Buildings, Volume 15, Issue 21
2025 November-1 - 205 articles
Cover Story: This study introduces a hybrid framework that combines full-scale experimental testing, finite element calibration, analytical homogenization, and machine learning surrogates for the mechanical characterization of composite panels. The approach enables the derivation of equivalent elastic and shear parameters from limited laboratory data and extends them through physics-informed AI models for fast prediction across diverse configurations. The proposed workflow bridges physical accuracy and computational efficiency, offering a practical tool for the design and optimization of modular composite structures. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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