54th U.S. Rock Mechanics/Geomechanics Symposium,
28 June - 1 July,
physical event cancelled
2020. American Rock Mechanics Association
2 in the last 30 days
10 since 2007
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Many experimental studies have been carried out on the performance of cable bolts to characterise their mechanical behaviour under axial or shear loading. The common limitation in all these studies is that only single-variate descriptive analysis was conducted on the test results leading to insufficient understanding of the interactive influences of a range of parameters on the cable bolt performance. Thus, to address this limitation in a sound and logical manner, the advanced statistical technique Response Surface Methodology (RSM) was utilized to demonstrate the advantages of multi-variate analysis over single-variate analysis of experimental studies on cable bolts. Such a task was performed on the data reported in the literature. Finally, it was concluded that with the aid of advanced yet simple statistical methodology, RSM, the interactive influence of a broad range of parameters on the performance of cable bolt subjected to either axial loading or shear loading can be determined. This will lead to the optimisation of cable bolt support design in the underground excavation resulting both economic and technical efficiency.
Cable bolt is one of the most effective ground support systems which has been widely utilized in different civil and underground mining operations. A number of studies have investigated the cable bolt behaviour experimentally (Bawden et al. 1992; Benmokrane et al. 1992; Chen et al. 2016; Chen and Mitri 2005; Goris 1990; Hutchinson and Diederichs 1996; Hyett et al. 1995a; Hyett et al. 1992a; Jeremic and Delaire 1983; Li et al. 2019; Li et al. 2018a; Li et al. 2018b; Stillborg 1984; Thenevin et al. 2017; Yazici and Kaiser 1992) and some analytically (Blanco Martín et al. 2011; Chen et al. 2015; Hyett et al. 1995b; Li et al. 2017). The proper design of experiments with the minimum number of experiments and maximum number of parameters has been the common limitation to all the earlier studies in this regard. A large number of experiments can result in a tremendous workload and huge cost to the research. On the other hand, if the number of tests is insufficient, it can adversely impact on the reliability of any conclusion. Hence, an appropriate experimental program should be designed to carry out the optimum number of experiments without compromising the quality of the research outcome. Through a suitable design of experiments, the most representative test results can be obtained leading to a reasonable and logical statistical analysis.
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