Results 191 to 200 of about 7,010,769 (298)

Lightweight Graph Neural Network-Driven Acoustic Anomaly Detection Method for Gas Pipeline Leakage Levels in Underground Utility Tunnels. [PDF]

Sensors (Basel)
Sun W, Li Y, Yang J, Cheng Y.
europepmc   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

Study on the multi-source response characteristics and damage evolution mechanisms of graphene-modified concrete. [PDF]

Sci Rep
Fu Q, Tang M, Zhang X, Yang K, Yang C, Wei J, Guo P, Wang C, Qin R.   +8 more
europepmc   +1 more source

Rock mechanical properties under reconstructed deep in situ thermo–hydro–mechanical conditions: Implications for CO₂‐related injection scenarios

Deep Underground Science and Engineering, EarlyView.
The graphical abstract illustrates a reconstructed in situ thermo‐hydro‐mechanical (THM) framework in which porosity serves as the central variable linking stress, pore pressure, and temperature to evolving mechanical properties of rocks. Under burial conditions, in situ stress, pore pressure, and temperature jointly govern volumetric strain and ...
Mingyuan Lu, Jun Wang, Zixiong Qi, Ruixuan Chen, Hongtao Wang, Hongwei Zhou   +5 more
wiley   +1 more source

A Review of Instability Mechanisms and Control Technologies for Gas Drainage Boreholes in Soft Coal Seams in China. [PDF]

ACS Omega
Liu H, Chen X, Li J, Wang L, Yang Z, Yu J.   +5 more
europepmc   +1 more source

Explainable hybrid stacking ensemble method for hard rock pillar stability prediction and engineering applications

Deep Underground Science and Engineering, EarlyView.
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang, Guoyan Zhao, Meng Wang, Taraka Pattela   +3 more
wiley   +1 more source

Optimizing the Reliability of Underground Utility Tunnel Localization via Multi-Source Fusion and DVAE-CNN. [PDF]

Sensors (Basel)
Chang S, Zhang Z, Gug X, Zhai T, Liu S, Zhao Y, Guo T.   +6 more
europepmc   +1 more source

A comprehensive review on advancements and challenges of deep learning in tunnel and underground engineering

Discover Artificial Intelligence
Chunlei Zhang, Md Habibullah, Jingke Wu, Mahabub Hasan Sajib, Arifuggaman Arif, Mohammed Alip, Boyina Manohar, Golam Mostakim Shikhon, Mingjie Feng, Ye Zhang, Md Sohel Rana   +10 more
openaire   +1 more source

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

Interpretable Graph-Temporal-Spectral Fusion for Precursor-Related Anomaly Detection in Underground Mine Sensor Networks. [PDF]

Sensors (Basel)
Mao S, Liang Y, Li Q.
europepmc   +1 more source