Youlin Qin , Li Yu , Mingnian Wang , Zhaohui Chen , Hong Jin , Mingyang Yu , Songshen Wang
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引用次数: 0
Abstract
Cutter spacing is a key factor influencing the efficiency of TBM operations. Meanwhile, rock brittleness, as a critical indicator of rock fracture, significantly influences fragmentation behavior and rock-breaking efficiency. This study investigates the influence of rock brittleness on rock-breaking through numerical penetration experiments based on the hybrid finite-discrete element method (FDEM) and proposes four intelligent hybrid models to optimize cutter spacing. The results show that as the rock brittleness index (BI) increases from 4.731 to 32.588, the count, depth, width, and proportion of tensile cracks increase, and crack propagation shifts from horizontal to oblique orientations. Moderate cutter spacing (90–110 mm) is optimal for generating tensile cracks. The rock-breaking force increases significantly with higher BI; for instance, at 80 mm spacing, the maximum force for rock with a BI of 13.134 is 5.51 times that for rock with a BI of 4.731. The influence of BI on cutter work and specific energy (SE) is more substantial than the effect of cutter spacing. As BI increases, both cutter work and SE rise considerably. Among the proposed models, the particle swarm optimization and extreme gradient boosting (PSO-XGBoost) model demonstrates the highest performance, achieving an R2 of 0.994, VAF of 99.418%, RMSE of 0.987, and MAPE of 5.217% on the test datasets. An optimization method for cutter spacing is proposed based on this model.
期刊介绍:
Underground Space is an open access international journal without article processing charges (APC) committed to serving as a scientific forum for researchers and practitioners in the field of underground engineering. The journal welcomes manuscripts that deal with original theories, methods, technologies, and important applications throughout the life-cycle of underground projects, including planning, design, operation and maintenance, disaster prevention, and demolition. The journal is particularly interested in manuscripts related to the latest development of smart underground engineering from the perspectives of resilience, resources saving, environmental friendliness, humanity, and artificial intelligence. The manuscripts are expected to have significant innovation and potential impact in the field of underground engineering, and should have clear association with or application in underground projects.