Predictive Modeling of Ductile-to-Brittle Transition in Hierarchical RC Frames: A Comparative Study of Deep Learning and Machine Learning Surrogate Models

Abstract

This research addresses the critical challenge of progressive collapse in Reinforced Concrete (RC) frames by establishing a rigorous multi-scale link between material fracture mechanics and macroscale structural hierarchy. The study investigates the highly non-linear 'Ductile-to-Brittle' transition, identifying two dimensionless ratios as the fundamental governing parameters: the Geometric Ratio (a/H), which marks the onset of brittle behavior at a threshold of approximately 0.5, and the Energetic Ratio (L

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