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Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion

Generally, numerical methods are required to model the non-Newtonian flow of polymer melts in single-screw extruders. Existing approximation equations for modeling the throughput–pressure relationship and viscous dissipation are limited in their scope of application, particularly when it comes to sp...

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Autores principales: Roland, Wolfgang, Kommenda, Michael, Marschik, Christian, Miethlinger, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419227/
https://www.ncbi.nlm.nih.gov/pubmed/30960318
http://dx.doi.org/10.3390/polym11020334
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author Roland, Wolfgang
Kommenda, Michael
Marschik, Christian
Miethlinger, Jürgen
author_facet Roland, Wolfgang
Kommenda, Michael
Marschik, Christian
Miethlinger, Jürgen
author_sort Roland, Wolfgang
collection PubMed
description Generally, numerical methods are required to model the non-Newtonian flow of polymer melts in single-screw extruders. Existing approximation equations for modeling the throughput–pressure relationship and viscous dissipation are limited in their scope of application, particularly when it comes to special screw designs. Maximum dimensionless throughputs of [Formula: see text] , implying minimum dimensionless pressure gradients [Formula: see text] for low power-law exponents are captured. We present analytical approximation models for predicting the pumping capability and viscous dissipation of metering channels for an extended range of influencing parameters ([Formula: see text] , and [Formula: see text]) required to model wave- and energy-transfer screws. We first rewrote the governing equations in dimensionless form, identifying three independent influencing parameters: (i) the dimensionless down-channel pressure gradient [Formula: see text] , (ii) the power-law exponent [Formula: see text] , and (iii) the screw-pitch ratio [Formula: see text]. We then carried out a parametric design study covering an extended range of the dimensionless influencing parameters. Based on this data set, we developed regression models for predicting the dimensionless throughput-pressure relationship and the viscous dissipation. Finally, the accuracy of all three models was proven using an independent data set for evaluation. We demonstrate that our approach provides excellent approximation. Our models allow fast, stable, and accurate prediction of both throughput-pressure behavior and viscous dissipation.
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spelling pubmed-64192272019-04-02 Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion Roland, Wolfgang Kommenda, Michael Marschik, Christian Miethlinger, Jürgen Polymers (Basel) Article Generally, numerical methods are required to model the non-Newtonian flow of polymer melts in single-screw extruders. Existing approximation equations for modeling the throughput–pressure relationship and viscous dissipation are limited in their scope of application, particularly when it comes to special screw designs. Maximum dimensionless throughputs of [Formula: see text] , implying minimum dimensionless pressure gradients [Formula: see text] for low power-law exponents are captured. We present analytical approximation models for predicting the pumping capability and viscous dissipation of metering channels for an extended range of influencing parameters ([Formula: see text] , and [Formula: see text]) required to model wave- and energy-transfer screws. We first rewrote the governing equations in dimensionless form, identifying three independent influencing parameters: (i) the dimensionless down-channel pressure gradient [Formula: see text] , (ii) the power-law exponent [Formula: see text] , and (iii) the screw-pitch ratio [Formula: see text]. We then carried out a parametric design study covering an extended range of the dimensionless influencing parameters. Based on this data set, we developed regression models for predicting the dimensionless throughput-pressure relationship and the viscous dissipation. Finally, the accuracy of all three models was proven using an independent data set for evaluation. We demonstrate that our approach provides excellent approximation. Our models allow fast, stable, and accurate prediction of both throughput-pressure behavior and viscous dissipation. MDPI 2019-02-14 /pmc/articles/PMC6419227/ /pubmed/30960318 http://dx.doi.org/10.3390/polym11020334 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Roland, Wolfgang
Kommenda, Michael
Marschik, Christian
Miethlinger, Jürgen
Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
title Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
title_full Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
title_fullStr Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
title_full_unstemmed Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
title_short Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
title_sort extended regression models for predicting the pumping capability and viscous dissipation of two-dimensional flows in single-screw extrusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419227/
https://www.ncbi.nlm.nih.gov/pubmed/30960318
http://dx.doi.org/10.3390/polym11020334
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