Results 191 to 200 of about 195,153 (293)

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.
Abstract Simulating compound flooding (CF) at the river‐ocean interface within large‐scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics‐informed and data‐driven machine learning (ML) approaches for ...
Dongyu Feng   +5 more
wiley   +1 more source

Viscosity driven variations in slot die coating of nanocellulosic barrier layers

open access: yesAIChE Journal, Volume 71, Issue 11, November 2025.
Abstract A suitable candidate for applying nanocellulose on paper as packaging material is slot die coating, but a complex rheological behavior makes process optimization challenging. In this work, coating windows of nanocellulosic suspensions modeled as Casson fluids with different viscosities have been determined with computational fluid dynamics ...
L. Maier, H. Briesen, D. S. Nasato
wiley   +1 more source

The effect of discontinuous injection on particle backflow in pneumatic conveying systems

open access: yesThe Canadian Journal of Chemical Engineering, Volume 103, Issue 11, Page 5680-5689, November 2025.
Abstract Pneumatic conveying is used in many process industries to transport dry, granular, and powdered solids. The triboelectrification of particles during conveying causes particle agglomeration, spark discharges, and disruptions in particle flow, making particles move upstream against the fluid flow. The effect of frequency of particle injection on
Otome Obukohwo   +3 more
wiley   +1 more source

Accelerating Vortex Particle Methods by Downsampling the Vorticity Field Representation

open access: yesInternational Journal for Numerical Methods in Fluids, Volume 97, Issue 11, Page 1410-1425, November 2025.
This paper presents two downsampling algorithms for vortex particle methods (VPMs) that reduce the number of computational elements representing the vorticity field. The two methods demonstrate significant reductions in particle count and computation time in benchmark cases at a cost of diffusive errors.
Jakub Siemaszko   +2 more
wiley   +1 more source

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