| 要約: | 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—<i>NBR</i>) 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 (<i>P<sub>50</sub></i>). Field data from metro line excavations in very weak rock (<i>RMR</i> 18-33) were used to develop empirical models via multiple linear regression. The analysis produced (1) a model predicting mucking duration (<i>tₘ</i>) from muck volume (<i>V</i>) and post-excavation mean particle size (<i>P<sub>50</sub></i>) and (2) a model predicting <i>NBR</i> from rock mass rating (<i>RMR</i>) and the rock size reduction ratio (<i>F</i>). These models are synthesized into a comprehensive operational equation, enabling engineers to select an impact hammer based on its ability to produce a target <i>P<sub>50</sub></i> 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.
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