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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.

The muck-removal at the bottom of the tunnel is a major constraint on the construction progress and advance rate. Removing the muck in a timely and effective manner is a prerequisite for the automated steel arch assembly. To solve this problem, a muck removal hydraulic manipulator with high-performance position tracking control is developed to handle with randomly scattered rock piles, slag and muck under the bottom of tunnel, so as to facilitate automated steel arch assembly. Firstly, an informative and compact description of the equation of screw swing cylinder actuated system is established by using ameliorated Lagrangian dynamic formulation and state space representation. Secondly, the cubic spline interpolation optimized by an improved genetic algorithm is carried out for the trajectory planning under the kinematic and dynamic constraints of the manipulator. Thirdly, a linearized feed-forward compensation approach and a parameter estimation based robust adaptive algorithm is proposed for position tracking control. In addition, the system stability is proved in the sense of Lyapunov stability theorem. The proposed controller performance is validated by comparative simulation analysis and experimental investigations. It turns out the proposed manipulator with trajectory planner and high precision tracking controller has great potential to help increase the efficiency of the slag and muck removal operation, so as to improve the automation level of the steel arch assembly.

The Robbins remote controlled small boring unit (SBU-RC) is a new type of boring machine capable of excavating small-diameter, hard rock tunnels at long distances, on line and grade. The SBU-RC is currently manufactured in the 900-millimeters diameter range, but it could be designed as small as 750 millimeters in diameter. It features a smart guidance system for pinpoint steering accuracy and is controlled from an operator's station on the surface. Muck removal is accomplished through a vacuum system, making the Robbins SBU-RC more cost effective than microtunnel boring machines requiring slurry and cleaning plants onsite.