Results 111 to 120 of about 856 (206)

Thermodynamics‐Based THMC Model for Solute Transport in Sorptive Fractured Rock: Coupling Multi‐Phase Flow, Heat, and Deformation

Geophysical Research Letters, Volume 53, Issue 11, 16 June 2026.
Abstract Fractured porous rocks host a complex interplay of heat, fluids, deformation, and chemical reactions, yet their combined influence on solute transport remains poorly resolved. Here we show that these processes are more tightly coupled than previously assumed.
Kai Wang, Yue Ma, Xu Li, Shangqi Ge, Zhitong Ma, Aizhong Ding, Xiaohui Chen   +6 more
wiley   +1 more source

Diffusion-Shock PDEs for Deep Learning on Position-Orientation Space. [PDF]

J Math Imaging Vis
Sherry FM, Schaefer K, Duits R.
europepmc   +1 more source

Numerical Modeling of Tank Cars Carrying Hazardous Materials With and Without Composite Metal Foam

Advanced Engineering Materials, Volume 28, Issue 11, 3 June 2026.
Large‐scale puncture models consisting of hazardous materials (HAZMATs) tank car with protective steel–steel composite metal foam (S–S CMF) are solved numerically. Tank car plate with added 10.91–13.33 mm thick S–S CMF layer does not puncture. Protective S–S CMF absorbs impact energy, reduces plate deformation, and prevents shear bands formation ...
Aman Kaushik, Afsaneh Rabiei
wiley   +1 more source

Fast automated adjoints for spectral PDE solvers. [PDF]

Proc Natl Acad Sci U S A
Skene CS, Burns KJ.
europepmc   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

Advanced Science, Volume 13, Issue 33, 15 June 2026.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich, Noah S. David, Markus J. Buehler   +2 more
wiley   +1 more source

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning. [PDF]

NPJ Artif Intell
Toscano JD, Chen DT, Ooomen V, Darbon J, Karniadakis GE.   +4 more
europepmc   +1 more source

Adaptive moving mesh method for partial differential equations

, 2019
In this talk, I present a robust moving mesh finite difference method for the simulation of fourth order nonlinear PDEs describing elastic-electrostatic interactions in two dimensions. The parabolic Monge-Ampà ´ere methods from [1] are extended to solve
DiPietro, Kelsey
core  

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

Advanced Science, Volume 13, Issue 31, 4 June 2026.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +1 more source

Deterministic, stochastic, and mean-field PDE models in neuroscience. [PDF]

Front Comput Neurosci
Çetin C, Piqueira JRC, İzgi B, Peker-Dobie A, Ahmetolan S, Özkaya M.   +5 more
europepmc   +1 more source

Defect Correction Methods

, 2015
Defect Correction (DeC) methods (also: `deferred correction methods´) are based on a particular way to estimate local or global errors, especially for differential and integral equations.
Auzinger, Winfried
core