Multifactor Interactive Response and SMDPI Predictive Model Development for Cutter Suction Dredging in Heterogeneous Sediment

This study conducted physical model experiments based on a Box-Behnken response surface design to systematically evaluate the interactive effects of cutterhead rotational speed, tooth quantity, and operational depth on sediment disturbance and suction concentration across silt, clay, and sand. Results demonstrate that silt is highly sensitive to mechanical disturbance, clay exhibits a marked increase in yield near 225 r/min (based on the fitted response surface), and sand yield is speed-dominated but constrained by mechanical shielding effects. Integrating the entropy weight method with a soil-specific sensitivity coefficient, we propose the Soil-Modified Dredging Performance Index (SMDPI), Notably, the SMDPI model achieves a reliable engineering approximation, with the relative error between the predicted and physically measured SMDPI values strictly constrained below 10%. This research elucidates multi-factor coupled mechanisms of sediment disturbance and extraction, providing a theoretical and empirical framework for the intelligent regulation and dynamic parameter optimization of eco-friendly dredging operations across diverse soil conditions. From a management perspective, these findings translate into soil-specific operational guidelines and a potential conceptual framework for decision-support for reservoir operators seeking to balance dredging throughput against turbidity-related environmental compliance.