Falling magnetizable bead in a Newtonian fluid

The use of magnetic fields allows to modify the trajectory of magnetizable particles in a fluid. If a ring magnet is centered on the cylinder containing the fluid, it enhances the dynamics of a falling ball, and an equilibrium position is found. To compute the particle dynamics, the magnetic force should be found accurately: a method based on virtual works allows to obtain the force as well as the stiffness matrix, to gain accuracy. The computed trajectories are compared to the experimental ones for Newtonian fluids at first, and extended to viscoplastic fluids.

Authors

Institutions

Publication Details

Journal
The European Physical Journal Applied Physics
Published
2024-11-22
DOI
https://doi.org/10.1051/epjap/2024025
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Falling magnetizable bead in a Newtonian fluid

G. Vinsard, Christel Métivier, Mateus Faria de Andrade Paschoal, S. Dufour
The European Physical Journal Applied Physics
Particle Dynamics in Fluid Flows
article

Falling magnetizable bead in a Newtonian fluid

G. Vinsard, Christel Métivier, Mateus Faria de Andrade Paschoal, S. Dufour
article en

Abstract

The use of magnetic fields allows to modify the trajectory of magnetizable particles in a fluid. If a ring magnet is centered on the cylinder containing the fluid, it enhances the dynamics of a falling ball, and an equilibrium position is found. To compute the particle dynamics, the magnetic force should be found accurately: a method based on virtual works allows to obtain the force as well as the stiffness matrix, to gain accuracy. The computed trajectories are compared to the experimental ones for Newtonian fluids at first, and extended to viscoplastic fluids.

The European Physical Journal Applied PhysicsVol. 100
Centre National de la Recherche Scientifique (FR), Laboratoire Énergies et Mécanique Théorique et Appliquée (FR), Université de Lorraine (FR)
Openalex Percentile: Top 72%
Particle Dynamics in Fluid Flows
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.