Volume 11, Issue 2 (2011)                   MCEJ 2011, 11(2): 0-0 | Back to browse issues page

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Golshani A, Rajabi H. Numerical Modeling of Confinement Effects on Failure Pattern of Brittle Rocks in Triaxial Tests. MCEJ. 2011; 11 (2)
URL: http://mcej.modares.ac.ir/article-16-3319-en.html
Abstract:   (5009 Views)
Abstract: One of the most important goals of the experiments is to determine deformation and strength of the rock specimen under applying triaxial load. The status of failure condition is one of the subjects, which can be used in soil mechanic and foundation engineering applications. To investigate the effect of confining pressure on the triaxial test, the rock was considered as bonded-particles method and simulated by PFC3D program. To compare the mechanical behavior and failure pattern of the numerical and experimental results at uniaxial and triaxial tests at the same conditions, the Young's modulus, Poisson's ratio and maximum axial stress were considered. On the other hand, the microcracks growth and change of failure pattern at the modeling of the uniaxial and triaxial tests with different confining pressures up to failure point were reported. According to the experimental work, the number density of microcracks decreases from starting value and remains almost constant up to the failure beyond that point. Comparison of the numerical and experimental results of maximum axial stress and the Poisson's ratio revealed a good accordance. The simulated Young's modulus was smaller in comparison with the experimental ones and the difference was about 36%, which seems to be due to absence of the pre-existing microcracks on the model. The initial number density of microcracks at the model was zero and increased while microcracking. Also the sudden increment around the maximum stress was observed, which is because of unstable growing of microcracks near the maximum stress. In all uniaxial and triaxial tests with different confining stresses, the number density of microcracks during the failure remained almost constant, which can be considered as a proof of failure occurring in the model. The experimental results indicated a similar trend as well.
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Received: 2009/07/15 | Accepted: 2011/09/6 | Published: 2012/03/1

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