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Öğe A brittleness index to estimate the sawability of carbonate rocks(A A BALKEMA PUBLISHERS, 2005) Kahraman, S.; Fener, M.; Gunaydin, O.; Konecny, PPerformance measurements of large-diameter circular diamond saws were conducted on eight different carbonate rocks in marble factories located in some areas of Turkey and hourly slab productions were calculated. Rock samples were collected from these factories for laboratory tests. Triaxial compressive strength test were carried out on each rock type and a brittleness index determined from Mohr's envelope. Slab productions of circular diamond saws and the brittleness index evaluated using both linear and exponential regression analysis. The both regression analysis produced strong correlations between the slab production and the brittleness index. Concluding remark is that the sawability of carbonate rocks can be predicted from the brittleness index determined from Mohr's envelope. However, the validity of the derived equations must be checked for the other rock types.Öğe Adaptive neuro-fuzzy modeling for the swelling potential of compacted soils(SPRINGER, 2009) Kayadelen, C.; Taskiran, T.; Gunaydin, O.; Fener, M.This paper aims to present the usability of an adaptive neuro fuzzy inference system (ANFIS) for the prediction swelling potential of the compacted soils that are important materials for geotechnical purposes such as engineered barriers for municipal solid waste, earth dams, embankment and roads. In this study the swelling potential that is also one of significant parameters for compacted soils was modeled by ANFIS. For the training and testing of ANFIS model, data sets were collected from the tests performed on compacted soils for different geotechnical application in Nigde. Four parameters such as coarse-grained fraction ratio (CG), fine-grained fraction ratio (FG), plasticity index (PI) and maximum dry density (MDD) were presented to ANFIS model as inputs. The results obtained from the ANFIS models were validated with the data sets which are not used for the training stage. The analyses revealed that the predictions from ANFIS model are in sufficient agreement with test results.Öğe Determination of fracture depth of rock blocks from P-wave velocity(SPRINGER HEIDELBERG, 2008) Kahraman, S.; Soylemez, M.; Fener, M.The quality of large rock blocks produced from quarries depends significantly on the fractures and the extent to which they penetrate into the rock. The paper reports a laboratory study to evaluate the possibility of the determining fracture depth in rock blocks from P-wave velocity. Three igneous, three sedimentary and three metamorphic rocks were studied. Inverse linear relations were found between the fracture depths and the P-wave velocities. Although, the slope of the regression lines is approximately the same for the rocks belonging to one rock class, different trends are seen for the different rock types. In addition, some correlation was found between the slopes of the regression lines and the physical properties of the rocks.Öğe Evaluating the geomechanical properties of Misis fault breccia (Turkey)(PERGAMON-ELSEVIER SCIENCE LTD, 2008) Kahraman, S.; Alber, M.; Fener, M.; Gunaydin, O.This study investigated the correlations between the uniaxial compressive strength (UCS), elastic modulus (E) or the differential stress (Delta sigma) and density, P- and S-wave velocity, volumetric block proportion (VBP), average block diameter (($) over bar (block)), average block diameter factor (ABD(F)), aspect ratio and roundness. The results were evaluated by both simple and multiple regression analysis. Simple regression analysis results show no correlation between UCS, E or Delta sigma and the other examined parameters, except S-wave velocity. A correlation was, however, found between UCS and S-wave velocity for 25% and 75% VBP. Other significant models including density, P- and S-wave velocity and textural properties for the prediction of UCS and Ds were found by multiple regression analysis. From these results it is concluded that the strength of the Misis fault breccia cannot be defined by a single parameter such as VBP as is the case for some bimrocks. It is also concluded that the models developed by multiple regression analysis can be used to predict the UCS and Ds of the Misis fault breccia. The multiple regression models including two or three independent variables are the most practical equations. Using these equations to predict the UCS and Ds of the fault breccia is easier, faster and cheaper than conducting triaxial or uniaxial compressive strength tests. (C) 2008 Elsevier Ltd. All rights reserved.Öğe Evaluating the strength and deformability properties of Misis fault breccia using artificial neural networks(PERGAMON-ELSEVIER SCIENCE LTD, 2009) Kahraman, S.; Gunaydin, O.; Alber, M.; Fener, M.Since the preparation of smooth specimens from the fault breccias are usually difficult and expensive, the development of some predictive models for the geomechanical properties of fault breccias will be useful. In this study, artificial neural networks (ANNs) analysis was applied on the data pertaining to Misis fault breccia to develop some predictive models for the uniaxial compressive strength (UCS) and elastic modulus (E) from the indirect methods. The developed ANNs models were also compared with the regression models. As a result of ANNs analysis, very good models were derived for both UCS and E estimation. It was shown that ANNs models were more reliable than the regression models. Concluding remark is that UCS and E values of Misis fault breccia can reliably be estimated from the indirect methods using ANNs analysis. (c) 2008 Elsevier Ltd. All rights reserved.Öğe Influence of orthoclase phenocrysts on point load strength of granitic rocks(ELSEVIER SCIENCE BV, 2012) Fener, M.; Ince, I.The point load index test involves loading cylindrical, block or irregular rock samples between two conical platens until sample failure. The point load strength index (I-s) determined using failure load and sample dimension is widely and variously used in engineering geological studies. Therefore, a comprehensive knowledge about the factors that could influence the index value is necessary. This paper explores the effects of orthoclase phenocryst dimension on the point load strength index (I-s) of granitic materials from Turkey. In this context, point load strength values of 117 granite core samples were determined. The granites used in this study included orthoclase phenocrysts as important mineral constituents. High-resolution image was obtained from the freshly fractured surface of each sample. The ratio of orthoclase phenocrysts (ROP) on the failure surface was determined using image analysis. When point load strength values were correlated with the ratios of orthoclase phenocrysts, an inverse relationship emerged. Issues in order to minimize the influence of orthoclase phenocrysts on the point load strength were discussed. (C) 2012 Elsevier B.V. All rights reserved.Öğe Modeling of the angle of shearing resistance of soils using soft computing systems(PERGAMON-ELSEVIER SCIENCE LTD, 2009) Kayadelen, C.; Gunaydin, O.; Fener, M.; Demir, A.; Ozvan, A.Precise determination of the effective angle of shearing resistance (phi') value is a major concern and an essential criterion in the design process of the geotechnical structures, such as foundations, embankments, roads, slopes, excavation and liner systems for the solid waste. The experimental determination of phi' is often very difficult, expensive and requires extreme cautions and labor. Therefore many statistical and numerical modeling techniques have been suggested for the phi' value. However they can only consider no more than one parameter, in a simplified manner and do not provide consistent accurate prediction of the phi' value. This study explores the potential of Genetic Expression Programming, Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy (ANFIS) computing paradigm in the prediction of phi' value of soils. The data from consolidated-drained triaxial tests (CID) conducted in this study and the different project in Turkey and literature were used for training and testing of the models. Four basic physical properties of soils that cover the percentage of fine grained (FG), the percentage of coarse grained (CG), liquid limit (LL) and bulk density (BD) were presented to the models as input parameters. The performance of models was comprehensively evaluated some statistical criteria. The results revealed that GEP model is fairly promising approach for the prediction of angle of shearing resistance of soils. The statistical performance evaluations showed that the GEP model significantly outperforms the ANN and ANFIS models in the sense of training performances and prediction accuracies. (C) 2009 Elsevier Ltd. All rights reserved.Öğe Predicting the compressive and tensile strength of rocks from indentation hardness index(SOUTH AFRICAN INST MINING METALLURGY, 2012) Kahraman, S.; Fener, M.; Kozman, E.The prediction of rock properties from indirect testing methods is important, particularly for preliminary investigations since indirect tests are easier and cheaper than the direct tests. In this study, we investigate the predictability of the uniaxial compressive strength (UCS) and Brazilian tensile strength (BTS) of rocks from the indentation hardness index (IHI) obtained using point load apparatus. Forty-six different rock types, 14 of which were igneous, 15 were metamorphic, and 17 were sedimentary were tested in the laboratory. The UCS and BTS values were correlated with the corresponding IHI values and the results were statistically analysed. The influence of rock classes on the relationships was also investigated. A strong correlation between UCS and IHI was found for all data. The correlation between BTS and IHI is not as strong as the correlation between UCS and IHI.However, it is in the acceptable limits. When the regression analyses were repeated for igneous, metamorphic, and sedimentary rocks, the correlation coefficients were generally increased. The results show the UCS and BTS can be estimated from IHI. In addition, the effect of rock classes on the relationships between IHI and both UCS and BTS is important.Öğe Predicting the Los Angeles abrasion loss of rock aggregates from the uniaxial compressive strength(ELSEVIER SCIENCE BV, 2007) Kahraman, S.; Fener, M.Los Angeles abrasion, Uniaxial compression, and porosity tests were performed on 35 different rock types collected from different areas of Turkey, nine of which were igneous, eleven of which were metamorphic and fifteen of which were sedimentary. To investigate the possibility of predicting the Los Angeles (LA) abrasion loss from the uniaxial compressive strength (UCS), the results of the tests were analyzed using regression analysis. A good correlation between L.A. abrasion loss and UCS was found. In addition, it was seen that when the rocks were classified into classes according to porosity, the correlation coefficients were increased. Concluding remark is that derived equations can reliably be used for the prediction of L.A. abrasion loss from the UCS. (c) 2007 Elsevier B.V All rights reserved.Öğe Predicting the physico-mechanical properties of igneous rocks from electrical resistivity measurements(TAYLOR & FRANCIS LTD, 2006) Kahraman, S.; Ogretici, E.; Fener, M.; Yeken, T.; Cotthem, AV; Charlier, R; Thimus, JF; Tshibangu, JPElectrical resistivity values of eight different igneous rocks were measured on core samples using a resistivity meter in the laboratory. The resistivity tests were conducted on the samples fully saturated with brine (NaCl solution) and uniaxial compressive strength, Brazilian tensile strength, density and porosity values of the samples were determined in the laboratory. Resistivity values were correlated with the corresponding physico-mechanical properties using simple regression analysis methods. Generally strong correlations obtained from regression analysis. Concluding remark is that electrical resistivity may be a representative measure of properties of igneous rocks. However, further research is necessary to check how the stronger and different igneous rocks affect the correlations.Öğe The effect of porosity on the relation between uniaxial compressive strength and point load index(PERGAMON-ELSEVIER SCIENCE LTD, 2005) Kahraman, S.; Gunaydin, O.; Fener, M.[Abstract Not Available]Öğe The Effect of Rock Sample Dimension on the P-Wave Velocity(SPRINGER/PLENUM PUBLISHERS, 2011) Fener, M.P-wave velocity is one of the non-destructive geophysical methods directly or indirectly used by engineering working by various filed. Thus the accuracy of the recorded P-wave velocity affects these parameters. In this survey whether the sample dimensions measured in laboratory have effect on P-wave velocity or not was investigated. Nine different rock groups were used in this study. Six different diameter core samples were prepared from each of the groups. Ultrasonic tests were carried out on the core samples having different diameter to investigate how the sound velocity varies with sample dimension. The test results were statistically analyzed using the method of least squares regression, exponential, and polynomial relationship with high correlation coefficient were found between the sample diameters and P-wave velocities. In four sample groups a decrease in ultrasonic velocity depending on an increase in diameter was observed. In five other sample groups in the samples up to 78.68 mm diameter, a decrease in P-wave velocity value was observed but a significant increase in the P-wave velocity was observed for the biggest diameter samples. This observed decrease connected with sample dimension varies dependently on physical characteristic properties of the sample.Öğe The usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: Regression and artificial neural networks analysis(PERGAMON-ELSEVIER SCIENCE LTD, 2010) Kahraman, S.; Alber, M.; Fener, M.; Gunaydin, O.The derivation of some predictive models for the geomechanical properties of fault breccias will be useful due to the fact that the preparation of smooth specimens from the fault breccias is usually difficult and expensive. To develop some predictive models for the uniaxial compressive strength (UCS) and elastic modulus (E) from the indirect methods including the Cerchar abrasivity index (CAI), regression and artificial neural networks (ANNs) analysis were applied on the data pertaining to Misis Fault Breccia. The CAI was included to the best regression model for the prediction of UCS. However, the CAI was not included to the best regression model for the prediction of E. The developed ANNs model was also compared with the regression model. It was concluded that the CAI is a useful property for the prediction of UCS of Misis Fault Breccia. Another conclusion is that ANNs model is more reliable than the regression models. (C) 2010 Elsevier Ltd. All rights reserved.
