QUADROTOR FRAME TOPOLOGY OPTIMIZATION: ANSYS DISCOVERY VS FUSION GENERATIVE DESIGN

Authors

  • Murat Taflan Lecturer, Faculty of Aeronautics and Aerospace, Gaziantep University, Gaziantep, Türkiye
  • Ünal Hayta Lecturer, Faculty of Aeronautics and Aerospace, Gaziantep University, Gaziantep, Türkiye
  • Gökhan Ateş Lecturer, Department of Mechanical Engineering, Abdullah Gül University, Kayseri, Türkiye

DOI:

https://doi.org/10.20319/stra.2025.125142

Keywords:

Topology Optimization, Drone, Quadrotor, ANSYS Discovery, Generative Design

Abstract

This study compares topology optimization of an additively manufacturable quadrotor frame using ANSYS Discovery (level-set) and Autodesk Fusion Generative Design under a shared domain, loads, supports, and printing guards: minimum-compliance objective, nominal mass target, 45° overhang limit, and 1.5 mm minimum thickness. In Discovery, increasing the volume-reduction target from 95 to 98 percent yields progressively truss-like morphologies and reduces modeled mass from 3.91 to 1.47 kg while approaching the thickness guard. In Fusion, varying outcome resolution and adding an explicit deflection constraint expose stiffness–mass trades: at nearly equal mass around 0.31–0.32 kg, predicted static deflection drops from 17.86 to 9.824 mm when lowering outcome resolution; enforcing a maximum-deflection requirement increases mass to 0.596 kg and lowers deflection to 1.496 mm. Absolute cross-solver masses are not directly comparable due to modeling and reporting differences, yet the trends show that solver settings can shift stiffness substantially without large mass penalties and that aggressive pruning risks manufacturability. The present baseline uses a single 2g vertical load and a fixed center of gravity. Future work will introduce combined load cases and CG variation and will validate and extend the workflow with ANSYS Mechanical static structural analysis and optimization.

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Published

2025-12-22

How to Cite

Murat Taflan, Ünal Hayta, & Gökhan Ateş. (2025). QUADROTOR FRAME TOPOLOGY OPTIMIZATION: ANSYS DISCOVERY VS FUSION GENERATIVE DESIGN. MATTER: International Journal of Science and Technology, 125–142. https://doi.org/10.20319/stra.2025.125142