Zur Hauptnavigation wechseln Zur Suche wechseln Zum Hauptinhalt wechseln

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

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

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.
OriginalspracheEnglisch
Seiten (von - bis)1521-1532
Seitenumfang12
FachzeitschriftMeccanica
Volume60
Ausgabenummer6
DOIs
PublikationsstatusVeröffentlicht - Dez. 2024

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 9 – Industrie, Innovation und Infrastruktur
    SDG 9 – Industrie, Innovation und Infrastruktur

Wissenschaftszweige

  • 205 Werkstofftechnik
  • 205011 Kunststofftechnik
  • 102009 Computersimulation
  • 102033 Data Mining
  • 104018 Polymerchemie
  • 502059 Kreislaufwirtschaft
  • 205012 Kunststoffverarbeitung
  • 104019 Polymerwissenschaften
  • 502058 Digitale Transformation

JKU-Schwerpunkte

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management

Dieses zitieren