An Experimental–Statistical Framework for Time-Dependent Strength Evolution: Self-Compacting Concrete with Recycled Materials as a Case Study

Reliable prediction of concrete strength development is important for mixture design and performance assessment, yet conventional experimental–statistical approaches often describe strength at discrete curing ages or require separate calibration for different material systems. This study develops and evaluates an experimental–statistical model for describing time-dependent compressive and flexural strength evolution by integrating mixture composition, curing age, and strength normalization within a common regression formulation. Self-compacting concrete incorporating recycled brick powder, recycled fine aggregate, and Na2SO4 activation was used as the primary experimental system. The experimental database combined the previously investigated mixtures with newly obtained 90-day compressive and flexural strength data. Using the resulting dataset, strength development was normalized with respect to the corresponding 28-day reference strengths and represented using alternative time-dependent functions. A second-order logarithmic function provided the best representation of the normalized strength trajectories, with R2 values of 0.999 for compressive strength and 0.983 for flexural strength. Unified regression models incorporating mixture-design factors, curing age, and composition–time interactions were subsequently developed for the investigated experimental system. Model performance and applicability were assessed through leave-one-mixture-out cross-validation, blind validation, and independent literature datasets covering different mixture compositions, experimental designs, and curing-age ranges. The results show that normalization provides a common representation of relative strength development across the investigated cement-based systems, while mixture composition remains relevant to the evolution of normalized strength. The findings support the use of the proposed experimental–statistical model as an engineering modeling framework for describing and predicting normalized compressive and flexural strength development from experimentally available data. When combined with a reference strength, the formulation can also be used to estimate absolute strength over the investigated curing-age range.