Browsing by Author "Esamaldeen Ali, Wu Guang"

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Assessments of Strength Anisotropy and Deformation Behavior of Banded Amphibolite Rocks
(Springer, 2014-04) Esamaldeen Ali, Wu Guang; Zhao zhiming, Jiang Weixue
Assessment of strength anisotropy in transversely isotropic rocks has been one of the most challenging subjects in rock engineering. However, far too little attention has been paid to banded amphibolite rocks. This study aim to evaluate strength and deformation anisotropy behavior of banded amphibolite rocks. The dynamic mechanical tests including ultrasonic pulse test, uniaxial compressive strength, Brazilian test and deformability test were performed on drilled rock samples as a function of foliation plane angle (b = 0 , 30 , 60 and 90 ). The results obtained have shown that the dynamic mechanical properties of amphibolite rocks have different values concerning banding plane. Compression and shear waves taken parallel to the foliation plane show highest values than those obtained in the other directions. Under uniaxial test, the banded amphibolite has a U-shaped anisotropy with maximum strength at b = 90 and minimum strength is obtained when b = 30 . Strength anisotropic index ranges between 0.96 and 1.47. It seems that the high range value of anisotropic index is mainly due to slight undulation of foliation planes, that being not perfectly straight. The results of elastic deformation test show that there is no clear dependence on microstructures characteristics of subtypeamphibolite rocks that controlling modulus ‘‘shapeanisotropy’’. However, in this study, Young modulus values of amphibolite rocks with b follow both types of shape-anisotropy, ‘‘U-shape’’ and ‘‘decreased order-shaped’’. Thus, this study recommended that further research be undertaken regarding the role of modulus ‘‘shape-anisotropy’’ within the same lithotype.
Empirical relations between compressive strength and microfabric properties of amphibolites using multivariate regression, fuzzy inference and neural networks: A comparative study
(Elsevier, 2014) Esamaldeen Ali, Wu Guang; Abdelazim Ibrahim
In this paper, microfabric properties including grain size, shape factor and quartz content are tailored to the specific evaluation of UCS of banded amphibolite rocks. However, the predicting capabilities of Artificial Neural Networks (ANNs) and Fuzzy Inference System (FIS) as well as the Multivariate Regression (MR) techniques have been evaluated and compared using the same input variables. To assess the model performances, some performance indices such as correlation coefficient (R), variance account for (VAF) and root mean square error (RMSE) were calculated and compared for the three models. The study revealed that even though the developed three models are reliable to predict the UCS, the presented ANN method displays an obvious potential for the reliable assessment of UCS according to model performance criterion. However, the outcomes of this study are quite satisfactory, which may serve microfabric characterization to be easily extended to the modeling of strength and deformation behavior of rocks in the absence of adequate budget and facility of testing UCS.