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    Shape-anisotropy Type of Young’s Modulus for Transverse Isotropic Rocks Regarding the Orientation of Foliation Plane
    (Nile Basin Research Journal, 2017-06) Esamaldeen Ali Mohammed
    Generally, engineers need to know how rocks deform when subject to the various loads associated with engineering structures. Hence, deformability of anisotropic rocks is essential for design purposes. However, intact rock deformability depends on the orientation of the applied load. This study carried out to assess the curve-type elastic modulus anisotropy of banded amphibolite rocks as a function of foliation plane angle (β = 0º, 30º, 60º and90º). The unconfined compressive test was performed on drilled rock samples and the values of elastic modulus are calculated. The results obtained have shown that Young modulus values of amphibolite rocks with β follow both types of shape anisotropy, “U-shape” and “decreased order-shaped”. However, there is no clear dependence on microstructures characteristics of subtype-amphibolite rocks that controlling modulus “shape-anisotropy”. It seems that this is mainly due to slight undulation of foliation planes, that being not perfectly straight. Thus, this study recommended further research could be undertaken regarding the role of modulus “shape-anisotropy” within the same litho-type.
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    Selection of Influential Microfabric Properties of Anisotropic Amphibolite Rocks on Its Uniaxial Compressive Strength (UCS): A Comprehensive Statistical Study
    (Scientific Research, 2014-11) Esamaldeen Ali, Guang Wu
    Occasionally, in complex inherent characteristics of certain rocks, especially anisotropic rocks it may be difficult to measure the uniaxial compressive strength UCS. However, the use of empirical relationships to evaluate the UCS of rock can be more practical and economical. Consequently, this study carried out to predict UCS from microfabrics properties of banded amphibolite rocks using multiple regression analysis. Based on statistical results, rock microfabric parameters, which adequately represent the UCS of a given rock type have been selected. The results show that grain size, shape factor and quartz content have high significant correlation with UCS at 95% confidence level. From multiple regression model, approximately 84% of the variance of the UCS can be estimated by the linear combination of these three parameters. However, according to model performance criteria: correlation coefficient (R = 0.919), variance account for (VAF = 97%) and root mean square error (RMSE = 4.16) the study clearly indicates that the developed model is reliable to predict the UCS. Finally, this approach can be easily extended to the modeling of rock strength in the absence of adequate geological information or abundant data.