Results 181 to 190 of about 84,349 (231)

Numerical source data for OsSTP13-mediated blast resistance and yield-related traits in rice

GUI XIAO
openalex   +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

Dynamic response at the terminus of oblique intersecting joints subjected to stress waves

Deep Underground Science and Engineering, EarlyView.
This study derives the propagation equation for stress waves impinging upon nonlinear oblique intersecting joints. It analyzes the dynamic response at the terminus of nonlinear oblique intersecting joints subjected to stress waves. Abstract To investigate the dynamic response at the terminus of oblique intersecting joints subjected to stress waves, a ...
Gang Hu, Xiang Chen, Honglu Fei, Shijie Bao, Jian Guo   +4 more
wiley   +1 more source

Carbon emission assessment of tunnel infrastructures: From construction to operation

Deep Underground Science and Engineering, EarlyView.
This study develops a lifecycle carbon accounting framework for tunnel infrastructures, covering design, construction, operation, maintenance, and dismantling. Applied to a subsea tunnel case, the framework reveals the carbon emission distribution among four typical tunnel types and highlights potential carbon offset methods for low‐carbon tunnel ...
Luyuan Long, Wout Broere, Xuehui Zhang, Tian Xia, Richard de Nijs   +4 more
wiley   +1 more source

Pre-blast joint descriptors and median fragment size: analysis data and validation outputs

yh c
openalex   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +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

Diagnosis of Rice Blast Disease Using UAV-Based Multispectral Data: A Comparative Study of Feature Selection Methods

Yonghao Wu, Shaozhong Song, Bingxue Zhu, Kaishan Song   +3 more
openalex   +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

Developing a universal tunnel span classification from global tunnel databases

Deep Underground Science and Engineering, EarlyView.
A universal tunnel span classification system is introduced that incorporates tunnel span, cross‐sectional area, typical tunnel types, and intended uses. Representative flatness ratio values are also provided for each span class. The classification is derived from a comprehensive database of 450 tunnel profiles from 47 countries.
Simon Heru Prassetyo, Inzagi Suhendar, Semmy Andrew Anugerah Djawa Tagi, Bonifacio Bondan Satryojati, Dzakwan Naufal Pratama, Yeremia Sintong Damero, Yudhidya Wicaksana, Erwin Lim, Ridho Kresna Wattimena   +8 more
wiley   +1 more source