Determining the minimal number of specimens for laboratory testing of rock properties

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

doi:10.1016/j.enggeo.2004.10.005

Cited by 69 publications

(48 citation statements)

References 15 publications

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“…The number of specimens in a group, coefficient of variation, confidence interval, and a targeted precision index were used in an algorithm that defined the minimum number. Gill et al (2005) concluded that the smallest sample size varies for different rocks and it is difficult to determine the sample size required to obtain certain confidence interval without actual testing. Gill et al's (2005) results are in general agreement with the findings of this study.…”

Section: Discussionmentioning

confidence: 98%

“…Although these tests were performed on one rock type at 99.7% confidence interval, 15-25 samples would give a less than 15% deviation from the mean at a 95% confidence interval. Gill et al (2005) used a rigorous statistical procedure to determine the number of samples to test for mechanical properties of rocks. The number of specimens in a group, coefficient of variation, confidence interval, and a targeted precision index were used in an algorithm that defined the minimum number.…”

Section: Discussionmentioning

confidence: 99%

“…The validity of statistics based on a theoretical distribution depends entirely on how closely the natural distribution follows the theoretical model (Borradaile, 2003). ASTM method E 122 (1989) and Gill et al (2005) state that strength data should be normally distributed to carry out statistical procedures. Although previous research suggests that unconfined compressive strength data tend to follow a normal distribution (Gill, 1963;Yamaguchi, 1970;Hsu and Nelson, 2002;Sari and Karpuz, 2006), Q-Q (quantile-quantile) probability plots were used to assess the normality of unconfined compressive strength data for each rock type.…”

Section: Data Distributionmentioning

confidence: 99%

“…Based on a series of tests performed on granite, andesite, and sandy tuff, Yamaguchi (1970) concluded that 10 or more samples were needed to determine the average compressive strength. Gill et al (2005) used a detailed statistical analysis to determine the minimum number of samples required for laboratory testing of rock properties and found that the minimum number varied with the rock type and that it was impossible to determine the number without prior testing. Various testing agencies have set their own standards to define the minimum number of samples required to test for unconfined compressive strength.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Variability of unconfined compressive strength in relation to number of test samples

Ruffolo

Shakoor

2009

Engineering Geology

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Data Distributionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Variability of unconfined compressive strength in relation to number of test samples

Ruffolo

Shakoor

2009

Engineering Geology

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“…According to a detailed statistical analysis performed by Gill et al (2005), it is impossible to determine the minimum sample number for laboratory testing of rock properties without prior testing. Numerous testing agencies have established their own standards for ascertaining the minimum number of samples required to test for unconfined compressive strength.…”

Section: Number Of Samplesmentioning

confidence: 99%

Development of a correlation between mineralogy, rock strength measures, and breakage of Copper Porphyries

Yildirim¹

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The role of the comminution step in mineral processing is to reduce the size of the ore so that the valuable minerals liberated from the gangue minerals, in preparation for beneficiation. The effectiveness of the comminution step is related to the rock strength, which controlled by the minerals making up the rock, relative mineral abundances, texture, fracture frequency, and its associations. Copper porphyry deposits account for approximately two-thirds of global copper and form a good basis for investigating the effects of ore structure in comminution.Recent developments in integrated studies between ore variability and mineral processing have driven the need to understand ore variability better as a means of maximizing the value from the ore. As a result, the developed methodologies are now being adapted for incorporation into geological and metallurgical databases, with the aim of linking ore mineralogy to comminution and beneficiation performance. However, the current developments are driven by statistical correlations rather than a fundamental and mechanistic understanding.This thesis aims to develop a fundamental mechanistic relationship between mineralogy, hardness, and breakage by focusing on proportional mineral ratio changes caused during copper ore formation. Incorporated geological understanding of porphyry copper ore formation and phyllic alteration to processing is studied for two case studies viz. Highland Valley Copper Mine (HVC) and Los Bronces Mine (LB) and the approach underpins and strengthens the current methodologies for predicting the mill throughput of copper porphyries.This new approach introduces the key ore-forming parameters to mineral processing. The relationship between processing performance (breakage) and the degree of phyllic alteration is studied. This provides a link of ore genesis with rock strength and breakage behavior. A mechanistic method of single impact load cell test was utilized to measure the rock strength. The link between the strength and primary geological features is studied using QXRD; X-ray computed tomography and automated logging instruments.The thesis establishes that there is a relationship between the proposed porphyry copper process alternation index (PAI) and rock strength. The methods in this study can be used in developing the relationships between primary geological features and the rock strength; providing a novel and powerful technique to propagate breakage characteristics into the geological model of an ore body. Barış Gazanfer Yıldırım ii Declaration by authorThis thesis is composed of my original work and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, and a...

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Fatigue Test Analysis of Automotive Key Parts Based on Censored Data and Small Sample Setting

Wang

Liu

Wang

et al. 2016

Quality & Reliability Eng

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The study discusses how some challenges from a small sample fatigue test can be analysed statistically and resolved. In terms of data dispersion, fatigue data are initially processed by confidence, and then, the fatigue life curve is replaced by the parabolic reliability approximation. Fatigue data under various reliability levels are obtained. Instead of the traditional single S–N curve, the mean value curve and mean square deviation curve of the S–N curve are computed based on the processed fatigue data. The S–N curve with reliability is deduced by applying quantile theory. The S–N curve is improved by considering the effects of low‐amplitude load strengthening. The benefits of the modification are visible in the comparison of the fatigue life before and after low‐amplitude load strengthening. Copyright © 2016 John Wiley & Sons, Ltd.

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Determining the minimal number of specimens for laboratory testing of rock properties

Cited by 69 publications

References 15 publications

Variability of unconfined compressive strength in relation to number of test samples

Variability of unconfined compressive strength in relation to number of test samples

Development of a correlation between mineralogy, rock strength measures, and breakage of Copper Porphyries

Fatigue Test Analysis of Automotive Key Parts Based on Censored Data and Small Sample Setting

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