SummaryOpen pit design and production scheduling considering the commodity price uncertainty is one of the important issues in the field of open pit mining, so that mine design and planning regardless of price uncertainty leads to erroneous assessments and non-operational production scheduling, which itself increases the investment risk. The amount of reserve that can be extracted and the location of surface facilities directly depends on the Final pit limit. In this paper, a mathematical algorithm based on Monte Carlo Simulation and Lerch and Grossman algorithm is presented, which is able to calculate the expected value of blocks based on the metal price history and estimating its distribution function and get the most likely Final pit limit. This pit can be the basis of long-term mine production planning as well as a criterion for locating surface facilities. IntroductionThe aim of the planning process for an open pit mine is usually to find optimum annual schedules that will give the highest Net Present Value (NPV). The primary input of this procedure is an economic block model, which includes a set of mining blocks representing the ore body and the surrounding rock. Net economic value is assigned to each block based on the revenue of recoverable metal content in a given block and subtracting all the operating costs, comprising mining, processing, refining, and selling costs. An economic evaluation of each block requires the estimation of ore tonnage and grade of mining blocks as well as some economic parameters such as metal prices and operation costs. In the current pit design approaches, the block economic values are calculated using a fixed known value. In this paper, using the metal prices in the past as well as the Monte Carlo simulation method, the most probable ultimate pit is obtained. Methodology and ApproachesIn this article, the price distribution function of the metal price (copper) was obtained using the metal price history. Then 100 prices were simulated using Monte Carlo simulation and the expected value of each block was obtained using these simulated values of other fixed technical and economic parameters. Finally, by using these values and using the NPV Scheduler software, a single optimal pit was obtained. Results and ConclusionsIn this article, the expected value of the blocks was obtained using the Monte Carlo simulation method, and then the optimal pit, which is actually the most probable pit, was obtained. Because the price history of the metal is considered in the design process, the obtained pit has little sensitivity to the changes in the price of the metal in the future.

The primary aim of this study was to define the Final pit boundaries utilizing the maximum flow Pseudoflow method in an open-pit mining context. Our methodology encompassed exploratory data analysis (EDA), establishing geomechanical and economic factors, and assessing the Final pit. The study was conducted using Python 3.11 and SGeMS 3.0. We discovered that our block model comprised 480,000 blocks of 10x10x10 m dimensions. We generated 20 pits with revenue factors between 0.1 to 2, increasing by increments of 0.1. The Study indicated that pit 20 was optimal, with an estimated NPV of 17855 MUSD, extracting 212 million tons of ore and 58 million tons of waste rock, achieving a stripping ratio based on block model and market conditions, and is subject to change with further block sequencing analysis. Nevertheless, pit 20 emerged as the most advantageous when considering economic feasibility, given its high estimated NPV and favorable stripping ratio.

Miduk in one of the largest copper ore reserves in Iran that is situated in the north west of Kerman province. It consititues approximately 157 million tons of ore with an average grade of 85%. One of the most important elements of the open pit planning is the determination of the Final pit limits. The simulation method (positive floating cone) is a commonly used method for this purpose in which the users design by grade blocks. In this presentation, geostatistic methods have been described and their application in open pit mine planning discussed. Furthermore, computer programs of CSMINE and VARIOC have then been explained and parameters required for the application of the software programs obtained. Finally, The optimum design of the pit is determined by using two sets of real data and applying the above computer programs. The recommended pit will produce appropriate ore for the ore dressing plant with maximum average and the highest amount of economic gain mind.

The Sungun copper deposit is located in about 40km North West of Ahm city in the east Azarbaigan province of Iran. The total geological ore deposit is estimated to be 740 million tons. In this study using all information from exploration and geotechnical studies of the area, Final pit limits of Sungun copper deposit is designed by the 2-D Lerchs & Grossmann Algorithm. By this method, from 740 million tons of geological ore reserve, 411 million tons can be mined by open-pit method with overall stripping ratio of 2.14:1. Cut off grade is found to be 0.32% Cu. The average ore grade is found to be 0.665% Cu.

The Sungun Copper Mine is located in a highly hazardous seismic area. Most recently, the Ahar-Varzeqan earthquake, M 6. 2, occurred on August 11, 2012; at a distance about 40 kilometers away from the mine. Nevertheless, the seismic stability of the Final pit wall was not comprehensively reviewed. In this research, the southwestern wall of Sungun’ s Final pit was investigated through pseudo-static, Newmark and numerical methods. Moreover, some of the difficulties in accomplishing and interpreting the results in dynamic analyses of a mining slope is explained. Pseudo-static analyses revealed that the Final pit wall is not safe against the design earthquake, and it is highly prone to failure. The results of Newmark analysis proved that a large failing region would form in the case of design earthquake. Based on a dynamic numerical analysis on the pit wall, continuous forward and downward earthquake-induced movements were observed, as well, which might be a sign of pit wall instability. The effect of underground water drainage on stability of the pit wall was investigated in the numerical model. Resulted time histories of displacements in the drained pit wall proved that only water drainage is sufficient for protecting the pit wall against the design earthquake.

this investigation was conducted to identify polymorphisms in growth hormone (GH), pit-1 and b-lactoglobulin (b-LG) genes in a Holstein cattle. Genomic DNA samples were genotyped by PCR-RFLP technique. Allele frequencies were 0.884 and 0.116 for L and variants of GH, 0.170 and 0.830 for A and B variants of pit-1, and 0.529 and 0.471 for A and B variants of b-LG genes, respectively. Hardy-Weinberg equilibrium was found in the population using X2 test.

Introduction: Electrocution is the cause of many deaths in the world annually, that electric current passing between the body and earth can be the reason; thus, it is of great importance to construct the ground protection system using earth pit. This study aimed to investigate the effective environmental conditions on the earth's pit resistance using the simulation method. Materials and Methods: In the present study, 192 different experiments were performed and repeated ten times. The parameters evaluated in this study include soil type, reducing agents type, depth, humidity, electrode type, soil density, and electrode placement shape. The resistance value is measured using a three-point ether tester by changing each of them. The obtained data were statistically analyzed, and the results were presented in tables. Results: According to the results of the experiments, soil density and moisture are considered the most effective parameters in determining the resistance of the earth pit; so that the value of resistance is significantly reduced by changing these two parameters separately or simultaneously. Also, as density and depth of placement increase, the value of resistance in all experiments had a decreasing trend. This study showed that sand was determined as the worst soil type among the soil types due to its high resistance. Conclusion: According to the results of this study, soil density and moisture among the seven parameters under study play a more important role in pit resistance and consequently the severity of an electric shock that should be given more attention to it.

Sequencing and analysis of the data obtained are best and most common methods in studies of genetic diversity. pit-1gene is known as growth hormone IGF-1 gene. this gene is a member of family of transcription factors in the poultry is located on chromosome 1, with a length of approximately 14 kb. This gene has seven exons and five introns in poultry. The purpose of this study was analysis region of intron 5 sequence of pit-1 gene in broiler chickens Arian lines and determining its phylogenetic relationship with other chicken breeds.For this study, blood samples were collected of seven broiler chickens of both sex Arian lines.After extracting DNA from them, target gene was amplified with specific primers and after purification was sequenced. Five different haplotypes were determined based on six single nucleotide polymorphism sequence and the Final sequences of each haplotype with length approximate 260 bp which includes 21.92% adenine, 18.8% guanine, 32.69% cytosine and 27.31% thymine. After ensuring the accuracy of sequencing, submitted to gene bank database (NCBI) with accession number of JQ946630- JQ946636.The phylogenic tree was drawn with consensus sequence of pit-1 gene of Arian line chicken and other similar sequences of different chicken breeds obtained from gene bank. Results the phylogeny indicated that Arian line chicken and American Chickens are on a lineages.

The aim of this study was to determine to pituitary-specific transcription factor (pit1) gene polymorphism relationship with milk production in Iranian Holstein dairy cows. For this purpose, blood samples were collected from 110 proof and un-proof Holstein bulls from North West and Tehran breeding centers of Iran. After performing extraction steps using modified phenol-chloroform method, pitI exon 6 polymorphism was determined with PCR-RFLP and HifI restriction enzyme. Two alleles and three genotypes were observed. Hinf1+ (G) allele and GG genotype were the more frequent. Allelic and genotypic variations in years do not show a specific trend, and for most of the years, the G allele was more frequent. The results of analysis of variance showed that pitI-HinfI polymorphism was not significant effect on milk, fat, protein production, fat percentage and protein content (p>0. 05). Allelic replacement effect results showed that allele change from G to A did not have a significant effect on any of the studied traits. Based on the results of this study, it can be concluded that for the use of this gene in the of milk production traits improvement, further research is needed.

So far a large number of algorithms have been developed for optimisation of ultimate pit limits, most of which follow deterministic rules. In this paper a new algorithm is introduced, which follows a probabilistic logic using Markov chains. The algorithm is implemented on a transition matrix that correspond the 2D conventional economic block model of the orebody. Probability of mining a block is proportional to the profit it may produce. Applying this algorithm, probability of mining each block is obtained and Finally the optimum pit is defined as the pit, which provides with the highest probability of mining. A 2D analysis of the problem is discussed in this paper; however, it is not difficult to expand the problem to 3D cases.