High fidelity, discrete element method simulation of magnetorheological fluids using accurate particle size distributions in LIGGGHTS extended with mutual dipole method

Leps, Thomas; Hartzell, C. M.

doi:10.1088/2053-1591/ac113c

Cited by 6 publications

(6 citation statements)

References 26 publications

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“…This puts a severe computational constraint on the number of particles that can be simulated with a direct computation of the inter-particle dipole-dipole force. To compute the magnetic moment of each particle, m, the fixed dipole model [15] or the mutual dipole model [20] can be used. In dilute MRFs (i.e., low concentration of magnetic particles), it is often acceptable to use the magnetic moment calculated from the background magnetic field (i.e., fixed dipole model).…”

Section: Magnetic Forces and Torquesmentioning

confidence: 99%

“…A particle, thus, is subjected not only to the primary magnetization due to the external magnetic field, but also to a secondary magnetization from the other particles' magnetic fields. Considering the mutual magnetization of N magnetizable particles with their centres at x i (i = 1, • • • , N ) in a uniform magnetic field with strength H 0 , the magnetic moment of the particle i, m i , is given by [20],…”

Section: Mutual Dipole Modelmentioning

confidence: 99%

“…They also showed that, in an alternating gradient magnetic field, magnetic particles oscillate along the flow direction, disturb the flow field, and increase the overall turbulence intensity. Leps and Hartzell [20] modeled the dynamics of MRFs using DEM method alone leveraging the open source LIGGGHTS [21] software. The algorithm is based on the mutual-dipole model to allow for the use of a large number of magnetic particles with several close neighbors while keeping a good trade-off between model accuracy and computational cost.…”

Section: Introductionmentioning

confidence: 99%

“…The magnetic force exerted on the particles is computed using the gradient of the magnetic field strength, which is obtained from the imposed external magnetic field [17]. The magnetic interactions between the particles are implemented using a mutual dipole model [20] allowing the magnetic fields of other particles to contribute to the magnetization and motion of the particle under consideration.…”

Section: Introductionmentioning

confidence: 99%

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Particle-level Simulation of Magnetorheological Fluids: A Fully-Resolved Solver

Fernandes¹,

Faroughi²

2023

Preprint

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Magnetorheological fluids (MRFs) are smart materials consisting of micro-scale magnetizable particles suspended in a carrier fluid. The rheological properties of a MRF can be changed from a fluid-state to a solid-state upon the application of an external magnetic field. This study reports the development of a particle-level simulation code for magnetic solid spheres moving through an incompressible Newtonian carrier fluid. The numerical algorithm is implemented within an open-source finite-volume solver coupled with an immersed boundary method (FVM-IBM) to perform fully-resolved simulations. The particulate phase of the MRF is modeled using the discrete element method (DEM). The resultant force acting on the particles due to the external magnetic field (i.e., magnetostatic polarization force) is computed based on the Clausius-Mossotti relationship. The fixed and mutual dipole magnetic models are then used to account for the magnetic (MAG) interactions between particles. Several benchmark flows were simulated using the newly-developed FVM-IBM-DEM-MAG algorithm to assess the accuracy and robustness of the calculations. First, the sedimentation of two spheres in a rectangular duct containing a Newtonian fluid is computed without the presence of an external magnetic field, mimicking the so-called drafting-kissing-tumbling (DKT) phenomenon. The numerical results obtained for the DKT case study are verified against published data from the scientific literature. Second, we activate both the magnetostatic polarization and the dipole-dipole forces and resultant torques between the spheres for the DKT case study. Next, we study the robustness of the FVM-IBM-DEM-MAG solver by computing multi-particle chaining (i.e., particle assembly) in a two-dimensional (2D) domain for area volume fractions of 20% (260 particles) and 30% (390 particles) under vertical and horizontal magnetic fields. Finally, the fourth computational experiment describes the multi-particle chaining in a three-dimensional (3D) domain allowing to study fully-resolved MRF simulations of 580 magnetic particles under vertical and horizontal magnetic fields.

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Section: Magnetic Forces and Torquesmentioning

confidence: 99%

Section: Mutual Dipole Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Particle-level Simulation of Magnetorheological Fluids: A Fully-Resolved Solver

Fernandes¹,

Faroughi²

2023

Preprint

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“…In contrast, the molecular dynamics simulation is very effective for solving such problems. In recent years, the analysis of the shear motion patterns of MRF using numerical computational methods has received a lot of attention from researchers [22][23][24]. However, up to now, there has been little research on the analysis of the normal stress of MRF using molecular dynamics simulation methods.…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis for the normal force of magnetorheological fluids

Zheng,

Lin

et al. 2023

Mater. Res. Express

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As one of the most important mechanical parameters of magnetorheological fluids (MRF), the normal force has been studied by a large number of researchers using various experimental equipment and methods. However, it is difficult to reveal the effects of particle microstructure characteristics on the normal force of MRF by experimental methods, especially for such factor as the particle size distribution. To advance this research area, a numerical method for calculating the normal force of MRF is proposed in this study. The accuracy of the simulation model is verified with the experimental results measured by a plate-plate magnetorheometer. The results show that the simulated values agree well with the experimental data, which indicates the feasibility of calculating the normal force of MRF using numerical methods and provides a new research idea for a more intuitive and comprehensive analysis of the normal force characteristics of MRF. Besides, the simulated data show that the increase in magnetic field intensity and particle volume fraction will sufficiently enhance the normal force of MRF and improve the response time of MRF. For the MRF with the same particle volume fraction, a decline in the average particle diameter will increase the normal force. Moreover, increasing the dispersion of particle size of MRF particles can also improve its normal force.

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An Automatized Simulation Workflow for Powder Pressing Simulations Using SimStack

Mieller,

Valavi,

Caldeira Rêgo

2024

Adv Eng Mater

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Automated computational workflows are a powerful concept that can improve the usability and reproducibility of simulation and data processing approaches. Although used very successfully in bioinformatics, workflow environments in materials science are currently commonly applied in the field of atomistic simulations. This work showcases the integration of a discrete element method (DEM) simulation of powder pressing in the convenient SimStack workflow environment. For this purpose, a Workflow active Node (WaNo) was developed to generate input scripts for the DEM solver using LIGGGHTS Open Source Discrete Element Method Particle Simulation code. Combining different WaNos in the SimStack framework makes it possible to build workflows and loop over different simulation or evaluation conditions. The functionality of the workflows is explained, and the added user value is discussed. The procedure presented here is an example and template for many other simulation methods and issues in materials science and engineering.

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High fidelity, discrete element method simulation of magnetorheological fluids using accurate particle size distributions in LIGGGHTS extended with mutual dipole method

Cited by 6 publications

References 26 publications

Particle-level Simulation of Magnetorheological Fluids: A Fully-Resolved Solver

Particle-level Simulation of Magnetorheological Fluids: A Fully-Resolved Solver

Numerical analysis for the normal force of magnetorheological fluids

An Automatized Simulation Workflow for Powder Pressing Simulations Using SimStack

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