Development of a universal landslide hazard potential model for mudrock slopes: fuzzy logic and molecular-level modelling approaches

Habib ur-Rehman (), Sahel N. Abduljauwad () and Muhammad Naeemuddin ()
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Habib ur-Rehman: National University of Computer and Emerging Sciences (NUCES)
Sahel N. Abduljauwad: King Fahd University of Petroleum and Minerals (KFUPM)
Muhammad Naeemuddin: GeoCrust

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 116, issue 3, No 34, 3583-3615

Abstract: Abstract The reduction in shear strength due to moisture-induced swelling and the subsequent slaking of mudrocks is one of the leading causes of landslide hazards in mountainous regions. In practice, empirical/semiempirical approaches that have been adopted to identify this hazard are mostly based on macrolevel factors. However, those do not comprehensively consider the microlevel factors that contribute to the complex swelling/slaking process. Therefore, this study developed a comprehensive fuzzy logic-based model, which includes both the macrolevel landslide contributing factors and the microlevel factors, such as mineralogy, cementation, cation exchange capacity, in situ moisture content, density, and stress state. The model was developed from molecular simulations of swelling, and the subsequent slaking processes were identified using Monte Carlo simulations, molecular mechanics, and molecular dynamics. The results of the microlevel model are incorporated into the fuzzy logic model to create a universal landslide hazard potential model for mudrock slopes. The microlevel behaviour is incorporated in the coupled model via the cohesive energy density parameter for the mudrocks. The final coupled model was verified via the accurate prediction of the landslides and by comparing the predicted terminal water content with the water content of the mudrock samples collected from the actual landslides.

Keywords: Landslide hazard potential; Mudrocks; Molecular-level simulations; Fuzzy logic (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-05826-0

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