Reduction of material usage in 3D printable structures using topology optimization accelerated with U-Net convolutional neural network

• Main Authors: Rasulzade, J., Maksum, Y., Nogaibayeva, M., Rustamov, S., Akhmetov, Bakytzhan
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Material reduction; 3D printing
• Online Access: https://hdl.handle.net/10356/173663
• Institution: Nanyang Technological University

Today’s 3D printers allow the creation of very advanced structures from various materials, starting from simple plastics up to metal alloys. Since the printing time and amount of material used to create structures are considered very important in terms of cost and energy consumption, it is better to...