Numerical simulations reveal cutter spacing impacts specific energy in TBM rock excavation, suggesting optimal mineral composition ratios.
In mining TBM excavation, the mineralogical heterogeneity of rock significantly impacts tunneling efficiency and rock-breaking performance. The cutting process of tunnel boring machine (TBM) double-disc cutters is significantly influenced by the combined effects of mineral composition differences and cutter spacing parameters. In this study, a heterogeneous granite model was constructed using the finite–discrete element method (FDEM), with quartz content fixed at 30%. Different mineral compositions were generated by adjusting the proportions of feldspar and mica, and a double-disc cutter–rock contact model was employed with various cutter spacings to perform numerical cutting simulations. Cutter work was calculated by integrating the force–displacement curves, rock-breaking efficiency was evaluated by the specific energy (SE) defined as the energy consumed per unit rock chip area, and fracture types, as well as fragmentation volumes, were identified. The results show that the total input energy ranged from 2.2 to 3.4 mJ, reaching a peak at medium cutter spacings of 50–70 mm; as feldspar content increased, the overall energy level rose significantly. Rock-breaking efficiency was relatively high at medium cutter spacings, and the favorable spacing range shifted from approximately 50 mm to 60 mm when feldspar content increased from 40–50% to 60%. Excessively small spacing led to a higher proportion of crushing and repeated damage, while overly large spacing weakened crack interactions, both of which reduced efficiency. Overall, cutter spacing mainly controlled the crack interaction patterns, whereas the feldspar–mica ratio dominated energy utilization. These findings suggest that, in practical TBM excavation, cutter spacing should be reasonably optimized according to the mineral composition of the surrounding rock to avoid energy waste caused by extreme spacing and to achieve a balance between efficiency and energy consumption.
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Meng et al. (2026) studied this question.
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