Sequential probabilistic back analyses of spatially varying soil parameters and slope reliability prediction under rainfall

M Pan, SH Jiang, X Liu, GQ Song, J Huang - Engineering Geology, 2024 - Elsevier
Accurately predicting slope reliability under a rainfall/rainstorm event is an important
prerequisite for preventing rainfall-induced landslide hazards. However, the predicted …

[HTML][HTML] Ensemble learning of soil–water characteristic curve for unsaturated seepage using physics-informed neural networks

HQ Yang, C Shi, L Zhang - Soils and Foundations, 2025 - Elsevier
The determination of the soil–water characteristic curve (SWCC) is crucial for hydro-
mechanical modelling and analysis of soil slopes. Conventional inverse analysis often relies …

A Digital Twin System for Rock Triaxial Mechanical Tests Incorporating Probabilistic Parameter Updates and Model Prediction Through Data Assimilation Technique

C Lyu, W Xu, H Wang, Y Wu, H Wang - Rock Mechanics and Rock …, 2025 - Springer
The rock digital twin is a virtual system that continuously learns real-time observations of the
physical entity, allowing for the dynamic updating of the mechanical parameters in the …

BACK ANALYSIS OF RAINFALL-INDUCED WASTE DUMP FAILURE USING COUPLED HYDRO-MECHANICAL ANALYSIS–A CASE STUDY IN COAL MINE

B Dwinagara, WN Akbar, S Saptono… - GEOMATE …, 2024 - geomatejournal.com
Managing the waste dumps has become a significant challenge, along with increasing
mining production. Maintaining waste dump stability is vital to prevent failures that could …