envelope, associated with an acceptable level ofrisk, to be selected for design. A study of the autocorrelation distance, a quantity often difficult to obtainaccurately in practice, has shown that the vertical autocorrelation distance has a much greater influenceon the variability of holding capacity than the horizontal and should be carefully chosen in offshore.applications


Publication metadata

Author(s): Charlton TS, Rouainia M

Publication type: Article

Publication status: Published

Journal: Computers and Geotechnics

Year: 2016

Volume: 80

Pages: 226–236

Print publication date: 01/12/2016

Online publication date: 18/08/2016

Acceptance date: 02/06/2016

Date deposited: 26/09/2016

ISSN (print): 0266-352X

ISSN (electronic): 1873-7633

Publisher: Pergamon Press

URL: http://dx.doi.org/10.1016/j.compgeo.2016.06.001

DOI: 10.1016/j.compgeo.2016.06.001


Altmetrics

Altmetrics provided by Altmetric


Share