Extended melt-conveying models for single-screw extruders: Integrating domain knowledge into symbolic regression

Christian Marschik, Wolfgang Roland, Michael Kommenda

Research output: Contribution to journalArticlepeer-review

Abstract

The literature provides several analytical approximation methods for predicting the flow of non-Newtonian fluids in single-screw extruders. While these are based on various flow conditions, they were developed mostly for extruder screws with standard geometries. We present novel analytical melt-conveying models for predicting the flow and dissipation rates of fully developed flows of power-law fluids within three-dimensional screw channels. To accommodate a broad range of industrial screw designs, including both standard and high-performance screws, the main intention of this work was to significantly extend the scope of existing theories. The flow equations were first rewritten in a dimensionless form to reduce the mathematical problem to its dimensionless influencing parameters. These were varied within wide ranges to create a set of physically independent modeling setups, the flow and dissipation rates of which were evaluated by means of a finite-volume solver. The numerical results were then approximated analytically using symbolic regression based on genetic programming. To support the regression analysis in finding accurate solutions, we integrated domain-specific process knowledge in the preprocessing of the dataset. We obtained three regression models for predicting the flow and dissipation rates in melt-conveying zones and tested their accuracy successfully against an independent set of numerical solutions. Highlights: Flow of power-law fluids in three-dimensional screw channels Identification of independent influencing parameters by dimensional analysis Numerical parametric design study for a broad range of industrial applications Integration of domain knowledge in symbolic regression Surrogate models derived from numerical simulation results.

Original languageEnglish
JournalPolymer Engineering and Science
DOIs
Publication statusAccepted/In press - 2023

Keywords

  • extrusion
  • modeling
  • processing
  • simulations

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