Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)

Optimization of Spline Slip Surfaces Using Metaheuristic Search in LEM

Authors
Terence Ma1, *, Brigid Cami1, Sina Javankhoshdel1, Brent Corkum1, Thamer Yacoub1
1Rocscience, 54 St. Patrick St, Toronto, ON, M5T 1V1, Canada
*Corresponding author. Email: terence.ma@rocscience.com
Corresponding Author
Terence Ma
Available Online 1 March 2023.
DOI
10.2991/978-94-6463-104-3_13How to use a DOI?
Keywords
Optimization; Slip Surface; Slope Stability; Limit Equilibrium; Critical; Spline; Searching
Abstract

The search for the critical slip surface on a slope is an optimization problem whereby the factor of safety is minimized over a set of parameters which define the shape of the slip surface. In limit equilibrium slope stability analysis, traditional methods for searching for the critical slip surface include grid search and auto-refine search. More recently, metaheuristic optimization methods such as Particle Swarm and Cuckoo Search, among other variations, have been used to search for critical slip surfaces. These simulate natural processes that search the solution space for a minimum solution for various optimization problems encountered in a vast range of disciplines. Typically, the parameters of spheres or ellipsoids which cut the ground topography are varied to create different slip surfaces. The parameters of cutting planes and wedges can also be varied to create multi-planar slip surfaces using the same metaheuristic techniques. However, critical slip surfaces are not always spherical, ellipsoidal, or planar in nature. This paper introduces a novel method which employs the use of three-dimensional spline surfaces in a metaheuristic search to find the critical slip surface in a slope. By varying the parameters which define the location, size and curvature of the spline, the critical slip surface can be found. The proposed formulation of parameters is shown to perform better than the parameters which define the preceding shapes due to the superior flexibility of a spline surface in its curvature.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

Volume Title
Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)
Series
Atlantis Highlights in Engineering
Publication Date
1 March 2023
ISBN
978-94-6463-104-3
ISSN
2589-4943
DOI
10.2991/978-94-6463-104-3_13How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Terence Ma
AU  - Brigid Cami
AU  - Sina Javankhoshdel
AU  - Brent Corkum
AU  - Thamer Yacoub
PY  - 2023
DA  - 2023/03/01
TI  - Optimization of Spline Slip Surfaces Using Metaheuristic Search in LEM
BT  - Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)
PB  - Atlantis Press
SP  - 130
EP  - 139
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-104-3_13
DO  - 10.2991/978-94-6463-104-3_13
ID  - Ma2023
ER  -