Results 181 to 190 of about 9,754 (259)

Investigation on the failure evolution characteristics of surrounding rock in deep cross‐fault roadway: Based on physical model test and numerical simulation

Deep Underground Science and Engineering, EarlyView.
This study reveals the failure evolution characteristics of deep cross‐fault roadway surrounding rock under excavation support and periodic weighting. Periodic weighting readily induces fault activation, with the spatial distribution of failed rock masses being controlled by the fault strike and dip.
Tiezhu Li, Suping Peng, Jing Zheng, Zhanhua Yang, Qijun Tian   +4 more
wiley   +1 more source

Creep Modeling and Influencing Factor Analysis of Ultradeep Salt Cavern Gas Storage. [PDF]

ACS Omega
Su Y, Shangguan S, Qi X, Zhao C, Song H, Zhang X, Li J, Wang X.   +7 more
europepmc   +1 more source

Combination of CO 2 ${\text{CO}}_{2}$ storage and geothermal energy production in porous and fractured superhot geothermal systems

Deep Underground Science and Engineering, EarlyView.
The graphical abstract depicts the workflow for porous‐ and fractured‐media simulations, where stochastically generated discrete natural fractures are required for the fracture‐media simulation. Abstract CO 2 ${\text{CO}}_{2}$ leakage is one of the main risks and barriers to geologic carbon storage. However, under the high‐temperature and high‐pressure
Christoph Scherounigg, Rotman Criollo, Victor Vilarrasa, Keita Yoshioka   +3 more
wiley   +1 more source

Experimental study on grouting diffusion mechanism of fractured rock. [PDF]

Sci Rep
Zhang C, Li D, Zhang X, Cong Y, Huang Y, Zhang H, Huang Y, Liu Q, Gao X.   +8 more
europepmc   +1 more source

Multi‐factor coupling effects in hydraulic fracturing of laminated shale: Experimental insights and physics‐informed neural network‐driven optimization

Deep Underground Science and Engineering, EarlyView.
This study establishes a multi‐factor coupling framework for predicting breakdown pressure in laminated shale by integrating experimental hydraulic fracturing tests, physics‐informed neural networks (PINNs), and Sobol sensitivity analysis. It reveals how differential stress, the bedding dip angle, and the injection rate interact to influence fracture ...
Tao Wang, Guoyao Xu, Liyuan Liu, Yao Zhang, Sitao Zhu, Hongyang Chu, Kaikai Zhao   +6 more
wiley   +1 more source

The Development and Performance Validation of a Real-Time Stress Extraction Device for Deep Mining-Induced Stress. [PDF]

Sensors (Basel)
Xi B, Shan P, Jiao B, Xu H, Meng Z, Yang K, Yan Z, Zhang L.   +7 more
europepmc   +1 more source

Integrated numerical simulation and source‐sink matching methodology for Basin‐Wide CO2 storage assessment in depleted reservoirs: A Cambay Basin case study

Deep Underground Science and Engineering, EarlyView.
This study presents an integrated workflow to evaluate secure and large‐scale CO2 storage in depleted oil reservoirs of the Cambay Basin, India. Industrial CO2 sources are systematically matched with mature oil fields using a quantitative source–sink framework to minimize transport distance and cost.
Bhaskarjyoti Khanikar
wiley   +1 more source

SADQN-Based Residual Energy-Aware Beamforming for LoRa-Enabled RF Energy Harvesting for Disaster-Tolerant Underground Mining Networks. [PDF]

Sensors (Basel)
Anabi HK, Frimpong S, Madria S.
europepmc   +1 more source

Mechanism of “seesaw‐type” rock burst in coal seam mining beneath mountainous areas

Deep Underground Science and Engineering, EarlyView.
This study reveals the mechanism of “seesaw‐type” rock bursts during coal mining beneath mountainous areas. The advancing working face induces nonuniform fracturing of the overburden. The detached mountain mass then undergoes a seesaw‐type rotational movement around a shifting pivot, driving the primary fracture through a characteristic “open‐close ...
Chao Zhou, Xueqiu He, Zhenlei Li, Ping Wang, Dazhao Song, Fuxing Jiang, Shan Yin, Anliang Lü, Menghan Wei, Taoping Zhong   +9 more
wiley   +1 more source

The recognition method of external force damage sources vibration signals based on LSTM-CNN-CatBoost-GSSSA. [PDF]

PLoS One
Chen X, Zhang L, Li X, Gao F.
europepmc   +1 more source