Results 171 to 180 of about 9,754 (259)

Numerical simulation study on the characteristics and propagation attenuation of vibration signals in freezing pipe fracture

Deep Underground Science and Engineering, EarlyView.
This research study employs analysis system (ANSYS) fluid–structure interaction simulations to investigate the generation and attenuation of vibration signals resulting from freezing pipe fractures in artificial ground freezing projects. By evaluating key variables—including frozen soil elastic modulus, brine inlet pressure, and external pipe pressure ...
Yi Cao, Yansen Wang, En Chen, Meng Zhao
wiley   +1 more source

Domain-Adversarial Neural Network for UWB NLOS Identification in Multiple Environments. [PDF]

Sensors (Basel)
Jiang S, Li J, Xu Y, Rong Y.
europepmc   +1 more source

Investigation on tunnel stability considering pipe‐roof support with transparent soil technology

Deep Underground Science and Engineering, EarlyView.
This study integrates transparent soil technology, 3D reconstruction and numerical simulation to captures the full‐field deformation of shield tunnel instability. Results demonstrate that pipe‐roof support enhances stability via the “soil‐arching barrier effect,” effectively restraining failure wedge development by extending stress transfer paths ...
Zhi Jia, Yunpeng Ji, Zhao Lu, Honghua Zhao, Limin Zhang   +4 more
wiley   +1 more source

Study on Underground Sewage Pipeline Temperature Based on OFDR Technology and Numerical Simulation Methods. [PDF]

Sensors (Basel)
Gao L, Wu X, Zheng Z, Guo M.
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

Exploring oceanic depths: unveiling hidden treasures with IoT and ensembled deep hybrid learning model. [PDF]

Sci Rep
Tada S, Jeevanantham V.
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

Metabolic potential of newly isolated bacterial species from the deep subsurface of the Iberian Pyrite Belt. [PDF]

Front Microbiol
Martínez-Bonilla A, Mateos G, Carrillo-Bautista M, Arranz D, Amils R, Escudero C.   +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

A Bio-Inspired Lightweight Human Action Recognition Method Based on Human Keypoint Detection. [PDF]

Biomimetics (Basel)
Huang W, Wu M, Chen W, Zhou Q.
europepmc   +1 more source