INVESTIGATION INTO AI-ASSISTED OPTIMIZATION OF THIN-WALLED CROSS-SECTIONS
DOI:
https://doi.org/10.30888/2709-2267.2025-31-00-018Keywords:
Artificial intelligence, Machine learning, Permanent formwork, Cross-section optimization, Surrogate modeling, Generative Design, Physics-informed neural networks, multi-fidelity data integration, Structural health monitoring, Hybrid AI-FEA workflows.Abstract
This research reviews the integration of artificial intelligence in structural cross-section selection, highlighting supervised learning, reinforcement learning, evolutionary algorithms, and physics-informed models as complementary methodologies. SupervisReferences
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