In the framework of extended irreversible thermodynamics, the Chen-Yeh theoretical “mixture” model treats magnetorheological (MR) fluids by evolutionary constitutive equations that, in the pre-yield region, manifest the co-presence of elastic, viscoelastic and viscoplastic behaviors.However, such model is characterized by high computational complexity; so, it is hoped to find possible qualitative correspondences between the evolutionary equations of this theoretical model and the evolutionary equations of experimental ones. Therefore, in this paper, we present an innovative sequential algorithm to achieve the qualitative correspondence between the Chen-Yeh model with the Susan-Resiga experimental one that, here, under the same operating conditions and in the framework of generalized standard materials (in shear thinning flow), has been proved to be characterized by acceptable computational complexity compatible with the most important industrial applications.

An Algorithmic Proposal for the Qualitative Comparison Between the Chen-Yeh EIT Mixture Model and the Susan-Resiga GSMs Experimental Model for MR Fluids

Palumbo Annunziata
2022

Abstract

In the framework of extended irreversible thermodynamics, the Chen-Yeh theoretical “mixture” model treats magnetorheological (MR) fluids by evolutionary constitutive equations that, in the pre-yield region, manifest the co-presence of elastic, viscoelastic and viscoplastic behaviors.However, such model is characterized by high computational complexity; so, it is hoped to find possible qualitative correspondences between the evolutionary equations of this theoretical model and the evolutionary equations of experimental ones. Therefore, in this paper, we present an innovative sequential algorithm to achieve the qualitative correspondence between the Chen-Yeh model with the Susan-Resiga experimental one that, here, under the same operating conditions and in the framework of generalized standard materials (in shear thinning flow), has been proved to be characterized by acceptable computational complexity compatible with the most important industrial applications.
978-3-030-96626-3
978-3-030-96627-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3232809
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