4.7 Article

In-line viscosity identification via thermal-rheological measurements in an annular duct for polymer processing

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2021.121988

关键词

In-line; Pseudo-plastic; Viscosity; Inverse method; Annular flow; Power law

资金

  1. French Ministry of Higher Education, Research and Innovation
  2. GEPEA Laboratory (IUT Nantes)

向作者/读者索取更多资源

This study proposes several inverse method strategies for estimating the viscosity of a fluid during an injection process through thermal-rheological measurements. The central axis of an annular duct provides robust thermal measurements that can be correlated to the fluid viscosity. The main advantage of these strategies is that flowrate modulation is not necessary for viscosity estimation.
In-line/on-line characterization is more and more important for more flexible and reactive production during the polymer processing. Conventional duct geometries have some disadvantages in terms of measurement efficiency. In this work, several strategies for inverse method are proposed to estimate the viscosity during an injection process via thermal-rheological measurements in an annular duct, which can be positioned downstream of the screw and combined with an axisymmetric model for further in line monitoring application. The central axis of an annular duct provides sensitive and robust thermal measurements, which can be correlated to the viscosity of the fluid. By analyzing the viscous heating, the heat convection and the pressure loss, the viscosity curve of a power-law fluid can be identified. The identification, involving thermal measurements, can be unsusceptible to the non-homogeneous inlet temperature profile caused by the screw. And the main advantage of these strategies is that the flowrate doesn't necessarily need to be modulated for the identification. That allows in-line viscosity estimation with a poorly known inlet temperature without interfering the production cadence. (c) 2021 Elsevier Ltd. All rights reserved.

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