Authors: Fillion, M-H; Hadjigeorgiou, J


Cite As:
Fillion, M-H & Hadjigeorgiou, J 2013, 'Reliability of strength estimates based on limited laboratory data', in PM Dight (ed.), Proceedings of the 2013 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, Australian Centre for Geomechanics, Perth, pp. 163-176.

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Abstract:
In an open pit mine operation, the quality and quantity of collected geomechanical data can have significant implications in the design of safe and economically viable slope designs. The selection of representative values of the rock mass properties is not straightforward, given the inherent geological and structural variability within an orebody. Under these circumstances the design of a comprehensive geomechanical sampling program is critical. Such a program, however, has to comply with practical and financial constraints while developing a degree of confidence in the quality of the geomechanical data. A common target level of confidence in the rock mass properties used in slope design is higher than 80% for an open pit mine at the operations stage. This requires an ongoing maintenance of the geomechanical database and model. In practice, given the perceived high costs of laboratory testing, quite often only a relatively small number of samples are selected for laboratory testing. This leads to a series of questions pertaining to the confidence level that can be assigned to values obtained by testing only a few samples. This paper investigates the potential of small-sampling theory to provide practical recommendations on the adequacy of a testing program. The geomechanical database of an Anglo American operating open pit mine was reviewed with respect to the strength properties obtained through a series of ISRM suggested testing methods. For the purposes of this investigation the focus was on uniaxial compressive strength (UCS) results but the methodology can be applied to other material properties. In this case study, the mine geological model identified six distinct rock types. Strength values for six different rock domains were analysed using the confidence interval approach. In order to investigate the sequence of testing on the interpretation of results, statistical analyses were also performed by randomly interchanging the order of test results for each rock domain. The results showed that even if the number of specimens tested is higher than the minimum proposed by the International Society for Rock Mechanics (ISRM) suggested methods, the sample size was too small to obtain a reliable strength value for most of the rock domains. Furthermore, the results showed that the minimum sample size obtained using the confidence interval approach is significantly influenced by the test results sequence used for the analyses. Based on the results of this study, there is a demonstrated need for a method to determine the minimum sample size while minimising the influence of the testing sequence.

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References:
Bieniawski, Z.T. and Bernede, M.J. (1979) Suggested methods for determining the uniaxial compressive strength and deformability of rock materials, International Journal of Rock Mechanics and Mining Sciences, Vol. 16, No. 2, pp. 137−140.
Gill, D.E., Corthésy, R. and Leite, M.H. (2005a) Determining the minimal number of specimens for laboratory testing of rock properties, Engineering Geology, Vol. 78, pp. 29–51.
Gill, D.E., Corthésy, R. and Leite, M.H. (2005b) A statistical approach for determining practical rock strength and deformability values from laboratory tests, Engineering Geology, Vol. 78, pp. 53–67.
Hadjigeorgiou, J. (2012) Where do the data come from? In Proceedings Sixth International Seminar on Deep and High Stress Mining (Deep Mining 2012), Y. Potvin (ed), 28–30 March 2012, Perth, Australia, Australian Centre for Geomechanics, Perth, pp. 259–278.
Hines, W.W., Montgomery, D.C., Goldsman, D.M. and Borror, C.M. (2003) Probability and statistics in engineering, Fourth Edition, John Wiley & Sons, p. 655.
Hoek, E. (1998) Reliability of the Hoek-Brown estimates of rock mass properties and their impact on design, International Journal of Rock Mechanics and Mining Sciences, Vol. 35, No. 1, pp. 63–68.
Kostak, B., Bielenstein, H.U. (1971) Strength distribution in hard rock, International Journal of Rock Mechanics and Mining Sciences, Vol. 8, pp. 501–521.
Matheron, G. (1963) Principles of geostatistics, Economic Geology, Vol. 58, pp. 1246–1266.
Montgomery, D.C. and Runger, G.C. (2003) Applied Statistics and Probability for Engineers, Third Edition, John Wiley & Sons.
Read, J. (2009) Data Uncertainty, Guidelines for Open Pit Slope Design, J. Read and P. Stacey (eds), CRC Press/Balkema,
pp. 213–220.
Ruffolo, R.M. and Shakoor, A. (2009) Variability of unconfined compressive strength in relation to number of test samples, Engineering Geology, Vol. 108, pp. 16–23.
Sari, M. and Karpuz, C. (2006) Rock variability and establishing confining pressure levels for triaxial tests on rocks, International Journal of Rock Mechanics and Mining Sciences, Vol. 43, pp. 328–335.
Spiegel, M.R. (1961) Theory and problems of statistics, Schaum’s Outline Series, McGraw-Hill, p. 359.




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