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Quantifying installation risk during spudcan penetration.
- Source :
-
Ocean Engineering . Nov2020, Vol. 216, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- Installation of a mobile jack-up rigs with spudcan foundations are sometimes challenge due to uncertain offshore environments. Prediction of penetration resistance during installation is often necessary to avoid hazards such as punch-through failure. When the field monitored data deviates with these predictions, engineers have to decide how severe this deviation is based on their experience. This paper provides a method that can quantify the installation risk by a set of percentile curves of penetration resistance against depth. The percentile curves can be quantified through combining a random large deformation finite element method with Monte-Carlo simulation. The spatial variability in seabed soils can be considered and the penetration resistance curves through the random soils can be obtained. This model was verified by a spudcan installation penetration into deeper seabed. Finally, four field cases in North-East Brazil and Gulf of Mexico are investigated. Results show that the installation risk during spudcan installation can be estimated by comparing the measured preloading and penetration depth values with the percentile curves, which indicates the proposed method is capable to help decision making during spudcan installation. • This paper provides a set of percentile curves to quantify the installation risk of spudcan foundation in random soils. • The percentile curves are quantified through combining RLDFE method with Monte-Carlo simulation. • Four field cases are investigated and the results indicate the proposed method can help decision making of the engineer. [ABSTRACT FROM AUTHOR]
- Subjects :
- *R-curves
*FINITE element method
*DECISION making
*FORECASTING
Subjects
Details
- Language :
- English
- ISSN :
- 00298018
- Volume :
- 216
- Database :
- Academic Search Index
- Journal :
- Ocean Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 147485800
- Full Text :
- https://doi.org/10.1016/j.oceaneng.2020.108050