Akademik Veri Yönetim Sistemi
ROCK MECHANICS AND ROCK ENGINEERING, cilt.51, sa.4, ss.1227-1248, 2018 (SCI-Expanded)
The main objective of this study is to investigate the effect of textural properties of stones on cutting performance of a standard chisel tool. Therewithal, the relationships between textural properties and cutting performance parameters and physical and mechanical properties were statistically analyzed. For this purpose, physical and mechanical property tests and mineralogical and petrographic analyses were carried out on eighteen natural stone samples, which can be grouped into three fundamentally different geological origins, i.e., metamorphic, igneous, and sedimentary. Then, texture coefficient analyses were performed on the samples. To determine the cuttability of the stones; the samples were cut with a portable linear cutting machine using a standard chisel tool at different depths of cut in unrelieved (non-interactive) cutting mode. The average and maximum forces (normal and cutting) and specific energy were measured, and the obtained values were correlated with texture coefficient, packing weighting, and grain size. With reference to the relation between depth of cut and cutting performance of the chisel tool for three types of natural stone groups, specific energy decreases with increasing depth of cut, and cutting forces increase in proportion to the depth of cut. The same is observed for the relationship between packing weighting and both of specific energy and cutter forces. On the other hand, specific energy and the forces decrease while grain size increases. Based on the findings of the present study, texture coefficient has strong correlation with specific energy. Generally, the lower depth of cut values in cutting tests shows higher and more reliable correlations with texture coefficient than the increased depth of cut. The results of cutting tests show also that, at a lower depth of cut (less than 1.5 mm), even stronger correlations can be observed between texture coefficient and cutting performance. Experimental studies indicate that cutting performance of chisel tools can be predicted based on texture coefficients of the natural stones.