About this Abstract |
| Meeting |
2027 TMS Annual Meeting & Exhibition
|
| Symposium
|
Biomedical Materials and Devices: From Laboratory to Market
|
| Presentation Title |
Closed-Loop Bayesian Optimization of Multi-Material 3D-Printed Tensegrity Crutch-Tip Impact Absorbers |
| Author(s) |
Jinkwan Han, Marcus E. Madsen, Audrey K. Christiansen, Sterling G. Baird, Jeffrey R. Hill |
| On-Site Speaker (Planned) |
Jinkwan Han |
| Abstract Scope |
Long-term crutch users load each crutch to ~0.5 body weights during partial-weight-bearing gait and suffer substantial upper-extremity overuse injury, yet commercial tips predominantly use rubber ferrules, while spring dampers add bulk without architected tunability. We present a generalizable closed-loop, multi-objective Bayesian-optimization pipeline for multi-material additive manufacturing, using the crutch-tip impact absorber as a low-regulatory-risk demonstrator. Pairing rigid PLA struts with elastomeric TPU in tensegrity-inspired lattices, we co-optimize unit-cell topology, strut diameter, relative density, and prestress—exploiting buckling-induced load-limiting plateaus and viscoelastic hysteresis—to maximize specific energy absorption and minimize peak force under quasi-static, impact, and cyclic gait loading, aiming to exceed a rubber ferrule's negligible absorption. Prior-art review identified no tensegrity-based crutch-tip absorber; an anticipated 510(k)-exempt Class I pathway (21 CFR 890.3790) and ISO 11334-1 verification let us mature the design-to-market loop. This architected-lattice, multi-material framework transfers to higher-stakes additively manufactured implant lattices, where fatigue resistance and stress-shielding mitigation dominate. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Machine Learning, Other |