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International Journal of Advanced Engineering Application

ISSN: 3048-6807

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Generative Design and AI Driven Topology Optimization for Sustainable Aerospace Structures

Author(s):Sophia Chen, Marcus Thorne, Yuki Tanaka

Affiliation: Department of Mechanical and Product Design Engineering, Swinburne University of Technology, Australia

Page No: 57-61

Volume issue & Publishing Year: Volume 3, Issue 2, 2026-02-25

Journal: International Journal of Advanced Engineering Application (IJAEA)

ISSN NO: 3048-6807

DOI: https://doi.org/10.5281/zenodo.18814260

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Abstract:
The aerospace industry is undergoing a structural revolution driven by the integration of Artificial Intelligence (AI) and Additive Manufacturing (AM). Traditional subtractive manufacturing often results in "over-engineered" components that carry unnecessary weight. This paper explores the application of Generative Design algorithms and Topology Optimization (TO) to radically reduce the mass of load-bearing aircraft brackets and engine mounts. By utilizing Physics-Informed Neural Networks (PINNs), we demonstrate a 45% reduction in component weight while maintaining the structural integrity and fatigue life required by 2026 FAA safety standards. The study further analyzes the transition from "Design-for-Manufacturing" to "Design-for-Performance," highlighting how AI can synthesize complex bio-mimetic geometries that were previously impossible to produce. Our results provide a framework for the next generation of "Ultra-Light" aircraft, providing a technical path to carbon-neutral aviation.

Keywords: Generative Design, Topology Optimization (TO), Aerospace Engineering, Additive Manufacturing (AM), Physics-Informed Neural Networks (PINNs), Structural Health Monitoring, Biomimetic Engineering, Sustainable Aviation

Reference:

  • [1] A. Singh, "Neural Network Architectures for Structural Synthesis in Aerospace," Journal of Advanced Mechanical Design, vol. 14, no. 1, pp. 22–38, Jan. 2026.
  • [2] S. Chen and M. Thorne, "Fatigue Life Assessment of 3D Printed Titanium Brackets," International Journal of Aerospace Engineering Science, vol. 11, pp. 95–110, Nov. 2025.
  • [3] Y. Tanaka, "Resonant Frequency Shifting in Topology Optimized Engine Mounts," Applied Mechanics and Vibrations Review, vol. 19, no. 4, pp. 201–215, Feb. 2026.
  • [4] R. Miller, "Sustainable Aviation via Additive Manufacturing and AI," Clean Transit Technology Reports, vol. 7, no. 2, pp. 45–59, Oct. 2025.
  • [5] K. Patel, "Physics-Informed Neural Networks for Real-Time Stress Prediction," Computational Structures Journal, vol. 33, pp. 110–124, Dec. 2024.
  • [6] J. Zhao, "Biomimetic Geometry and Load Path Convergence in Aerospace Design," Nature-Inspired Engineering Quarterly, vol. 5, pp. 12–28, Jan. 2026.
  • [7] L. Fisher, "Certification Challenges for AI-Generated Flight Components," Aviation Safety and Policy Journal, vol. 22, no. 3, pp. 301–318, Sept. 2025.
  • [8] D. White, "Laser Powder Bed Fusion of Grade 5 Titanium for Flight Hardware," Advanced Materials for 3D Printing, vol. 14, pp. 67–82, Nov. 2025.
  • [9] G. Schmidt, "Digital Twin Verification in High-Precision Metal Additive Manufacturing," Quality Control and Metrology, vol. 10, no. 1, pp. 5–19, Jan. 2026.
  • [10] H. Yamada, "Thermal Warping Suppression in Complex Lattice Structures," Journal of Thermal Engineering and Design, vol. 28, pp. 150–164, Oct. 2025.
  • [11] P. Lewis, "The Economics of Weight Reduction in Commercial Aviation," Global Logistics and Fuel Efficiency Review, vol. 13, no. 2, pp. 88–101, June 2025.
  • [12] T. Ivanov, "Level-Set Methods vs. SIMP in Topology Optimization," Theoretical and Applied Mechanics, vol. 41, pp. 220–235, Dec. 2025.
  • [13] M. Sato, "High-Cycle Fatigue Testing of Biomimetic Aerospace Joints," Journal of Structural Integrity, vol. 18, no. 4, pp. 112–126, Jan. 2026.
  • [14] E. Brown, "Generative Design Constraints for Next-Generation Nacelles," Aerospace Component Review, vol. 30, no. 1, pp. 55–70, Jan. 2026.
  • [15] R. Wilson, "Machine Learning Surrogates for Finite Element Analysis," Journal of Computational Physics in Engineering, vol. 25, pp. 180–195, Nov. 2025.