Chunjiang Zou , Boyuan Chen , Huakun Yu , Sihan Yan , Ruoge Wang , Ruoxi Zhu , Yunshun Li , Daokun Zhang
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引用次数: 0
Abstract
The coalescence of the discontinuities often leads to rock mass failure. This study develops a novel data-driven approach to predict crack coalescence in Carrara marble with double pre-existing flaws, focusing on flaw geometric parameters: inclination angle (β), bridging angle (α), and ligament length (L). Using 252 groups of numerical simulations validated against physical Carrara marble experiments, a Gaussian Process classifier was trained to predict coalescence types (no coalescence, direct, indirect) with high accuracy. Results reveal direct coalescence dominates (78 %), with β exerting the strongest influence (40 % weight). Non-linear relationships between flaw geometry and coalescence were quantified, enabling probabilistic predictions for untested configurations. This method eliminates the need for resource-intensive simulations or experiments, offering an efficient tool for failure forecasting in the future. Findings can enhance rock mass stability assessments in tunneling, mining, and rock slope, and will advance predictive modeling in geohazard mitigation.
期刊介绍:
Engineering Geology, an international interdisciplinary journal, serves as a bridge between earth sciences and engineering, focusing on geological and geotechnical engineering. It welcomes studies with relevance to engineering, environmental concerns, and safety, catering to engineering geologists with backgrounds in geology or civil/mining engineering. Topics include applied geomorphology, structural geology, geophysics, geochemistry, environmental geology, hydrogeology, land use planning, natural hazards, remote sensing, soil and rock mechanics, and applied geotechnical engineering. The journal provides a platform for research at the intersection of geology and engineering disciplines.