基于NSGA⁃II遗传算法的黄土滑坡参数反分析与稳定性预测

曾鹏; 王宇豪; 张天龙; 张琳; 南骁聪

doi:10.3799/dqkx.2023.034

Volume 48 Issue 5

May 2023

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Article Navigation > Earth Science > 2023 > 48(5): 1675-1685

Zeng Peng, Wang Yuhao, Zhang Tianlong, Zhang Lin, Nan Xiaocong, 2023. Parameter Back Analysis and Stability Prediction of Loess Landslide Based on NSGA-II Genetic Algorithm. Earth Science, 48(5): 1675-1685. doi: 10.3799/dqkx.2023.034

Citation:

Zeng Peng, Wang Yuhao, Zhang Tianlong, Zhang Lin, Nan Xiaocong, 2023. Parameter Back Analysis and Stability Prediction of Loess Landslide Based on NSGA-II Genetic Algorithm. Earth Science, 48(5): 1675-1685. doi: 10.3799/dqkx.2023.034

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Parameter Back Analysis and Stability Prediction of Loess Landslide Based on NSGA-II Genetic Algorithm

doi: 10.3799/dqkx.2023.034

Zeng Peng^{1, 2
,
,},
Wang Yuhao^{1, 2, 4},
Zhang Tianlong³,
Zhang Lin^{1, 2},
Nan Xiaocong⁵

1.
College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu 610059, China
2.
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
3.
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
4.
Sichuan Chuanjian Survey and Design Institute Co. Ltd., Chengdu 610094, China
5.
Shandong High-Speed Engineering Detection Co. Ltd., Jinan 250002, China

Received Date: 2022-10-10
Available Online: 2023-06-06
Publish Date: 2023-05-25

Abstract

Abstract

Many loess landslides were caused by the agricultural irrigation in Heifangtai terrace, Yongjing County, Gansu Province. Their stability analysis and critical slip surface identification are particularly important, as it can provide a good support to disaster prevention. The loess landslides located on the margin of Heifangtai terrace have the characteristics of progressive backward failure, and the occurred and potential landslides are highly similar. The results from back analysis can provide important data basis for future landslide stability prediction. In this paper, the finite difference strength reduction method was used to calibrate the cohesion and internal friction angle of loess based on the NSGA-II genetic algorithm by setting three objective optimization functions (i.e., mean value of soil strength parameters, slip surface and factor of safety). Taking Dangchuan 2^# landslide in Heifangtai terrace as a study case, based on the slip surface observed after the first slide and assuming its factor of safety was equal to 1, the back analysis results show that the cohesion and internal friction angle of natural loess were 28.20 kPa and 25.16°; and the effective cohesion and internal friction angle of saturated loess were 16.59 kPa and 16.11°. Based on the computed results, the factor of safety and critical slip surface of the three subsequent slides were predicted, with their comparison with in-site observation information. The results show that a more reasonable estimation of loess strength parameters can be obtained by using the multi-objective constraint optimization algorithm, which provides a new solution for the stability analysis and quantitative risk assessment of landslides in Heifangtai terrace.
- loess landslide,
- stability back analysis,
- multi-objective optimization,
- genetic algorithm,
- slip surface identification,
- hazard geology

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References(67)

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Parameter Back Analysis and Stability Prediction of Loess Landslide Based on NSGA-II Genetic Algorithm

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