| نویسندگان | Hibert Alexan,Mojtaba Bahaaddini,Amin Hekmatnejad,Maryam Sarmast Sakhvidi,Mohammad Saadatseresht,Hamid Zare,Mohammad Amiri Hossaini |
| نشریه | Engineering Geology |
| شماره صفحات | 1-15 |
| شماره سریال | 357 |
| شماره مجلد | 1 |
| ضریب تاثیر (IF) | 1.242 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2025 |
| رتبه نشریه | ISI |
| نوع نشریه | چاپی |
| کشور محل چاپ | هلند |
| نمایه نشریه | JCR،Scopus |
| کلید واژه ها | Non, parametric model; Discrete fracture network; Sequential Gaussian simulation; Volumetric fracture intensity; Probabilistic slope stability |
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چکیده مقاله
Mechanical behavior of the rock mass is predominately governed by the presence of discontinuities, especially at
surface and near-surface excavations. Given the inherent uncertainty in characterizing the geometrical properties
of rock discontinuities, precise and sound simulation of fracture systems becomes crucial for reliably predicting
rock mass behavior in engineering geology applications. This paper presents a non-parametric discrete fracture
network (DFN) approach to simulate fracture networks within the rock mass, offering an alternative to conventional
methods that rely on predefined statistical distributions. The methodology employs bootstrapping
techniques to generate a three-dimensional DFN model that better captures the heterogeneity and spatial
complexity of natural fracture systems. High-resolution fracture data were collected using unmanned aerial
vehicle photogrammetry, providing the basis for the DFN model development. For fracture size characterization,
a non-parametric approach was employed to estimate the cumulative distribution function of fracture diameters
from observed trace data, modeling the network as a Poisson point process (disc model). Additionally, the P32
fracture intensity parameter was estimated using direct calculation and sequential Gaussian simulation, allowing
the construction of a detailed block model. To demonstrate the practical application of this approach, the
methodology was applied to a geological sector of the Golgohar open-pit mine, Iran. The developed model was
subsequently utilized to evaluate the mine wall stability through probabilistic kinematic stability analysis. This
study demonstrates effectiveness of non-parametric modeling in geomechanical applications, offering an
advanced tool for analyzing and predicting rock mass behavior.
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