4.6 Article

Microstructure Simulation and Constitutive Modelling of Magnetorheological Fluids Based on the Hexagonal Close-packed Structure

期刊

MATERIALS
卷 13, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/ma13071674

关键词

microstructure; particle dynamics analysis; magnetorheological fluids; constitutive modeling; hexagonal close-packed structure

资金

  1. National Key R&D Program of China [2018YFB1304504]
  2. Fundamental Research Funds for the Central Universities [N2003017]

向作者/读者索取更多资源

This paper presents a new constitutive model of high particles concentrated magnetorheological fluids (MRFs) that is based on the hexagonal close-packed structure, which can reflect the micro-structures of the particles under the magnetic field. Firstly, the particle dynamic simulations for the forces sustained by carbonyl iron powder (CIP) particles of MRFs are performed in order to investigate the particles chain-forming process at different time nodes. Subsequently, according to the force analyses, a hexagonal close-packed structure, which differs from the existing single-chain structure and body-cantered cubic structure, is adopted to formulate a constitutive model of MRFs with high concentration of the magnetic-responsive particles. Several experiments are performed while considering crucial factors that influence on the chain-forming mechanism and, hence, change the field-dependent shear yield stress in order to validate the proposed model. These factors include the magnetic induction intensity, volume fraction and radius of CIP particles, and surfactant coating thickness. It is shown that the proposed modeling approach can predict the field-dependent shear yield stress much better than the single-chain model. In addition, it is identified that the shear yield stress is increased as the particle volume fraction increases and surfactant coating thickness decreases. It is believed that the proposed constitutive model can be effectively used to estimate the field-dependent shear yield stress of MRFs with a high concentration of iron particles.

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