System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
A data driven multivariate adaptive regression splines (MARS) based algorithm for system reliability analysis of earth slopes having random soil properties under the framework of limit equilibrium method of slices is considered. The theoretical formulation is developed based on Spencer method (valid for general slip surfaces) satisfying all conditions of static equilibrium coupled with a nonlinear programming technique of optimization. Simulated noise is used to take account of inevitable modeling inaccuracies and epistemic uncertainties. The proposed MARS based algorithm is capable of achieving high level of computational efficiency in the system reliability analysis without significantly compromising the accuracy of results.
General slip surface, Monte Carlo simulation, Multivariate adaptive regression splines, Noise, Slope stability, System reliability analysis
212-228
Metya, Subhadeep
11a54110-0395-4f7d-a574-de9305607418
Mukhopadhyay, Tanmoy
2ae18ab0-7477-40ac-ae22-76face7be475
Adhikari, Sondipon
12cf62cf-340a-4da6-9ad4-f4dd64384a73
Bhattacharya, Gautam
baa482a0-852f-41bd-a300-29b91bd91b5e
1 July 2017
Metya, Subhadeep
11a54110-0395-4f7d-a574-de9305607418
Mukhopadhyay, Tanmoy
2ae18ab0-7477-40ac-ae22-76face7be475
Adhikari, Sondipon
12cf62cf-340a-4da6-9ad4-f4dd64384a73
Bhattacharya, Gautam
baa482a0-852f-41bd-a300-29b91bd91b5e
Metya, Subhadeep, Mukhopadhyay, Tanmoy, Adhikari, Sondipon and Bhattacharya, Gautam
(2017)
System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines.
Computers and Geotechnics, 87, .
(doi:10.1016/j.compgeo.2017.02.017).
Abstract
A data driven multivariate adaptive regression splines (MARS) based algorithm for system reliability analysis of earth slopes having random soil properties under the framework of limit equilibrium method of slices is considered. The theoretical formulation is developed based on Spencer method (valid for general slip surfaces) satisfying all conditions of static equilibrium coupled with a nonlinear programming technique of optimization. Simulated noise is used to take account of inevitable modeling inaccuracies and epistemic uncertainties. The proposed MARS based algorithm is capable of achieving high level of computational efficiency in the system reliability analysis without significantly compromising the accuracy of results.
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Published date: 1 July 2017
Additional Information:
Funding Information:
This research has been supported by the Newton-Bhabha PhD Placement Grant 2015-16 jointly funded by the British Council (United Kingdom) and the Department of Science and Technology (DST), Govt. of India for a collaborative research project at the Zienkiewicz Centre for Computational Engineering (ZCCE), Swansea University, UK. This support is gratefully acknowledged. TM acknowledges the financial support from the Swansea University through the award of Zienkiewicz Scholarship during the period of this work. SA acknowledges the financial support from the Royal Society of London through the Wolfson Research Merit award.
Publisher Copyright:
© 2017 Elsevier Ltd
Keywords:
General slip surface, Monte Carlo simulation, Multivariate adaptive regression splines, Noise, Slope stability, System reliability analysis
Identifiers
Local EPrints ID: 483549
URI: http://eprints.soton.ac.uk/id/eprint/483549
ISSN: 0266-352X
PURE UUID: 58aa2687-0ab4-49b3-af3e-85a07f1c179f
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Date deposited: 01 Nov 2023 17:59
Last modified: 18 Mar 2024 04:10
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Contributors
Author:
Subhadeep Metya
Author:
Tanmoy Mukhopadhyay
Author:
Sondipon Adhikari
Author:
Gautam Bhattacharya
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