modulus of elasticity

Dynamic and static properties of the rocks are very important for designing geotechnical structures and modeling rock foundations. The main purpose of this paper is to present the regional and global relationships between the static and dynamic elasticity modulus with an experimental approach and to estimate the shear wave velocity of limestone by statistical methods and artificial neural network (ANN). For this purpose, petrographic, physical and mechanical experiments were first conducted on 80 limestone cores from the Karun 4 dam site. A database was then created using the literature data and compared with the results of this study. The results of statistical analysis show that the ratio of dynamic to static modulus of elasticity for the studied samples is 2.5. Also, the ratio of dynamic to static Poisson for these rocks was 1.41. The average value of the dynamic modulus obtained from the literature was equal to 19.90 GPa, which is less than the average value of the dynamic modulus of the present study (31.20 GPa). Due to the most accurate fit, the global relationship (R2 = 0.98, RMSE = 7.9, MAPE = 1.67) and the regional relationship (R2 = 0.96, RMSE = 5.24 MAPE = 0.91) were presented with very high accuracy between the dynamic and static modulus of elasticity. The results of artificial neural network and multivariate regression showed that estimation of shear wave velocity (Vs) based on P-wave velocity, water absorption and density is possible with high accuracy. The results showed that the ANN accuracy (R2 = 0.98, RMSE = 0.27) was higher than the multivariate linear regression (R2 = 0.86, RMSE = 0.39). The neural network also acts conservatively in predicting this variable.

The accurate determine of uniaxial compressive strength (UCS) and modulus of elasticity (E) using laboratory methods requires substantial time and cost. To overcome these difficult, development of predictive empirical equations to estimate the UCS and E of rocks is very important in rock engineering. This study deals with the prediction of UCS and E of sandstones from petrographic characteristics using multivariable linear regression analysis (MLR). For this purpose, 20 rock blocks were collected from sandstones in different locations of Upper Red Formation in southwestern Qom. Samples were subjected to petrographic examination, which included the observation of 16 parameters and modal analysis. The specimens were also tested to determine the uniaxial compressive strength, modulus of elasticity, porosity, and dry density. Based on the results of statistical analysis, multiple predictive equations were developed to estimate the mechanical properties using petrographic characteristics. The performance of developed equations was assessed using R, RMSE and VAF. Based on the results, it was observed that the proposed equations have a good performance in predicting the UCS and E.

Accurate determination of geo-mechanical properties of rocks such as uniaxial compressive strength (UCS) and modulus of elasticity (E) using standard laboratory tests is a difficult, expensive and time consuming task. This is particularly true for anisotropic, thinly bedded, highly fractured, porous and weak rocks. In order to overcome these difficulties, the development of predictive models for the estimation of these properties seems to be essential in rock engineering projects. The main purpose of this study is prediction of UCS and E of sandstones using artificial neural network (ANN) and multiple regression analysis (MLR). For this, a database of laboratory tests (including 130 sandstone samples) was prepared, which includes porosity, P-wave velocity, dry density, slake durability index, and water absorption as input parameters and UCS and E as output parameter. The performance of the MLR and ANN models are evaluated by comparing statistic parameters, including correlation coefficient (r), root mean square error (RMSE), and variance account for (VAF). Comparison of the multiple linear regressions and ANNs results indicated that respective ANN models were more acceptable for predicting UCS and E than the other.

In the present study, the effect of density (ρ) and porosity (n) on the accuracy of correlation between uniaxial compressive strength (UCS) and modulus of elasticity (E) with Schmidt rebound hardness (HR) was investigated. For this purpose, 15 different limestones were selected and their petrographical characteristics, physical (ρ, n) and mechanical (UCS, E, HR) properties were determined. In the following, simple and multivariable regression analyses based on the HR, ρ and n for estimating the UCS and E were proposed. The relationships proposed based on the statistical tests have been investigated, which indicates their appropriate accuracy. Comparison of simple and multivariate relationships shows that ρ, n play an important role in increasing the estimation accuracy of UCS and E from HR. Moreover, the results show When HR and ρ be used as the input parameter in the regression analysis, the value of the determination coefficient for estimating the UCS and E are 0.88 and 0.83, respectively. Whereas, if HR and n be used as input parameters, the value of the determination coefficients for estimating the UCS and E are 0.91 and 0.74, respectively.

There are three notch displacement modes including the Mode I or opening mode where the notch displacement is perpendicular to the notch front, Mode II or shear mode where notch dimensions are displaced in the notch plane and the Mode III or tear mode where the notch dimensions are displaced in the notch plane parallel to the notch front. Some application areas of rock fracture mechanics can be listed as hydraulic fracturing, rock blasting, rock cutting, mechanized drilling, rock slope stability and comminution in mineral processing. The aim of the present study was to examine the effect parameter of , modulus of elasticity and confining pressure on the mode I Critical Stress Intensity Factor (Critical SIF) using a thick-walled hollow cylindrical chalky specimen and the oil well environment was simulated in the laboratory. To perform the tests on artificial chalky specimens, two artificial symmetrical notches with certain dimensions were created in specimens with an outer diameter (OD) of 73 mm, an inner diameter (ID) of 25 mm and a height of 150 mm. A triaxial stress was applied on the specimen and the pressure required for the propagation of the artificial notches was measured. Five tests were conducted to investigate the effect of modulus of elasticity and six tests to investigate the effect of confining pressure on the mode I Critical SIF. By conducting five tests, it was concluded that with increasing modulus of elasticity, mode I Critical SIF increases and with increasing Poisson’s ratio mode I Critical SIF decreases, also, effect of modulus of elasticity on mode I Critical SIF is more. Meanwhile, it was found that the mode I Critical SIF nonlinearly increased with an increase in modulus of elasticity and it linearly increased with an increase in confining pressure.

The ever increasing growth and development of the metropolitan city of Karaj in recent years has placed implementation of basic studies on Alluvium of Karaj Plain on the top of significant priorities of the region’s development projects. Therefore, in the present paper, the alluvium of South Karaj was studied based on relevant numerous geotechnical laboratory and field tests. In this regard, an area from Pol-e Fardis to Serāh-e Andishe with a length of 10 km is selected and the geotechnical engineering features of this area were taken into careful consideration and study. The carried out studies divide South Karaj Alluvium into five independent parts whose engineering description are presented. On the other hand, since the results of most of relevant laboratory and field tests have been collected, some relations for calculating Elasticity Modulus, Soil Inner Friction Angle as well as other geotechnical parameters in South Karaj Alluvium are introduced. Finally, the process of soil classification in South Karaj Alluvium is compared with the same process in other regions of Karaj, and, given the soil engineering features of Southern part of South Karaj Alluvium, some suggestions are presented for optimization and facilitation of future development projects in south Karaj Alluvium. Geotechnical studies.