Results 171 to 180 of about 144,184 (291)

A review on rockburst prediction and prevention to shape an ontology‐based framework for better decision‐making for underground excavations

Deep Underground Science and Engineering, EarlyView.
A scientometric analysis of 2449 journal articles and a comprehensive review of 336 papers were conducted, discussing and identifying challenges and research gaps in rockburst prediction and prevention and proposing an ontology‐based framework for better decision‐making in underground excavations. Abstract With underground engineering projects becoming
Hongchuan Yan, Haijiang Li, Hongqiang Xie, Mingli Xiao, Jianliang Pei, Huaizhong Liu, Jiangda He   +6 more
wiley   +1 more source

Shock wave propagation characteristics of aluminum‐containing explosive in corrugated steel‐lined tunnel

Deep Underground Science and Engineering, EarlyView.
Aluminum‐enhanced afterburning renders AE explosives more hazardous than conventional ones. Corrugated steel linings reduce far‐field AE blast overpressure by ~50% through wave reflection and dissipation. The developed model accurately predicts peak pressure (<10% error) and arrival time (<3% error), supporting protective design.
Zhen Wang, Jiayu Peng, Hujun Li, Yuguo Ji, Shuobiao Li, Guokai Zhang   +5 more
wiley   +1 more source

Operations On Strict Fuzzy Graphs and Dominant Fuzzy Graphs

Journal of Ultra Scientist of Physical Sciences Section A, 2017
VASANTHA KANDASAMY W.B, REGIN THANGARAJ
openaire   +1 more source

Thermodynamic Mechanisms of Co‐S Bond Anchoring in Few‐Layered 1T‐MoS2 for Enhanced Capacitive Performance via Spin State Regulation and Ion Diffusion Kinetics

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
The one‐pot hydrothermal prep of Co‐doped few‐layer 1T‐MoS2 shows Co‐S bonds stabilizing the 1T phase, enhancing supercapacitor performance. Few‐layered 1T‐MoS2 is highly promising for supercapacitor applications due to its wide interlayer spacing, high electrical conductivity, and abundant active sites.
Qingling Jia, Han Li, Shun Lu, Chuanyin Xiong, Yongxing Zhang   +4 more
wiley   +1 more source

Anode/Electrolyte Interfacial Engineering Toward Sustainable and Practical Solid‐State Metal‐Sulfur Batteries: A Prospective Review

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Coordinated engineering of the anode, electrolyte, and interface underpins the rational design of next‐generation solid‐state metal‐sulfur batteries. Solid‐state metal‐sulfur batteries are emerging as a transformative energy storage platform with the potential to overcome the fundamental limitations of conventional flooded cells, particularly ...
Ziyu Feng, Hong Zhang, Peng Wang, Ke Lu, Fei Du   +4 more
wiley   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

Image contraction through fuzzy soft outerplanar graph structures. [PDF]

Sci Rep
Jaisankar D, Ramalingam S, Zegeye GB.
europepmc   +1 more source

Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm

Energy Science &Engineering, EarlyView.
Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson, Sivarani Thankamony Saradha Devi, Kumar Chandrasekaran, Sourav Barua   +3 more
wiley   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Anchor-guided multi-view fuzzy clustering for hyperspectral and LiDAR images. [PDF]

Sci Rep
Xiao L, Liu S, Liu Y.
europepmc   +1 more source