Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance
This contribution provides a detailed comparison of the impact of various rheological models on the filling phase of injection molding simulations in order to enhance the accuracy of flow predictions and improve material processing. The challenge of accurately modeling polymer melt flow behavior und...
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MDPI AG
2024-09-01
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| author | Markus Baum Denis Anders Tamara Reinicke |
| author_facet | Markus Baum Denis Anders Tamara Reinicke |
| author_sort | Markus Baum |
| collection | DOAJ |
| description | This contribution provides a detailed comparison of the impact of various rheological models on the filling phase of injection molding simulations in order to enhance the accuracy of flow predictions and improve material processing. The challenge of accurately modeling polymer melt flow behavior under different temperature and shear rate conditions is crucial for optimizing injection molding processes. Therefore, the study examines commonly used rheological models, including Power-Law, Second-Order, Herschel-Bulkley, Carreau and Cross models. Using experimental data for validation, the accuracy of each model in predicting the flow front and viscosity distribution for a quadratic molded part with a PA66 polymer is evaluated. The Carreau-WLF Winter model showed the highest accuracy, with the lowest RMSE values, closely followed by the Carreau model. The Second-Order model exhibited significant deviations in the edge region from experimental results, indicating its limitations. Results indicate that models incorporating both shear rate and temperature dependencies, such as Carreau-WLF Winter, provide superior predictions compared to those including only shear rate dependence. These findings suggest that selecting appropriate rheological models can significantly enhance the predictive capability of injection molding simulations, leading to better process optimization and higher quality in manufactured parts. The study emphasizes the significance of comprehensive rheological analysis and identifies potential avenues for future research and industrial applications in polymer processing. |
| format | Article |
| id | doaj-art-c6f69e5b46bf47aebedfc27c1806a8e8 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-c6f69e5b46bf47aebedfc27c1806a8e82025-08-20T01:55:58ZengMDPI AGApplied Sciences2076-34172024-09-011418846810.3390/app14188468Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model PerformanceMarkus Baum0Denis Anders1Tamara Reinicke2Group for Computational Mechanics and Fluid Dynamics, Cologne University of Applied Sciences (TH Köln), Steinmüllerallee 1, 51643 Gummersbach, GermanyGroup for Computational Mechanics and Fluid Dynamics, Cologne University of Applied Sciences (TH Köln), Steinmüllerallee 1, 51643 Gummersbach, GermanyChair of Product Development, University of Siegen, Paul-Bonatz-Str. 9-11, 57068 Siegen, GermanyThis contribution provides a detailed comparison of the impact of various rheological models on the filling phase of injection molding simulations in order to enhance the accuracy of flow predictions and improve material processing. The challenge of accurately modeling polymer melt flow behavior under different temperature and shear rate conditions is crucial for optimizing injection molding processes. Therefore, the study examines commonly used rheological models, including Power-Law, Second-Order, Herschel-Bulkley, Carreau and Cross models. Using experimental data for validation, the accuracy of each model in predicting the flow front and viscosity distribution for a quadratic molded part with a PA66 polymer is evaluated. The Carreau-WLF Winter model showed the highest accuracy, with the lowest RMSE values, closely followed by the Carreau model. The Second-Order model exhibited significant deviations in the edge region from experimental results, indicating its limitations. Results indicate that models incorporating both shear rate and temperature dependencies, such as Carreau-WLF Winter, provide superior predictions compared to those including only shear rate dependence. These findings suggest that selecting appropriate rheological models can significantly enhance the predictive capability of injection molding simulations, leading to better process optimization and higher quality in manufactured parts. The study emphasizes the significance of comprehensive rheological analysis and identifies potential avenues for future research and industrial applications in polymer processing.https://www.mdpi.com/2076-3417/14/18/8468injection molding simulationcomputational fluid dynamicsAnsys CFXrheological modelsfilling phase |
| spellingShingle | Markus Baum Denis Anders Tamara Reinicke Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance Applied Sciences injection molding simulation computational fluid dynamics Ansys CFX rheological models filling phase |
| title | Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance |
| title_full | Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance |
| title_fullStr | Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance |
| title_full_unstemmed | Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance |
| title_short | Enhancing Injection Molding Simulation Accuracy: A Comparative Evaluation of Rheological Model Performance |
| title_sort | enhancing injection molding simulation accuracy a comparative evaluation of rheological model performance |
| topic | injection molding simulation computational fluid dynamics Ansys CFX rheological models filling phase |
| url | https://www.mdpi.com/2076-3417/14/18/8468 |
| work_keys_str_mv | AT markusbaum enhancinginjectionmoldingsimulationaccuracyacomparativeevaluationofrheologicalmodelperformance AT denisanders enhancinginjectionmoldingsimulationaccuracyacomparativeevaluationofrheologicalmodelperformance AT tamarareinicke enhancinginjectionmoldingsimulationaccuracyacomparativeevaluationofrheologicalmodelperformance |