• Steel and Composite Structures
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• 제53권4호
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• pp.443-460
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• 2024

This study develops Titanium (Ti) and Magnesium (Mg)-based nano-alloys to enhance the earthquake resilience of steel structures using machine learning (SVM) and sensor technology. Embedding Ti and Mg into steel at the nanoscale creates a lightweight, durable, and flexible material capable of withstanding seismic forces. Ti enhances tensile strength and flexibility, while Mg reduces weight, lowering seismic loads on buildings. The performance of these nano-alloys was assessed through shake table tests, cyclic load testing, and dynamic response testing, showing that nano-alloy-enhanced steel structures experienced 60% less displacement and 40% lower acceleration than traditional steel, demonstrating superior energy absorption and stress distribution. Fatigue tests revealed that the nano-alloy could endure 20,000 loading cycles, outperforming the 8,000 cycles of conventional steel. Integrated sensor technology, including strain gauges and accelerometers, provided real-time stress and deformation data, confirming the material's effectiveness in stress distribution and vibration damping. The SVM model optimized alloy composition, achieving 94% prediction accuracy in assessing seismic performance, highlighting the nano-alloys' durability and resilience. This study suggests that Ti and Mg nano-alloys could greatly improve earthquake-resistant construction.