[HTML][HTML] DFN: an emerging tool for stochastic modelling and geomechanical design

P Kolapo, NO Ogunsola, P Munemo, D Alewi… - Eng, 2023 - mdpi.com
The discrete fracture networks (DFN) have become indispensable tools for geomechanical
modelling of jointed rock masses. The technology creates a three-dimensional (3D) …

[HTML][HTML] Advances in statistical mechanics of rock masses and its engineering applications

F Wu, J Wu, H Bao, B Li, Z Shan, D Kong - Journal of Rock Mechanics and …, 2021 - Elsevier
To efficiently link the continuum mechanics for rocks with the structural statistics of rock
masses, a theoretical and methodological system called the statistical mechanics of rock …

Determination of statistical discontinuity persistence for a rock mass characterized by non-persistent fractures

W Zhang, Z Lan, Z Ma, C Tan, J Que, F Wang… - International Journal of …, 2020 - Elsevier
The discontinuity persistence is an important parameter that affects the strength of rock
masses and stability in rock engineering. However, determining the 3D discontinuity …

[HTML][HTML] Automated classification analysis of geological structures based on images data and deep learning model

Y Zhang, G Wang, M Li, S Han - Applied Sciences, 2018 - mdpi.com
Featured Application This work aims to build a robust model with a comparison of machine
learning, convolutional neural network and transfer learning. The model can be combined …

A precise modeling method of three‐dimensional discrete fracture network based on rectangular joint model

J Kang, X Fu, Q Sheng, J Chen, K Wu… - … Journal for Numerical …, 2024 - Wiley Online Library
As the weak structure and main seepage channel of rock mass, the discrete fracture network
(DFN) has a significant influence on the physical and mechanical properties of rock mass. In …

Copula-based simulating and analyzing methods of rock mass fractures

S Han, M Li, G Wang - Computers and Geotechnics, 2020 - Elsevier
The uncertainty analysis of fractures is always an important task in studying the structures of
rock masses. Traditional univariate and bivariate statistical methods have limitations for …

Deep learning–based stochastic modelling and uncertainty analysis of fault networks

S Han, H Li, M Li, J Zhang, R Guo, J Ma… - Bulletin of Engineering …, 2022 - Springer
Limited by the survey data and current interpretation methods, the modelling processes of
fault networks are fraught with uncertainties. In hydraulic geological engineering, the …

[HTML][HTML] Grouting process simulation based on 3D fracture network considering fluid–structure interaction

Y Zhu, X Wang, S Deng, W Chen, Z Shi, L Xue, M Lv - Applied Sciences, 2019 - mdpi.com
Grouting has always been the main engineering measure of ground improvement and
foundation remediation of hydraulic structures. Due to complex geological conditions and …

Two-dimensional discrepancies in fracture geometric factors and connectivity between field-collected and stochastically modeled DFNs: a case study of sluice …

W Zhang, R Fu, C Tan, Z Ma, Y Zhang, S Song… - Rock Mechanics and …, 2020 - Springer
This study takes sluice foundation rock mass in Datengxia Hydropower Station, China as an
example to examine two-dimensional (2D) discrepancies in fracture geometric factors and …

An Analysis of Trace Information of Different-shaped Fracture Networks Having a Same Fracture Intensity (P32)

J Guo, J Zheng, Q Lü, Z Xiao, T Liu - KSCE Journal of Civil Engineering, 2022 - Springer
Discrete fracture network (DFN) simulation is the basis of studying the properties of a rock
mass. An important premise of constructing three-dimensional (3-D) DFNs is to ensure that …