Geometric-topologically constrained modeling of stochastic fracture networks and uncertainty quantification of dominant factors controlling flow behavior

초록

Stochastic fracture network models are important tools for characterizing heterogeneity and seepage behavior in fractured rock masses in geotechnical engineering. To address the limitations of conventional models—poor generalization, high uncertainty in flow description, and susceptibility to distortion—this paper proposes a novel computational framework: a geometric-topologically constrained stochastic fracture network modeling method that accounts for the synergistic interplay between fracture geometry and topological connectivity. After validating the seepage reliability of the constrained model, uncertainty quantification analysis identifies the respective contributions of various geometric and topological parameters to fracture network connectivity efficiency. Furthermore, a practical modeling approach driven by dominant controlling factors is proposed. Results indicate that fractured rock samples exhibit pronounced dominant-flow characteristics. Fractures create preferential flow channels, accelerating gas migration from free space into the porous medium region. Uncertainty quantification reveals that the average number of connections per branch (CB), the average number of connections per fracture (CL), and the angle deviation of fracture (θ) are the core controlling factors governing system-scale seepage behavior. Fracture aperture (b), the number of X-type nodes (NX), and the number of fracture branches (NB) are identified as key influencing factors. Volumetric fracture intensity (P32) and the number of I-type nodes (NI) indirectly regulate seepage responses through interactions with other topological parameters. Based on these findings, a dominant-factor-driven modeling approach is proposed, which prioritizes accurate characterization of parameters controlling fracture network connectivity and the dominant seepage direction, while reasonably simplifying secondary factors that contribute less to seepage behavior. The fracture network model constructed using this new method achieves a consistency rate of approximately 96.6% with the reference model in terms of seepage behavior, demonstrating its robustness in effectively characterizing the baseline seepage response. These findings provide a practical solution for engineering-scale fractured rock mass modeling, offering a balance between accuracy and computational efficiency.

키워드