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Showing 7 of 7 academic articles

Characterizing particle crushing behavior of dry granular soils by acoustic emission

Wenli Lin, Shuyu Tian, Deqi He, Xiao Kang et al. • Journal of Rock Mechanics and Geotechnical Engineering (2026)

This study investigates particle crushing mechanisms in granular soils during shearing through staged triaxial compression experiments performed at prescribed axial strains and varying confining stresses, integrating a high-performance acou...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrmge.2025.07.039

Accuracy Analysis of Convergence Monitoring in Twin-tube Shield Tunnels Using Mobile Laser Scanning

WANG Xinhong, XIA Caichu, HU Guojin, WU Ting et al. • Chengshi guidao jiaotong yanjiu (2025)

[Objective] Mobile 3D laser scanning technology is widely applied in single-tube tunnel monitoring due to its excellent measurement efficiency and high accuracy. However, the application of this technology for deformation monitoring in twin...

DOAJ Open Access (DOAJ) DOI: 10.16037/j.1007-869x.20230782

Creep behaviors and constitutive model of transversely isotropic rocks

WANG Zhe-chao 1, 2, ZONG Zhi 1, QIAO Li-ping 1, 2, LI Wei1, LIU Jie 1 • Yantu gongcheng xuebao (2018)

The bedded carbonaceous slate exhibits transversely isotropic creep properties. The creep behaviors of carbonaceous slate are studied using the triaxial compressive creep tests on horizontal bedding specimens and vertical bedding specimens....

DOAJ Open Access (DOAJ) DOI: 10.11779/CJGE201807008

Physical model test study on shear strength characteristics of slope sliding surface in Nanfen open-pit mine

Zhigang Tao, Yu Shu, Xiaojie Yang, Yanyan Peng et al. • International Journal of Mining Science and Technology (2020)

A physical model for the footwall slope of Nanfen open-pit mine, China was established using a self-developed deep geological engineering disaster model test system. A thermosensitive similar material, paraffin, was selected to simulate a w...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ijmst.2020.05.006

Machine learning and data-driven prediction of pore pressure from geophysical logs: A case study for the Mangahewa gas field, New Zealand

Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering (2022)

Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrmge.2022.01.012

Bayesian machine learning-based method for prediction of slope failure time

Jie Zhang, Zipeng Wang, Jinzheng Hu, Shihao Xiao et al. • Journal of Rock Mechanics and Geotechnical Engineering (2022)

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomen...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrmge.2021.09.010