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By Greg Yuriy

Over the past two decades, Vale Canada has used discrete-event simulation in a key role to support many underground mining studies. Traditionally, general purpose simulation software was developed for manufacturing and service applications. Not until recently have Mine Designers and Simulation Specialists been able to model the dynamics of underground mining scenarios without extensive manipulation of the inherent tools and entities contained within these simulation environments. This paper discusses Vale Canada?s past experiences with a variety of simulation software, describing model development methods and highlighting some of the lessons learned. The paper concludes with a review of recently considered software and provides a framework of desired attributes/functions for modeling mining scenarios.

Aug 1, 2013

By Nora M. Hutt, Kevin A. Morin

There is currently some pessimism over mixing of net-acid-neutralizing (NAN) and net-acid-generating (NAG) rock to obtain indefinite near-neutral seepage from mined-rock piles. This is due in large part to the lack of well- documented, successful cases of blending and layering, and to the knowledge of unsuccessful attempts. Past work often defined a potentially successful mix in terms of the ratio of net-acid-neutralizing rock to net-acid-generating rock. For example, one case study indicated the bulk pile-wide ratio was approximately 3: 1. Since this exceeded a common ratio used in acid-base accounting, no acidic drainage was predicted. However, acidic drainage appeared within two years. A large part of the ambiguity in mixing arises from attempts to predict success based on a ratio. This paper looks in detail at simple discrete-zone mixing, where at least one truckload of NAG rock is placed in a particular location with no further rehandling or dozing. The lack of acidic drainage in this scenario is dependent on the intervening distance between the discrete NAG zones, along flowpaths occupied by NAN rock. Calculations show that the bulk mixing ratio of a mined-rock pile is not an accurate indication of whether near-neutral drainage can be maintained. For example, a pile with a bulk ratio around 300: 1 could still release some acidic drainage. Calculations also show that the minimum separation distance of the NAG zones (L) can be so great, even with typical NAG and NAN rock, that the mixed pile could safely contain only a few percent of NAG rock, which would not be sufficient for many minesites with NAG rock. The comparison to a more elaborate, computer-based statistical model shows that the simple discrete-zone approach will provide a reliable yes-no indication of whether any acidic drainage will leave a pile. However, predictions of whether combined downstream drainages will be acidic depend on numerous site-specific physical and geochemical factors within and below a pile that cannot be modelled in a general way, like the number of flowpaths and the nature of their intersections.

Jan 1, 2000

By Andrea Koschinsky, Akira Usui, Michael Bau, Katja Schmidt, James Hein, Thomas Kuhn

Marine ferro-manganese (Fe-Mn) crusts and nodules are metal-rich chemical sediments that are archives of paleoceanographic proxies and potential metal resources and targets of deep-sea mining. Traditionally, crusts and nodules are subdivided into hydrogenetic, diagenetic, and hydrothermal types. While hydrogenetic Fe-Mn crusts are a potential resource for Co, Te, Pt, and REY, nodules are enriched in Cu, Ni, Mo, and Li, and hydrothermal deposits may be enriched in individual metals such as Mo, Ba, and Li, depending on the temperature and composition of the hydrothermal fluid. The different types of marine oxidic Fe-Mn precipitates, therefore, have different economic potential. Hence, a robust classification is not only helpful in the general geochemical characterization of such precipitates (and as such is a useful teaching tool, for example), but may also simplify the evaluation of their importance as a potential metal resource, which helps to prioritize exploration targets for deep-sea mining.

Sep 1, 2014

By M Shaffer, D C. Grant, D J. Goudie, P Sylvester, C Voisey

Scanning electron microscope–Mineral Liberation Analyser SEM-MLA can be used to discriminate between hematite/magnetite in iron ores, but achieving backscattered electron (BSE) segmentation between the two minerals is difficult for particles =75 µm using typical preparation and analysis methods for the MLA based on a tungsten filament SEM (Quanta 400) with 25 kV high voltage. Preparing iron ore sample mounts using a slow-speed polishing method, and conducting the experiment on a field emission gun SEM-MLA (Quanta 650) with the high voltage (HV) setting lowered to 15 kV reduces instrument noise and results in very clean BSE images and segmentation. This method requires new X-ray standards to be acquired for each mineral identity at 15 kV because of major changes in the spectra at lower kV. However, once these X-rays are added to the mineral reference list, effective segmentation can be achieved and a proper analysis obtained.CITATION:Grant, D C, Goudie, D J, Voisey, C, Shaffer, M and Sylvester, P, 2017. Discriminating hematite/magnetite via scanning electron microscope–mineral liberation analyser in the - mesh size fraction of iron ores, in Proceedings Iron Ore 2017, pp 541–548 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 24, 2017

By Guangyao Si, Ismet Canbulat, Xun Luo, Yi Duan

Routine analyses of seismicity and event locations are essential for coal burst risk management, especially in the presence of unfavorable and complex geology. In an Australian longwall coal mine, a small-scale seismic monitoring network was installed to monitor a section of a major dyke intersected by the roadway, which was classified as a coal burst prone zone. The Deep Convolutional Neural Network (DCNN) technique was adopted for automatically discriminating seismic events to assess seismicity in this zone. The discriminated seismic events were located with the Shortest Path Method based on the Boundary Discretization Scheme (BDS-SPM) for temporal-spatial seismic event distribution analysis. The results demonstrate that the seismic events are discriminated with an average accuracy of 94%. Moreover, the seismic events are more accurately located using the BDS-SPM with a 3D heterogeneous velocity model compared with results obtained with a homogeneous velocity model. The temporal and spatial variances in seismic activities identify that the rock fractures in the dyke zone are closely related to the longwall mining process and a local dyke has a controlling influence on the stress concentration in its vicinity.

Apr 26, 2022

Dr C. M. van Staden (Fellow): Mr President, ladies and gentlemen, thank you very much for this opportunity to contribute to the paper by Dr Stander, and Messrs Henzen and Funke. First of all, my congratulations to Dr Stander on being re-elected President of the International Association of Water Pollution Research. We in South Africa are proud that this honour was again bestowed on our leading scientist in the field of water research. Furthermore, my congratulations to the authors of this paper. The growth of the pollution problem caused by acidic water discharged from abandoned collieries, is known to most of us. However, I am not aware of any case where an abandoned gold mine is directly discharging polluted underground water. I think it is also a debatable point as to what the quality of underground water being discharged from abandoned gold mines would be in the long run. Any reduction works on a gold mine which practises only fairly good housekeeping, should not cause any water pollution by cyanide. First of all, any cyanide solution before gold precipitation would be too valuable to lose. Secondly, the precipitated solution, which contains the cyanide, is used to pump slime to slimes dams. Any cyanide pollution that may occur at the slimes dam, must come from the top and, fortunately, the days when pen stock water was discharged directly from the top of dams into public streams, have gone. Run-off and seepage is usually acidic, thus decomposing the cyanide. The code of practice by the Chamber of Mines is quite clear on the point as to how the tops of dams should be secured, to prevent any process water or storm-water polluting public streams. The general standards are given on page three of the paper. To my knowledge, under certain circumstances a degree of relaxation can be given regarding the faecal coli count; namely a permissible count of 1 000 per 100 ml. I feel very strongly that research aimed at inhibiting the activity of acid-producing bacteria should be encouraged. Success in this field would be of great benefit to the mining industry. I am very thankful that the authors have mentioned vegetation of dumps as a method to combat water pollution, with the full awareness that the key objective in vegetating dumps is to prevent air pollution. A problem that I have not heard mentioned before and on which I would appreciate the views of the authors, is the pollution that may be caused by power-stations discharging

By R. R. Maclachlan

The Estimation of Fragmentation in Blast Muckpiles by Means of Standard Photographs, by H. van Aswegen and C.V.B. Cunningham. Journal of the South African Institute of Mining and Metallurgy, vol.86,no. 12. pp. 469-474. Dec.1986.We have recently read the above paper and wish to make a number of observations.

Jan 1, 1988

THE CHAIRMAN.-Thank you. Since the papers are rather closely related, I think rather than taking them one at a time we will entertain discussion on any of these problems at this time. W. A. REICH.*-We, of course, quite a while ago got the yellow light that Mr. Cole spoke of, and like everyone else immediately started to study silicon bronzes and brasses. We were interested in the silicon bronzes and brasses because we felt that in order to replace gun metal which makes up a large part of our use we needed something with an elastic limit at least equal to that of gun metal. That means at least 12,000 lb. per sq. in. This study was aimed only at tin conservation. Then we dropped the study of silicon bronzes because high purity copper which is needed in their manufacture became a scarce item. To make a long story short we have recommended to our designing engineers that they use 85-5-5-5 wherever possible because 85-5-5-5 we understand can be made entirely from scrap with little or no tin addition. 85-5-5-5 has a lower elastic limit than 88-8-4, so we felt that we would need another substitute material, a structural alloy with an elastic limit equal to that of 88-8-4, and we immediately turned to the manganese bronze type of alloy. The poor foundry properties of standard manganese bronzes were mentioned by Mr. Thieme and since we feel that high zinc content is largely responsible for this difficulty, our development is directed along the lines of uncovering a material with a lower zinc content and which gains its elastic strength from the addition of other alloying elements, such as, aluminum, manganese and iron. It must be possible to make this alloy entirely from scrap with no additions of scarce high purity material. I would appreciate an expression of opinion on how low we can go in zinc content with this type of alloy without seriously impairing the availability, and how high we can go in aluminum content without making use of aluminum restricted for that use. We assume that the maximum lead content must be placed at 1 ½ per cent to insure good availability and we feel that about I per cent of tin in the alloy would improve salt water corrosion resistance similar to the effect of tin in Admiralty Metal. Has anyone here had experience with the effect of tin and lead on the weldability of such an alloy? C. S. COLE.-What percentage of lead and tin? W. A. REICH.-About 1 per cent of lead and 1 per cent of tin. We are studying the weldability of the alloy but perhaps someone already has the answer. (Pause, no answer) The claim has been made that 1 per cent of lead can be added to certain silicon bronzes without impairing their properties. A silicon bronze with a low zinc content requires high purity copper in its manufacture but if say the 15 per cent zinc, 44 silicon balance copper alloy could be made, with a I per cent lead content, some quantity could be made from scrap. We do not know whether the aforementioned is

Jan 1, 1943

The Role of the Drilling Contractor BY FERRIS E. SAINSBURY Ron Haxby, Occidental Minerals What is the best method for drilling a 12-in. diam hole to a depth of 1200 ft and maintaining the deflection within 25ft from vertical? Ferris Sainsbury: In order to drill a 12-111. hole down to 1200 ft, In most places you would have to employ a rotary tricone bit With a down-the-hole hammer, I expect by that depth significant Inflows of water would be experienced Even with foams, we would not be able to get the water out of a hole of that diameter So the down-the-hole tricone method of drilling would be best. To keep it straight, we would probably employ the largest square drill stem compatible with the diameter of the hole. Ron Haxby: Is it common in drilling contracts to put in a vertical hole clause? Ferris Sainsbury: You can put in the vertical hole clause Ron Haxby: Does it cost more? Ferris Sainsbury: Normally, if the hole deviates, the driller can correct it with deflection wedges and will charge it back to you at cost, plus 10% or somewhere along that range Any drill hole has a tendency to go perpendicular to the dip, and there are times when stabilization systems are not successful in preventing the hole from turning into the dip of the formation. The only solution, in this situation, is to go in with an oriented wedge and kick the hole back out.

Jan 1, 1979

T. T. READ, BUREAU OF MINES: Mr. McAuliffe has asked a very practical question. Expressed in another way, the question is: If we have decided to use rock dust to prevent coal dust from exploding, have we got to take rock, that is, solid material,, break it up and finally grind it into dust (and fine grinding is very expensive), or can we take material that is already in a pretty fine state of subdivision and thereby save the expense of pulverizing it? Most of the preceding discussion has been from the view-point of practical experience, and I should like to suggest that we have not had enough practical experience in rock dusting to be able to answer this question, from the viewpoint of experience, with the degree of definiteness that Mr. McAuliffe desires. With your permission I will discuss the matter briefly from the theoretical standpoint, because after all the theoretical considerations, insofar as we understand them correctly, will apply to every' case, whereas in coming to a decision on this matter it will be necessary to take into consideration local conditions, which will necessarily vary in every case. Considering the matter in a rather elementary way, the first point is: What makes coal dust explode? The air of this room is full of dust at the present moment, even though we do not notice it. If you were to close up the room for a week, enough dust would settle on the floor so you could write your name on it. Of course, the dust which is in the air of this room is not coal dust but even if it were coal dust and you were to bring an open light in' here we all know that the dust would not explode. The reason for that is that the dust particles are not close enough together for the flame to propagate itself from one to the next. You will probably be able to see in the demonstration in the gallery on Saturday that the coal dust explosion is practically a very rapid burning of the dust. When you light one piece of dust it burns and gives out heat and if there is another piece of dust close enough to it so that the heat from the first piece is able to bring a second piece up to the burning temperature, then the flame will propagate itself through the mixture. But, if the particles are so far apart in the air that the' heat from one particle is dissipated before it reaches an adjoining one, and is therefore not able to bring the second particle up to the burning temperature, then the flame will not propagate. To get a coal dust explosion, it is not sufficient to have coal dust suspended in the air. The coal dust particles must be close enough together in the air so that the heat from one burning particle is able to heat the adjoining particles up to the point at which they will burn. There has been some discussion of the size of dust particles that will cause an explosion to propagate, and it has been pointed out that the minus 200-mesh dust is the most dangerous, and that particles coarser than 20-mesh will not propagate an explosion. There are two reasons for that. A large particle has very much smaller surface in proportion to its weight than a small particle has. You know the old story about the Indian who when asked how he could go around in cold weather without any clothes on said that an Indian was all face. A 200-mesh particle is almost all surface and there= fore is able to burn almost instantaneously, which means that it gives out its heat almost instantaneously, whereas a large particle with less surface in proportion to its weight burns more slowly, gives out its heat more slowly, and the heat has more time to be dissipated. The second reason why coarse dust does not easily propagate a flame is because it is so hard to make it

Jan 1, 1924

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 au thors claim that their proposed jackknife method, which is a rekriging of each block by eliminating, in turn, one sample from 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 consist 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 valuebased 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, 1998

By C. J. Pritchard, R. E. Gundersen

I commend the authors on examining an interesting method of shaft lining and attempting to improve safety in a dangerous environment by remotely installing the shaft lining. It is important, though, to not trade off shaft lining safety for long-term mine safety by lining an intake shaft with combustible material. In many operations, the mine utilities are installed next to the lining of the intake shaft, supplying a possible ignition source if damaged or overloaded. Although the polyurethane studied in the paper is of relatively high density, no mention is made of the flame retardency of the samples. When exposed to heat, small amounts of polyurethane will melt and bum but are extinguished when the heat source is removed. If large surface areas of combustible polyurethane - a tunnel or mine shaft- are exposed to ignition heat sources that are not removed or extinguished early, an uncontrollable, fuel rich fire may result with high carbon monoxide levels, low oxygen concentrations, and greatly increased burning rates that can have devastating effects on the ventilation system and miners' safety. Although these heavy polyurethanes lend themselves to a "pouring" application around the annulus of the shaft liners and is a continuous process, past experience with atomizing and frothing polyurethane spray systems indicates a high degree of maintenance and operator attention to the nozzle1 delivery system. This may require more miner's time to be spent in the shaft maintaining the foam system, negating some of the safety advantages of the system. If polyurethane foams are to be used in mines, they must be of the highest quality available in terms of flame spread, heat emitted while curing, and contaminants emitted while curing and spraying. In addition, employees must be given adequate training and be thoroughly informed in all aspects of polyurethane foam safety procedures. As witnessed by our fellow miners in South Africa, we can accept no less.

Jan 1, 1991

By H. Nemutolluhi

Discussion by G.E. Agar In the April issue of Mining Engineering there is a technical note "New size laboratory ball mill for Bond Work Index determination" written by M. Nematollahi which is very confusing. My recollection is that a description of an experimental procedure should be such that someone skilled in the art should be able to reproduce the results. Applying this test to this particular article would according to me cause a failure to be registered. There are apparently three batch laboratory test procedures referred to in the article. One of these is the traditional Bond test with all its limitations such as dry grinding followed by exclusively dry screening, two attributes which fail to simulate conventional industrial grinding. There is a second procedure (NSBM) which the author is advocating as an improvement of the Bond procedure but from the description I doubt that anyone would be able to repeat the procedure. For instance, is the grinding to be done wet or dry, if wet at what pulp density, and how is the screening to he done, wet or dry or a combination? On top of that uncertainty the author refers to a simplified "Anaconda" test. No reference is provided for this procedure and in the text the results of the technique are referred to "Denver wet ball mill" results and say nothing of Anaconda results. Reply by H. Nematollahi I think that the method proposed to determine the Bond Work Index in this paper is clearly described in the paper as follows: •The method of grinding is dry (Ref. paragraph I, subject Method description); •The size of ball mill, the quantity and size of balls are noted (Ref. paragraph 1, subject Test equipment); and The test procedure is described in detail (Ref. paragraphs 1, 2 and 3, subject Test procedure). As it is noted in the paper, the test has been worked out under the same condition as Standard Bond Test with ball mill, so dry (screening should be dry also), but using a smaller ball mill and a smaller quantity of sample. Considering the above mentioned points, I believe that the method has been fully and clearly described and it ought to be repeatable as well. The Anaconda test is a method for determination of Work Index and could be done by any types of laboratory wet ball mill (Yan, R.F., et al., cf. References). I applied this method using a laboratory Denver ball mill (Ref. paragraph I subject Determining the Bond Work Index). So the results referred to Denver wet ball mill can be equated the same as Anaconda method.

Jan 1, 1996

By Jay F. Smith

The Alan Wood BOF Shop consists of two 140 ton furnaces with a rated yearly capacity of 1-1/4 million ingot tons, he hot metal for the BOF Shop is supplied by two 18 foot blast furnaces which produce an average of 2000 tons per day, To achieve the rated ingot ton capacity with this limited supply of hot metal, the preheating of scrap is necessary. This is accomplished in the furnace by using an oxygen-natural gas burner. Piping Arrangement The natural gas and oxygen are piped into the Shop through 8-inch lines to their respective valving stations. As can be seen from Figure 1, the flow of natural gas passes through a flow control valve which is common to both furnaces, after which it divides into two 6-inch lines forming two identical and independent gas control lines, one for each furnace.

Jan 1, 1972

Contribution by G. Narsimhan It was with much pleasure that I went through D.F. Malan's excellent paper. The following explanatory and critical note has been the result of my deep study of the paper. Although by qualifications and experience I have been a chemical engineer, involved over four decades with problems in the modeling and simulation of transport-limited (heat and mass) chemical reactions in multi-phase systems, I have of and on interested myself in challenging problems in extractive metallurgy. This is the first time I have veered of to continuum mechanics, at the age of 71! Author's reply. I thank Professor Narsimhan for his extensive contribution to the paper. It provided me with the stimulus to derive an extended model. However, there are some inaccuracies in his arguments that need further discussion. Professor Narsimhan's main concern is that there is not a good enough fit between the derived viscoelastic Kelvin model and the experimental data supplied by Güler1 (see Figure l1 on page 218 of my paper). I will therefore explain the choice of a viscoelastic model in more detail and also make specific comments on the arguments given in his contribution.

Jan 1, 1996

By E. Tulcanaza

M.S. Azun I do not at all agree with the basic points of the author's conclusion. The use of lognormal or normal model to respond to the attribute distribution function should be carefully questioned. If fitting a distribution function of regionalized variables is the main purpose, one may employ one of certain well-known families of distributions, such as Tukey's lambda functions. For instance, the distribution function of gold assay values studied by Krige (Krige, 1978) may fit the lognormal model well, but one should not exclude that the basic idea of using the distribution function of observed data is to have insight of the physical mechanism that gives rise to the regionalized variables. In Applied Geostatistics, there are many examples considering only lognormal or normal model for the distribution function of geostatistical data even if the observed distribution function has more than one mode. Of course, using lognormal or normal model always brings easy computation for the statistical properties of attribute under investigation. Still, I object to adopting any of those models without having any "statistical inference." As seen from the author's paper, lognormal and normal model produce the same average grade (0.746% copper) and almost the same sample variance. Therefore, which model explains the probabilistic behavior of ore deposit is always an important question that should be replied by the geostatistician using not the common sense but the statistical and probabilistic methods. For kriging procedures, such as linear kriging, one should describe either second order stationary properties or bivariate properties of regionalized variables. Second order properties, such as correlogram function or semivariogram function, are the inputs of the so-called kriging equations. Selecting one of any useable models for the observed second order properties, such as spherical model, is not easy since the models are not based on the correlations structure of the regionalized variables. How those models being used in Applied Geostatistics can be distinguished is another important problem. One may develop many fitting models to respond to the observed second order properties of regionalized variables. However, I suggest that the model should be based on the probabilistic behavior of geologic process. The author used spherical model for copper, wolfram, and silver grades from isotropic sector (Fig. 2, 4, 3b) and exponential model for silver grades obtained along raises in isotropic sector (Fig. 3a). It seems that those semivariograms given in Fig. 3b for isotropic sector and Fig. 4 may be described by the random model implying that regionalized variables do belong to renewal process (Azun, 1983). If I knew the total number of data points used in estimation, I may prove that my conclusion is correct. Recalling the test for the first order sample correlogram value, the test procedure is introduced such that the independence is rejected if [ ] where Za/2 is the a/2 percentile of standard normal random variable and N is the total number of samples used in estimation (Azun, 1983). For the other observed semivariogram functions I suggest the author might try to use the so-called "Markovian model" describing not only the correlation structure of regionalized variables, but also the physical mechanism that produces the regionalized variables. The Markovian model for correlogram function is, [ ] The Markovian model for the other second order properties of ReV are also derived. T ve B, in the above equation, show, for example, structural change and mineralizational variation in a considered deposit, respectively (Azun, 1983). In selecting any model, it is not easy to search for the "best" response to the observed second order properties of ReV's. The Markovian model, based on a theoretical understanding of underlying mechanism, gives more information about the occurrence of regionalized variables and respond to all properties. Random model and the so-called hole effect structure can be easily defined as a special form of the Markovian model (Azun, 1983). An estimation of any second order properties of regionalized variables may be computed through (N-1) lag. However, the dependency between the regionalized variables may be deemed to have "died out" after the so-called stationarity width (range). In practice, the estimation is carried out through 25% of the total number samples available. Therefore, the large fluctuations around the zero level and variance for correlogram or covariogram function and semi-variogram function, respectively, cannot be observed. Since the number of pairs involved in the estimation of higher second order properties is small, the estimation variance at those lags is large. There is no need to show higher order estimated second order properties. After using one of any kriging procedure for block estimation, the distribution function of average grades has the same mean as the drilling sample grades but

Jan 3, 1985

By M. S. Azun

I do not at all agree with the basic points of the author's conclusion. The use of lognormal or normal model to respond to the attribute distribution function should be carefully questioned. If fitting a distribution function of regionalized variables is the main purpose, one may employ one of certain well-known families of distributions, such as Tukey's lambda functions. For instance, the distribution function of gold assay values studied by Krige (Krige, 1978) may fit the lognormal model well, but one should not exclude that the basic idea of using the distribution function of observed data is to have insight of the physical mechanism that gives rise to the regionalized variables. In Applied Geostatistics, there are many examples considering only lognormal or normal model for the distribution function of geostatistical data even if the observed distribution function has more than one mode. Of course, using lognormal or normal model always brings easy computation for the statistical properties of attribute under investigation. Still, I object to adopting any of those models without having any "statistical inference." As seen from the author's paper, lognormal and normal model produce the same average grade (0.746% copper) and almost the same sample variance. Therefore, which model explains the probabilistic behavior of ore deposit is always an important question that should be replied by the geostatistician using not the common sense but the statistical and probabilistic methods. For kriging procedures, such as linear kriging, one should describe either second order stationary properties or bivariate properties of regionalized variables. Second order properties, such as correlogram function or semivariogram function, are the inputs of the so-called kriging equations. Selecting one of any useable models for the observed second order properties, such as spherical model, is not easy since the models are not based on the correlations structure of the regionalized variables. How those models being used in Applied Geostatistics can be distinguished is another important problem. One may develop many fitting models to respond to the observed second order properties of regionalized variables. However, I suggest that the model should be based on the probabilistic behavior of geologic process. The author used spherical model for copper, wolfram, and silver grades from isotropic sector (Fig. 2, 4, 3b) and exponential model for silver grades obtained along raises in isotropic sector (Fig. 3a). It seems that those semivariograms given in Fig. 3b for isotropic sector and Fig. 4 may be described by the random model implying that regionalized variables do belong to renewal process (Azun, 1983). If I knew the total number of data points used in estimation, may prove that my conclusion is correct. Recalling the test for the first order sample correlogram value, the test procedure is introduced such that the independence is rejected if [Ir(1) I > Za/2 N1/2] where Za/2 is the a/2 percentile of standard normal random variable and N is the total number of samples used in estimation (Azun, 1983). For the other observed semivariogram functions I suggest the author might try to use the so-called "Markovian model" describing not only the correlation structure of regionalized variables, but also the physical mechanism that produces the regionalized variables. The Markovian model for correlogram function is, [p (h) = T 1ih , h>1 ,] The Markovian model for the other second order properties of ReV are also derived. [T veß], in the above equation, show, for example, structural change and mineralizational variation in a considered deposit, respectively (Azun, 1983). In selecting any model, it is not easy to search for the "best" response to the observed second order properties of ReV's. The Markovian model, based on a theoretical understanding of underlying mechanism, gives more information about the occurrence of regionalized variables and respond to all properties. Random model and the so-called hole effect structure can be easily defined as a special form of the Markovian model (Azun, 1983). An estimation of any second order properties of regionalized variables may be computed through (N-1) lag. However, the dependency between the regionalized variables may be deemed to have "died out" after the so-called stationarity width (range). In practice, the estimation is carried out through 25% of the total number samples available. Therefore, the large fluctuations around the zero level and variance for correlogram or covariogram function and semivariogram function, respectively, cannot be observed. Since the number of pairs involved in the estimation of higher second order properties is small, the estimation variance at those lags is large. There is no need to show higher order estimated second order properties. After using one of any kriging procedure for block estimation, the distribution function of average grades has the same mean as the drilling sample grades but

Jan 1, 1986

By M. A. Schimmelpfennig, A. D. S. Gillies

M.J. McPherson Having worked on the thermodynamics of air/liquid-water mixtures passing through the surface fans of deep mines, I find this paper of great interest and congratulate the authors on producing it. There are two matters, however, deserving discussion. First, the authors have described the classical theory of fog formation with fogging occurring at "supersaturation." In fact, the process of fog formation begins well below 100% humidity. The more strongly hygroscopic nuclei in the atmosphere will attract water molecules and begin to grow at a relative humidity perhaps as low as 70%. The process is a dynamic one with both condensation and evaporation taking place throughout the mixture on microscopic liquid surfaces. As saturation is approached, the rate of condensation accelerates rapidly producing the familiar reduction in visibility. Hygroscopic nuclei are present in all natural atmospheres and under the appropriate conditions of pressure and temperature, will produce clean fogs. However, if the air is polluted by particulates from combustion or other processes then the resultant coagulation with growing liquid particles may produce dense (and sometimes photochemical) smogs. It is this process that is likely to occur in underground mines when moist air is cooled below dew point. Second, the authors have summarized very well the individual measures that might alleviate the problem. In particular, I agree that neither heating nor refrigerating the air, by themselves, provides a satisfactory solution. However, there is a combination of these that provides a neat and effective control of fog formation. This involves a small, self-contained refrigeration unit within a duct but without the usual external heat rejection facility. The air is cooled below dew point and, hence, dehumidified on passing over the cold evaporator coils. The heat from the condenser is rejected back into the air downstream from the water eliminator, as shown in Fig. 1. The duct configuration can be designed to create good mixing at the outlet. I have used a climatic simulation program to illustrate the effect, assuming a 500-m (1,640 ft) long airway of cross section 60 m2 (645 sq ft), an airflow of 9 m3/s (318 cu ft per sec), inlet conditions of 19/19.25°C (66/67°F) wet bulb/dry bulb temperatures, a virgin rock temperature of 17°C (63°F) and typical rock thermal properties for a hard-rock mine. I have also assumed that 10% of the rock surface is wet. Figure 2 shows the variation in temperatures along the airway if no measures are taken. The relative humidity remains close to 100% and condensation will occur throughout the length of the airway. Before any such installation is designed, the exercise must, of course, be repeated for each location with accurate data. However, this example demonstrates the potential of the system. The idea is not new - the principle is sometimes used in air-conditioning plants for buildings. Figure 3 shows the effect of removing 30 kw of heat by evaporator coils sited 40 m (131 ft) along the airway and rejecting that heat (plus another 10 kw of compressor and fan power) into the air at 60 m (197 ft). Condensate water is produced, at a rate of 0.45 L/min (0.12 gpm). The result of this sequential cooling/dehumidification/heating process is to separate the wet and dry bulb temperatures along the length of the airway. The relative humidity increases from 80% at the duct outlet to 92% at 500 m (1,640 ft). The airway is maintained free from fog.

Jan 11, 1983

By M. J. McPherson

Having worked on the thermodynamics of air/liquid-water mixtures passing through the surface fans of deep mines, I find this paper of great interest and congratulate the authors on producing it. There are two matters, however, deserving discussion. First, the authors have described the classical theory of fog formation with fogging occurring at "supersaturation." In fact, the process of fog formation begins well below 100% humidity. The more strongly hygroscopic nuclei in the atmosphere will attract water molecules and begin to grow at a relative humidity perhaps as low as 70%. The process is a dynamic one with both condensation and evaporation taking place throughout the mixture on microscopic liquid surfaces. As saturation is approached, the rate of condensation accelerates rapidly producing the familiar reduction in visibility. Hygroscopic nuclei are present in all natural atmospheres and under the appropriate conditions of pressure and temperature, will produce clean fogs. However, if the air is polluted by particulates from combustion or other processes then the resultant coagulation with growing liquid particles may produce dense (and sometimes photochemical) smogs. It is this process that is likely to occur in underground mines when moist air is cooled below dew point. Second, the authors have summarized very well the individual measures that might alleviate the problem. In particular, I agree that neither heating nor refrigerating the air, by themselves, provides a satisfactory solution. However, there is a combination of these that provides a neat and effective control of fog formation. This involves a small, self-contained refrigeration unit within a duct but without the usual external heat rejection facility. The air is cooled below dew point and, hence, dehumidified on passing over the cold evaporator coils. The heat from the condenser is rejected back into the air down-stream from the water eliminator, as shown in [Fig. 1]. The duct configuration can be designed to create good mixing at the outlet.

Jan 1, 1984

By Bunting S. Crocker

Bunting S. Crocker (Executive Vice President, Kilborn Engineering Ltd., Toronto, Ont., Canada)-This is an interesting report on laboratory-scale testing with pebble charges in 12-in.-diam mills, and the author correctly concludes that useful laboratory testing can be done. In the opening paragraphs he states, "laboratory pebble-milling tests have been considered too difficult to perform and not relevant enough to the actual grinding situation"!! This is definitely not so! The writer published detailed tests done in a 12-in.-diam mill comparing pebble and steel balls in 1952 6 and again in 1954 7. We note that our review paper in 1963 was the only one mentioned in the References. The author states that "a smooth lining is more frequently used in commercial-scale pebble grinding." The writer has designed some 22 plants treating 134,000 tpd in North America and Australia. He has also visited pebble installations in Norway, Sweden, Finland, and South Africa. All these plants correctly use heavier lifters than would be considered standard for ball mills of a similar size. Smooth liners are not recommended in wet ore treating plants. In the 1952 paper6 it was clearly demonstrated in the test work that the individual ore pebbles had to be the same weight-not the same diameter or size-as the steel balls if comparable grinding results were to be obtained. In the tests performed in this study most of the pebbles "passed 50-mm round hole screen openings and remained on a 40-mm round hole sieve. Correspondingly most of the ball mill experiments were performed with 50 or 40-mm steel balls". Thus, the balls and pebbles were essentially the same size or diameter. This means we are comparing apples and oranges. When the feed being ground is fine enough the pebbles will be superior. When the feed is coarse the steel balls will be the better. This is similar to grinding tests in which two sizes of steel balls are compared. In the middle of the article, "Crocker5 has reported that equal weights of pebbles and steel balls achieve the same grinding capacities under similar conditions …", then he proceeds to question this postulate. In the eight reports that I have published, I have never made this statement. What I have said is "for comparable grinding, the individual pebbles in the mill charge should be the same weight as the individual steel balls." This is not the first time that I have been misquoted on this point! It is most unfortunate that this test work has been done with a ball and pebble of the same diameter and not the same weight. It is impossible to properly evaluate the results. I also regret the fact that the screen analyses of the tests were not shown. Many of us who have been 40 years or less in the grinding game can easily read screen analyses at a glance. We can tell whether the top meshes are being ground by the ball charge, etc., etc. The graphs are fine for the summary or to illustrate conclusions but are often misleading in the report itself. However, we do agree that useful pebble grinding tests can be done in a 12-in. mill.

Jan 1, 1973