ArticlePolymers2023
Improved Optimization of a Coextrusion Die with a Complex Geometry Using the Coupling Inverse Design Method.
Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Anisotropic Extrudate Swell from a Slit Die: A Velocity-Centre Hypothesis and Numerical Verification.Polymers · 2026Article
- A Novel Approach to Automatically Balance Flow in Profile Extrusion Dies Through Computational Modeling.Polymers · 2025Article
- Article
- Coating Extrusion Characteristics of Thin-Walled Tubes for Catheters Using Thermoplastic Elastomer.Polymers · 2025Article
- Compliance Prediction for Structural Topology Optimization on the Basis of Moment Invariants and a Generalized Regression Neural Network.Entropy (Basel, Switzerland) · 2023Article
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3 authors.
Funding
Abstract
The main challenge in a polymer coextrusion process is to have a good die design prior to the process, which can minimize the geometric errors that are caused by extrusion swell and interface motion. For this purpose, a coupling method of optimization and inverse design for a coextrusion die was studied for a medical striped catheter. In the study, the main material was thermoplastic polyurethane (TPU), and the auxiliary material was TPU filled with 30 wt% barium sulfate. An overall optimization design method was used to optimize the geometry of the extrusion die channel for the striped catheter, which had a complex geometry. In the global optimization process, the local inverse design method was used to design the inlet of the auxiliary material. The non-linear programming by quadratic Lagrangian (NLPQL) algorithm was used to obtain the optimal geometric solution of the coextrusion die runner. The experimental verification results showed that the coupling method for coextrusion die design improved the design efficiency of the coextrusion die remarkably. The value of the objective function, which was used to measure the geometric error of the product, was reduced by 72.3% compared with the initial die design.
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