Experimental and Synthetic Datasets for FRCM-to-Concrete Bond Behaviour Prediction

This dataset contains both experimental and synthetic data related to the bond strength performance of fabric-reinforced cementitious matrix (FRCM) systems applied to concrete substrates. Experimental data were sourced from the published articles from 2012-2024 on single and double lap shear tests, including relevant input parameters (e.g., geometric properties, material properties, and load conditions) and corresponding bond strength outputs. To validate the experimental findings, synthetic datasets were generated using CTGAN and TVAE generative models. Synthetic datasets were assessed for verifying that statistical properties, i.e., minimum and maximum, SD KS and T-test values of all input and output feature of the synthetic datasets were closely matching with the experimental dataset (only for TVAE synthesizer). The dataset is intended to support research in:Development of deterministic and probabilistic learning models for bond behaviour prediction,Quantification of FRCM-to-concrete bond behaviour with uncertainty,Automation of structural engineering design, andBenchmarking of civil engineering generative modeling approaches.All datasets are provided in .xlsx format to ensure reproducibility and facilitate reuse.