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A BP neural network-based micro particle parameters calibration and an energy criterion for the application of strength reduction method in MatDEM to evaluate 3D slope stability

Wei Jiang1, Yihong Tan2, Jinzhou Yan3, Ye Ouyang4, Zhaoyu Fu4, Qiang Feng4

1 Hubei Key Laboratory of Disaster Prevention and Mitigation, China Three Gorges University, Yichang, Hubei, 443002, China
2 Key Laboratory of Geological Hazards on Three Gorges Reservoir Area, Ministry of Education, Yichang, Hubei, 443002, China
3 Yichang Construction Investment & Development Co., Ltd., Yichang, Hubei, 443002, China
4 College of Civil Engineering & Architecture, China Three Gorges University, Yichang, Hubei, 443002, China

* Corresponding Authors: Wei Jiang (email), Yihong Tan (email), Jinzhou Yan (email), Ye Ouyang (email), Zhaoyu Fu (email), Qiang Feng (email)

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería 2023, 39(1), 1-14. https://doi.org/10.23967/j.rimni.2023.01.003

Abstract

To enhance the applicability of discrete element method in 3D slope stability analysis, a BP neural network-based micro parameter calibration method and an energy criterion are proposed by taking MatDEM as an example. Firstly, the relationship between the micro particle parameters and the shear strengths of particle aggregate are represented by using the BP neural network. And then the micro particle parameters are obtained for the given shear strengths by using a correction calibration. Next, the energy conversions are investigated for the stable and instable slope models in MatDEM. From a view of practical application, the abrupt in variation tendency and magnitude of the kinetic energy is selected for indicating the emergence of the limit equilibrium state of a slope. Finally, the effectiveness of the proposed improvements is testified by taking Baijiabao landslide as an example. Results verify that the calibration method established in this study is applicable to provide the micro particle parameters when the shear strength is constantly reduced, and the factor of safety determined by the kinetic energy criterion reflects the landslide stability at the global level.

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Cite This Article

APA Style
Jiang1, W., Tan2, Y., Yan3, J., Ouyang4, Y., Fu4, Z. et al. (2023). A BP neural network-based micro particle parameters calibration and an energy criterion for the application of strength reduction method in matdem to evaluate 3D slope stability. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, 39(1), 1-14. https://doi.org/10.23967/j.rimni.2023.01.003
Vancouver Style
Jiang1 W, Tan2 Y, Yan3 J, Ouyang4 Y, Fu4 Z, Feng4 Q. A BP neural network-based micro particle parameters calibration and an energy criterion for the application of strength reduction method in matdem to evaluate 3D slope stability. Rev int métodos numér cálc diseño ing. 2023;39(1):1-14 https://doi.org/10.23967/j.rimni.2023.01.003
IEEE Style
W. Jiang1, Y. Tan2, J. Yan3, Y. Ouyang4, Z. Fu4, and Q. Feng4 "A BP neural network-based micro particle parameters calibration and an energy criterion for the application of strength reduction method in MatDEM to evaluate 3D slope stability," Rev. int. métodos numér. cálc. diseño ing., vol. 39, no. 1, pp. 1-14. 2023. https://doi.org/10.23967/j.rimni.2023.01.003



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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