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3D Geometrical-Stochastical Modeling of Rock mass joint networks: Case study of the Right Bank of Rudbar Lorestan Dam plant
Author(s) -
Mehdi Noroozi,
Reza Kakaie,
Ecu S
Publication year - 2015
Publication title -
journal of geology and mining research
Language(s) - English
Resource type - Journals
ISSN - 2006-9766
DOI - 10.5897/jgmr14.0213
Subject(s) - joint (building) , rock mass classification , joint probability distribution , computer science , code (set theory) , key (lock) , stability (learning theory) , function (biology) , marginal distribution , network model , stochastic modelling , algorithm , geology , geotechnical engineering , data mining , mathematics , engineering , structural engineering , statistics , random variable , machine learning , set (abstract data type) , computer security , evolutionary biology , biology , programming language
Nowadays, modeling is increasingly used as a method for determination of the mechanical and hydraulic behavior of the rock mass. In this paper, with regard to the high importance of joint persistence characteristic on the mechanical and hydraulic behavior of the rock mass, geometric-stochastic joint network model has been developed by considering the statistical characteristics of joint size based on Veneziano model. With the use of surveyed data in the right bank of Rudbar Lorestan dam plant and estimation of the best probability distribution function on geometric characteristics of existing joint sets in this region, the three-dimensional geometric model of joint network has been developed. In order to model implementation, a computer code written in C++, called FRAC3D, has been developed that is able to represent the joint network in different directions and to generate text outputs. The results of this model can be a useful input for numerical stability analysis and hydraulic behavior studies of rock mass.   Key words: Geometrical-Stochastic modeling, joint network, joint surveying, statistical studies.

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