Assessment of rock geomechanical quality by quantitative rock fabric coefficients: Limitations and possible source of misinterpretations

Přikryl, Richard

doi:10.1016/j.enggeo.2006.05.011

Cited by 131 publications

(33 citation statements)

References 30 publications

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“…Results from this linear correlation revealed that five of the eight predictive variables were exhibit statistically significant correlations with UCS at the 95% confidence level, which include grain size, grain area, shape factor, quartz and hornblende. Grain size is the most significant petrographical property affecting rock strength with negative r-value of 0.85 for UCS, which being in line with the previous studies by Přikryl [10] and Raisänen [19]. Similarly, strength of rocks tested decreases as the grain area increases with r-value of 0.86.…”

Section: Basic Descriptive and Correlation Analysissupporting

confidence: 77%

“…In fact, up to date there is a full agreement on that quantitative petrographic image analysis (PIA) is an efficient technique for the numerical description of rock microfabric [10]. However, the correct interpretation of rock strength variation is mainly influenced by precise determination of microstructures properties.…”

Section: Quantitative Microfabrics Measurementsmentioning

confidence: 99%

“…Geometrical parameters of rock-forming minerals (microstructures), known to affect mechanical properties of rocks include mineral composition, grain size, grain shape and spatial arrangement of minerals visible in micro-scale [9]. However, quantitative microfabrics study can provide initial estimate of rock properties required at the feasibility and initial design stage [10]. In fact, one obvious reason for this is the complexity of rock materials and the variation in quantitative relationships between different rock types.…”

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confidence: 99%

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Selection of Influential Microfabric Properties of Anisotropic Amphibolite Rocks on Its Uniaxial Compressive Strength (UCS): A Comprehensive Statistical Study

Ali¹,

Wu²

2014

JAMP

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Occasionally, in complex inherent characteristics of certain rocks, especially anisotropic rocks it may be difficult to measure the uniaxial compressive strength UCS. However, the use of empirical relationships to evaluate the UCS of rock can be more practical and economical. Consequently, this study carried out to predict UCS from microfabrics properties of banded amphibolite rocks using multiple regression analysis. Based on statistical results, rock microfabric parameters, which adequately represent the UCS of a given rock type have been selected. The results show that grain size, shape factor and quartz content have high significant correlation with UCS at 95% confidence level. From multiple regression model, approximately 84% of the variance of the UCS can be estimated by the linear combination of these three parameters. However, according to model performance criteria: correlation coefficient (R = 0.919), variance account for (VAF = 97%) and root mean square error (RMSE = 4.16) the study clearly indicates that the developed model is reliable to predict the UCS. Finally, this approach can be easily extended to the modeling of rock strength in the absence of adequate geological information or abundant data.

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Section: Basic Descriptive and Correlation Analysissupporting

confidence: 77%

Section: Quantitative Microfabrics Measurementsmentioning

confidence: 99%

mentioning

confidence: 99%

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Selection of Influential Microfabric Properties of Anisotropic Amphibolite Rocks on Its Uniaxial Compressive Strength (UCS): A Comprehensive Statistical Study

Ali¹,

Wu²

2014

JAMP

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“…During PIA, the following fabric parameters were measured and computed: carbonate grain size (i.e. equivalent diameter from that mean and maximum grain size was computed), carbonate grain's shape (compactness, shape factor, aspect ratio), index of grain size homogeneity, area, perimeter, length, and the slope of the carbonate grain's principal axes (for the precise formulae of the studied grain fabric parameters see Přikryl 2006).…”

Section: Analytical Approachmentioning

confidence: 99%

Comparison of quantitative petrographic, stable isotope and cathodoluminescence data for fingerprinting Czech marbles

2011

Self Cite

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Various marbles from both historic quarries and historical artefacts of the Czech Republic were examined in order to make determinations of their provenance. The methodology used was based upon a combination of petrographic image analysis (PIA) of thin sections, stable isotope geochemistry of carbonates, and cathodoluminescence. Multivariate statistical methods (i.e. cluster analysis and discriminant analysis) confirmed the geoscientific relevance of the marble's different characteristics with a high degree of consistency as well as the enhanced significance of stable C and O isotopes in correlation with the petrographic data. The qualitative cathodoluminescence data provided a useful additional tool to help recognise the fingerprinting of marbles with similar petrographic and/or geochemical characteristics.

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“…Hence, the study of geology including index properties and microfabrics is important for durable and sustainable engineering structures. Index properties of rocks such as unit weight, specific gravity, porosity and point load strength index rely on their composition and texture (Prikryl, 2006). Some parameters dealing with index properties of rocks may be clearly demonstrated by studying textures study Infrastructures such as road, building, cannals, dam, bridges and so on lie on geological bases.…”

Section: Introductionmentioning

confidence: 99%

Texture and index properties of rocks from Malekhu-Thopal Khola area, Central Nepal Lesser Himalaya

Maharjan

2017

Bull. Dept. Geol.

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Infrastructures such as road, building, cannals, dam, bridges and so on lie on geological bases. Durability of the structures demands detail study of rocks in microscopic level. Such study helps to give knowledge about strength and physical properties of rocks, and their usefulness as construction materials. Index properties are the basic parameters to be found out before the developent of engineering structures, and are governed by the texture of the rock such as grain interlocking, crystallinity, shape factor, grain size homogeneity, grain orientation, micro fractures, etc.Textural study of the samples gave the micropetrographic quality index ranging from 0.05 to 49, grain size homogeneity from 0.06 to 0.74, interlocking index ranging from 7 to 92% and texture coefficient ranging from 1.08-1.97. Micropetrographic index has great influence on porosity and point load strength index. Siliceous rocks having high texture coefficient are mechanically sound. When homogeneity in grain size, shape and orientation increases, texture coefficient tends to diminish. Therefore, texture coefficient is an important variable.Dry density of samples ranges from 2309 to 3224 kg/m3, porosity from 0.08 to 8.91% and point load index from 0.26 to 13.13 MPa. Water Absorption Value (WAV) is entirely below 2% except for the slates indicating that most of the rocks have low effective porosity. Strength of rocks varies from very low to very high. Considering the texture and index properties, the rock types suggested for the construction aggregates are quartzites of the Nourpul Formation, the Fagfog Quartzite, and the Chisapani Quartzite, and psammitic schist of the Robang Formation. The quartzite samples from the Fagfog and the Norpul Formations are useful for silica sources. Siliceous dolomite ‘Np3’ of the Nourpul Formation and dolomite ‘Ml1’ of the Malekhu Limestone also show good interlocking, high density and high strength.Bulletin of the Department of Geology Vol. 18, 2015, pp. 1–14

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Assessment of rock geomechanical quality by quantitative rock fabric coefficients: Limitations and possible source of misinterpretations

Cited by 131 publications

References 30 publications

Selection of Influential Microfabric Properties of Anisotropic Amphibolite Rocks on Its Uniaxial Compressive Strength (UCS): A Comprehensive Statistical Study

Selection of Influential Microfabric Properties of Anisotropic Amphibolite Rocks on Its Uniaxial Compressive Strength (UCS): A Comprehensive Statistical Study

Comparison of quantitative petrographic, stable isotope and cathodoluminescence data for fingerprinting Czech marbles

Texture and index properties of rocks from Malekhu-Thopal Khola area, Central Nepal Lesser Himalaya

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