Enhancing extrusion die design efficiency through high-performance computing based optimization

Mohammadreza Aali, João Miguel Nóbrega, João Vidal, Joel Oliveira, A. Sacramento, Alberto Srivastava, Marta Sacramento

Research output: Contribution to journalArticlepeer-review

Abstract

This work presents a new computational framework for designing profile extrusion dies. The framework utilizes High-Performance Computing (HPC) resources to optimize parameterized die flow channels within a one-day time-frame, resulting in a significant reduction in the typical design time required for profile extrusion dies. By employing objective function-controlled convergence criteria, the framework achieved a 50% reduction in calculation time compared to runs where only the unknowns residuals were considered for the same purpose. Furthermore, it offers full optimization capability, requiring no user intervention once the CAD parameterization is complete. OpenFOAM and Dakota were employed for modeling and optimization, respectively. Fusion 360 and Onshape CAD software were used for drawing and parameterizing the flow channel. By leveraging HPC systems, the optimization framework can automatically test hundreds of alternative geometries within one day to find the optimal solution. This research demonstrates the feasibility and advantages of HPC-driven extrusion die optimization, which contributes to increased efficiency and competitiveness in the manufacturing industry.
Original languageEnglish
Number of pages12
JournalMeccanica
Publication statusPublished - Dec 2024

Fields of science

  • 205 Materials Engineering
  • 205011 Polymer engineering
  • 102009 Computer simulation
  • 102033 Data mining
  • 104018 Polymer chemistry
  • 502059 Circular economy
  • 205012 Polymer processing
  • 104019 Polymer sciences
  • 502058 Digital transformation

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management

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