Modeling solid color reinforced composite aggregates and concrete-steel bond strength properties with novel computations

This study presents a computational framework for modeling solid-color reinforced composite aggregates and concrete–steel bond strength using a physics-informed and data-driven simulation strategy. The approach integrates experimental observations with a structured model-development protocol that formalizes hypothesis testing, parameter calibration, and validation pathways to enhance reproducibility and transparency. The framework enables systematic investigation of interactions among silica-fume-modified cement matrices, rubberized aggregates, and steel reinforcement interfaces. A series of nonlinear computational models is established to predict compressive strength, tensile performance, and bond stress–slip relationships. The models are calibrated using experimental datasets and refined through iterative evaluation of competing constitutive assumptions, improving both predictive robustness and mechanistic interpretability. Results indicate that composite aggregate incorporation significantly modifies interfacial stress transfer mechanisms, leading to enhanced bond strength and ductility under optimized silica fume content. Compared with conventional empirical fitting approaches, the proposed modeling framework reduces parameter uncertainty and demonstrates improved generalization across material configurations. The methodology provides a scalable basis for the design and evaluation of sustainable composite concrete systems with improved structural reliability and interface performance.