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<p>The Discrete Fracture Network (DFN) model is utilized to characterize the heterogeneous nature of rock masses. The most reliable parameter for fracture intensity within DFN modeling is the volumetric fracture intensity, denoted as P32. Direct field measurement of P32 is not feasible; hence, it is estimated using other 1D and 2D fracture intensity parameters. The influence of P32 uncertainties on rock mass characterization and the representative elementary volume (REV) demands analysis. This paper examines the effects of P32 estimation uncertainties, derived from 2D fracture intensity—specifically aerial density, P20— on the geometrical-based REV size. Discrete Fracture Network simulations were employed to infer P32 values from P20 inputs. A novel method for estimating P32 from P20 is proposed and compared with the conventional approaches using the underground powerhouse cavern of the Azad dam as a case study. In the proposed method, P32 is directly calculated within the DFN, which is generated based on size, orientation distribution, and P20 values. Subsequent numerical analyses validate the DFN models via rock quality designation (RQD) and assess the impact of P32 uncertainties on REV size, considering both RQD and P32. Results indicate that the RQD values computed within the DFN model, based on the proposed method, suggest greater accuracy compared to conventional methods. Although the REV size estimates showed no significant difference between the two approaches, the proposed method was found to be more time-efficient, offering advantages in both computational performance and modeling accuracy.</p>

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Beyond conventional methods: direct calculation of P32 in DFN models for enhanced rock mass analysis

  • 期刊论文

  • 发表日期：

    2025年8月5日

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  • Mehrdad Zanganeh,
  • Mosleh Eftekhari,
  • Morteza Ahmadi

摘要

The Discrete Fracture Network (DFN) model is utilized to characterize the heterogeneous nature of rock masses. The most reliable parameter for fracture intensity within DFN modeling is the volumetric fracture intensity, denoted as P32. Direct field measurement of P32 is not feasible; hence, it is estimated using other 1D and 2D fracture intensity parameters. The influence of P32 uncertainties on rock mass characterization and the representative elementary volume (REV) demands analysis. This paper examines the effects of P32 estimation uncertainties, derived from 2D fracture intensity—specifically aerial density, P20— on the geometrical-based REV size. Discrete Fracture Network simulations were employed to infer P32 values from P20 inputs. A novel method for estimating P32 from P20 is proposed and compared with the conventional approaches using the underground powerhouse cavern of the Azad dam as a case study. In the proposed method, P32 is directly calculated within the DFN, which is generated based on size, orientation distribution, and P20 values. Subsequent numerical analyses validate the DFN models via rock quality designation (RQD) and assess the impact of P32 uncertainties on REV size, considering both RQD and P32. Results indicate that the RQD values computed within the DFN model, based on the proposed method, suggest greater accuracy compared to conventional methods. Although the REV size estimates showed no significant difference between the two approaches, the proposed method was found to be more time-efficient, offering advantages in both computational performance and modeling accuracy.