Results 111 to 120 of about 39,650 (263)

Mechanistic insights across curing regimes for enzymatic and biopolymer‐optimized reinforcement in rock masses

Deep Underground Science and Engineering, EarlyView.
This study examines the effects of curing temperature on the mechanical behavior of underground rock masses treated with enzyme‐induced calcite precipitation (EICP) and an innovative biopolymer‐modified EICP (BP‐EICP). Abstract Biocementation is an innovative and sustainable technique for reinforcing weak and weathered rock masses in natural and ...
Mary C. Ngoma, Oladoyin Kolawole
wiley   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

PSO-Optimized Ensemble Learning with SHAP for Seasonal Groundwater Quality Prediction. [PDF]

Ground Water
Selmane T, Hasnaoui Y, Aloui N, Lachehab S, Seraiche L, Dougha M.   +5 more
europepmc   +1 more source

Thermal‐induced fracture evolution and acoustic signature of Beishan granite: Insights into tensile strength of barrier system for high‐level radioactive waste disposal

Deep Underground Science and Engineering, EarlyView.
The tensile strength of granite, a proposed host for nuclear waste, degrades severely above 400°C. We link this to specific microcracking patterns captured by acoustic emission, establishing a scientific basis for assessing repository safety under thermal load.
Wei Zeng, Shijie Li, Xiaozhao Li, Zhen Huang, Shangtong Yang, Wentao Xu, Biao Wang, Yun Wu   +7 more
wiley   +1 more source

Microplastics as Emerging Cotracers in Groundwater Quality Assessments. [PDF]

ACS ES T Water
Zambelli B, Pemberton E, Viaroli S, Krause S, Giannecchini R, Re V.   +5 more
europepmc   +1 more source

Upper bound limit analysis of coral reef limestone cavern roof stability incorporating a tension‐shear failure mechanism with tensile‐strength cut‐off

Deep Underground Science and Engineering, EarlyView.
For the roof of coral reef limestone caverns, a novel tension‐shear composite failure mechanism was developed. The most critical tensile crack model was identified using a hybrid optimization algorithm, and the stability of the cavern roof was analyzed accordingly.
Dongsheng Xu, Chenxu Li, Chuantan Hou
wiley   +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

Assessment of Groundwater Quality Using the Water Quality Index (WQI) in Woreillu Town, Ethiopia. [PDF]

Int J Anal Chem
Asfaw MD.
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