A random forest model for the prediction of spudcan penetration resistance in stiff-over-soft clays

• Autorzy: Gao Pan , Liu Zhihui , Zeng Ji , Zhan Yiting , Wang Fei

Identyfikatory

DOI

10.2478/pomr-2020-0073

• Języki publikacji: EN

Abstrakty

EN

Punch-through is a major threat to the jack-up unit, especially at well sites with layered stiff-over-soft clays. A model is proposed to predict the spudcan penetration resistance in stiff-over-soft clays, based on the random forest (RF) method. The RF model was trained and tested with numerical simulation results obtained through the Finite Element model, implemented with the Coupled Eulerian Lagrangian (CEL) approach. With the proposed CEL model, the effects of the stiff layer thickness, undrained shear strength ratio, and the undrained shear strength of the soft layer on the bearing characteristics, as well as the soil failure mechanism, were numerically studied. A simplified resistance profile model of penetration in stiff-over-soft clays is proposed, divided into three sections by the peak point and the transition point. The importance of soil parameters to the penetration resistance was analysed. Then, the trained RF model was tested against the test set, showing a good prediction of the numerical cases. Finally, the trained RF was validated against centrifuge tests. The RF model successfully captured the punch-through potential, and was verified using data recorded in the field, showing advantages over the SNAME guideline. It is supposed that the trained RF model should give a good prediction of the spudcan penetration resistance profile, especially if trained with more field data.

Słowa kluczowe

EN

machine learning; random forest; jack-up; penetration resistance; stiff-over-soft clays

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2020
• Tom: nr 4
• Strony: 130--138
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Gao Pan

• College of Ocean Science and Engineering, Shanghai Maritime University, No. 1550, Haigang Avenue, 201306 Shanghai, China

autor

Liu Zhihui

• College of Ocean Science and Engineering, Shanghai Maritime University, No. 1550, Haigang Avenue, 201306 Shanghai, China

autor

Zeng Ji

• College of Ocean Science and Engineering, Shanghai Maritime University, No. 1550, Haigang Avenue, 201306 Shanghai, China

autor

Zhan Yiting

• College of Ocean Science and Engineering, Shanghai Maritime University, No. 1550, Haigang Avenue, 201306 Shanghai, China

autor

Wang Fei

• China Oilfield Services Limited, No. 201, Haiyou Avenue, 065201 Sanhe, China

Bibliografia

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• 4. Hossain M. S., Randolph M. F. (2010): Deep-penetrating spudcan foundations on layered clays: numerical analysis. Géotechnique, 60(3), 171-184. DOI: 10.1680/geot.8.P.040
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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).