mohammadjavad rahimdel

Mines and mining industries are an important way to reach the sustainable development and investing in these sectors creates the suitable economics value added. Therefore, prioritization of the mineral activities are helpful for persuasion of future investments. The main aim of this research is to rank the mining activities of the Azerbaijan-e-Gharbi Province in Iran with considering five main criteria including economic, cultural and social, environmental, technical and also political criteria.

In this study, the main in-operation mines are considered. The technique for order of preference by similarity to ideal solution and also the analytical hierarchy process are used to prioritize the mining activities. To reduce the uncertainties, all calculations are done under the fuzzy environment. Results and

Results of this study show that, the cultural, social and environmental criteria have the highest importance degree in comparison to the other criteria. The iron and gold mines are in the first priority, while the chromic and manganese mines and lead and zinc mines are respectively in the second and third priority. The quarry and gypsum mineral types, the barite, red and yellow soil, kaolin, fireclay and dolomite, salt and silica, sand, rubble, mica, limestone and ballast mines are respectively ranked.

Steep slopes developed on the loose ground, either natural or artificial, are prone to landslide phenomena. During con-struction activities for the development of new Qaen-Afin road in South Khorasan and adjacent to Ravoshk village, a sudden landslide occurred in a shale slope, and newly-built stone bridge for the road destructed. In this paper, using geologic conditions, satellite images, the field evidence of landslide and SLIDE6 and Phase2 programs, the type, and cause of the landslide will be examined. The survey conducted with the help of satellite images and field visits showed that the land-slide occurred is a circular landslide with dimensions of ap-proximately 50×80 m. It had happened a few months ago, but unfortunately, no attention paid to it, and continued construc-tion activities in the rainy season stimulated the sliding mass and led to extreme conditions. The geometrical condition of the slope, just before the slope failure, was determined by us-ing GPS, surveying meter, and satellite images. Using this in-formation, the two-dimensional model of the natural slope, before any construction activity, created in SLIDE6. Slope stability analysis was performed using the simplified Bishop limit equilibrium method, and failure of the slope predicted successfully. Finite element analysis of the slope in Phase2 software arrived at similar results. This paper has shown that a lack of attention to first slope movements and continuing construction work was the primary cause of financial losses incurred.

Drivers of mining trucks are exposed to whole-body vibrations (WBV) and shocks during the various working cycles. These exposures have an adversely influence on the health, comfort and also working efficiency of drivers. Determination and prediction of the vibrational health risk of the mining haul trucks at thevarious operational conditions is the main goal of this study. To this aim, three haul roads with low, medium and poor qualities are considered based on the ISO 8608 standard. Accordingly, the vibration of a mining truck in different speeds, weights and distribution qualities of the materials in the dump body are evaluated for each haul road quality using the Trucksim software. An artificial neural network (ANN) is used to predict the vibrational health risk. The obtained results indicate that the haul road qualities, the truck speeds and the accumulation sides of material in the truck dump body have significant effects on the root mean square (RMS) of vertical vibrations. However, there is no significant relation between the material’s weight and the RMS values. Also, the application of ANN revealed that there is a good correlation between the predicted and simulated RMS values. The performance of the proposed neural network to predict the moderate and high health risk are 88.11% and 93.93% respectively

Crushing is the first stage of operations involving size reduction and separation of ores. Throughput، feed and product size، rock compressive strength، and abrasion index among main criteria of crusher selection. In this Paper، Selection of different primary crusher type based on above mention criteria using Elimination Choice Translating Reality (ELECTRE) is discussed. The crushers that are considered include Double toggle jaw، Single toggle jaw، High speed roll crusher، Low speed sizer، Impactor، Hammer mill and Feeder breaker crushers. Results have been offered the Double toggle Crusher as the suitable primary crusher.