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International Journal of Mining and Geo-Engineering، جلد ۵۶، شماره ۱، صفحات ۵۳-۶۰
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عنوان انگلیسی Assessment of rock fragmentation and strength properties using the Rosin-Rammler and Extended Swebrec Distribution functions parameters
چکیده انگلیسی مقاله This work assessed the curve fitting ability of Rosin-Rammler and Swebrec functions and the comparison of their fitting parameters with rock strength properties. The work aimed to show if there exist a relationship between the function’s distribution parameters and rock strength properties. The rock strengths properties were determined in accordance with International Society of Rock Mechanics standards. The two functions were used to reproduce sieving curves of different rocks fragmented on a laboratory scale using electric detonators. The Swebrec function reproduces the sieving curves better than Rosin-Rammler. The Rosin-Rammler curve fitting performs creditably with well fragmented rocks of poor grading or uniformly sorted fragments. The Rosin-Rammler curve fitted better to Class II rocks than the Class I rocks. The Rosin-Rammler parameters are shown to be interdependent while only factor ‘a’ and exponent ‘c’ parameters of Swebrec function are mutually dependent. The undulating exponent ‘b’ of Swebrec is related to the uniformity index, ‘n’ and characteristic size, ‘Xc’ of Rosin-Rammler. By comparison, the parameters of the two functions show correlations with rock strength properties (BTS, UCS, E and v). The uniformity index, ‘n’ is related to rock properties included in this study while the Swebrec ‘c’ parameters did not show any relationship with rock properties. The ‘Xc’ parameter of Rosin-Rammler is related to UCS, E and v. The ‘a’ and ‘b’ parameters of Swebrec function are related to BTS, UCS and v and BTS UCS and E respectively. In all cases the correlation coefficients are greater than 0.6 and can be fitted by power form function.
کلیدواژه‌های انگلیسی مقاله curve fitting, Fragmentation, rock strength, Rosin-Rammler and Swebrec function
نویسندگان مقاله Victor Abioye Akinbinu |
Federal University of Technology, Akure, Nigeria

Gafar O Oniyide |
Federal University of Technology, Akure, Nigeria

Musa Adebayo Idris |
Lulea University of Technology, Sweden

نشانی اینترنتی https://ijmge.ut.ac.ir/article_86271_b3f00e399fa5472df39dfbe5d99e2271.pdf
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