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Pinnaduwa H. S. W. Kulatilake Srisharan Shreedharan Taghi Sherizadeh Biao Shu Yan Xing Pengfei He 《Geotechnical and Geological Engineering》2016,34(6):1723-1735
Numerical modeling of complex rock engineering problems involves the use of various input parameters which control usefulness of the output results. Hence, it is of utmost importance to select the right range of input physical and mechanical parameters based on laboratory or field estimation, and engineering judgment. Joint normal and shear stiffnesses are two popular input parameters to describe discontinuities in rock, which do not have specific guidelines for their estimation in literature. This study attempts to provide simple methods to estimate joint normal and shear stiffnesses in the laboratory using the uniaxial compression and small-scale direct shear tests. Samples have been prepared using rocks procured from different depths, geographical locations and formations. The study uses a mixture of relatively smooth natural joints and saw-cut joints in the various rock samples tested. The results indicate acceptable levels of uncertainty in the calculation of the stiffness parameters and provide a database of good first estimates and empirical relations which can be used for calculating values for joint stiffnesses when laboratory estimation is not possible. Joint basic friction angles have also been estimated as by-products in the small scale direct shear tests. 相似文献
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K. Ram Chandar V. R. Sastry Chiranth Hegde Srisharan Shreedharan 《Geomechanics and Geoengineering》2017,12(3):207-214
Ground vibrations produced from blasting operations cause structural vibrations, which may weaken structure if it occurs at the resonant frequency. Measurable parameters associated with ground vibrations are peak particle velocity (PPV), amplitude and dominant frequency (frequency of highest PPV amongst translational, vertical and horizontal vibrations). In this paper, an attempt is made to correlate measurable parameters associated with ground vibrations with scaled distance. Using the correlated data, it was found that a predictor equation can be determined for the amplitude and PPV, but not for dominant frequency as it is dynamic and depends upon infinitesimal changes that occur within a number of other parameters. Another analysis of the same is made using multiple linear regression analysis. This included predicting the PPV using scaled distance, maximum charge per delay, amplitude as predictors. A considerable improvement is seen in the prediction on adding the interaction of the predictors in multiple regressions. A comparison of different combination of predictors is made so as to assess the best combination giving the best R2 value for the given mine. Frequency is also plotted using the aforementioned method. However, it was found that the dominant frequency cannot be predicted with high accuracy even with this method. 相似文献
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