Results 251 to 260 of about 10,608 (327)

Machine Learning‐Aided Spatial Adaptation for Improved Digital Image Correlation Analysis of Complex Geometries

Strain, Volume 62, Issue 1, February 2026.
ABSTRACT Digital image correlation (DIC) is a widely used experimental technique for measuring full‐field deformation, but its application to complex scenarios involving large deformations, discontinuities, or intricate geometries is often hampered by the need for manual region of interest (ROI) definition.
Jeffrey Leu, Zixiang Tong, Andrew Doty, Solon Tsimpoukis, Bolei Deng, Jin Yang   +5 more
wiley   +1 more source

Local‐Hybrid Functional With a Composite Local Mixing Function Built From a Neural Network and a Strong‐Correlation Model

Journal of Computational Chemistry, Volume 47, Issue 3, 30 January 2026.
A new local hybrid functional, LH25nP, is reported, that uses a neural‐network local mixing function for the position‐dependence of exact‐exchange admixture trained with a human‐designed strong‐correlation factor. It thereby escapes the usual zero‐sum game between delocalization and static‐correlation errors.
Artur Wodyński, Martin Kaupp
wiley   +1 more source

Non‐Linear Reduced Order Modelling of Transonic Potential Flows for Fast Aerodynamic Analysis

International Journal for Numerical Methods in Engineering, Volume 127, Issue 2, 30 January 2026.
ABSTRACT This work presents a physics‐based reduced order modelling (ROM) framework for the efficient simulation of steady transonic potential flows around aerodynamic configurations. The approach leverages proper orthogonal decomposition and a least‐squares Petrov‐Galerkin (LSPG) projection to construct intrusive ROMs for the full potential equation ...
M. Zuñiga, S. Ares de Parga, R. Zorrilla, R. Rossi   +3 more
wiley   +1 more source

Modified preconditioned iterative methods for solving elliptic partial differential equations

, 1982
Christopher C. Okeke
openalex   +1 more source

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Advances in Iterative Methods and Preconditioners for the Helmholtz Equation

Archives of Computational Methods in Engineering, 2008
The Helmholtz equation \(\nabla ^{2}u(\mathbf{x})+\kappa ^{2}u(\mathbf{x})=h( \mathbf{x}),\) where \(\nabla ^{2}\) is the Laplacian, \(\kappa \) is the wave number, \(h\) is a forcing function and \(u\) is the amplitude, finds applications in many important fields including aeroacoustics, under-water acoustics, seismic inversion and electromagnetics ...
Y. Erlangga
semanticscholar   +3 more sources

Incomplete LU Preconditioners for Conjugate-Gradient-Type Iterative Methods

SPE Reservoir Engineering, 1988
Summary In recent years, such conjugate-gradient-type methods as orthomin have been used very successfully with various preconditioners to solve the unsymmetric linear systems that arise in reservoir simulation. Here these successful iterative methods are combined with a new set of preconditioners that have been derived from some ...
H. Simon
semanticscholar   +2 more sources

Iterative Substructuring Preconditioners For Mortar Element Methods In Two Dimensions

SIAM Journal on Numerical Analysis, 1999
The paper is devoted to the construction of effective model grid operators (preconditioners) for classes of linear grid systems with positive operators. The suggested constructions lead to estimates of the spectral condition number like \(O(\log^2N)\); the model operators are almost spectrally equivalent to the original ones.
Y. Achdou, Y. Maday, O. Widlund
semanticscholar   +2 more sources

Using Performance Profiles to Evaluate Preconditioners for Iterative Methods

Communication Systems and Applications, 2006
We evaluate performance profiles as a method for comparing preconditioners for iterative solvers by using them to address three questions that have previously been asked about incomplete LU preconditioners. For example, we use performance profiles to quantify the observation that if a system can be solved by a preconditioned iterative solver, then that
M. Lazzareschi, Tzu-Yi Chen
semanticscholar   +2 more sources

On Single Precision Preconditioners for Krylov Subspace Iterative Methods

Large-Scale Scientific Computing, 2009
Large sparse linear systems Ax= barise in many scientific applications. Krylov subspace iterative methods are often used for solving such linear systems. Preconditioning techniques are efficient to reduce the number of iterations of Krylov subspace methods.
Hiroto Tadano, T. Sakurai
semanticscholar   +2 more sources