Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods
Rock as a natural material is heterogeneous. Rock material consists of minerals, crystals, cement, grains, and microcracks. Each component of rock has a different mechanical behavior under applied loading condition. Therefore, rock component distribution has an important effect on rock mechanical be...
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Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2018/7010817 |
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doaj-3e15256d830443f49393f8724dd98b752020-11-25T00:12:30ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942018-01-01201810.1155/2018/70108177010817Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical MethodsH. Molladavoodi0Y. RahimiRezaei1Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, IranDepartment of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, IranRock as a natural material is heterogeneous. Rock material consists of minerals, crystals, cement, grains, and microcracks. Each component of rock has a different mechanical behavior under applied loading condition. Therefore, rock component distribution has an important effect on rock mechanical behavior, especially in the postpeak region. In this paper, the rock sample was studied by digital image processing (DIP), micromechanics, and statistical methods. Using image processing, volume fractions of the rock minerals composing the rock sample were evaluated precisely. The mechanical properties of the rock matrix were determined based on upscaling micromechanics. In order to consider the rock heterogeneities effect on mechanical behavior, the heterogeneity index was calculated in a framework of statistical method. A Weibull distribution function was fitted to the Young modulus distribution of minerals. Finally, statistical and Mohr–Coulomb strain-softening models were used simultaneously as a constitutive model in DEM code. The acoustic emission, strain energy release, and the effect of rock heterogeneities on the postpeak behavior process were investigated. The numerical results are in good agreement with experimental data.http://dx.doi.org/10.1155/2018/7010817 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. Molladavoodi Y. RahimiRezaei |
spellingShingle |
H. Molladavoodi Y. RahimiRezaei Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods Advances in Civil Engineering |
author_facet |
H. Molladavoodi Y. RahimiRezaei |
author_sort |
H. Molladavoodi |
title |
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods |
title_short |
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods |
title_full |
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods |
title_fullStr |
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods |
title_full_unstemmed |
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods |
title_sort |
heterogeneous rock simulation using dip-micromechanics-statistical methods |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8086 1687-8094 |
publishDate |
2018-01-01 |
description |
Rock as a natural material is heterogeneous. Rock material consists of minerals, crystals, cement, grains, and microcracks. Each component of rock has a different mechanical behavior under applied loading condition. Therefore, rock component distribution has an important effect on rock mechanical behavior, especially in the postpeak region. In this paper, the rock sample was studied by digital image processing (DIP), micromechanics, and statistical methods. Using image processing, volume fractions of the rock minerals composing the rock sample were evaluated precisely. The mechanical properties of the rock matrix were determined based on upscaling micromechanics. In order to consider the rock heterogeneities effect on mechanical behavior, the heterogeneity index was calculated in a framework of statistical method. A Weibull distribution function was fitted to the Young modulus distribution of minerals. Finally, statistical and Mohr–Coulomb strain-softening models were used simultaneously as a constitutive model in DEM code. The acoustic emission, strain energy release, and the effect of rock heterogeneities on the postpeak behavior process were investigated. The numerical results are in good agreement with experimental data. |
url |
http://dx.doi.org/10.1155/2018/7010817 |
work_keys_str_mv |
AT hmolladavoodi heterogeneousrocksimulationusingdipmicromechanicsstatisticalmethods AT yrahimirezaei heterogeneousrocksimulationusingdipmicromechanicsstatisticalmethods |
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1725399309210353664 |