Results 101 to 110 of about 9,582 (250)

Advancing mine pillar design: Evaluating traditional methods and integrating AI for enhanced stability of pillars in the Great Dyke, Zimbabwe

Deep Underground Science and Engineering, EarlyView.
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza, Hendrik Grobler, Peter Apata Olubambi, Moshood Onifade, Manoj Khandelwal   +4 more
wiley   +1 more source

TAMNet: Temporal and adaptive‐frequency network with MixStyle for cross‐region oil and fluid production forecasting

Deep Underground Science and Engineering, EarlyView.
This paper presents temporal and adaptive‐frequency network with MixStyle (TAMNet), a deep time‐series modeling framework for accurate and robust multi‐well oil productivity forecasting. TAMNet integrates transformer and long short‐term memory architectures to capture both short‐ and long‐term temporal dependencies, enhanced by a temporal gate unit ...
Chunxi Yang, Leifeng Meng, Qinghu Fan, Ziang Guo, Ting Bao, Pingdong Zhong, Fulin Luo   +6 more
wiley   +1 more source

Multi‐factor coupling effects in hydraulic fracturing of laminated shale: Experimental insights and physics‐informed neural network‐driven optimization

Deep Underground Science and Engineering, EarlyView.
This study establishes a multi‐factor coupling framework for predicting breakdown pressure in laminated shale by integrating experimental hydraulic fracturing tests, physics‐informed neural networks (PINNs), and Sobol sensitivity analysis. It reveals how differential stress, the bedding dip angle, and the injection rate interact to influence fracture ...
Tao Wang, Guoyao Xu, Liyuan Liu, Yao Zhang, Sitao Zhu, Hongyang Chu, Kaikai Zhao   +6 more
wiley   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

Solving Benjamin-Bona-Mahony equation by using the sn-ns method and the tanh-coth method [PDF]

Mathematica Moravica, 2017
In this study, we consider the Benjamin Bona Mahony equation which is in the form of ut + ux + uux - uxxt = 0: The sn-ns method and the tanh-coth method have been applied to this equation. And then, exact solutions have been obtained.
Gündoğdu Hamı, Gözükızıl Faruk Ömer   +1 more
doaj  

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source

Tree‐Boost–Guided CNN–BiLSTM–Transformer for Solar Irradiance Forecasting: Cross‐Regional Evidence for Sustainable Energy Planning

Energy Science &Engineering, EarlyView.
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif, Usama Hassan, Javid Hussain, Irfan Ali Khan, Yuldasheva Gulora, Syed Masood Arif Bukhari   +5 more
wiley   +1 more source

Effects of Camber of S‐Series Airfoils on Aerodynamic Performance, Entropy Generation Rate, Irreversibility, and Second Law Efficiency of Horizontal Axis Wind Turbines

Energy Science &Engineering, EarlyView.
Due to the depletion of fossil fuels, enhancing wind turbine efficiency is crucial. Utilizing airfoils with high lift‐to‐drag ratios significantly improves power generation by optimizing aerodynamic parameters. Furthermore, entropy generation analysis serves as an effective method for design optimization by minimizing energy losses and exergy ...
Mitra Yadegari
wiley   +1 more source

Mechanical Behaviour of Vacuum‐Infused GFRP Composites at Elevated Temperatures—Influence of Fibre Architecture

Fire and Materials, EarlyView.
ABSTRACT This study addresses the influence of fibre architecture on the mechanical properties of vacuum‐infused glass fibre reinforced polymer (GFRP) composites at elevated temperatures (ET). Laminates with three different fibre configurations—unidirectional (UD), bidirectional 0°/90° cross‐ply (BD), and ±45° off‐axis angle‐ply (OA) – were tested in ...
Eloísa Castilho, João P. Firmo, Mário Garrido, João R. Correia, Afonso Ataíde   +4 more
wiley   +1 more source

Subspace Acceleration for Efficient Nonlinear Water Wave Simulation

International Journal for Numerical Methods in Fluids, EarlyView.
We introduce an exponentially weighted subspace acceleration technique to reduce GMRES iterations for solving the Poisson equation with time‐dependent coefficients in nonlinear, dispersive free‐surface flows governed by the incompressible Navier‐Stokes equations. The method significantly reduces memory requirements and computational complexity compared
Rasmus Kleist Hørlyck Sørensen, Margherita Guido, Allan Peter Engsig‐Karup, Daniel Kressner   +3 more
wiley   +1 more source