BLASTING PRINCIPLES FOR OPEN PIT MINING PDF

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Blasting principles for open pit mining Vol-1 William computerescue.info - Ebook download as PDF File .pdf), Text File .txt) or read book online. Blasting Principles for Open Pit Mining Vol 1 William Hustrulid - Ebook download as PDF File .pdf), Text File .txt) or read book online. blasting. Blasting principles for open pit mining Vol. 1 - William computerescue.info - Ebook download as PDF File .pdf), Text File .txt) or read book online.


Blasting Principles For Open Pit Mining Pdf

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computerescue.info - Ebook download as PDF File .pdf), Text File .txt) or read book online. Request PDF on ResearchGate | Blasting principles for open pit mining / William Hustrulid | Incluye bibliografía e índice v.1 General design concepts-- v Apr 16, to highlight the principles and practices adopted in rock blasting breaking the massive rocks in quarries, open pits, surface and underground.

The selection operator chooses a chromosome from the available generation to put in to the next generation. The crossover operator combines two chromosomes parents to generate a new chromosome, which indeed is better than each of the individual parents providing, taking the T k best characteristics from each of the parents. Various types of crossover operators e. Crossover is performed according to the Crossover Probability, which is set during Table 2 Training error obtained from the trained network Optimization summary Best fitness Average fitness Generation no.

The porphyry rock has been changed to a more MSE 0. The other minerals observed in the area are R2 0. Copper is consid- ered the main product of the mine, whereas molybdenum is a byproduct.

The grade of this products increases with probability should usually be set fairly low 0. The first choice. Process of searching for the optimal solution is geological reserve in the Sungun deposit is about continued until a specified termination criterion e.

Also, blast holes are stemmed using drill solutions are compared with each other, and the solution cuttings. The most important undesirable incidents of the with the best fitness is selected to be the optimal solution. For back- In this study, NeuroSolutions software for Excel break, a maximum amount of 10 m has been observed, Release 5. Figure 1 shows genetic model to select the optimum network parameters the location of Sungun copper mine.

Input parameters Input parameters such as burden, spacing, stemming, Case study charge per delay, powder factor, etc. The utilized parameters Sungun open pit copper mine along with the other details are given in Table 1. The datasets of 2, m above sea level.

Geological dominant were divided into training and testing datasets. Mineralization of this porphyry type of deposit training, and the rest was kept to test the model. Here, the neural network Multivariable regression analysis is used in various related parameters including number of neurons in hidden layers, fields of mining engineering and geosciences Grima and learning rate, and momentum are considered as genes in a Verhoef ; Finol et al.

Here, this method was implemented to obtain the relationship The work in genetic algorithm gets started with the creation between the input and output parameters, for which SPSS 16 of a random generation composed of a chromosome collection.

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Equation 1 shows the relationship Normally, a population size of 50— is practiced; however, it between flyrock and the other pertinent parameters. Determi- can be changed according to the time and memory disposed on nation coefficient R2 of 0. The same operation was performed reached. Here, the size of initial population was considered to to develop a relationship for backbreak. Here, also R2 of be For generating an initial population, a specified 0.

In fact, a chromosome is a possible 0 0. The genes which represent the Measured Flyrock feature of each individual parameter consist of some bits. As it is seen from 0. Furthermore, 0 0 0.

The optimum model Architecture is depicted in Fig. Roulette Wheel method was used for the selection operator, whereas for crossover and mutation, Model performance probabilities of 0. After each generation is produced, all To evaluate the model performance MSE, normalized MSE of the chromosomes exited in that they were applied in the NMSE and coefficient correlation R2 were chosen and neural network to evaluate appropriateness of each chromo- calculated.

NMSE can be determined using Eq. The some. The evolution process was repeated up to production of calculated MSE, NMSE, and R2 of the optimum model for 50 selected termination criterion new generations. In the last predicting flyrock and backbreak are given in Table 3.

As it step, network with the lowest training error and highest fitness can be seen from this table, the calculated errors are little value is selected as the optimum model.

The fitness of each bit more as compared with the model performance during network is determined by calculating mean square error MSE training. NP Fig. Recognition of the To identify the relative influence of the each parameter on the optimum model with this method as compared with the flyrock and backbreak, sensitivity analysis was performed.

The classic networks is faster and convenient. Main articles: Mineral processing and Extractive metallurgy Once the mineral is extracted, it is often then processed. The science of extractive metallurgy is a specialized area in the science of metallurgy that studies the extraction of valuable metals from their ores, especially through chemical or mechanical means.

Mineral processing or mineral dressing is a specialized area in the science of metallurgy that studies the mechanical means of crushing, grinding, and washing that enable the separation extractive metallurgy of valuable metals or minerals from their gangue waste material. Processing of placer ore material consists of gravity-dependent methods of separation, such as sluice boxes. Only minor shaking or washing may be necessary to disaggregate unclump the sands or gravels before processing.

Processing of ore from a lode mine, whether it is a surface or subsurface mine, requires that the rock ore be crushed and pulverized before extraction of the valuable minerals begins. After lode ore is crushed, recovery of the valuable minerals is done by one, or a combination of several, mechanical and chemical techniques. Since most metals are present in ores as oxides or sulfides, the metal needs to be reduced to its metallic form.

This can be accomplished through chemical means such as smelting or through electrolytic reduction, as in the case of aluminium. Geometallurgy combines the geologic sciences with extractive metallurgy and mining. In , led by Chemistry and Biochemistry professor Bradley D.

Smith, University of Notre Dame researchers "invented a new class of molecules whose shape and size enable them to capture and contain precious metal ions," reported in a study published by the Journal of the American Chemical Society. The new method "converts gold-containing ore into chloroauric acid and extracts it using an industrial solvent. The container molecules are able to selectively separate the gold from the solvent without the use of water stripping. Environmental issues can include erosion , formation of sinkholes , loss of biodiversity , and contamination of soil , groundwater and surface water by chemicals from mining processes.

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In some cases, additional forest logging is done in the vicinity of mines to create space for the storage of the created debris and soil. Mining companies in most countries are required to follow stringent environmental and rehabilitation codes in order to minimize environmental impact and avoid impacting human health.

These codes and regulations all require the common steps of environmental impact assessment , development of environmental management plans, mine closure planning which must be done before the start of mining operations , and environmental monitoring during operation and after closure.

However, in some areas, particularly in the developing world, government regulations may not be well enforced. For major mining companies and any company seeking international financing, there are a number of other mechanisms to enforce environmental standards. These generally relate to financing standards such as the Equator Principles , IFC environmental standards, and criteria for Socially responsible investing. Mining companies have used this oversight from the financial sector to argue for some level of industry self-regulation.

For example, ISO and ISO , which certify an "auditable environmental management system", involve short inspections, although they have been accused of lacking rigor.

Open Pit Mine - Planning and Design-3rd Edition

Miscellaneous other certification programs exist for various projects, typically through nonprofit groups. It found existing literature suggesting donors encourage developing countries to: Make the environment-poverty link and introduce cutting-edge wealth measures and natural capital accounts.

Reform old taxes in line with more recent financial innovation, engage directly with the companies, enacting land use and impact assessments, and incorporate specialised support and standards agencies.

The other influential parameters in designing ; Bajpayee et al. For neural networks are momentum and learning rate. Since example, Holmeberg and Persson studied the event all of the parameters are environment dependent, a with the help of a high-speed camera.

Furthermore, some suitable network topology has to be designed so as to experiments have been performed by Ladegaard-Pedersen reach a well-trained model, thus obtaining global minima. Apart in which interrelation between the pertinent parameters from this, it should be noted that the whole modeling cannot be easily figured out, has caused previously process is perfectly context dependent.

It means that developed empirical methods to be not properly applicable network designed for a particular problem may not be for solving such problems. Rather, new techniques such as applicable for the other one. Likewise, in the selection of artificial neural networks ANNs , a branch of the artificial the network parameters, various network structures have intelligence, can be utilized in solving complicated prob- to be tried for a new given problem, which makes the task lems including blast-induced unwanted phenomena such as more and more hectic and boring.

ANN technique, hybrid neuro-genetic algorithm can be implemented, hence developed in the s, has been used in the field of recognizing the optimum ANN parameters in an automated mining engineering and earth sciences by many investi- prompt way by examining sufficient number of combina- gators Nie and Zhang ; Meulenkamp and Alveraz tions of all the parameters.

Furthermore, this particular ; Koike and Matsuda ; Khandelwal and Singh procedure can also be used for different contexts. The idea of application of neuro-genetic modeling first In this study, a new ANN model was developed to originated in the late s Heisterman ; Miller et al.

A specialty of this new so-called White , and thereafter, an intense research was neuro-genetic model is that the neural network parameters performed during the s Kinato ; Heisterman are optimized using genetic algorithm, which results in the ; Schiffmann et al.

As such, many attempts shortening time of the optimum model recognition. For have been reported in the literature for training feed- validation of the ANN model, regression analysis was forward neural networks Fogel et al.

Pattern 0. For training, the model sufficient number of 0. Feed-forward back-propagation method is normally used for training multilayer percep- 0.

Back-propagation 0 neural networks always consists of at least three layers 1 5 9 13 17 21 25 29 33 37 41 45 49 input layer, hidden layer, and output layer containing Generation interconnected processing units, called neurons Neaupane and Adhikari Being responsible for mapping, the Fig.

The probability is usually considered to be literally and Hopfield neural networks using advanced evolutionary high of say 0. In the mutation Graudenz The investigation by the GA to arrive at a better solution comparing with the made by De Jong showed the utility of the GA for previous solutions. Mutation occurs during evolution function optimization.

Blasting principles for open pit mining Vol. 2 - William Hustrulid.pdf

Genetic algorithms combine selec- according to the probability defined by designer. The tion, crossover, and mutation operators to recognize the best solution of a problem. The selection operator chooses a chromosome from the available generation to put in to the next generation. The crossover operator combines two chromosomes parents to generate a new chromosome, which indeed is better than each of the individual parents providing, taking the T k best characteristics from each of the parents.

Various types of crossover operators e. Crossover is performed according to the Crossover Probability, which is set during Table 2 Training error obtained from the trained network Optimization summary Best fitness Average fitness Generation no.

The porphyry rock has been changed to a more MSE 0. The other minerals observed in the area are R2 0. Copper is consid- ered the main product of the mine, whereas molybdenum is a byproduct.

The grade of this products increases with probability should usually be set fairly low 0.

The first choice. Process of searching for the optimal solution is geological reserve in the Sungun deposit is about continued until a specified termination criterion e. Also, blast holes are stemmed using drill solutions are compared with each other, and the solution cuttings. The most important undesirable incidents of the with the best fitness is selected to be the optimal solution. For back- In this study, NeuroSolutions software for Excel break, a maximum amount of 10 m has been observed, Release 5.

Figure 1 shows genetic model to select the optimum network parameters the location of Sungun copper mine. Input parameters Input parameters such as burden, spacing, stemming, Case study charge per delay, powder factor, etc. The utilized parameters Sungun open pit copper mine along with the other details are given in Table 1.

The datasets of 2, m above sea level. Geological dominant were divided into training and testing datasets.Copper is consid- ered the main product of the mine, whereas molybdenum is a byproduct.

The probability is usually considered to be literally and Hopfield neural networks using advanced evolutionary high of say 0. Proceeding of the international joint conference on neural network. Here, this method was implemented to obtain the relationship The work in genetic algorithm gets started with the creation between the input and output parameters, for which SPSS 16 of a random generation composed of a chromosome collection.

The cratering concept presented as a thought-experiment Preview this Book. Introduction 2. A typical cycle includes sumping launch-pushing forward and shearing raising and lowering the cutterhead boom to cut the entire height of the coal seam.

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