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Mathematical modelling with experimental validation of viscoelastic properties in non-Newtonian fluids.


ABSTRACT: The paper proposes a mathematical framework for the use of fractional-order impedance models to capture fluid mechanics properties in frequency-domain experimental datasets. An overview of non-Newtonian (NN) fluid classification is given as to motivate the use of fractional-order models as natural solutions to capture fluid dynamics. Four classes of fluids are tested: oil, sugar, detergent and liquid soap. Three nonlinear identification methods are used to fit the model: nonlinear least squares, genetic algorithms and particle swarm optimization. The model identification results obtained from experimental datasets suggest the proposed model is useful to characterize various degree of viscoelasticity in NN fluids. The advantage of the proposed model is that it is compact, while capturing the fluid properties and can be identified in real-time for further use in prediction or control applications. This article is part of the theme issue 'Advanced materials modelling via fractional calculus: challenges and perspectives'.

SUBMITTER: Ionescu CM 

PROVIDER: S-EPMC7287316 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Mathematical modelling with experimental validation of viscoelastic properties in non-Newtonian fluids.

Ionescu C M CM   Birs I R IR   Copot D D   Muresan C I CI   Caponetto R R  

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 20200511 2172


The paper proposes a mathematical framework for the use of fractional-order impedance models to capture fluid mechanics properties in frequency-domain experimental datasets. An overview of non-Newtonian (NN) fluid classification is given as to motivate the use of fractional-order models as natural solutions to capture fluid dynamics. Four classes of fluids are tested: oil, sugar, detergent and liquid soap. Three nonlinear identification methods are used to fit the model: nonlinear least squares,  ...[more]

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