Simulation Method and Application of Three-Dimensional DFN for Rock Mass Based on Monte-Carlo Technique

被引:2
作者
Li, Ang [1 ]
Li, Yaodong [2 ]
Wu, Feng [1 ,3 ]
Shao, Guojian [2 ]
Sun, Yang [1 ]
机构
[1] Hohai Univ, Coll Harbour Coastal & Offshore Engn, Nanjing 210098, Peoples R China
[2] Hohai Univ, Coll Mech & Mat, Nanjing 210098, Peoples R China
[3] Shanghai Third Harbour Engn Sci & Technol Res Ins, Shanghai 200032, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 22期
基金
中国国家自然科学基金;
关键词
rock mass; three-dimensional DFN; rectangular fractures; probability models; visualization technology; TRACE LENGTH; GEOMETRY;
D O I
10.3390/app122211385
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In this study, the authors simulate a polygonal discrete fracture network (DFN) in rock masses. The probability models of the relevant geological parameters, including the orientation, trace length, volume density, and coordinates of the centroid, are firstly developed as fractures are in the shape of rectangles. In the process, the probability distribution of rectangular fractures with side lengths as random variables is introduced and described in terms of mean trace lengths on the basis of the probability model of disk-shaped fracture with the diameter as the random variable. The relationship between the volume density and the linear density of rectangular fractures is given for a negative exponential distribution. Following this, the coordinates of the vertices of fractures are derived based on spatial algebraic geometry, and the data for the three-dimensional DFN model are generated using the Monte-Carlo technique. The resulting three-dimensional DFN is visualized by calling the Open GL graphics database in the environment of Visual C, and the process of implementation of the DFN simulation is given. Finally, the validity of the simulation is verified by applying it to engineering practice.
引用
收藏
页数:12
相关论文
共 30 条
[1]  
Baecher G.B., 1977, P 18 US S ROCK MECH, P22
[2]   STATISTICAL-ANALYSIS OF ROCK MASS FRACTURING [J].
BAECHER, GB .
JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR MATHEMATICAL GEOLOGY, 1983, 15 (02) :329-348
[3]   CHARACTERIZING ROCK JOINT GEOMETRY WITH JOINT SYSTEM MODELS [J].
DERSHOWITZ, WS ;
EINSTEIN, HH .
ROCK MECHANICS AND ROCK ENGINEERING, 1988, 21 (01) :21-51
[4]   A three-dimensional fracture network dataset for a block of granite [J].
Dowd, P. A. ;
Martin, J. A. ;
Xu, C. ;
Fowell, R. J. ;
Mardia, K. V. .
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, 2009, 46 (05) :811-818
[5]  
EINSTEIN HH, 1983, ROCK MECH ROCK ENG, V16, P39, DOI 10.1007/BF01030217
[6]   Spatial Topology Identification of Three-Dimensional Complex Block System of Rock Masses [J].
Fu, Xiaodong ;
Sheng, Qian ;
Wang, Liwei ;
Chen, Jian ;
Zhang, Zhenping ;
Du, Yuxiang ;
Du, Wenjie .
INTERNATIONAL JOURNAL OF GEOMECHANICS, 2019, 19 (12)
[7]   Upscaling of fractured rock mass properties - An example comparing Discrete Fracture Network (DFN) modeling and empirical relations based on engineering rock mass classifications [J].
Gottron, D. ;
Henk, A. .
ENGINEERING GEOLOGY, 2021, 294
[8]   Copula-based simulating and analyzing methods of rock mass fractures [J].
Han, Shuai ;
Li, Mingchao ;
Wang, Gang .
COMPUTERS AND GEOTECHNICS, 2020, 127
[9]  
Hudson J.A., 1989, ROCK MECH PRINCIPLES
[10]   Mathematical algorithm development and parametric studies with the GEOFRAC three-dimensional stochastic model of natural rock fracture systems [J].
Ivanova, Violeta M. ;
Sousa, Rita ;
Murrihy, Brian ;
Einstein, Herbert H. .
COMPUTERS & GEOSCIENCES, 2014, 67 :100-109