16 May 2005 Genetic algorithms for rheological parameter estimation of magnetorheological fluids
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Abstract
The primary objective of this study is to estimate the parameters of constitutive models characterizing the rheological properties of ferrous and cobalt nanoparticle-based magnetorheological fluids. Constant shear rate rheometer measurements were carried out using suspensions of nanometer sized particles in hydraulic oil. These measurements yielded shear stress vs. shear rate as a function of applied magnetic field. The MR fluid was characterized using both Bingham-Plastic and Herschel-Bulkley constitutive models. Both these models have two regimes: a rigid pre-yield behavior for shear stress less than a field-dependant yield stress, and viscous behavior for higher shear rates. While the Bingham-Plastic model assumes linear post-yield behavior, the Herschel-Bulkley model uses a power law dependent on the dynamic yield shear stress, a consistency parameter and a flow behavior index. Determination of the model parameters is a complex problem due to the non-linearity of the model and the large amount of scatter in the experimentally observed data. Usual gradient-based numerical methods are not sufficient to determine the characteristic values. In order to estimate the rheological parameters, we have used a genetic algorithm and carried out global optimization. The obtained results provide a good fit to the experimental data.
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Anirban Chaudhuri, Anirban Chaudhuri, Norman M. Wereley, Norman M. Wereley, R. Radhakrishnan, R. Radhakrishnan, } "Genetic algorithms for rheological parameter estimation of magnetorheological fluids", Proc. SPIE 5761, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, (16 May 2005); doi: 10.1117/12.600881; https://doi.org/10.1117/12.600881
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