Experimental and Physics-Informed Synthetic Dataset for Mechanical Properties and Failure Modes of FRP Coupons

This dataset comprises both experimental and physics-informed synthetic data related to the mechanical properties and failure modes of FRP coupons. The experimental data were compiled from peer-reviewed publications spanning 1998-2025 and include key input parameters such as coupon geometry, material properties, specimen configuration, and test methods, along with corresponding outputs (mechanical properties and failure modes). To address data scarcity and enhance analytical capability, high-fidelity synthetic datasets were generated using a Physics-Informed Tabular Variational Autoencoder (PI-TVAE). The quality and reliability of the synthetic data were rigorously evaluated against the experimental dataset using multiple statistical measures, including range comparison (minimum and maximum), standard deviation, Kolmogorov–Smirnov test, entropy difference, and Cramér’s V. The results confirm that the synthetic data closely replicate the statistical characteristics and dependency structures of the experimental data. This dataset is intended to support research in: Development of probabilistic machine learning models for predicting mechanical properties and failure modes of FRP coupons Uncertainty quantification in material performance and structural behavior Data-driven and automated design in structural and civil engineering Benchmarking and validation of generative modeling approaches in engineering applications All datasets are provided in .xlsx format to ensure accessibility, reproducibility, and ease of reuse by the research community.