Other pde from mechanics - Open Access .click

Results 101 to 110 of about 60,531,842 (194)

<h2>What's Changed</h2> <ul> <li>Improved documentation by @david-zwicker in https://github.com/zwicker-group/py-pde/pull/509</li> <li>Replaced decorator <code>skipUnlessModule</code> by @david-zwicker in ...
Diego Volpatto +7 more
core +1 more source

Four Decades of Research at the MADE Site and Beyond: Advancing the Understanding and Modeling of Solute Transport in Heterogeneous Media

Reviews of Geophysics, Volume 64, Issue 4, December 2026.
Abstract Spatial heterogeneity, manifested as strong variability in hydraulic conductivity (K) within geological formations, exerts a fundamental control on groundwater flow and solute transport. Because K can vary over multiple orders of magnitude in complex three‐dimensional patterns, predicting contaminant plume migration remains a long‐standing ...
Zhilin Guo +8 more
wiley +1 more source

cGMP Signaling in Arterioles Revealed by FRET‐Based Real‐Time Measurement in Mice In Vivo

Acta Physiologica, Volume 242, Issue 11, November 2026.
ABSTRACT cGMP evokes arteriolar vasorelaxation and is generated in smooth muscle by the soluble guanylyl cyclase (sGC) stimulated by endothelial NO. Phosphodiesterases (PDEs) degrade cGMP and may contribute in diameter regulation. We examined arteriolar cGMP levels in real‐time in vivo upon NO and acetylcholine (ACh) and effects of PDE inhibition ...
Lukas Thiele +6 more
wiley +1 more source

Sliding physical invariant neural operator for long-term prediction of complex dynamics in physical systems. [PDF]

Natl Sci Rev
Wang Y, Li Y, Peng Y, Ying S.
europepmc +1 more source

Fracture Modeling of Nearly Incompressible Hyperelastic Materials: A Phase‐Field Approach via Simo–Taylor–Pister Three‐Field Variation

International Journal for Numerical Methods in Engineering, Volume 127, Issue 19, 15 October 2026.
ABSTRACT Incompressibility is commonly observed in the majority of hyperelastic materials, which are fundamental to a wide range of technical applications owing to their distinctive properties, particularly their flexibility, stretchability, and resilience.
Le Zhang +4 more
wiley +1 more source

Volumetric Ablation of Phenolic Resin in Extreme Environments: A Variable-Property Physics-Informed Neural Network Framework. [PDF]

Polymers (Basel)
Du W, Ma T, Song H.
europepmc +1 more source

A Unified Block‐Modal Framework for Inverse Source Problems in Heat and Mass Transfer

International Journal for Numerical Methods in Engineering, Volume 127, Issue 19, 15 October 2026.
ABSTRACT This work presents a unified block–modal framework for inverse source identification in linear diffusive problems arising in heat and mass transfer. Starting from a general parabolic model with mixed boundary operators, the Classical Integral Transform Technique is employed to project the dynamics onto an orthonormal eigenbasis, yielding a ...
André J. P. de Oliveira +5 more
wiley +1 more source

Going with the flow to solve for symmetry-driven PDE dynamics with physics-informed neural networks. [PDF]

Nat Commun
Kavousanakis ME +5 more
europepmc +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, Volume 2, Issue 5, October 2026.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source

AI-driven predictive modelling of residual stress of HVOF thermal sprayed carbon-based composite coatings using physics-informed neural networks. [PDF]

Sci Rep
Tyagi A, Dadhich A, Sirohi S, Gupta AK.
europepmc +1 more source