Artificial neural network joined with lattice Boltzmann method to study the effects of MHD on the slip velocity of FMWNT/water nanofluid flow inside a microchannel

DOI10.1016/j.enganabound.2022.05.027OpenAlexW4283024560WikidataQ113875206 ScholiaQ113875206MaRDI QIDQ2085885

Samia Elattar, Maawiya Ould Sidi, Xinlin He, N. Ameer Ahammad, Mohamed Abdelghany Elkotb, A. M. Algelany

Publication date: 19 October 2022

Published in: Engineering Analysis with Boundary Elements (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.enganabound.2022.05.027

zbMATH Keywords

heat transferlattice Boltzmann methodartificial neural networkmicrochannelmicro flow

Mathematics Subject Classification ID

Fluid mechanics (76-XX) Statistical mechanics, structure of matter (82-XX)

Related Items (3)

Heat transfer and fluid flow around starfish-inspired cylinder by immersed boundary-simplified thermal lattice Boltzmann method ⋮ The possibility of availing active and passive methods to achieve a flow with desirable characteristics via using the lattice Boltzmann method ⋮ Blending machine learning and sequential data assimilation over latent spaces for surrogate modeling of Boussinesq systems

Cites Work

• Binary collision of drops in simple shear flow at finite Reynolds numbers: geometry and viscosity ratio effects
• Interaction between two drops ascending in a linearly stratified fluid

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