Rock Mechanics
Amirhossein Naseri; Behnam Maleki; Tohid Asheghi Mehmandari; Amin Tohidi; Ahmad Fahimifar
Abstract
The present study delves into investigating the impact of sample size and geometry on the mechanical behavior of rock and concrete. More specifically, it examines factors including Uniaxial Compressive Strength (UCS), Elastic Modulus (E), and Pressure Wave Velocity (Vp). Results indicated a notable correlation ...
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The present study delves into investigating the impact of sample size and geometry on the mechanical behavior of rock and concrete. More specifically, it examines factors including Uniaxial Compressive Strength (UCS), Elastic Modulus (E), and Pressure Wave Velocity (Vp). Results indicated a notable correlation between the dimensions and morphology of the specimens with these properties. All tests were conducted at a uniform loading rate of 0.002 mm/s. According to the outcomes, the effect of sample size and shape on UCS for concrete is more predictable than for rock. The increase in the sample size led to an initial increase followed by a decline in the UCS values of the rocks. Furthermore, the concrete typically showed a drop in the UCS values as sample size increased. The UCS and E values rose at first before falling, suggesting the existence of a sample size with maximum UCS. The Vp values of the prismatic rock and concrete samples continually grew. After attaining their optimum strength, the prismatic samples showed greater degrees of flexibility and ductility compared to cylindrical ones because of post peak behavior. This suggests that prismatic samples, with their less slender geometry and reduced tendency for brittle behavior, are deemed more suitable for UCS testing. These results can improve the accuracy of assessing the mechanical properties of tunneling materials, particularly those used in subsurface construction in urban roads and highways.
Rock Mechanics
Ekin Koken
Abstract
In this study, several soft computing analyses are performed to build some predictive models to estimate the uniaxial compressive strength (UCS) of the pyroclastic rocks from central Anatolia, Turkey. For this purpose, a series of laboratory studies are conducted to reveal physico-mechanical rock properties ...
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In this study, several soft computing analyses are performed to build some predictive models to estimate the uniaxial compressive strength (UCS) of the pyroclastic rocks from central Anatolia, Turkey. For this purpose, a series of laboratory studies are conducted to reveal physico-mechanical rock properties such as dry density (ρd), effective porosity (ne), pulse wave velocity (Vp), and UCS. In soft computing analyses, ρd, ne, and Vp are adopted as the input parameters since they are practical and cost-effective non-destructive rock properties. As a result of the soft computing analyses based on the classification and regression trees (CART), multiple adaptive regression spline (MARS), adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN), and gene expression programming (GEP), five robust predictive models are proposed in this study. The performance of the proposed predictive models is evaluated by some statistical indicators, and it is found that the correlation of determination (R2) value for the models varies between 0.82 – 0.88. Based on these statistical indicators, the proposed predictive models can be reliably used to estimate the UCS of the pyroclastic rocks.
A. Ghanizadeh Zarghami; K. Shahriar; K. Goshtasbi; A. Akbari Dehkharghani
Abstract
Calculation of the specific charge and specific drilling before a blasting operation plays a significant role in the design of a blasting pattern and the reduction of the final extraction cost of minerals. In this work, the information from the Sungun, Miduk and Chah-Firouzeh copper mines in Iran was ...
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Calculation of the specific charge and specific drilling before a blasting operation plays a significant role in the design of a blasting pattern and the reduction of the final extraction cost of minerals. In this work, the information from the Sungun, Miduk and Chah-Firouzeh copper mines in Iran was assessed, and it was found that there was a significant relationship between the specific charge and specific drilling and the hole diameter, bench height, uniaxial compressive strength and joint set orientation. After finding a technical and economic model to calculate the specific charge and specific drilling, this model was tested on the Sungun copper mine. Due to the insufficient consideration during the design of a blast pattern and because of the high hardness of the rocks in some parts of the mine, lots of destructive events such as boulders, back break, bench toe, high specific charge and high specific drilling, fly rock, and ground vibration in the blast operations were observed. The specific charge and specific drilling were found to be the most important technical and economic parameters involved in designing a blasting pattern, and they were found to play an important role in reducing the blasting cost. The blasting cost could be largely controlled by the accurate examination and computation of these parameters. An increase in the rock strength and the angle between the bench face and the main joint set would increase the specific charge and specific drilling. On the other hand, a specific charge and a specific drilling would decrease when the hole diameter increased in every range of the uniaxial compressive strength.
Hadi Fattahi
Abstract
The uniaxial compressive strength of weak rocks (UCSWR) is among the essential parameters involved for the design of underground excavations, surface and underground mines, foundations in/on rock masses, and oil wells as an input factor of some analytical and empirical methods such as RMR and RMI. The ...
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The uniaxial compressive strength of weak rocks (UCSWR) is among the essential parameters involved for the design of underground excavations, surface and underground mines, foundations in/on rock masses, and oil wells as an input factor of some analytical and empirical methods such as RMR and RMI. The direct standard approaches are difficult, expensive, and time-consuming, especially with highly fractured, highly porous, weak, and homogeneous rocks. Numerous endeavors have been made to develop indirect approaches of predicting UCSWR. In this research work, a new intelligence method, namely relevance vector regression (RVR), improved by the cuckoo search (CS) and harmony search (HS) algorithms is introduced to forecast UCSWR. The HS and CS algorithms are combined with RVR to determine the optimal values for the RVR controlling factors. The optimized models (RVR-HS and RVR-CS) are employed to the available data given in the open-source literature. In these models, the bulk density, Brazilian tensile strength test, point load index test, and ultrasonic test are used as the inputs, while UCSWR is the output parameter. The performances of the suggested predictive models are tested according to two performance indices, i.e. mean square error and determination coefficient. The results obtained show that RVR optimized by the HS model can be successfully utilized for estimation of UCSWR with R2 = 0.9903 and MSE = 0.0031203.
S. R. Torabi; M. Ataei; M. Javanshir
Abstract
A literature review revealed that most of the empirical equations introduced for determination of the uniaxial
compressive strength (UCS) of rocks based on the Schmidt hammer rebound number (N) are not sufficiently
reliable mostly due to the relatively low coefficient of correlations. This is ...
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A literature review revealed that most of the empirical equations introduced for determination of the uniaxial
compressive strength (UCS) of rocks based on the Schmidt hammer rebound number (N) are not sufficiently
reliable mostly due to the relatively low coefficient of correlations. This is attributed to the fact that in most
cases one formula is used for all types of rocks, although the density of rocks is introduced to the formulae in
some cases. On the other hand, if one specific relationship between N and UCS is introduced for one rock
type, the equation will yield a much higher coefficient of correlation. During a research program supported
by the Shahrood University of Technology, Iran, a third type of approach was considered. The study aimed
to establish a relationship between N and UCS of a rock mass under particular geological circumstances. As
an example, in this study, the immediate roof rock of coal seams in North-Eastern coal fields of Iran was
selected. In order to determine the N and UCS, a significant number of samples were selected and tested,
both in-situ and in the laboratory, and a new equation was established. The equation can be used to predict
UCS of the roof rock in coal extracting areas in this zone by performing simple in-situ Schmidt hammer
tests. It is predicted that such a procedure will be feasible for other geological conditions.
