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System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines

Subhadeep Metya, Tanmoy Mukhopadhyay, Sondipon Adhikari Orcid Logo, Gautam Bhattacharya

Computers and Geotechnics, Volume: 87, Pages: 212 - 228

Swansea University Author: Sondipon Adhikari Orcid Logo

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DOI (Published version): 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...

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Published in: Computers and Geotechnics
ISSN: 0266-352X
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa32324
first_indexed 2017-03-08T13:51:48Z
last_indexed 2018-02-09T05:20:08Z
id cronfa32324
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spelling 2017-03-08T09:16:43.1800231 v2 32324 2017-03-08 System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines 4ea84d67c4e414f5ccbd7593a40f04d3 0000-0003-4181-3457 Sondipon Adhikari Sondipon Adhikari true false 2017-03-08 ACEM 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. Journal Article Computers and Geotechnics 87 212 228 0266-352X Slope stability; General slip surface; System reliability analysis; Multivariate adaptive regression splines; Monte Carlo simulation; Noise 31 12 2017 2017-12-31 10.1016/j.compgeo.2017.02.017 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2017-03-08T09:16:43.1800231 2017-03-08T09:15:50.7475022 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Subhadeep Metya 1 Tanmoy Mukhopadhyay 2 Sondipon Adhikari 0000-0003-4181-3457 3 Gautam Bhattacharya 4
title System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
spellingShingle System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
Sondipon Adhikari
title_short System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
title_full System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
title_fullStr System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
title_full_unstemmed System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
title_sort System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines
author_id_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3
author_id_fullname_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3_***_Sondipon Adhikari
author Sondipon Adhikari
author2 Subhadeep Metya
Tanmoy Mukhopadhyay
Sondipon Adhikari
Gautam Bhattacharya
format Journal article
container_title Computers and Geotechnics
container_volume 87
container_start_page 212
publishDate 2017
institution Swansea University
issn 0266-352X
doi_str_mv 10.1016/j.compgeo.2017.02.017
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 0
active_str 0
description 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.
published_date 2017-12-31T19:09:14Z
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score 11.048453

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