A statistical approach for determining practical rock strength and deformability values from laboratory tests

Gill, D.E.; Corthésy, Robert; Leite, M.H.

doi:10.1016/j.enggeo.2004.10.006

Cited by 13 publications

(17 citation statements)

References 4 publications

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“…Reliability-based design (Kulhawy et al, 2012) requires more rigorous attention to uncertainty in geotechnical parameters than is included in simple statistical analyses. The purpose of this paper is to utilize simple statistics described by Gill et al (2005) to aid in selecting geotechnical strength parameters that include explicit values of confidence interval, precision index, and an acceptable non-failure probability (i.e., reliability) for use in stability analyses. The statistical method is suitable for use with data from small numbers of tests intended to be used as input in some way in probabilistic stability analyses.…”

Section: Introductionmentioning

confidence: 99%

“…The statistical method is suitable for use with data from small numbers of tests intended to be used as input in some way in probabilistic stability analyses. Gill et al (2005) describe a rigorous procedure of statistical inference for determining practical values of strength and deformability obtained from laboratory testing of rock specimens. This paper focuses on the strength parameter and extends the method to shear strength of uncemented soil deposits.…”

Section: Introductionmentioning

confidence: 99%

“…This paper focuses on the strength parameter and extends the method to shear strength of uncemented soil deposits. Gill et al (2005) use a statistical inference methodology based on statistical parameters from laboratory test results, along with a chosen confidence interval, precision index, and failure or nonfailure probability. Rock engineering design can require stability in some cases and instability (i.e., failure) in other cases, such as for block caving applications.…”

Section: Introductionmentioning

confidence: 99%

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Selection of Geotechnical Parameters Using the Statistics of Small Samples

Keaton¹,

Ponnaboyina²

2014

Geo-Congress 2014 Technical Papers

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Geotechnical engineers commonly collect measurements and perform laboratory tests for guiding judgment as well as for use in calculations. So-called "old school" engineers might plot results from a few tests and draw a lower-bound line by hand that would be used as the strength envelope for allowable-stress analyses. Calculated results would be reduced by a factor that was reported as the "factor of safety". Statistical parameters calculated with software today provide routine mean and standard deviation values. Reliability-based approaches should consider confidence interval, precision index, and stability probability (i.e., non-failure probability) for selecting practical strength values. Small-sample statistics utilizes degrees of freedom associated with the number of tests performed, the t-distribution associated with the degrees of freedom, confidence interval based on test results, the t-distribution probability, and the Chi squared distribution. Thus, the desired confidence interval, precision index, and stability probability cannot be determined until test result variability is known. Plotting confidence and prediction limits along with expected values based on actual test results aids in understanding the statistics of small samples, whether the parameter is unconfined compressive strength based on 5 samples or a power-function regression of shear strength from 50 direct shear tests.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Selection of Geotechnical Parameters Using the Statistics of Small Samples

Keaton¹,

Ponnaboyina²

2014

Geo-Congress 2014 Technical Papers

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show abstract

“…compacted powders) and outlined a statistical approach for processing of strength test data. Using statistical inference, Gill et al [10] focused on a rigorous procedure leading to the determination of practical laboratory strength and deformability parameters obtained for rock specimen. The application of most of these analytical studies has been demonstrated on specimens of brittle materials like concrete and compact powders.…”

Section: Introductionmentioning

confidence: 99%

Modified Stanley's approach for statistical analysis of compression strength test data of rock specimens

Maheshwari

Viladkar

Venkatesham

2009

International Journal of Rock Mechanics and Mining Sciences

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“…There are a limited number of numerical studies [18][19][20][21][22][23][24] that applied stochastic analysis for evaluating the strength and deformability characteristics of rocks. However, since these stochastic analyses were performed on the data obtained from laboratory tests on the rock samples, not on the scale of REV (representative elementary volume) or engineering problems, so that the results may not be applicable for evaluating uncertainty or variability of the properties/parameters concerned, since the random nature and the stochastic distributions of the fracture system geometry of the fractured rocks were not properly handled at a proper scale.…”

Section: Introductionmentioning

confidence: 99%