Journal of Engineering Geology

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With respect to development of underground structures and their high construction costs in intra- and inter-municipal transportation, it is necessary to study the stability of such structures. In this research, tunnel stability of Mashhad Metro line 2 with 17 km length is studied. First, the type of sediments and geotechnical properties in Mashhad Plain are investigated. The SPT profiles were prepared using Rock Work 2006 software. The soil classification tests and XRD results show that the soils in this line are mostly clay such as Illite and Kaolinite types. Afterwards, because most of the soils in this line are characterized as fine grained, the ground settlement using PLAXIS V8 software was performed. According to the numerical modeling and the depth of tunnel, the optimum depth for tunnel was determined.

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Tunneling in complex geological and geotechnical conditions is often inevitable, especially in urban areas. The stability analysis and the assessment of ground surface settlement of a shield tunneling are of major importance in real shield tunneling projects. The objective of this research is to determine the collapse pressure of a shallow circular tunnel driven by a Tunnel Boring Machine (TBM) of the Earth Pressure Balance (EPB) type.  In this study, analytical methods and three-dimensional numerical modeling with ABAQUS software were implemented to examine the effect of face pressure on the behavior of the tunnel. The parameters were calculated using data from Karaj subway-line 2 as a case study. The analytical method used in this study is Leca-Dormiex which is based on limit analysis theory.  The method is based on a translational multiblock failure mechanism.  Also, elastic and Mohr-Coulomb constitutive model have been used for soil behavior. The results of analytical method and numerical modeling were then compared. Based on the obtained results, face pressure assessed from the analytical method of Leca-Dormiex (upper bound) is the minimum pressure that can be implemented on the face tunnel. It also indicates that with implementation of suggested pressure of analytical method, Karaj subway face tunnel is stable and consequently execution of pre-consolidation methods in this section of the tunnel does not seem to be necessary

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Introduction
One of the most sensitive and important issues in some civil engineering projects is slope design and application. The process of slope design always involve many uncertainties. Hence, it is impossible to accurately comment on its stability or instability. Most of the uncertainties in the slope stability analysis are related to the nature of materials, geometry, environmental conditions, model errors, and measuring errors as well. Therefore, the slope stability analysis with a deterministic approach which uses the concept of safety factor would often not result satisfactory. Consequently, the use of probabilistic methods is more advised. Accordingly, in recent years, the probability analysis has been used to slope stability analysis. In these analyses, the effective quantities of slope stability are considered as statistical distributions, and the reliability coefficient would then be a statistical distribution. Likewise, one of the approaches to simulate uncertainties in the probabilistic analysis is to use the variation coefficient. If the variation coefficient changes, the probability of failure will change accordingly. When the variation coefficient becomes a larger number, costly solutions are required to reduce the probability of failure. If the variation coefficient becomes low, the reliability will be increased and the required costs to reduce the probability of failure will be decreased. Therefore, determining the amount of variation coefficient in these analyses is very important. Furthermore, the correlation coefficient between the quantities is another effective parameter in computing the probability of failure.
Material and methods
In this research, the stability analysis of the slope facing the spillway of the Shiraz Kavar dam has been done in two probabilistic and deterministic methods. Since circular slip probability is more likely than other types of failure, in the analysis of the stability of this slope, the problem of circular failure is very important, and an appropriate equilibrium program should be used for circular failure analysis. Therefore, SLIDE software was used to slope stability analysis. For material behavior, the Hook-Brown failure criterion was applied. In order to determine the strength parameters of the criterion, Geological Strength Index (GSI), uniaxial compressive strength (UCS) and rock constant parameter m_i were used. For crushed rock with a moderate quality of crushing, the GSI quality of the rock mass was about 23 to 38, which the average value of that for the rock mass of the overflow was assumed 35. Also, the uniaxial compressive strength of the rock was evaluated about 50 to 100 MPa with an average value of 75 MPa. In addition, the value of m_i was 10, and due to mechanized drilling, the disturbance factor was considered to be 1. The amount of unit weight was assumed to be 22 kN/m³. The initial model used for deterministic and probabilistic analyses, is the Morgenstern-Price model. To conduct probabilistic analyses, Monte Carlo simulation was performed using random sampling method (RS-MC) and 200,000 sampling were used to converge the simulation results. To determine the coefficient of variation and the probability distribution of UCS, GSI and m_i, the proposed values ​​of Hook (1998) were applied and for unit weight (γ) James Rodriguez and Sitar (2007) studies were used. Also, the minimum and maximum values ​​of UCS and GSI are determined based on the results of experiments, and Third Sigma rule was utilized for m_i and γ quantities. Since the earthquake phenomenon is rarely of great intensity and the number of small earthquakes is higher, therefore the truncated exponential distribution function can be in good agreement with the results of the earthquake. Usually, the maximum magnitude of the earthquake acceleration coefficient is twice that of the average.
Results and discussion
In the presented paper evaluation denotes that the safety factor computed by probabilistic analysis is given as a distribution function. The function provides a clearer view of failure condition. However, a deterministic analysis only illustrates a certain value for the failure. In addition, the results of the probabilistic analysis show that it is possible to optimize the dip of the slope; such that it remains completely stable and the volume of earthwork is also minimized. Therefore, by using probabilistic analysis, the optimal dip of the slope was determined. In these circumstances, the amount of earthwork was decreased by 28,000 cubic meters. Also, the sensitivity analysis of the variation coefficient and correlation coefficient between parameters are analyzed. The results of the sensitivity analysis of the failure probability versus the variation coefficient of the quantities showed that the quantities of sensitivity factor for static conditions is greater than the corresponding pseudo-static, and the GSI amount is the highest, while the specific gravity has the least effect on the probability value. In addition, the analysis indicated that if the GSI coefficient of over 21% is selected, the probability of a static failure is higher than the permissible limit. Also, increasing the variation coefficient of quantities by as much as 50% exhibits that the probability of static failure is still below the permissible limit. Also, the correlation coefficient between UCS and GSI shows that the higher variation coefficient of the quantities is chosen, the more variations of failure probability compared to . In the case of pseudo-static conditions, variations in the failure probability are linear in relation to , while in static conditions, these changes are exponential for an increase of 50% in the variation coefficient. Also, to reduce the coefficient of variation by 50%, the probability of static failure for different values of  is approximately zero.
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Introduction
The main objective of this contribution is to focus on the portion of the comminution process which deals with the prediction of the energy consumption due to the comminution portion of the milling processes.
The comminution energy in mineral processing and cement industry is usually determined by empirical Bond Work Index (BWI), regardless of the mechanical properties of a rock. The BWI is a measure of ore resistance against grinding and is determined by using the Bond grindability test. Determining the BWI value is quite complicated and time consuming. Its value constitutes ore characteristic and is used for industrial commination plants designing and optimization. The BWI is defined as the calculated specific energy (kW h/t) applied in reducing material of infinite particle size to 80% passing 100 µm. The higher the value for BWI, the more energy is required to grind a material in a ball mill. The energy consumed in the process of comminution depends on both the mechanism of comminution and the mechanical properties of the materials being ground. It is interesting to study the effect of the essential ones of these properties on the energy efficiency of grinding process.
Material and methods
Several attempts have been made to obtain and optimize the comminution energy. An efficient Response Surface Method, (RSM)-based method for the BWI approximate value determination, which is based on physico-mechanical tests, is presented in this paper.
BWI and some physico-mechanical tests on 8 typical rock samples and its correlation are studied; it would be beneficial to examine this relation based on physical concept. The database including Uniaxial Compressive Strength (UCS), Abrasion (AT), Hardness (HT) and Modulus of Elasticity (ME) are assembled by collecting data from Haffez experiments.
Results and discussion
The determination of the BWI from RSM- based multivariate model is almost matched with measured Bond’s work index. As a result of analysis the best equation obtained from RSM-based model is formulized in Equation 1:
                                      (1)
Standard statistical evaluation criteria are used to evaluate the performances of predictive models.
Conclusion
The performance of the estimator models can be controlled by R², VAF, RMSE, MAPE, VARE and MEDAE. The RSM- based model with higher VAF as well as lower RMSE, MAPE, VARE, MEDAE shows better performance in comparison to the Haffez single-variable models. AT and ME have the greatest effect on the value of BWI; and also HT has the least impact../files/site1/files/134/6.pdf