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Study on an N-Parallel FENE-P Constitutive Model Based on Multiple Relaxation Times for Viscoelastic Fluid

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10862)

Abstract

An N-parallel FENE-P constitutive model based on multiple relaxation times is proposed in this paper, which aims at accurately describing the apparent viscosity of viscoelastic fluid. The establishment of N-parallel FENE-P constitutive model and the numerical approach to calculate the apparent viscosity are presented in detail, respectively. To validate the performance of the proposed constitutive model, it is compared with the conventional FENE-P constitutive model (It only has single relaxation time) in estimating the apparent viscosity of two common viscoelastic fluids: polymer and surfactant solutions. The comparative results indicate the N-parallel FENE-P constitutive model can represent the apparent viscosity of polymer solutions more accurate than the traditional model in the whole range of shear rate (0.1 s−1–1000 s−1), and the advantage is more noteworthy especially when the shear rate is higher (10 s−1–1000 s−1). Despite both the proposed model and the traditional model can’t capture the interesting shear thickening behavior of surfactant solutions, the proposed constitutive model still possesses advantage over the traditional one in depicting the apparent viscosity and first normal stress difference. In addition, the N-parallel FENE-P constitutive model demonstrates a better applicability and favorable adjustability of the model parameters.

Keywords

FENE-P constitutive model N-parallel Viscoelastic fluids Multiple relaxation times Apparent viscosity 

Notes

Acknowledgements

The authors thank for support of National Natural Science Foundation of China (No. 51636006), project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges under Beijing Municipality (No. IDHT20170507), National Key R&D Program of China (Grant No. 2016YFE0204200) and the Program of Great Wall Scholar (CIT&TCD20180313).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechanical Engineering, Beijing Key Laboratory of Pipeline Critical Technology and Equipment for Deepwater Oil and Gas DevelopmentBeijing Institute of Petrochemical TechnologyBeijingChina
  2. 2.Computational Transport Phenomena Laboratory, Division of Physical Science and EngineeringKing Abdullah University of Science and TechnologyThuwalSaudi Arabia

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