Effects of Rock Properties on Specific Cutting Energy in Linear Cutting of Sandstones by Picks |
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| Authors: | B Tiryaki A Cagatay Dikmen |
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| Institution: | (1) Department of Mechanical Engineering, The University of Queensland, Brisbane, Australia;(2) CRC Mining, Australia;(3) Ministry of Environment and Forestry, Ankara, Turkey |
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| Abstract: | Summary. Specific cutting energy (SE) has been widely used to assess the rock cuttability for mechanical excavation purposes. Some
prediction models were developed for SE through correlating rock properties with SE values. However, some of the textural
and compositional rock parameters i.e. texture coefficient and feldspar, mafic, and felsic mineral contents were not considered.
The present study is to investigate the effects of previously ignored rock parameters along with engineering rock properties
on SE. Mineralogical and petrographic analyses, rock mechanics, and linear rock cutting tests were performed on sandstone
samples taken from sites around Ankara, Turkey. Relationships between SE and rock properties were evaluated using bivariate
correlation and linear regression analyses.
The tests and subsequent analyses revealed that the texture coefficient and feldspar content of sandstones affected rock cuttability,
evidenced by significant correlations between these parameters and SE at a 90% confidence level. Felsic and mafic mineral
contents of sandstones did not exhibit any statistically significant correlation against SE. Cementation coefficient, effective
porosity, and pore volume had good correlations against SE. Poisson’s ratio, Brazilian tensile strength, Shore scleroscope
hardness, Schmidt hammer hardness, dry density, and point load strength index showed very strong linear correlations against
SE at confidence levels of 95% and above, all of which were also found suitable to be used in predicting SE individually,
depending on the results of regression analysis, ANOVA, Student’s t-tests, and R2 values. Poisson’s ratio exhibited the highest correlation with SE and seemed to be the most reliable SE prediction tool in
sandstones. |
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| Keywords: | : Specific cutting energy linear rock cutting picks texture coefficient rock properties bivariate correlation linear regression |
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