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    Proposing a new model to approximate the elasticity modulus of granite rock samples based on laboratory tests results

    , Article Bulletin of Engineering Geology and the Environment ; 2017 , Pages 1-10 ; 14359529 (ISSN) Behzadafshar, K ; Esfandi Sarafraz, M ; Hasanipanah, M ; Mojtahedi, S. F. F ; Tahir, M. M ; Sharif University of Technology
    Abstract
    An accurate examination of deformability of rock samples in response to any change in stresses is deeply dependent on the reliable determination of properties of the rock as analysis inputs. Although Young’s modulus (E) can provide valuable characteristics of the rock material deformation, the direct determination of E is considered a time-consuming and complicated analysis. The present study is aimed to introduce a new hybrid intelligent model to predict the E of granitic rock samples. Hence, a series of granitic block samples were collected from the face of a water transfer tunnel excavated in Malaysia and transferred to laboratory to conduct rock index tests for E prediction. Rock index... 

    Estimation of carbonates permeability using pore network parameters extracted from thin section images and comparison with experimental data

    , Article Journal of Natural Gas Science and Engineering ; Volume 42 , 2017 , Pages 85-98 ; 18755100 (ISSN) Rabbani, A ; Assadi, A ; Kharrat, R ; Dashti, N ; Ayatollahi, S ; Sharif University of Technology
    Elsevier B.V  2017
    Abstract
    Petrography and image analysis have been widely used to identify and quantify porous characteristics in carbonate reservoirs. This paper uses the thin section images of 200 carbonate rock samples to predict the absolute permeability using intelligent and empirical methods. For each thin section, several pore network parameters are extracted from thin section images of rocks including the average pore size, average throat size, average throat length and average 2-D coordination number of pore network. A neural-based model successfully predicts the permeability of samples using pore network parameters as the inputs. Second neural network is applied for predicting absolute permeability... 

    Proposing a new model to approximate the elasticity modulus of granite rock samples based on laboratory tests results

    , Article Bulletin of Engineering Geology and the Environment ; Volume 78, Issue 3 , 2019 , Pages 1527-1536 ; 14359529 (ISSN) Behzadafshar, K ; Esfandi Sarafraz, M ; Hasanipanah, M ; Mojtahedi, S. F. F ; Tahir, M. M ; Sharif University of Technology
    Springer Verlag  2019
    Abstract
    An accurate examination of deformability of rock samples in response to any change in stresses is deeply dependent on the reliable determination of properties of the rock as analysis inputs. Although Young’s modulus (E) can provide valuable characteristics of the rock material deformation, the direct determination of E is considered a time-consuming and complicated analysis. The present study is aimed to introduce a new hybrid intelligent model to predict the E of granitic rock samples. Hence, a series of granitic block samples were collected from the face of a water transfer tunnel excavated in Malaysia and transferred to laboratory to conduct rock index tests for E prediction. Rock index...