Synergistic Mechanisms and Operational Parameter Optimization of Excavation–Muck Removal Systems in AGF Shaft Sinking

Shaft sinking in soft, water-rich strata frequently suffers from low cutting efficiency, cycle-time mismatches between excavation and muck removal, and weak system-level coordination. To elucidate the synergistic mechanisms governing excavation–muck removal interactions and to realize end-to-end performance gains, we investigate the East Ventilation Shaft of the Xinjie Taigemiao mining district as a representative artificial ground freezing (AGF) project. First, drawing on the mechanics of frozen ground and field monitoring, we establish a relationship model linking advance rate, drum rotational speed, cutting depth, and muck production, thereby clarifying why lower rotational speeds, moderate cutting depths, and rational traction reduce energy consumption and mitigate disturbances to the frozen wall. Next, for muck handling, we build a full-process discrete element method (DEM) model, integrate design-of-experiments with response-surface optimization to identify key factors, calibrate contact models, and select collection geometries. The results show that a graded-angle collecting structure improves pile concentration and discharge compliance; combined with a tiered chain-bucket–vertical belt–twin-skip configuration, it delivers matched cycle times and stable “gather–convey–hoist” operation. Finally, two-stage full-scale tests jointly validate excavation and muck removal, demonstrating that the proposed synergy model and optimized parameters sustain continuous, efficient performance across operating conditions. The study provides a reusable mechanistic framework and parameterization blueprint for AGF shaft design and construction.