Advances in Numerical Model and Methods for Magnetic Fluids

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematical Physics".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1126

Special Issue Editors


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Guest Editor
Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
Interests: engineering; mathematics; medicine; chemistry
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
Interests: engineering; material science; computational electromagnetics; magnetic fluids; electrical machines

Special Issue Information

Dear Colleagues,

In the last few decades, magnetic fluids have become an area of broad interest, since these are new materials that open possibilities for their use in different areas. The concept of magnetic fluids is a multi-disciplinary topic that covers physical and colloidal chemistry, magnetism, hydro- and thermomechanics, physics of fluids, disperse systems, and engineering science. It is essential to know their magnetic and thermal properties and their behavior in case of exposure to external magnetic fields and exposure to different ambient temperatures. For this purpose, various theoretical and numerical models have been developed and used along with different numerical methods, such as the finite element method, boundary element method, and also optimization methods, neural networks, etc.

We are searching for papers on original approaches based on modern numerical and optimization techniques used to develop magnetic fluids models that are as realistic as possible. Experimental support is desirable but not necessary. In addition, magnetic fluid models and their applications in engineering, medicine, etc., where the fusion of mathematics (numerical models) and computation (numerical methods) stimulate progress in magnetic fluid research, are also welcome. Practical applications that involve optimization methods adapted for use in the case of magnetic fluids to achieve better design results or characteristics are also welcome.

Dr. Marko Jesenik
Dr. Mislav Trbušić
Guest Editors

Manuscript Submission Information

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Keywords

  • magnetism
  • magnetic fluids
  • ferrohydrodynamics
  • physical and colloidal chemistry
  • hydro- and thermomechanics
  • numerical models
  • numerical methods
  • optimization methods
  • hyperthermia
  • measurement methods

Published Papers (1 paper)

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Research

23 pages, 4780 KiB  
Article
Design and Optimization of a Spherical Magnetorheological Actuator
by Jakob Vizjak, Anton Hamler and Marko Jesenik
Mathematics 2023, 11(19), 4098; https://doi.org/10.3390/math11194098 - 27 Sep 2023
Cited by 1 | Viewed by 865
Abstract
Recently, an increasing number of electromagnetic devices have been using smart fluids. These include ferrofluids, electrorheological fluids, and magnetorheological (MR) fluids. In the paper, magnetorheological fluids are considered for use in a spherical actuator for haptic applications. An approach is presented to the [...] Read more.
Recently, an increasing number of electromagnetic devices have been using smart fluids. These include ferrofluids, electrorheological fluids, and magnetorheological (MR) fluids. In the paper, magnetorheological fluids are considered for use in a spherical actuator for haptic applications. An approach is presented to the design and optimization of such a device, using finite element method modelling linked with differential evolution (DE). Much consideration was given to the construction of the objective function to be minimized. A novel approach to objective function assembly was used, using reference values based on the model design and created with parameters set to the midpoint values of the selected range. It was found to be a useful strategy when the reference values are unknown. There were four parameters to be optimized. Three of them gravitated towards the boundary value, and the fourth (actuator radius) was somewhere in between. The value of the objective function reached a minimum in the range of actuator radius between 42.9880 mm and 45.0831 mm, which is about a 5% difference in regard to the actuator radius. Three passes of optimization were performed with similar results, proving the robustness of the algorithm. Full article
(This article belongs to the Special Issue Advances in Numerical Model and Methods for Magnetic Fluids)
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