IRANIAN JOURNAL OF MINING ENGINEERING (IRJME)
Year:2006 | Volume:1 | Issue:1|Papers Count:12

Dynamic methods are, nowadays, fast and inexpensive ways of estimating elastic constants in rock engineering. Therefore, In order to get reliable ontputs all effective factors of such methods are to be assessed. One of fundamental factor affecting the test results is the shape or height/diameter (L/D) ratio of the tested specimen. The existing standards, namely ASTM and ISRM standards imply that, in spite of the great role of the (L/D) ratio on the static test results, this ratio does not play an important role on dynamic test results. With aim of determining the exact role of (L/D) ratio on static and dynamic properties of rocks, 3 dynamic and 5 static tests were conducted on Neka Limestone samples with 6 various (L/D) ratios of 0.5, 1, 1.5, 2, 2.5 and 3 (48 sets of tests in all).The data produced through these tests showed that varying (L/D) ratio from 0.5 to 3 results in ample variation of mechanical parameters in both types of tests. The laboratory produced data indicated that static tests are affected more by (L/D) ratio than dynamic ones. It was also concluded that when the value of (L/D) gets close to 3, elastic dynamic parameters reach more or less constant values whereas static parameters are still in change. These finding show that the effect of sample shape on dynamic properties of rock has not been counted for properly. This importance of this factor has to be recognized. Also, when static tests are concerned, the previously recommended ratio of (L/D) has to be further assessed.

Different factors control penetration rate, which is an influencing part of drill ability. To study penetration rate it is recommended to record and analyze the effect of one or two variables, while keeping others constant. In this study, 81 data of penetration rate from 12 drill rigs, 14 data of two Robolt rigs, and data gathered by their manufacturers, from a dam site, were analyzed to check the role of influencing parameters of equipments. Rock type of the study area is Bakhtiari conglomerate and is constant for all the studied samples. Diameter of the bit and impact power of the rig are two main influencing factors, but with different level of consequences. The effect of rig's impact power is so pronounced that change of rig or rock type cannot highly diminish its role. Changing the bit type, from ballistic to spherical, have not the same effect on penetration rate and it is related to the type and design of the hammer.

The basic purpose of this research was to study cyanide adsorption on zeolite surface from tailing dam water in Aghdareh Takab gold processing plant. Results indicated that the solution pH, adsorption time, temperature and the amount and size of zeolites particles were the most important parameters in the adsorption mechanism. Zeolite was used in two fraction sizes; 100-300 and 300-1000 microns in tests in two type natural and impregnated conditions. The optimum amounts of zeolite in solution for natural and impregnated were determined 30 and 24gr/l for the small and large fraction sizes, respectively. The maximum percent of cyanide adsorbed on (100-300)· particles sizes 50.2% and 86.1% on (300-1000)· particle sizes. In any fractions optimum values of pH were 10.5 and 10 for natural and impregnated types, respectively. Contact time in equilibrium conditions for each types of (100-300)· and (300-1000)· sizes were 40 and 50 min respectively. In (100-300)· particle size adsorption isotherm follow natural type from. The amount of cyanide adsorption one impregnated zeolite was more than natural type.

Mechanized tunnel boring method is over than fifty years old. Performance prediction is one of important categories in tunneling projects and is important in selection of excavation method and type of tunnel boring machine. In this paper penetration rate of Ghomrud conveyance tunnel TBM had predict with NTH model. The important advantage of this model is applying the effect of ground condition and rock mass properties. Calculations show that average penetration rate and average advance rate of machine must be 4.7 meter per hour and 20 meter per day respectively. Predictions have shown, with 28 workdays per month, excavation of this tunnel must be completed in 32 months. Maximum penetration rate of 5.04 meter per hour was predicted for foliated Jurassic sandstone, shale and slate layers and minimum penetration rate of 3.72 meter per hour was predicted for quartzite layers. Similarly maximum advance rate of 22.7 meter per day was predicted for foliated Jurassic sandstone, shale and slate layers and minimum advance rate of 11.5 meter per day was predicted for faulted zones. Therefore with comparison of TBM operation and predicted values it can be evaluated a relationship between real operation and result of applied model, for use in future excavations in tunnel root.

Drilling in rocks is the initial stage in extraction operation. Therefore recognition of correct parameters which are interfering on drilling and studying the qualitative and quantitative effects of everyone of them would result affects the technical and economical aspect of extraction operation. In the previous studies on drilling, parameter are mainly related to rock material characteristics such as hardness, texture, grain size, density and abrasion were considered. However, in this study rock mass reaction was aimed. For this purpose in order to study the drilling in jointed rocks with different filling materials and spacing of 10, 20, 30, 50 and 100 centimeters, physically modeled in laboratory by using concrete blocks. The models were drilled and the time of drilling was recorded. Results obtained from drilling in the physical models reveal that with reduction in spacing, drilling time is increased exponentially and with reduction in size of filling material, drilling time is increased logarithmically and drilling efficiency is decreased.

The principal aim of present study was the application of the Artificial Neural Network (ANN) system to the determination of the optimal powder factors, based on a series of observations and numerical experiments. The input parameters were 12 geological conditions. The data for the NN application in this study were collected in the spillway tunnel of Kosar Dam, which located in West south of Iran. An optimum NN model was determined by training and testing models with the collected data. It was shown that the NN model could predict the powder factor depending upon the selected input parameters. In addition, the strength of the relationship between the powder factor and the 14 input parameters was evaluated by three different sensitivity analysis methods, i.e. the analysis of relative strength effect, the cosine amplitude method and the fractional factorial design. From these analyses, not only the dominant factors among the input parameters, but also their interactions could be determined.