Results 71 to 80 of about 11,812,491 (293)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Computational Contact Problems: Investigations on the Robustness of Generalized Newton Method, Fixed-Point method and Partial Newton Method

, 2018
International audienceDealing with frictional contact simulations, one can use generalized Newton method or Fixed-point method. In this article, we present partial Newton method which combines advantages from both algorithms.
Lebon, Frédéric, De-Soza, Thomas, Kudawoo, Ayaovi Dzifa, Rosu, Iulian, Abbas, Mickaël   +4 more
core   +1 more source

Trump Tariffs 2.0: Assessing the Impacts on US Distilled Spirits Imports

Agribusiness, EarlyView.
ABSTRACT The proposed 25% tariff on Mexico and Canada could have significant repercussions on US imports of distilled spirits. This study estimates US import demand across various spirit categories (e.g., tequila, whiskey) and assesses the potential impact of the proposed tariff.
Andrew Muhammad
wiley   +1 more source

O método de Newton inexato aplicado às equações de Navier-Stokes: Hilbeth Parente de Deus ; orientador, Mário César Zambaldi [PDF]

, 2004
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas. Programa de Pós-Graduação em Matemática e Computação CientíficaO trabalho aqui presente destina-se a fazer uma análise comparativa, no contexo do ...
Deus, Hilbeth Parente de
core  

Pseudo-loadflow formulation as a starting process for the Newton Raphson [PDF]

, 2010
This paper introduces new models which approximate the AC loadflow problem, but are able to converge (using the Newton Raphson algorithm) from a wider range of starting points.
Irving, MR
core   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

A Semismooth Newton-Based Augmented Lagrangian Algorithm for the Generalized Convex Nearly Isotonic Regression Problem

Mathematics
The generalized convex nearly isotonic regression problem addresses a least squares regression model that incorporates both sparsity and monotonicity constraints on the regression coefficients.
Yanmei Xu, Lanyu Lin, Yong-Jin Liu
doaj   +1 more source

GMRES based numerical simulation and parallel implementation of multicomponent multiphase flow in porous media

Cogent Engineering, 2020
This article considered the numerical simulation of multicomponent multiphase flow in porous media. The resulting system of nonlinear equations linearized by the Newton-Raphson method and solved with the iterative Generalized minimal residual method ...
Saltanbek T. Mukhambetzhanov, Danil V. Lebedev, Nurislam M. Kassymbek, Timur S. Imankulov, Bazargul Matkerim, Darkhan Zh. Akhmed-Zaki   +5 more
doaj   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Generalized Newton Method for a Kind of Complementarity Problem

, 2020
A generalized Newton method for the solution of a kind of complementarity problem is given. The method is based on a nonsmooth equations reformulation of the problem by F-B function and on a generalized Newton method.
Shou-Qiang Du
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