As the results were quite similar, the recommendation still is that correlations should be used with caution, and associated to other methods and field analysis. The best fit was the Rutledge & Pearson correlation equation, which presented the best combination of R² and S, after the equation created on basis of the real values for RMR, though the other equations have results similar to it. The result of the regression was compared with selected correlation equations and the best fit for the data was chosen. An empirical equation was obtained from the data, using a simple linear regression. In order to study a correlation between the RMR and Q systems, the most popular rock mass classifications, and their application as a validation tool, a selection of measurements of Q and RMR, organized in a database from seven natural caves of ferruginous lithology, are submitted to a study and statistical analysis. This article presents the study of various models of correlation between the RMR and Q systems used for the stability assessment of natural iron ore caves.
The physical integrity of caves adjacent to mining operations is an issue of pivotal importance to be scrutinised in studies towards the delimitation of the cave’s protection radius. The National Environment Commission (CONAMA 347 Resolution/2004) establishes that the speleological heritage, as well as its area of influence, cannot sustain irreversible environmental impacts. In addition, the classification results of Q, RMR, and BQ showed more significant differences when less consideration is given to the integrity of the rock mass.įor the Brazilian iron ore mines, the presence of caves presents a challenge, since most of them are located within the ore deposit. Our data demonstrated that the grading differences between the systems are proportional to the discontinuous state of rock mass in the classification. Depending on the consistency of the grading results, we arranged the values from large to small as the amplitude of the slope of the curve, and the grading results differed by either one or two levels. To evaluate the relations between RMC indexes and P-wave velocity, we conducted a group study on the different grading differences among RMR, Q, or BQ.
Further analysis showed that the grading differences between any two RMC systems yield different characteristics when the rock mass score is at different intervals. Here, based on linear or nonlinear regression analysis of 231 samples, we established the RMR–Q, –Q, and –RMR relationships with R2 = 0.935, 0.732, and 0.759, respectively. The relationship between the different RMC systems and P-wave velocity indexes is conducive to the interpretation of the rock mass. Besides, the accuracy of the RMC should be checked through the correlations between different RMC systems. To confirm the robustness of a tunnel, the quality of the rock mass is usually evaluated by several rock mass classification (RMC) systems before its design.
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