Innovative uncertainty-aware probabilistic framework for quantification of fiber-reinforced cementitious matrix-concrete bond

• Developed a data-augmented probabilistic framework to predict FRCM–concrete bond behaviour with quantified uncertainty. • Integrated synthetic data generation, deterministic/probabilistic models, uncertainty propagation, and SHAP analysis. • NGB model trained on synthetic data showed superior calibration and accuracy (testing MAPE ≈7.61%). • Operationalized validated model in DAB-FRCM tool for risk-informed design and reduced experimental burden. Fiber-reinforced cementitious matrix (FRCM) com