Estimation of the nonlinear parameters of viscoelastic constitutive models using CFD and multipass rheometer data

Although there are many studies in the literature concerning viscoelastic fluids, it remains a challenging subject in the field of polymer rheology to determine which is the most appropriate model and parameter set to describe the rheological behavior of a given viscoelastic fluid under real flow. T...

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Bibliographic Details
Published in:Journal of non-Newtonian fluid mechanics Vol. 281; p. 104284
Main Authors: Pereira, J.O., Farias, T.M., Castro, A.M., (Al-Baldawi), A.A., Secchi, A.R., Cardozo, N.S.M.
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01-07-2020
Elsevier BV
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Summary:Although there are many studies in the literature concerning viscoelastic fluids, it remains a challenging subject in the field of polymer rheology to determine which is the most appropriate model and parameter set to describe the rheological behavior of a given viscoelastic fluid under real flow. The aim of this work is to present an optimization procedure for the estimation of nonlinear parameters of the viscoelastic constitutive equations implemented in the viscoelasticFluidFoam solver available in the OpenFOAM software. The code allows simultaneous fitting of experimental data of two rheological properties: (i) shear viscosity, obtained by rotational and capillary rheometers and (ii) principal stress difference, determined by the flow induced birefringence images obtained during the flow of melt polymer sample in multipass rheometer. In order to illustrate the methodology, a polyethylene sample was characterized at 140°C in the multipass rheometer MPR5S through a slit-die at 0.1 and 0.5 mm/s. The results using multi-mode Giesekus and EPTT constitutive equations showed that the models with the parameters estimated by the proposed methodology were able to satisfactorily represent the shear thinning, observed in the experiments of conventional rheometry, and the stress field determined using birefringence images.
ISSN:0377-0257
1873-2631
DOI:10.1016/j.jnnfm.2020.104284