Modeling melt conveying and power consumption of <scp>co‐rotating twin‐screw</scp> extruder kneading blocks: Part A. Data generation

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Intermeshing co‐rotating twin‐screw extruders are very versatile because their screw configurations can be tailored both to the application and to the properties of the materials used. Finding the best screw configuration is one of the main purposes of twin‐screw extrusion modeling, and requires models that accurately predict conveying and power consumption. The better the process can be predicted, the better the requirements of the final product can be met. We present novel prediction models of the conveying and power‐consumption behaviors of intermeshing co‐rotating twin‐screw extruder kneading blocks for Newtonian fluids. These are based on numerical simulations and therefore consider the complex three dimensional (3D) geometry of this element type without the need for common simplifications. Our models are thus capable of including all leakage flows and gap influences, which are usually ignored, for example, by the flat‐plate model. Since our models are derived by symbolic regression based on genetic programming, they consist of algebraic functions and are low‐threshold. They can be used to calculate various process parameters for individual kneading blocks or entire screw configurations, as illustrated by a use case.

Section: Preprocessingmentioning

confidence: 99%

A_{3}

as a function of the influencing parameters is plotted in Figure 1.…”

Section: Data‐based Modelingmentioning

confidence: 99%

Section: Data‐based Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The dimensionless geometry parameters, including the dimensionless diameter ratio

Π_{D}

, the staggering angle

α

, the dimensionless kneading disc width

Π_{B}

, and the dimensionless disc distance

Π_{s_{2}}

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modeling melt conveying and power consumption of co‐rotating twin‐screw extruder kneading blocks: Part B. Prediction models

Stritzinger

Roland

Berger‐Weber

et al. 2023

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Correction factors for the drag and pressure flows of power‐law fluids through rectangular ducts

Marschik

Roland

2023

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There are many industrial examples of low Reynolds number non-Newtonian flows through rectangular ducts in polymer processing. They occur in all types of manufacturing processes in which raw polymeric materials are converted into products, ranging from screw extrusion to shaping operations in dies and molds. In addition, they are found in numerous rheological measurement systems. The literature provides various mathematical formulations for non-Newtonian flows through rectangular ducts, but-if not simplified furthertheir solution usually requires use of numerical techniques. Removing the need for these time-consuming techniques, we present novel analytical correction factors for the drag and pressure flows of power-law fluids in rectangular flow channels. We approximated numerical results for a fully developed flow under isothermal conditions using symbolic regression based on genetic programming. The correction factors can be applied to the analytical theory that describes the flow of power-law fluids between parallel plates to include effects of the side walls in the prediction of flow rate and viscous dissipation.

Optimal design and operation of reactive extrusion processes: Modeling, model validation, and optimization algorithm

Cegla,

Engell

2023

In this work, a methodology for the optimal design and operation of reactive extrusion processes in twin‐screw extruders is presented. As a process model, a very accurate mechanistic finite volume twin‐screw extruder model is used which is adapted to the reactive extrusion case. In the model, in contrast to other models, the pressure is described as a differential state in order to have a consistent set of equations. The model is compared to other models and advantages and disadvantages with respect to accuracy and computation time are discussed. For optimization, a memetic optimization algorithm (MA) that consists of a combination of a local optimization for the continuous operating parameters and an evolutionary algorithm (EA) for the global optimization of the discrete decision variables is employed to overcome the drawback of the longer model simulation time compared to simpler models. A reduction of optimization time by 90% for the MA compared to the EA was observed. The presented modeling and optimization methodology is validated on the widely investigated reactive extrusion process for ε‐Caprolactone. The methodology is very flexible and the underlying model has good prediction characteristics, thus it is applicable to a wide range of reactive extrusion processes of industrial interest.Highlights Simulation and optimization of reactive extrusion. Improved mechanistic twin‐screw extruder model. Novel approaches for pressure and residence time modeling. Efficient combination of local and global optimization in a memetic algorithm. Benchmarking of the optimization results and performance with literature data.