A Fragmentation-Centric Framework for Impact Hammer Selection in Immediate-Collapse-Prone Tunneling: Integrating Mucking Efficiency into Cycle-Time Optimization

Tunneling through weak rock masses under shallow urban overburdens is critically constrained by stand-up time. Conventional models for hydraulic impact hammers prioritize the excavation rate (Net Breaking Rate—NBR) but overlook a key operational bottleneck: the mucking process. This study introduces a paradigm shift from “how fast can we excavate?” to “how can we excavate to facilitate rapid muck clearance?”; it presents a novel, data-driven framework that, for the first time, quantitatively links impact hammer operation to mucking efficiency via the resulting particle size distribution (P50). Field data from metro line excavations in very weak rock (RMR 18-33) were used to develop empirical models via multiple linear regression. The analysis produced (1) a model predicting mucking duration (tₘ) from muck volume (V) and post-excavation mean particle size (P50) and (2) a model predicting NBR from rock mass rating (RMR) and the rock size reduction ratio (F). These models are synthesized into a comprehensive operational equation, enabling engineers to select an impact hammer based on its ability to produce a target P50 that ensures mucking can be completed within the project’s critical stability window. This transforms rock fragmentation from an incidental byproduct into a central, controllable factor in equipment selection and proactive risk management.