scholarly journals Computational Scale-Up for Flood Fed/Starve Fed Single Screw Extrusion of Polymers

Polymers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 240
Author(s):  
Andrzej Nastaj ◽  
Krzysztof Wilczyński
Keyword(s):  
Genetic Algorithms ◽  
Objective Function ◽  
Process Parameters ◽  
Scale Up ◽  
Scaling Up ◽  
Extrusion Process ◽  
Functional Dependencies ◽  
Single Screw ◽  
Single Screw Extrusion ◽  
Screw Extrusion

A novel scaling-up computer system for single screw extrusion of polymers has been developed. This system makes it possible to scale-up extrusion process with both starve feeding and flood feeding. Each of the scale-up criteria can be an objective function to be minimized, represented by single values or functional dependencies over the screw length. The basis of scaling-up is process simulation made with the use of the GSEM program (Global Screw Extrusion Model). Scaling-up is performed using the GASES program (Genetic Algorithms Screw Extrusion Scaling) based on Genetic Algorithms. Scaling-up the extrusion process has been performed to increase extrusion output according to the scaling-up criteria defined by the single parameters of unit energy consumption, polymer plasticating rate and polymer temperature, as well as by the process parameters profiles of the temperature and plasticating. The global objective function reached the lowest value for the selected process parameters, and extrusion throughput was significantly increased.

SSEM-AG Computer Model for Optimization of Polymer Extrusion

2006 ◽  
Author(s):  
K. Wilczynski ◽  
A. Nastaj
Keyword(s):  
Power Consumption ◽  
Extrusion Process ◽  
Global Optimum ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Melt Temperature ◽  
Local Optima ◽  
Single Screw ◽  
Single Screw Extrusion ◽  
Screw Extrusion

The optimization of an extrusion process is a conflicting, multi-objective problem. It is complicated by the number of variables (screw/die geometry, operating conditions, material data) and their non-linear relations, as well as by the opposing criteria, for example extrusion throughput and power consumption. It is difficult to find the global optimum for the process avoiding local optima. There are two approaches to solve the problem, experimental and using a mathematical model of extrusion. Optimization techniques based on an experimentation are time-consuming and very expensive. In this paper we present an optimization methodology based on the Genetic Algorithms (AG), where response surface is given by the extrusion model. A mathematical Single-Screw Extrusion Model SSEM developed at the Warsaw University of Technology is used to predict the extruder behavior, and AG approach is used for optimization. An integrated SSEM-AG system was developed to study optimization of the single-screw extrusion process. Three design criteria (output variables) are selected for optimization: maximum extrusion throughput, minimum power consumption and low melt temperature. As input variables, screw speed, barrel temperature and screw channel depth are chosen.

scholarly journals Optimization and Scale-Up for Polymer Extrusion

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1547
Author(s):  
Andrzej Nastaj ◽  
Krzysztof Wilczyński
Keyword(s):  
Genetic Algorithms ◽  
Process Simulation ◽  
Scale Up ◽  
Optimization Techniques ◽  
Twin Screw Extrusion ◽  
Polymer Extrusion ◽  
Single Screw ◽  
Reference Process ◽  
Screw Extrusion ◽  
Twin Screw

A review paper is presented on optimization and scale-up for polymer extrusion, both single screw and twin screw extrusion. Optimization consists in obtaining a multidimensional space of process output variables (response surface) on the basis of an appropriate set of input data and searching for extreme values in this space. Scaling consists in changing the scale of the process according to specific criteria, that is, changing the process while maintaining the scaling parameters at a level that is as close to the reference process parameters as possible. It consists in minimizing the differences between the parameters characterizing the reference process and the resulting process. This may be obtained by using optimization techniques leading to the minimization of discrepancies between the parameters of scaled processes. In the paper, it was stated that optimization and scale-up based on process simulation are more effective than those based on experimentation which is time consuming and expensive. The state-of-the-art on extrusion process modeling which is the basis of optimization and scale-up has been presented. Various optimization techniques have been discussed, and the Genetic Algorithms have been identified as powerful and very efficient. Optimization and scale-up based on the process simulation using Genetic Algorithms have been broadly reviewed and discussed. It was concluded that, up to date, there is a lack of optimization studies on the counter-rotating twin screw extrusion, although the global models of this process are known. There is also a lack of process simulation-based scaling-up studies, both on the counter-rotating twin screw extrusion and on the starve fed single screw extrusion. Finally, development perspectives in this field have been discussed.

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