Abstract
Shotcrete is critical for providing rapid support and deformation control in drill-and-blast tunnel construction; however, the suppression of its rebound from the rock surfaces remains a persistent challenge in practice. This study developed a real-time shotcreting simulation engine based on the position-based dynamics algorithm. A staged physical–virtual calibration strategy is proposed to identify key parameters across velocity regimes: low-velocity fluid and collision parameters governing deformation, rheological, and adhesion behaviors are calibrated using dynamic slump and inclined-plate tests, whereas high-velocity jet-flow parameters governing transport, impact, and rebound are calibrated using jet mass-field and velocity-field measurements. This calibration workflow links observable responses to the dominant behaviors in different velocity regimes and enables the engine to reproduce both low-velocity deformation/adhesion and high-velocity jetting/rebound processes. Using the calibrated model, the spatial pattern of rebound can be reproduced and assessed quantitatively. Field validation in the Yangjiawopu Tunnel demonstrated excellent agreement between simulation and measurement results, with a maximum local error of 13.7% at the near-wall location where rebound was the highest. The proposed approach maintained stable real-time computation, achieving 38 fps for a 2 m × 2 m wall section. Overall, this simulation engine provides a physically grounded and computationally efficient basis for smart shotcreting in tunnel excavation, supporting future integration with sensing, automation, and digital-twin-based construction control.