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By Surendra K. Mishra

The increasing volume of wastes being generated by industry is a legacy of the industrial revolution and subsequent industrial growth. Social and regulatory pressures have been mounting on industry to improve its waste management practices. In many industrial sectors, waste disposal has been the only method of waste management. Land farming, underground burial, deep wells and incineration are still practiced. Often, concentration and volume reduction of waste streams are also practiced to reduce the waste management costs. In the recent years, there has been emphasis on waste minimization. Since the 19th century, industry has practiced recycling of usable resources as a way of handling unwanted byproducts. The mining industry has recovered or extracted economic minerals from tailings for decades. For example, during the gold rush period of 1970s, extraction of gold from tailings dams became economically attractive. Similarly, when it was economical, coal and shale fractions have also been recovered from tailings and refuge materials for commercial uses. In the steel industry, with the development of new furnace technology, recycling of flue dust and scrap iron was practiced as early as in the 19th century. Before 1900, there was little incentive for the industry to reduce the waste volumes. Manufacturers, however, did see a rationale for adopting profit-increasing techniques. They made an effort to recover and recycle economic materials from waste sources. One of the pioneering examples of resource recovery is the coke making industry. As the industry was market driven, products recycled from coke batteries included ammonia for use in fertilizers, gas for power generation and heating, and tar for road construction, wood preservation and roofing. Tar had been avery troublesome waste byproduct. But it quickly became a valuable chemical raw material, providing the foundation for Germany's dominance of the world's dye and medicine markets before World War I. Similar trends evolved in the chemical industry. In the context of current environmental regulations and escalating mining and processing costs, recycling of re- [ ] sources is becoming economically more attractive. Solid and liquid wastes generated by industries contain a range of inorganic and organic contaminants. Among these contaminants, metals and hydrocarbons form major groups. Treatment of these wastes is essential to meet regulatory disposal requirements. In the recent years, based on the principles of chemical and mineral process engineering, processes have been developed to treat these industrial wastes. This article reviews some of the processes that have made impacts and have proven to be effective at commercial scales.

Jan 1, 1999

By J. M. Velazquez, J. H. Meza Viveros

This paper describes some of the parameters and technologies used at the Mexicana de Cobre smelter, and discusses the principal design parameters and new technologies that are being implemented in a smelter-expansion project designed to increase the production capacity of anode copper from 180 to 300 kt/year (200 to 330,000 stpy). In addition, some parallel projects under construction in the smelter plant are described.

Jan 1, 1999

By J. K. Ross, K. O. Hoal, S. K. Appleby

Understanding ore variability is a key factor in the geometallurgical analysis of a deposit and is beneficial to process development and mine planning. Ore variability is a function of the mineralogy of a deposit, in terms of both ore and gangue minerals and their textural relationships. This study integrates optical microscopy and quantitative mineral analysis to characterize the mineralogy and texture from 13 samples from different lithologic units at the Bingham Canyon Mine. The analysis identified several parameters, such as modal mineralogy, alteration assemblages, distribution of mineral phases and alteration assemblages and microfracture and void space distribution. These parameters can have an impact on the materials’ behavior during processing. This study demonstrates that quantitative mineralogical analysis can provide detailed information for improved understanding of ore variability.

Jan 1, 2010

By Fred W. Shultz

In the past we have been somewhat harrassed by the terms "'quality control" and "process control". This is especially true where the industry is dependent upon the chemical analysis of their product which in turn informs them how, well they have been controlling the process. The information which they have received, in most cases, is of an historical nature rather than of current value. The word "control" is to have more significance in future operations. This is particularly true in the metals industry. As the industry continues to process lower grade ores, and processing costs continue to rise, they must obtain more information faster to exercise "control" to its fullest extent.

Jan 1, 1963

By J. H. Tu

The technical paper correctly points out that the kriging variance is not a good measure of the uncertainty of the estimated (i.e., kriged) value of individual blocks. The authors claim that their proposed jack-knife method, which is a rekriging of each block by eliminating, in turn, one sample from m the original sample set and then taking the average of the rekriged estimates, not only gives good block estimates, but the resulting jackknife kriging standard deviation is a useful indicator of the "true uncertainty associated with block estimates." However, they immediately abandon the idea of using the block-by-block standard deviations, reasoning that these standard deviations are not independent and that there is no easy way to utilize them. There may be another reason for not using them. The jackknife standard deviations for individual blocks given in their example are mostly in the range of 0.004 to 0.005 oz/st (0.14 to 0.17 g/t) with only one block having a high value of 0.012 oz/st (0.41 g/ t). These individual block standard deviations are as low as the jackknife standard deviation for the mean grade of the entire shape, i.e., 0.0041 oz/st (0.14 g/t). Do they represent the "true uncertainty" .of the individual block estimates? Could the authors explain this? In a global shape consisting of a large number of blocks, any given sample will affect the kriged estimate of only those few blocks within its vicinity. This is the rationale for the authors' selective rekriging, making the jackknife algorithm more efficient. On second thought, why not do away with jackknifing altogether? Just cumulate and normalize, if necessary, the kriging weights of each sample used during the ordinary block kriging process, and then compute the global variance from these kriging weights and their respective sample grades? After all, isn't the global mean grade nothing but the weighted average of the samples used in the estimation? Reply by G.S. Adisoma and M.G. Hester The jackknife is one of the many tools in a practitioner's toolbox to solve estimation problems. The strengths of the technique lies in its simplicity, i.e., it uses the concept of mean and standard deviation and the fact that it can be easily combined with other tools, in this case kriging. Because the jackknife kriging (JK) estimate is also the mean of the pseudovalues, the JK standard deviation is attractive just as the standard deviation of the mean explains the variability of the data. The difference is that the pseudovalue calculation in jackknife kriging uses the ordinary kriging (OK) weighting scheme instead of simple arithmetic averaging. The data used to illustrate the jackknife technique in the paper con¬sist of high values that are roughly three times the low values. The resulting JK estimate of the block grades show that the highest estimate is roughly twice the grade of the lowest estimate. The contrast between the low and the high estimate is more evident in the JK estimate than in the OK estimate, even though the mean grades of the blocks for the two estimates are very similar. Nonetheless, in this paper, we are concentrating more on the need for a more realistic measure of uncertainty, or precision, for the estimate. Unlike its OK counterpart, the JK standard deviation of the blocks clearly reflects the original data variation. The highest JK standard deviation of the blocks is three times its lowest value. This follows our intuition that, when the samples used to estimate a block is more variable, the resulting estimation variance (or standard deviation) should be higher than the case where the samples are more uniformly valued. However, block-by-block standard deviation or variance is of little practical value in reserve estimation and classification, as well as in mine planning. One is usually more interested in quantifying not the variance of the individual block estimate, but the uncertainties associated with a much larger dimension, such as the minable reserve. Thus, the thrust of the paper is to find a simple way to obtain a single estimation variance or standard deviation associated with the reserve grade estimate. The discussion by J.H. Tu did not mention how one would obtain the global variance from the OK weights and the sample grades. As a technique that offers a data value-based measure of uncertainty for its estimate, the "leave-one-out" jackknife fills this need nicely through the block kriging shortcut approach described in the paper. Note: The first column and the last two columns of Table 3 in the paper should have contained a single number each, namely, an OK estimate of 0.0317, a JK estimate of 0.0333 and a JK standard deviation of 0.0041 oz/st, respectively, for the shape, as are obvious from the text.

Jan 1, 1997

By William Lyman

GENERAL DESCRIPTION Shrinkage or shrinkage stoping refers to any mining method in which broken ore is temporarily retained in the stope to provide a working platform and/or to offer temporary support to the stope walls during active mining. Since ore "swells" when broken, it is necessary to shrink the muck pile a corresponding amount by draw¬ing some of the broken ore out as the stope is advanced-hence the name. Broken ore retained during stoping is drawn out after the stope has reached its limits. The stope may be left empty or may be filled with waste contemporaneous with, or subsequent to, the final draw. Traditionally the method implies conventional overhand stoping methods with miners working between the muck pile and the stope back, in a space which advances updip with mining and is maintained by balanc¬ing "swell" with "shrink." The shrinkage classification is also applicable to so-called "semishrinkage" methods in open pillar-supported stopes where broken ore is temporarily retained as a working platform but offers no wall support; and to various blasthole shrinkage methods which utilize broken ore temporarily retained in the stope for wall support, but which do not require miners to work from muck pile in the stope. The method is generally applied to steeply dipping veins of strong ore between strong walls. APPLICATION Geometry The geometry of a shrinkable vein is described in terms of dip, width, and regularity along dip. Overall strike and dip dimensions and irregularities along the strike generally impose no restrictions on the method. Dip is ideally 1.2 to 1.5 rad (70 to 90°). As dip falls below 1.2 rad (70°), the shrinkage draw begins to strongly favor the hanging wall side, thus leaving a poor working platform for conventional overhand work. This is particularly true in relatively wide stopes. The sup¬port afforded to the hanging wall also diminishes with decreasing dip, reaching nil as the dip approaches the repose angle of broken ore. Dips below 0.78 to 0.87 rad (45 to 50°) are not generally shrinkable except by open stope "seinishrinkage" methods. Minimum mining width is fixed by working space requirements in the stope-generally about 1 m. Shrink¬age in narrower veins requires that waste rock from one or both walls be broken with the ore and the attendant dilution accepted to achieve the minimum width. Nar¬row stopes are less suitable, encouraging hang-ups and bridging of broken ore, with the attendant problems of erratic draw and incomplete recovery of broken ore. Maximum practical width may be 3 m or less to over 30 m, depending upon the competency of the ore and its ability to stand unsupported across the stope back. This is a vital safety consideration in conventional over¬hand stopes, but is much less of a factor in blasthole shrinkage methods. Very wide veins and massive ore bodies have been mined by transverse vertical shrinkage panels separated by transverse vertical pillars which are either abandoned or recovered later by other methods. Regularity along the dip is a prerequisite of shrink¬age as there must be no serious obstruction to the flow of broken ore downward through the stope to the sill level. Gentle rolls along the dip are acceptable if the local footwall dip everywhere exceeds 0.78 to 0.87 rad (45 to 50°). Off-dip hanging wall and/or footwall splits can generally be mined selectively from a conventional shrink stope as they are encountered without ad¬versely affecting subsequent continuation of shrinkage mining updip on the main vein. Vertical offsets or major rolls along the dip which cannot be "smoothed over" generally require that a sublevel be established with new draw control development. Blasthole shrinkage methods are much less flexible (and thus less selective) in their ability to accommodate any of these irregularities. Ground Conditions The wall rock must be strong enough to stand with the minimal support afforded by the dynamic mass of broken ore in the stope. During active mining, local sloughing from the walls is restrained, but the broken ore affords little, if any, useful resistance to closure of the stope walls. Such squeezing, if present, may bind up the stope and cause the loss of much ore. Pillars left between and/or within stopes are effective in preventing closure but reduce overall recovery. Walls may be re¬inforced by bolting after each stope cut in conventional shrinkage but not in blasthole shrinkage. Ore in place must be strong enough to stand with no natural support across the stope width, although tem¬porary artificial support or reinforcement may be used locally in conventional stopes. Some spalling or sloughing is permissible in blasthole shrinkage as men are never present in the stope. Physical and/or mineralogical characteristics of the broken ore may impose restrictions on stope design and/or operational plan¬ning, and may even preclude the use of shrinkage al¬together. Examples include: ores which, when broken, are cohesive or which tend to pack or cement together under the influence of ground water, wall pressure, and/ or chemical reaction. Such conditions precipitate er¬ratic draw during mining and often result in difficult and/or incomplete final draw; pyritic ores which oxidize very rapidly in the stopes and may generate heat, imposing a fire hazard by spontaneous combustion; sulfide ores which oxidize sufficiently in the stopes to adversely affect mill recovery by flotation; and ores (es¬pecially those containing uranium minerals) which ex¬ude radon gas and thereby impose ventilation constraints on stope design. In most cases these problems can be minimized by limiting the size of stopes, by minimizing the duration of mining activity in each stope, and by promptly drawing each stope empty following comple¬tion of mining.

Jan 1, 1982

By Gerald G. Griswold, James O. Greenslade, Cherie Tilley, Richard Reseigh

INTRODUCTION The Harrison Western Corporation, a leading Denver based mine contracting and engineering concern, is presently engaged in sinking two 1,006 m (3,300 ft) shafts for the Phillips Uranium Corporation at their Nose Rock Project, approximately 13 miles northeast of the small community of Crownpoint in McKinley County, New Mexico. The Nose Rock Project is the first attempt by the Phillips Uranium Corporation to tap the deep uranium reserves in what has become known as the Grants Mineral Belt. (See Figure 1) Project Description Phillips Uranium Corporation's plan for the large 2700 metric ton per day (2950 tons/day) mining facility calls for a series of deep access and ventilation shafts ranging from 4.27 m (14 ft) to 5.49 m (18 ft) in diameter to approximate depths of 1,006 m (3,300 ft). The initial pair of shafts consists of one production shaft and one ventilation shaft separated by a distance of 91 m (300 ft). The interbedded layers of sedimentary sandstones and shales to be penetrated by the shafts contain several major water producing aquifers, the deepest being the mineralized zone called the Westwater Canyon Member of the Morrison Formation.

Jan 1, 1981

By G. F. Raymond

Discussion by G.F. Raymond Knudsen's study presents two curious conclusions: • The kriging of blasthole assays can systematically overstate mill head grades by as much as 21% as a result of unbiased sample variance. • No estimation method is able to reduce this bias to a small margin. The study is based on a simulation using real data and what are presumed to be actual variogram parameters from a real deposit. Although I have no doubt that the first conclusion (21% overestimation) is correct for the author's simulation, I do not believe this represents a realistic mining situation. Over the past 15 years I have done extensive comparisons between exploration drill-hole assays, blasthole assays and mill head grades on seven major open-pit mines, including some very erratic gold deposits. Commonly, nugget effects on blasthole variograms were 10% - 20% higher than on exploration variograms. And in one extreme case, the difference was 50%. Even in the extreme case, ordinary kriging on blastholes agreed well with the mill head grade over the long term. In Knudsen's simulation, the blasthole nugget effect is assumed to be 200% higher than exploration data's. He supports this by variogram plots from each. My guess is that the apparent, large difference between these variograms results from a failure to account for the proportional effect (blasthole assays are likely from a higher-grade area). A simple check would be a comparison of the variance of exploration samples nearest blastholes. As for a nearly conditionally-unbiased estimator of a large random error, the arithmetic mean of all of the data certainly qualifies, provided there is an even data spacing. As a corollary, so does simple kriging, which would include, in this case, a large weighting to the arithmetic mean. Similarly, using a large number of samples with ordinary kriging or indicator kriging would significantly reduce the bias in the case of a large nugget effect for the variogram.[ ] Reply by H. Peter Knudsen Raymond questions two conclusions in the paper. First, he wonders whether a 21 % overestimation represents a realistic mining situation. I agree that 21 % is high, but overestimation in the range of 10% to 15% is certainly common in my experience. Furthermore, several years ago I consulted on a gold mine that was experiencing a 45% overestimation due, predominantly, to poor blasthole samples: In further questioning of the 21 % value, Raymond wonders whether the nugget effect of the blastholes is really so much larger than the nugget values of the exploration data. It is consistently larger throughout the deposit. In my experience with six Nevada gold mines, the high nugget value is not unusual. In fact, for some reason, nugget values for blasthole samples are typically about 0.0005 (opt squared). I am of the opinion that this high nugget effect observed at many gold mines is predominantly due to the inherent inadequacies of the blasthole sample and subsequent sample preparation. The second conclusion Raymond questions is the inability of the estimators tested to reduce the conditional bias. In fact, the conditional bias is extreme with the polygon estimator and greatly reduced by ordinary kriging. However, it was not eliminated. Raymond suggests using simple kriging, or perhaps a larger number of samples, to reduce the conditional bias. The technique of simple kriging may be less affected by the random errors in the data, but I did not test the technique. Using a larger amount of data presupposes that too few samples were used initially. In ordinary kriging and indicator kriging, the screen effect comes into play and ensures that samples beyond the second screen are given zero weight. Hence, increasing the sample size does not change the estimates nor the conditional bias. The main point of my paper is that the random unbiased errors (a fact of life in blasthole samples) cause a conditional bias in our estimates. The mechanics by which the conditional bias is introduced are nicely explained by Springett. My paper simply shows that the bias is also present when working with linear estimators, such as ordinary kriging, and even with nonlinear estimators, such as indicator kriging.[ ]

Jan 1, 1993

By William F. Butler

I propose to do three things today. First, take a broad look at the role of mining in the Latin American economy; then, review briefly the current situation in four principal metallic mineral exporting nations -- Chile, Mexico, Peru and Venezuela; and. finally, raise some, policy questions that seem to me to be important. The Role Of Latin America In World Mining First, let's consider Latin America's position in world mining markets. Latin America provides more than 5% of world output in 16 metals or ores, ranging from antimony and barite to Tungsten and Zinc. Latin America supplies a fifth or more of the world's antimony, beryl, bismuth, copper, fluorspar, silver and Tellurium.

Jan 1, 1962

By George A. Desborough

Marine black shales of Paleozoic age in the Western United States that exceed 10 weight percent organic carbon contain as much as 5,000 ppm vanadium, 1,000 ppm molybdenum, 1,300 ppm nickel, 600 ppm cobalt, 16 ppm silver, 7,000 ppm chromium, 18,000 ppm zinc, 280 ppm cadmium, and 350 ppm selenium. Depositional settings include: (1) continental-rise and marginal-ocean basins, (2) continental-shelf and foreland basins, and (3) cratonic-platform embayments. Most of these metalliferous organic-rich shales have not been examined for resources because of rapid weathering and poor exposures which preclude easy sampling of unoxidized rock necessary to determine actual concentration and residence of indigenous metals. Generally, the marine black shales of Paleozoic age in the Western United States are richer in metals than marine Paleozoic black shales in the Eastern United States.

Jan 1, 1982

By Ellis Brien, O&apos

The fine coal fraction of a coal stream is that fraction which contains particles essentially in the -28 mesh size range. This fraction will normally first appear, in a coal preparation process, as a result of classification to segregate raw coal into various size components for beneficiation. More specifically, it could appear in desliming screen underfiow, classifying cyclone overflow, and in other process circuit components. It's recognized that the top size of this fraction has been determined more by secondary reasons, such as desliming screen area for the heavy medium cyclone circuit, the dewatering equipment for the fine clean coal, or even the stability of the refuse thickener circuit. Benefits, both economic and environmental, gained by beneficiating the fine coal fraction of a raw coal stream are increasing in number, until today, fine coal beneficiation is a necessity in most coal operations requiring any degree of preparation. This is due to some of the following reasons: • In the past it was frequently more economical to discard -28 mesh raw coal sizes than to recover the coal values from them. Today, mining costs have escalated to the point where all coal values leaving the mine should report to the finished product if possible. • Today's mining methods are producing run-of-mine coals containing higher percentages of -28 mesh sizes. This heavily weighs the economic balance in favor of beneficiating this fraction. As much as 25% of the run-of-mine coal from some mines is in the fine coal fraction. Beneficiation is recommended so that clean coal contained in the fraction can be recovered to reduce the loss of coal values. • Existing and pending environmental regulations mandate that solid fuels now consumed in power station boilers contain almost no pyritic sulfur. This form of sulfur appears in raw coal in the fine coal fraction, but can be removed by coal beneficiation. Environmental considerations dictate that every year, more of the fine coal produced for steam generating purposes in the US be beneficiated. To deliberately discard any portion of the fine coal can only add to this cost, not only in the sense that fewer tons will be recovered but, more importantly, additional tonnage will be diverted to the most capital- and labor-intensive section of the entire preparation plant-the fine refuse dewatering section. It is apparent to preparation engineers that dewatering and ultimate disposal of the fine refuse derived from this beneficiation step is certainly the most difficult technical problem presented in the entire plant design. Therefore, any beneficiation procedure which increases the fine coal recovery, or in any manner decreases the tonnage of fine refuse to be dewatered, is going to be cost effective. Since the -28 mesh fraction contains both coal and refuse particles in their finest particle sizes and thus presents the greatest degree of liberation, one would immediately infer that the highest degree of beneficiation would be achieved. This is not the case-the opposite is more likely true. Conventional coal cleaning devices based on specific gravity (such as

Jan 8, 1980

By D. A. Wheeler

Invented by Pierre Boutin in the early 1960s the column was a complete break from the conventional flotation cell. 1. When used as a rougher-scavenger, the column is excellent. 2. When used as a cleaner, the results can be spectacular. The very first column tests were carried out using it as a rougher-scavenger in a reverse float where silica was floated from iron. It produced a concentrate underflow as good or better than that produced from roughing and scavenging stages in cells, The froth tailing overflow was better than that produced by several stages of cell cleaning. Column scaleup progressed rapidly from the two inch diameter unit to a semi automated 12 inch diameter column on material from the Iron Ore Company of Canada. A change in operating philosophy within IOCC brought all flotation development, column or conventional, to a halt. At that time, IOCC had an exclusive right to the use of the column in Canada in the field of iron ore. We moved into the field of sulphides. A Canadian copper producer sent ore for testing and the results led to their purchase of the first commercial size of column - a 36 inch diameter machine. It was a mechanical disaster. It took several years to raise sufficient funds to return to that mill with our basic 18 inch square unit. It was to be tested and modified in order to learn how to properly design a large column. Originally used as a rougher- scavenger, it had to produce tails equal to the final tailings from this well run plant. It did, and did so while producing a rougher-scavenger concentrate almost equal to the plant final concentrate. It was finally used as a cleaner and produced concentrate 5% higher in copper than the plant final concentrate with equal cleaner tails. This phase of the column development was carried out under very difficult circumstances. The mill superintendent had realized that if he took the froth removal system from our original mechanical disaster and applied it to a conditioner while injecting air, he would have a flotation cell. He had personally applied for patents on this Maxwell Cell. Our development work was done in his mill and as our results became better and better, our difficulties became worse and worse. We finally had to terminate this work. The 18 inch column installed at Mines Gaspé 14 years later was identical to the one removed from Opemiska. The 18 inch column was tried on various ores over the following years and always produced excellent results. However, it was not really a production size unit. We had always aimed for the 72 inch column (72" x 72" x 44' 9"). Prior to this huge machine, we needed the intermediate 36 inch column. The failure of the original 36 inch diameter unit at Opemiska had raised the possibility of short circuiting inside the column as the cross section increased. The first 36 inch square unit was tested in parallel with the proven 18 inch column. If the underflow of the 36 incher was not as good as that of the 18 incher, short circuiting was a possibility in the larger unit. It had been designed for insertion of drop in partitions, four feed points had been provided and the 36 inch column would have become a modular unit of four 18 inch columns. Testing showed the underflows of both columns to be identical. There was no short circuiting in the 36 inch column. Once we had the 36 incher, we had no fear of the 72 inch column. It is permanently partitioned into four 36 inch columns but uses only one set of instrumentation. All the component parts of the 72 inch column come from the 36 inch unit. In spite of our results, the mining community did not believe the column could work. Finally, in 1980, Mines Gasp6 ordered an 18 and 36 inch column for their byproduct molybdenum

Jan 1, 1988

By C. W. Schultz

The Mineral Resources Institute at The University of Alabama is engaged in a program whose objective is to develop a beneficiation system for Eastern oil shales. Prior experience (1,2) at The University had shown that the grind required for liberation of the oil rich kerogen was substantially below 20~m. Based on this fact and the rapidly emerging consensus that column flotation is the preferred method for ultrafine particle separation, efforts were focused on the column flotation of oil shale. This paper, which must be regarded as a progress report on a continuing MRI project, describes the observations made and the results achieved to date. The investigation is being conducted in two phases. The first phase has been completed and consisted of a factorially designed experiment conducted for the purpose of screening a set of primary flotation variables. The second phase, which is still in progress, is focused on optimization of the operating conditions and development of a flowsheet for specific shales.

Jan 1, 1989

By L. A. Puchkov, Mesentsev. V. K., I. O. Temkin

The problem of increasing underground mine ventilation efficiency is still of top priority. The complication of geological conditions with the depth of underground mining processes and reinforcement of requirements to technological and ecological safety are extorting the necessity of solving this complex problem with using of new information technologies. There exist different approaches to the ventilation problem. One of them, which the authors adhere to, is based on the concept of monitoring (under special mining and geological conditions-automatic control) of mining atmosphere and operative re-distribution of underground mining air among consumer , in accordance with the criterion of optimality [ 1.3 1. ] The set of tasks which should be decided in the frame of con- crete ventilation system depends on the peculiarities of deposit, technological schemes and so on. Nevertheless, some ventilation tasks such as: defining of ventilation network parameters; finding of dependence between these parametrs; operative redistribution of air streems, could be interpreted as universal ones. Main aspects of practical solving of different ventilation problems and their classification were investigated and considered in detail before [I ,2 ]. Some years ago we have began our investigations to develope quite simple and effective methods for decision of ventilation tasks on the base of neural network technology. It is well known that ventilation net, formed by various mine workings, is the main component of underground mining ventilation system. In general, network air distribution may be described by some functional F(Q,R,H), where Q- is a vector of air consumptions; H- is a vector of depressions; R- is a vector of airdynamic resistences. (Q,R,H) - are the informative entities , characterising every branch of the net. There exist some fundamental tasks which should be decided during the process of control of mining ventilation: calculating of natural air distribution Q = Q,{R, H,}, or Q = Q2(R, Q?}, where H, - is the maximal depression of the ventilation net, Q, - is the air consumption in the ventilation shaft; identifying of airdynamic resistance for some branches on the base either of air-depression removal or operative monitoring: [ ]

Jan 1, 1996

By J. R. Hindman

The vermiculite review arrived too late for the June issue. In 1992, production of commercial vermiculite in the United States increased 1 % to 170 kt (187,000 st), according to the US Bureau of Mines. The estimated value of vermiculite concentrate was $13.6 million, yielding an average value of $80/t ($72.50/st). Vermiculite is used in several physical forms. Use of the thermally exfoliated product include light weight aggregates, horticultural growth media, thermal insulation applications and absorbents for spill control and liquid waste containment. The untreated commercial concentrates are used as intumescent fillers in plaster board, gaskets and paints. Several chemically modified vermiculite products include clay-sized dispersions and granules for treating flue gas. South Africa was the only major foreign source of vermiculite used in the United States. It exported about 40 kt (44,000 st) to the United States last year. In 1992, Palabora Mining Co. began processing vermiculite in a new beneficiation mill at Phalabowra. It produced about 164 kt (181,000 st). Minor sources of foreign vermiculite concentrates consumed in the United States included about 140 kt (154,000 st) from China. Brazil also exports some concentrate to the United States.

Jan 1, 1993

By P. T. Luckie

The selectivity curve -- a continuous function which predicts the expected proportion of feed material of a particular size that will appear as coarse material -- is the preferred model for describing classification. In a previous paper (I), the authors presented a technique for determining the selectivity curve of a classifier from experimental data. The separation process is defined by a binomial distribution of the form [ ] where s(x), the probability of particles of size x reporting to the coarse stream, is obviously the selectivity value for material of size x.

Jan 1, 1975

By Gary Repetto

Hiring trends in the construction materials industry have remained steady through the years, with some seasonal and geographical variances. However, after several years of a depressed market, the base metals industry has begun to actively hire only over the past two years, due to the continued strength in the prices of copper, lead, zinc, molybenum, etc. The expanding precious metals industry, which for the most part escaped the depressed markets of the mid-1980s, actually preceded the base metal companies in hiring of engineers and operations personnel. The coal industry has not seemed to rebound much from the cutbacks of the early 1980s. And the uranium industry, which began its decline a year or two earlier than the other mineral industries, has remained nearly nonexistent in the United States. In nearly all of the mineral industries, new hires have been mostly in the engineering and operations areas, not exploration.

Jan 1, 1990

By Ibrahim S. Balbaa, J. Terry Strack, James G. Hopkins

A microwave system for continuously reactivating carbon, used in gold processing, has been demonstrated at a gold mine in Ontario, Canada. The pilot unit produced reactivated carbon at a rate of 12 kg/h. Comparisons with the mine's existing reacti­vation kiln indicate that microwave reactivation technology has several clear advantages over conventional regeneration kilns. Upon completion of the original study, the microwave reacti­vation technology was further developed. An advanced rotary type microwave system that can be scaled up to reactivate car­bon at a rate of 120 kg/hr was designed and smaller pilot-scale equipment was commissioned and tested. Under an agreement with OHT, Harper International Corporation will manufacture, supply, and market the new technology. In addition to carbon reactivation, the rotary microwave system can be used in many other heating applications such as ore treatment, ceramic pro­cessing, and cleaning of minerals.

Jan 1, 1998

By A. de Ferran

Is the Brazilian gold rush over? Judging from the situation in Brazil over the past few decades, the answer is almost certainly yes. The picture of swarms of Brazilian prospectors or "Garimpeiros" crowding or, more correctly, overcrowding the gold regions of the Amazon jungle using the time-aged empirical approach to gold exploration has finally run its course. There are two fallacies that have lead to a reduction in the discovery of new gold fields in Brazil. The first fallacy is that "Brazil's geology is largely unknown." The extreme depth of weathering and the general lack of understanding of the shield deposits are at the origin of this misconception. The second fallacy is that "Brazilian prospectors (`garimpeiros') are very naive, have very little technical knowledge and can only produce gold at very low recovery rates." This is more of a result of wishful thinking for the purpose of justifying limiting exploration programs than it is a real consideration. In this paper, the author takes a methodical heuristic approach to gold exploration in Brazil and offers this as an alternative to the empirical approach of the garimpeiros.

Jan 1, 1997

By Takeshi Tanaka, Shinya Ono, Tsuyoshi Kato, Masaji Kato, Yuusaku Tominaga

The knowledge of the macroscopic characteristics of a ventilation network is of fundamental importance for taking counter- measures to increase air quantity in-specified branches, such as those corresponding to working faces at advancing entries or longwall panels. Because the ventilation characteristics are inherent properties of each mine, it takes a long time for an engineer to accumulate experience on how a specific regulator may affect the air quantity in a specific branch of a mine with a complicated ventilation system. A computer-simulation training system, based on the macroscopic ventilation characteristics, is presented in this paper. When a trainee selects a specific condition from five regulator option (closed, almost closed, slightly open, half open, open), the change in air quantity for a network branch is indicated by the color allocated to the ratio of the new air quantity to the old or planned air volume. After the ventilation simulation, the colors in the specified branches are defined by using the fuzzy set theory. The trainee continues practicing the selection of closed/open conditions for different regulators until each of the specified branches is displayed in good state of airflow. The ventilation net- work of the Horonai coal mine is used as an example of the training system to control air quantities in six working faces with 33 regulators.

Jan 1, 1996