About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
|
Symposium
|
Artificial Intelligence Applications in Integrated Computational Materials Engineering
|
Presentation Title |
Tuning Fracture Characteristics for Chiral Aperiodic Monotile Based Composites by Employing Multi-Objective Bayesian Optimization |
Author(s) |
Jiyoung Jung, Kundo Park, Grace Gu |
On-Site Speaker (Planned) |
Jiyoung Jung |
Abstract Scope |
Developing advanced materials with superior mechanical properties is essential for different engineering applications. This study presents innovative composite structures designed by using chiral aperiodic monotile patterns, distinguished by their curved edges. By adjusting the topology, volume fraction, and constituent materials, we demonstrate a significant enhancement in the fracture properties of these aperiodic composites. Pareto-optimal designs are chosen for experimental validation through additive manufacturing and mechanical testing. The results reveal that these aperiodic composites exhibit enhanced properties, including increased strength, toughness, and failure strain, due to the superior interlocking effect of the curved edges. Furthermore, our findings indicate that the toughening mechanisms and crack propagation paths of these aperiodic composites are tunable, allowing for overcoming certain trade-offs in mechanical properties. This research highlights the potential of this novel composite family based on aperiodic monotiles, paving the way for the development of high-performance structural materials. |
Proceedings Inclusion? |
Planned: |
Keywords |
Machine Learning, Computational Materials Science & Engineering, Additive Manufacturing |