Results 221 to 230 of about 1,628,973 (292)

A novel construction approach for the pore structure model principally focuses on the controllable roundness of rock particles

open access: yesDeep Underground Science and Engineering, EarlyView.
Particle rounding effects comparison of different methods: (a), (b), and (c) are the rounding results using the B‐spline curve method with different R; (d), (e), and (f) are the results of vertex rounding substitution method with different rounding radii.
Jiabin Dong   +6 more
wiley   +1 more source

Effect of confining pressure on fracture characteristics and mineralogical behavior of tight sandstone specimens after hydraulic fracturing

open access: yesDeep Underground Science and Engineering, EarlyView.
Hydraulic fracturing in tight sandstone and fracture propagation characteristics using backscattered electron‐scanning electron microscope (BSE‐SEM) images. Abstract This study focuses on hydraulic fracturing experiments conducted under triaxial conditions on tight sandstone specimens from Shivpuri district, Madhya Pradesh, India.
Pankaj Rawat, Narendra Kumar Samadhiya
wiley   +1 more source

Generalized Matsuoka–Nakai criterion considering hydrostatic pressure dependence in the brittle–ductile region

open access: yesDeep Underground Science and Engineering, EarlyView.
Three sets of strength data were selected, including hydrostatic pressure independent within the brittle region (HPI‐B), hydrostatic pressure dependent within the brittle region (HPD‐B), and hydrostatic pressure dependent within the brittle–ductile region (HPD‐BD). For HPI type, the failure envelope within the deviatoric plane remains constant.
Jiacun Liu   +3 more
wiley   +1 more source

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

open access: yesInternational Journal for Numerical Methods in Fluids, EarlyView.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das   +2 more
wiley   +1 more source

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