Monotonicity-constrained physics-informed neural networks for concrete compressive strength prediction
Accurate prediction of concrete compressive strength is critical for mix design optimization, quality control, and reliable decision-making in modern construction. While data-driven machine learning models have demonstrated strong predictive capability, most existing approaches treat concrete behavior as a purely stati...