نشریه روش های تحلیلی و عددی مهندسی معدن
پیاپی 30 (بهار 1401)

One of the important issues in designing non-level tunnels is determining the optimal location of tunnels relative to each other. In this research, to optimally locate the two factors of land subsidence and stability (safety factor) of tunnels have been used. Optimal placement of non-level tunnels in various geological conditions should use probabilistic methods and reliability. In this paper, PLAXIS3D finite element software is used to study different states of non-level tunnels. Then, using the harmony search algorithm, two limit state functions are estimated separately for the safety factor and maximum ground surface subsidence. Then, using the two limit state functions obtained from the previous step and the first-order reliability methods and the Monte Carlo simulation in RT software, the best location for excavation of the second tunnel in relation to the previous (existing) tunnel is based on having the highest safety factor and lowest ground subsidence. 

Due to the complexity of the interaction between the tunnels and also due to the uncertainty in the design parameters, in this paper, using probabilistic analyzes such as the Monte Carlo simulation method and first-order reliability, the optimal stability and placement of non-level tunnels in RT probabilistic software was discussed. Because RT software requires a correct and accurate limit state function, the harmonic search algorithm in MATLAB was used to calculate the stability and also to achieve this limit state function. 

In this paper, using PLAXIS3D software, the tunnel was modeled in 32 different rock masses and the results are different in each of the 32 rock masses due to the inequality in the input parameters (safety factor and maximum settlement). To evaluate the reliability of the new tunnel excavation (existing sub-tunnel), 32 models which were analyzed by PLAXIS3D software were compared with the predicted model to achieve the lowest settlement rate and the highest safety factor by the harmony search algorithm. The comparison showed good consistency between the model predicted by the harmony search algorithm and the model performed by numerical methods. Therefore, due to the proximity of the performed model and the predicted model, the limit state function is accurate to obtain the probability of failure of the new tunnel. 

According to the results obtained in both Monte Carlo simulation methods and first-order reliability, the probability of failure (approximately 0.33%) and the high-reliability index are shown and the tunnel position is in very good condition. According to the analysis of tunnel random variables by RT software, it was found that the geological durability index is very important and effective. It should be noted that the results of this study show that the reliability methods used in the RT program to stabilize and locate the new tunnel under the existing tunnel can be used as a high-performance method in analyzing underground space problems.

As the most important phosphate producer in Iran, the Esfordi phosphate complex produces apatite concentrate from the igneous ore by the flotation method. This plant is designed to separate phosphate from iron minerals. There is a type of rock in the Esfordi deposit that contains magnesium-bearing silicate minerals as gangue, which refers to green rock. Although the green rock includes five million tons of the mine reserve with an average grade of 7% P2O5, it has not been fed to the beneficiation plant, so far. In this research, the green rock processing was investigated using the current processing plant. A representative sample of green rock was prepared and characterized to evaluate the chemistry, mineralogy, and degree of freedom of apatite minerals. The laboratory magnetic separation and flotation tests along with the plenary sampling and characterization from the processing plant were performed. 

Esfordi Phosphate Mine has the largest reserves of igneous phosphate in the country. At present, the feed for the dressing plant is supplied from apatite and iron-apatite. The green rock is an alternative feed for the beneficiation plant. The presence of magnesium-bearing silicates and fine particles are the two main obstacles of green rock flotation. In this research, flotation experiments were performed to process green rock, and the performance of the current phosphate processing plant was assessed. 

Sampling was performed in two stages. In the first step, a sample was taken from the stock to identify the characteristics of green rock. The laboratory magnetic separation experiments at different magnetic field intensities and flotation experiments were performed. Fatty acid collector (to float apatite) and corn starch (for depressing iron ores and silicate minerals) were used in the flotation tests. The industrial-scale investigations were made by feeding the green rock to the plant, and sampling procedures were performed from different grinding, classification, and flotation streams. 

The results of High-intensity magnetic separation experiments showed that some of the silicate minerals found their way to the iron magnetic separation concentrate (recovery of 10.38% MgO at 5000 gausses). Flotation experiments showed that the recovery for green rock samples was very low and under normal conditions, recovery and P2O5 grades of 7.39 and 21.11% were gained, which increased to 38.65 and 27.98% after desliming. The efficiency of feeding green rock to the current circuit was monitored and low flotation recovery was observed along with high froth stability. The efficiency of the grinding circuit and desliming cyclones was also evaluated. Then, suggestions were made to improve the current processing circuit for green rock beneficiation.

In this study, using the DEM (which exhibits suitable abilities to simulate the mechanical behavior of discrete media), the bearing capacity of a stone column has been modeled. The results showed that increasing the diameter of the stone column increases the bearing capacity and the trapped stone column has between 25 to 30% more bearing capacity than the floating stone column. 

It is necessary to study the actual behavior of stone columns in different boundary conditions and soils and against incoming loads. In this regard, researchers have used laboratory tools to study the performance of these columns. However, due to some limitations of laboratory methods, it is impossible to control all effective microstructural parameters in understanding stone column behavior. In this regard, some numerical studies based on the continuum mechanics were performed. Numerical modeling based on the mechanics of continuous media has provided valuable results on subsidence, lateral deformation, and stress-strain diagrams based on macroscopic behavior. However, stone columns are generally composed of washed sand materials and their behavioral nature is distinct sometimes their behavior depends on the performance of their particles in interaction with loose soil particles and it is not possible to accurately evaluate the performance of stone columns using finite element modeling. The discrete component method has been considered as the purpose of this research. 

The dimensions of the model were selected due to the limited number of particles due to the increase in the time of analysis on the scale of the laboratory physical model. These dimensions are determined in such a way that, with a scale of 20 times, they are similar to real projects and represent the diameter of a column of 1 meter with a length of 6 meters in reality. To eliminate the effects of lateral borders on the results, the distance of the borders from the center of the stone column was considered to be 5 times the diameter of the column. A behavioral model with rolling resistance was used. 

The modeled stone column is a tall stone column. Because the soil around the stone column is loose, the failure of the stone column is in the form of lateral expansion, which in this form is the tendency of the main force chains. The tall stone column, without lateral restraint, which rests on the trapped end and the forces are transmitted along with them, acted like a tall and thin column, which if its axis exceeds the thinness of the column. The buckle follows it. Evaluation of the behavior of the stone column can be simulated with the DEM, and micro-mechanical evaluations, especially the buckling of force-carrying chains and the path of particles can be observed. Also, the reduction of particle size has limited effects on reducing the bearing capacity of the loose stone-soil column complex.

According to the results, as the injection duration and the pumping rate increase, the fracture length increases and the maximum length created is about 22 meters by applying a fluid with a viscosity of one centipoise during 5 minutes injection time and the rate of 35 barrels per minute or similarly by the same fluid with 18 minutes injection time and the rate of 10 barrels per minute. 

Hydraulic fracturing if properly implemented can be one of the least costly ways to increase the maximum production of the reservoir. Due to the complexity of the hydraulic fracturing process, various modeling has been performed to find the closest predictions of the actual fracture characteristics. Linear elastic fracture mechanics (LEFM), adhesion zone method, and plastic criteria can be used to evaluate the fracture onset time and its expansion in rock. 

To investigate the effect of injection duration on fracture growth, fluid was injected into the well with a viscosity of 1 cp and an injection rate of 0- 10 barrels per minute for periods of 5, 8, 10, 12, 15, and 18 minutes. This injection is made by drilling a well in the middle part of the reservoir. In the first 5 seconds, the injection rate increases linearly from zero to 0.07 barrels per minute and remains constant until the end of injection time. This distribution of injection rate over time is chosen to avoid sudden pressure. As the injection begins, the fluid pressure within the fracture increases, and as the fracture pressure is reached, fracture occurs. 

The purpose of designing hydraulic fracturing operations is to make some predictions to optimize these operations. There are five important factors to design for a hydraulic fracture: the length, height, and fracture opening that the propane holds, the fracture initiation pressure, and the fracture orientation. Four of these critical parameters are derived from hydraulic fracture modeling, so modeling provides 80% of the required solutions.The main input parameters for modeling hydraulic fractures are surface stresses, pore pressure, Young's modulus, Poisson's coefficient, porosity, permeability, angle of friction, and rock adhesion, and parameters related to rock fracture mechanics such as fracture energy, toughness, and components. As the injection duration and pumping rate increase, the fracture length increases, and the maximum length created for a fluid with a viscosity of one centipede at an injection of 5 min at 35 barrels per minute or 18 min at 10 barrels, is about 3 meters high while its maximum height is about 70 meters. Also, the maximum fracture opening in its opening is about 1 mm. Fluid viscosity affects the fracture width more than its length and also increases with the fracture width viscosity.

One of the problems with NATM tunneling in urban areas is the risk of excessive surface settlement during excavation operations. For real analysis and detailed study of surface settlement, it is necessary to pay attention to the real soil conditions. However, the conventional methods are always deterministic, rather than taking the natural spatial variability of soil properties into account. Therefore, in this study, an attempt has been made to model the real soil conditions by spatial variability of the soil young modulus based on a three-dimensional random field. By combining finite difference analysis with random field theory, a preliminary investigation has been performed into the surface settlement with spatially random Young modules. For this purpose, a combination of finite difference numerical method, random field, and Monte Carlo simulation is used which is known as the random finite difference method (RFDM). The procedure used is re-implemented by the authors in a MATLAB environment to combine it with The FLAC3D program and a series of parametric analyses were conducted to study the effects of uncertainty due to the variability of soil Young’s modulus on ground movements.

Excessive surface settlement is one of the major problems we encounter when constructing shallow tunnels in soft grounds. For the analytical study of surface settlement, it is necessary to consider soil properties in design calculations with high accuracy. In this research, the complex RFDM method is used to express the spatial variability of soil properties so that we can show its effects on surface settlement. The results demonstrate that soil variability exerts an influence both on the magnitude and distribution of surface settlement. In addition, it is concluded that negligence of the spatial variability of soil properties in surface settlement probability analysis can lead to underestimation of tunnel design parameters.

To create a random field, the values of SOF are determined first. Then, a three-dimensional random field is created by the random field generation functions. The random field created is assigned to the finite difference mesh by the embedded FISH language in FlAC3D.Finally, 1000 Monte Carlo simulations are performed and 1000 surface settlement curves for each SOF are generated. 

The mean values ​​of the Smax in numerical stochastic analysis when the SOF is 60 m is approximately equal to the obtained Smax from the numerical model because with increasing SOF the spatial correlation of the Young modulus parameter increases and is closer to the soil characteristics of the tunnel. In addition, the COV of the Smax tends to be 0.3 with increasing the SOF, but in general, it increases significantly (from 0.01 to 0.3), which causes changes in the magnitude of the Smax (between 5 and 80). Mm) becomes.The spatial variability of the Young modules causes the change in the magnitude of the surface settlement as well as a change in its location, so three-dimensional numerical analyzes can accurately display the maximum displacement of the Smax in both a vertical and longitudinal section of the tunnel.

This research deals mainly with the degassing method with cross-measure boreholes in the longwall mining method. Determining the appropriate values ​​of different parameters of methane drainage boreholes is necessary to increase efficiency. These parameters include the length of the methane drainage boreholes, the angle of the boreholes relative to the axis of the tailgate, and the inclination of the boreholes. Accordingly, the analysis of operational data obtained from the methane drainage of the E4 panel has shown that with increasing the dip of the panel, the angle of boreholes relative to the axis of the tailgate should be considered less. Also, typically, the exhaust gas flow of methane drainage stations starts to increase at a distance of 15 to 25 meters from the edge of the face, so the length of methane drainage boreholes should not be considered more than 45 meters. 

Cross-measure boreholes method involves drilling boreholes from the tailgate to a stress-free area in the roof and floor layers of a working seam of coal. To prevent methane from entering the work area or reducing the amount of gas entering, it is necessary to perform methane drainage in this area. After specifying this area, the parameters of methane drainage boreholes can be specified. These parameters include the distance between the degassing stations, the angle of the drainage boreholes to the horizon, the angle to the longitudinal axis of the upper corridor, and the length of the drainage boreholes. Therefore, the main purpose of this paper determines the appropriate value of cross-methane drainage borehole parameters to increase the amount of removed gas from each borehole by analyzing operational data. 

To determine the appropriate values of the parameters of methane drainage boreholes in the cross-measure boreholes method, data from 67 methane drainage stations including 280 boreholes drilled in the E3 panel and 68 stations containing 152 boreholes in the E4 panel were collected.  These data include the length of the boreholes, the angle to the axis of the upper corridor, the dip of the borehole, the distance between the stations, and the amount of exhaust gas from each station and borehole in cubic meters per minute. The collected data had been analyzed using Minitab and Excel software. 

The steeper the dip of the coal seam, the more the boundary of the methane disposal area tends to the tailgate. As a result, the angle of methane drainage boreholes relative to the tailgate axis should be considered less. Reducing the distance of gas stations from 18 to 22 meters to about 9 to 12 meters leads to an increase in exhaust gas from the stations. The discharge of the stations starts to increase at a distance of about 15 to 25 meters from the edge of the face, so considering the boreholes angle and other parameters it is suggested that the length of the boreholes be between 35 and 45 meters.

Since a significant part of mine operating cost belongs to hauling operations, optimizing the allocation and scheduling of trucks in a dynamic system is essential and significantly affects production efficiency. So far, different models and methods have been proposed for optimizing haulage scheduling. In this paper, scheduling models have been reviewed, and a flow-shop model has been developed to optimize truck dispatching systems in open-pit mines. The proposed model has been implemented on a small-scale example, driven by a real-world case study, and results have been discussed. Numerical investigation demonstrates that this model is a powerful tool for optimizing truck scheduling and can result in an enhancement in the productivity of mining operations. The most crucial challenge that must be addressed in future work is the development of fast solution techniques to solve real-scale instances of the developed model.  

The hauling operation is responsible for a significant portion of the operating cost in an open pit mine operation. Therefore, as the main hauling machine, trucks' optimum scheduling is crucial and can dramatically affect mine production productivity. Conventionally, assignment and dispatching of the trucks are defined as two main optimization problems in scheduling hauling operations. Simulation and stepwise mathematical programming have been proposed in the literature to solve these two problems. However, a dynamic and integrated optimization model is required to optimize hauling operations of the state-of-the-art revolution in data collection systems, computational capacity, and the necessity of real-time decision-making. Therefore, this study aims to develop an integrated and single-stage optimization model to optimize truck scheduling problems.

In this study, the truck dispatching problem has been discussed, and a flow-shop scheduling model has been suggested as the best model to be considered for modeling open-pit hauling operations. In a flow shop problem, a set of jobs flow through several stages in the same machine order. The proposed flow shop model has been evaluated using an example from real case study data.  

The results show that job scheduling models for truck optimization can optimize haulage scheduling and truck dispatching in open-pit mines. Using the developed flow shop model, it is possible to incorporate different mining KPI’s such as production time, production productivity, and fuel consumption. This model can also provide a prototype tool for real-time scheduling. Future work is on track to develop fast and reliable metaheuristic solution techniques for this problem's large-scale instances.