Quantification of strength anisotropy of metamorphic rocks of the Hamedan province, Iran, as determined from cylindrical punch, point load and Brazilian tests

Khanlari, Gholamreza; Heidari, Mojtaba; Sepahi, Ali Asghar; Fereidooni, Davood

doi:10.1016/j.enggeo.2013.11.014

Cited by 58 publications

(17 citation statements)

References 22 publications

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“…Failure load, rock size, rock shape, and loading mode are used to calculate the point load strength index (PLSI or Is (50) ) [3,4]. e PLSI is an important strength parameter index for the classification of rock strength [4][5][6][7], determination of UCS [1][2][3][4][8][9][10][11][12][13][14], and estimation of strength anisotropy [4,11,[15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Point Load Test of Half‐Cylinder Core Using the Numerical Model and Laboratory Tests: Size Suggestion and Correlation with Cylinder Core

Ren

Liu

et al. 2018

Advances in Civil Engineering

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The point load test (PLT) is intended as an index test for rock strength classification or estimations of other strength parameters because it is economical and simple to conduct in the laboratory and in field tests. In the literature, calculation procedures for cylinder cores, blocks, or irregular lumps can be found, but no study has researched such procedures for half-cylinder cores. This paper presents the numerical model and laboratory tests for half-cylinder and cylinder specimens. The results for half-cylinder and cylinder specimens are then presented, analysed, and discussed. A correlation of failure load between half-cylinder and cylinder specimens is established with a suitable size suggestion and correction factor. It is found that the failure load becomes stable when half-cylinder specimens have a length/diameter ratio higher than 0.9. In addition, the results show that the point load strength index (PLSI) of half-cylinder cores can be calculated using the calculation procedures for diametral testing on cylinder cores, and it is necessary to satisfy the conditions that the length/diameter ratio be higher than 0.9 and the failure load be multiplied by 0.8.

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Section: Introductionmentioning

confidence: 99%

“…Many researchers have studied the PLT of cylinder cores. Khanlari et al [17] studied the PLT of metamorphic rocks from the cylindrical punch. Chau and Wong [23] studied the PLT (axial tests) of specimens from borehole rock cores.…”

Section: Introductionmentioning

confidence: 99%

Point Load Test of Half‐Cylinder Core Using the Numerical Model and Laboratory Tests: Size Suggestion and Correlation with Cylinder Core

Ren

Liu

et al. 2018

Advances in Civil Engineering

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“…To date, point load test have yielded the best estimation and prediction of UCS index compared to other tests (Sonmez et al [35]; Diamantis et al [12]; Yilmaz and Yuksek [44]; Basu and Kamran [10]; Heidari et al [17]; Kohno and Maeda [23]; and Wong Li and Diyuan [42]; Khanlari and Abdi-lor [26]). Furthermore, block punch and cylinder punch tests have been used for predicting uniaxial compressive strength of different types of rocks (Van der Schrier [41]; Ulusay and Gokceoglu [39]; Gokceoglu and Aksoy [14]; Ulusay et al [40]; Sonmez et al [34][35]; Sonmez and Tunusluoglu [36]; Aksoy [3]; Aksoy et al [4][5]; Karakul et al [22]; Jafari et al [19]; Mishra and Basu [32]; Khanlari et al [24][25][26]; Abatan et al [1]; Khanlari and Naseri [27]; Heidari et al [18]). More recently, a wide variety of statistical methods have been utilized for developing a proper correlation between UCS index and other engineering properties of rocks, among which different statistics analysis models, multiple regression analysis, ANN model, fuzzy models, and ANFIS models have received a greater attention (Alvarez and Babuska [6]; Sonmez et al [34]; Yilmaz and Yuksek [44]; Kahraman et al [21]; Heidari et al [16][17]; Manouchehrian et al [29]; Mishra and Basu [32]; Torabi-Kaveh et al [38]; Armaghani et al [2]; Jalali [20]).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Uniaxial Compressive Strength and Modulus of Elasticity in Calcareous Mudstones Using Neural Networks, Fuzzy Systems, and Regression Analysis

Mahdiabadi¹,

Khanlari²

2018

Period. Polytech. Civil Eng.

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The uniaxial compressive strength (UCS) and modulus of elasticity (E) are two important rock geomechanical parameters that are widely used in rock engineering projects such as tunnels, dams, and rock slope stability. Since the acquisition of high-quality core samples is not always possible, researchers often indirectly estimate these parameters. In the present study, prediction of UCS and E was investigated in calcareous mudstones of Aghajari Formation using multiple linear regression (MLR), multiple nonlinear regression (MNLR), artificial neural networks (ANN), and adaptive neuro-fuzzy ınference system (ANFIS). For this purpose, 80 samples from calcareous mudstones were subjected to the point loading, block punch, and cylinder punch tests. The performance of developed models was assessed based on determination coefficients (R2), mean absolute percentage error (MAPE), and variance accounted for (VAF) indices. The comparison of the obtained results revealed that, among the studied methods, ANFIS is the most suitable one for predicting UCS and E. Moreover, the results showed that ANN and MLNR respectively predict UCS and E better than MLR and a meaningful relationship between the observed and estimated UCS values in all regressions.

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“…The existence of this particularity plays an important role in many deformation and failure phenomena of jointed rock mass [2][3][4] . There have been numerous experimental investigations on the anisotropic characteristics in rock joints, such as point load test, Brazilian test and shear test [5][6][7][8] . The studies show the surface roughness is considered as the most important factors influencing the anisotropic behaviour of rock joints [9][10][11][12] .…”

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confidence: 99%

Characterization of rock joint surface anisotropy considering the contribution ratios of undulations in different directions

Huang

Hong

Luo

et al. 2020

Sci Rep

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Anisotropy in rock joint is strongly dependent on undulating surface morphology. Recent research of the morphology showed the parameter can express the different types of anisotropic characteristics of the joint surface separately. This report aims to analyze the common characteristic of the anisotropic distribution and exhibit the anisotropic variation trend. The joint morphology function consists of two morphology functions of regular plane in orthogonal directions, and the anisotropic variation determined by the contribution ratios of the two morphology. The roughness weight ratio in orthogonal direction of joint surface is used as an index to describe the anisotropic variation behavior, which proposes the anisotropic variation coefficient (AVC). On this basis, it is divided into 5 levels from strong anisotropic to isotropic. According to the assumption of anisotropic arc distribution, the anisotropic analytic function is derived and the agreement between the deduced curves and measured data therefore suggests the possibility of defining the morphology anisotropy through the index AVC. Finally, we verify the characteristic of three natural rock joints, and prove the proposed function can reflect the anisotropic distribution trend. The new index can be used to describe the anisotropic variation behaviour of rock joint surfaces.

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Quantification of strength anisotropy of metamorphic rocks of the Hamedan province, Iran, as determined from cylindrical punch, point load and Brazilian tests

Cited by 58 publications

References 22 publications

Point Load Test of Half‐Cylinder Core Using the Numerical Model and Laboratory Tests: Size Suggestion and Correlation with Cylinder Core

Point Load Test of Half‐Cylinder Core Using the Numerical Model and Laboratory Tests: Size Suggestion and Correlation with Cylinder Core

Prediction of Uniaxial Compressive Strength and Modulus of Elasticity in Calcareous Mudstones Using Neural Networks, Fuzzy Systems, and Regression Analysis

Characterization of rock joint surface anisotropy considering the contribution ratios of undulations in different directions

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