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By J. Hanna, H. R. Gonzalez

Discussion by N.L. Hargett Dear Dr. Hanna: As discussed in our phone conversation, we are enclosing a suggested revision to the paper, "Application of Bentonitic Clays in Suspension Fertilizer Formulations," published in MINERAL & METALLURGICAL PROCESSING, May 1990. The revision will replace the second paragraph in the article. The reason for the revision is that suspensions have decreased in market share since 1984 and at present comprise an estimated 25% to 30% of fluid mixtures. This represents 6% to 7% of all fluids and only 2% to 3% percent of all fertilizers. Based on national surveys conducted by the Association of American Plant Food Control Officials (AAPFCO), suspensions comprised an estimated 25% of all fluid mixtures in 1974, 33% in 1976, 35% in 1980, 40% in 1984, and 36% in 1988. Revision to "Application of Bentonitic Clays in Suspension Fertilizer Formulations." Suspension fertilizers are an important segment of the fertilizer industry in the United States. Suspensions allow higher concentrations of nutrients (N, P2O5, K2O) than clear liquid solution fertilizers. K20 content of solutions is limited to about 10%, while suspensions can contain more than 30% K2O. Suspensions can tolerate greater variations in temperature than solutions. In suspensions, if crystallization occurs, the crystals can remain suspended in a clay jell instead of settling as they would in solutions. Solubility is not a limiting factor in suspensions, since complete solubility of phosphate is not required. This allows a wider range of phosphate materials to be used. Also, materials commonly used in formulating suspensions are less expensive and more widely available than those for clear liquids (Getsiner et al., 1984).

Jan 1, 1992

By Adrian C. Dorenfeld, John T. Oleksy

John D. Maefadyen Subject paper unfortunately has some serious flaws negating the usefulness of the paper. The authors claim that sulfur is the major source of production problems in cement kilns. This is not the case. Sulfur is not a problem as long as the mole ratio of sulfur to alkali oxides is less than, or equal to, 1. This is attributed to the sulfur preferentially combining with the alkali oxides and not acting as a clogging agent due to the nature of the pre-heater vessels. Where the mole ratio exceeds 1, many methods are available to eliminate or reduce the clogging problems such as using the preheater bypass or a precalciner with up to 100% kiln gas bypass. In non-preheater kilns, the presence of sulfates is hardly ever a problem anyhow. Thus, the level of sulfur in the fuel and raw material that might cause problems is not a fixed amount, but is predictable. The purpose of the paper is to discuss the economics of conversion of kilns in the Indonesian and Phillippine cement industries from oil firing to coal firing. This economic analysis has very little to do with the sulfur levels. Thus, the section of the paper on sulfates is actually rather meaningless. The economic analysis is also rather meaningless because the authors have failed to follow accepted economic analysis procedures by including interest charges. They have fallen into the trap of confusing financing with economic evaluation. When the accepted methods of economic evaluation are used, the return on investment increases to about 35%. In conclusion, the paper is not a meaningful contribution, and sadly, quite erroneous.

Jan 11, 1982

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 R. J. Pindred

Discussion by R.J. Pindred In his paper, Davis presents an overview of risk. He also introduces the Capital Asset Processing Model (CAPM) as a foundation for selecting the appropriate discount rate for a mining project. While applying portfolio theory is more defensible than the ad hoc adjustment of discount rates, the CAPM is not a panacea. CAPM shortcomings [The CAPM, as Davis stated, is expressed in the equation: ri=rf+pi4) where ri is the project discount rate rf is the risk free interest rate (3i is the project beta, and 0 is the market risk premium (rm - rf)] Application of the CAPM is more difficult than Davis indicates. Valuation is prospective, while the CAPM parameters are historical. Beta is determined from a regression analysis of historical data, while the beta needed for valuation is the expected beta. Betas are known to be unstable and the regressions that generate them often have low explanatory power. The difficulty of estimating a "project" beta must also be considered. Thus, the beta that is used in the CAPM will be based on the analyst's judgment. Like Cavender's discount rate, this judgment can lead to different project NPVs. Subjectivity in valuation cannot be avoided by a mechanical application of the CAPM. The risk-free rate, which Davis identifies as a short-term real rate of 4%, is also subject to scrutiny. A mining project is not a short-term investment and no single risk-free rate is appropriate for all of the cash flows. The hypothetical mine discussed in Cavender's paper is a six-year project. One might argue for the application of a risk-free rate from the Treasury yield curve at the duration of the project (in a bond-duration sense). This, too, is inappropriate. The risk-free rate should be matched to the timing of the cash flow. These rates can be determined by calculating the implied forward rates from the yield curve using a procedure known as "bootstrapping." It is likely that each of the project's cash flows would be discounted at a different rate. Commodity prices Davis criticizes the "ad hoc adjustment to the discount rate." Yet, in his discussion of the value of stochastic simulation, he suggests that the gold price be modeled as a "random walk, with or without a trend." This is essentially an arbitrary modeling of price risk. Consider that a liquid market in gold futures exists. The futures' price curve, which is closely related to the market's estimate of future spot gold prices, should be used to provide inputs to the model. This is especially true of a relatively short six-year project. Alternatively, as Davis correctly points out, a risk-averse investor can sell the commodity short to hedge price risk. Is it any more correct, in the portfolio sense, to account for price risk at all ?? References Cavender, B., 1992, "Determination of the optimum lifetime of a mining project using discounted cash flow and option pricing techniques," Mining Engineering, Vol. 44, No. 10, pp.1262-1268 Fabozzi, F.J., 1993, Bond Markets, Analysis and Strategies, Second Edition, Prentice Hall, Inc. Higgins, R.C., 1992, Analysis for Financial Management, Third Edition, Richard D. Irwin, Inc. Solnik, B., 1991, International Investments, Second Edition, Addison Wesley Reply by G.A. Davis Pindred discusses two issues related to my paper, the shortcomings of the Capital Asset Pricing Model (CAPM) and which commodity price values to use in the valuation exercise. Even though these topics are not directly related to the use or misuse of Monte Carlo simulation, they are important points to take into consideration in valuation exercises. Since I do not appear to have addressed these issues satisfactorily in my original paper, I will comment on each here. Pindred agrees with me that applying portfolio theory, and specifically the CAPM, to the selection of project discount rates is more defensible than ad hoc methods. But he then points out that the application of the CAPM to project valuation is more difficult that I indicate. It is true that the CAPM is a difficult tool for project valuation in general,. But the application of the CAPM to mining projects is one of the easiest I can think of. The biggest problem with using the CAPM for project valuation is coming up with an expected project beta. I suggest a project beta for gold projects of 0.45. The "true" value might be 0.35, 0.55 or whatever. Pindred correctly notes that the selection of the appropriate project beta is based

Jan 1, 1996

By L. W. Saperstein

P.J. Ehret By and large, I agree with many of the precepts discussed in the Saperstein paper. I believe there is much more that can be done on the local level to involve both government and planning in the mine permit review process. Admittedly, much can be done to improve discussion between the state regulatory authority, local authorities, and mine operators. However, I strongly disagree, as suggested in the paper's conclusion, that such a system, as outlined in Saperstein's paper, could result in a reduction of review time or a lowering in the cost of permitting. The implementation of such a system by its very nature would only add a new level of bureaucracy to an already cumbersome process. This system, in my opinion, would only add to the cost of permitting and the time necessary to obtain a permit. Admittedly, it would achieve the result of adding local influence into the permitting process, but at what off-setting cost? It has been my professional first-hand experience and observation in the permitting and lands unsuitable processes to note that under the present system, local governments that do feel they have a stake in local mines and actively ad¬vocate their position (not simply comment), have had significant input into the conduct of mining and reclamation plans in their areas. Mining companies that mine in these areas are aware of local interests and attitudes, and do consider them in their plans. Simply put, local governments that want to get involved and want to play significant roles can and do. Those that do not advocate a position or have no input to offer do not. Although the present system is not as direct in effect in regard to local control as Saperstein's, it does work. It does so without the red tape that would result from developing miniature regulatory authorities in every county in which mining occurs. Although local input is important, there are many more sections of the Surface Mining Control and Reclamation Act (SMCRA) than Sections 508(a)(8) and 522(a)(3)(A) that also are important. It appears Saperstein's paper may overindulge these sections. An additional specific comment is made in regard to the statement that while local areas benefit from mining (wages, salaries, and purchases), they also endure environmental deterioration caused by mining affects. It is believed that the whole purpose for which SMCRA and its resulting regulations were enacted and developed was so mining would not be permitted if significant environmental deterioration could occur. Therefore, it could be argued that this point under current law is moot. Reply by L.W. Saperstein P.J. Ehret writes in a reasoned and rational way and makes some good points. The arguments in favor of central control of the designation process reflect all of the benefits associated with central environmental control: consistency of enforcement, efficiency of operation, ease of communication among enforcing agency, etc. Nonetheless, the decision to mine or not to mine is a landuse decision which, in substance, is similar to the decision to build a shopping mall, a new highway, or a housing subdivision. Although, state and federal governments' interests in the protection of public welfare are real and are expressed properly in mining laws and mining enforcement agencies (OSM, Illinois Department of Mines and Minerals, etc). I continue to maintain that the permitting and designation processes should originate with local government, which is in keeping with the American tradition of delegation of the land-use decision to local or regional government.

Jan 4, 1984

By B. Mather

Discussion by B. Mather I was very glad to see an article on alkali-silica reactivity of concrete aggregate in Mining Engineering. It is a topic that should be reexamined every 45 or 50 years. The last paper (that I am aware of) that examined this topic in Mining Engineering was Rexford (1950), who, at the time, was chief of the Petrography Section, South Pacific Division Laboratory, Corps of Engineers, Los Angeles, CA. The paper was presented at the AIME meeting in Los Angeles in October 1948. Professor Leming's discussion generally reflects the current state-of-the-art; but it provides no references for more detailed information. I wrote a paper titled "How to avoid excessive expansion of concrete due to alkali-aggregate reaction," which was included in the Proceedings of the Second International Conference on Alkali-Aggregate Reactions in Hydroelectric Plants and Dams (Mather, 1995). In it, I emphasized that it was the hydroxide ion (not the alkali ion) that caused the pore fluid in the concrete to dissolve reactive silica, producing alkali-silica gel capable of taking up water, thereby, causing swelling and rupturing of the concrete. Excessive expansion will not occur unless there is a sufficient amount of potentially expansive alkali-silica reaction product and water. However, this will not occur unless there is a sufficient quantity of reactive aggregate and unless there is a mechanism by which the pH of the pore fluid can get well above the normal value of about 12.6. In many cases it is sufficient that the cementitious medium not only contains portland cement but also contains ground granulated blast-furnace slag (GGBFS) or a pozzolan such as fly ash, silica fume, metakaolin, volcanic glass or calcined shale - any of which may have been included for economic reasons. If, however, the person selecting the ingredients for concrete knows that the aggregate is reactive (with no alternate nonreactive aggregate available) and if the person knows that the only available portland cement has a high alkali content (i.e., more than 0.6% Na2Oe; Na2Oe = % Na2O + 0.658 x % K20), then it becomes irresponsible not to establish what reasonable precaution one should take. Professor Leming suggests using one of the following: 30% Class F fly ash, 50% GGBFS or 7% to 10% silica fume. My view is that one should prepare test specimens with the cement and aggregate to be used and then expose these both with and without at least two dosages of each of the various alternative materials (slag, pozzolan and lithium salts), so that the required dosage to control the expansion is established. Then, economic considerations can dictate the final selection. I would point out to the author that GGBFS is not a pozzolan and is not an admixture, but, rather, it is a latent hydraulic cement. An admixture is, by definition, a material other than hydraulic cement. I commend him for suggesting that aggregate producers should become more active in knowing about the reactivity of their products and the precautions needed to permit those products to be safely used in concrete. ? References Mather, B., 1995. "How to avoid excessive expansion of concrete due to alkali-aggregate reaction," Proceedings, Second International Conference on Alkali-Aggregate Reactions in Hydroelectric Plants and Dams, US Committee on Large Dams, Denver, CO, pp. 421-439. Rexford, E.P, 1950, "Some factors in the selection and testing of concrete aggregates for large structures," Mining Engineering, Trans. AIME, Vol. 187, pp. 395-402. Reply by M.L. Lerning Mr. Mather has once again provided a cogent and useful discussion. I am grateful to him for bringing these issues to my attention, as well as to the readers, and I am grateful for his discussion of several important factors in alkali-silica reactivity. Mr. Mather's discussion of the mechanism of alkali-silica reactivity (ASR) notes the critical role of the hydroxide ion. While the alkali hydroxides are highly soluble (reducing the solubility of the other primary hydroxide in pore solution, i.e., calcium hydroxide, and providing hydroxide ions that initiate alkali-silica reactivity), it is, as Mr. Mather quite correctly notes, the hydroxide ion that attacks the silica structure. This point was not clearly stated in my original article. As noted in the text, the requirements for mineral admixtures to mitigate or control ASR vary widely depending on the specific characteristics of the materials

Jan 1, 1998

By M. E. Gershon

I would like to congratulate Professor Gershon on an idea that is obviously valuable and is certainly new to me. It has, however, to be further developed, in that one can get fallacious results by limiting oneself to positional weights. In the example problem, the positional weight of one block was 8.6 (the 8.0 value in the paper was incorrect) for 36 units in the cone, for a mean block value of 0.239. The positional weight of the second block was 4.4 for 15 units, for a mean block value of 0.293. Surely one would expect the second block to be rated higher. Additionally, the time value of money adjustment cannot be determined by depth, because the time that a block is mined is determined by the mining sequence, not depth. Figure 1 shows a slightly altered version of Professor Gershon’s pit. The overall value of the pit is the same, as are the total values under each of his blocks. The values in the right-hand cone have been reversed top to bottom, and the values in the rest of the pit adjusted to keep the central cone total unchanged. All values have been multiplied by 10. Figure 2 shows the sequence of mining, at three blocks per year, for Professor Gershon’s pit, and Fig. 3, the sequence for a pit under the other block. Table 1 shows the value and discounted value (157. ) of Professor Gershon’s pit, and Table 2 shows similar values for the second pit. It is apparent that the second pit schedule is more valuable than the first.

Jan 12, 1987

By C. J. Hall

I would like to congratulate Professor Gershon on an idea that is obviously valuable and is certainly new to me. It has, however, to be further developed, in that one can get fallacious results by limiting oneself to positional weights. In the example problem, the positional weight of one block was 8.6 (the 8.0 value in the paper was incorrect) for 36 units in the cone, for a mean block value of 0.239. The positional weight of the second block was 4.4 for 15 units, for a mean block value of 0.293. Surely one would expect the second block to be rated higher. Additionally, the time value of money adjustment cannot be determined by depth, because the time that a block is mined is determined by the mining sequence, not depth. Figure 1 shows a slightly altered version of Professor Gershon's pit. The overall value of the pit is the same, as are the total values under each of his blocks. The values in the right-hand cone have been reversed top to bottom, and the values in the rest of the pit adjusted to keep the central cone total unchanged. All values have been multiplied by 10. Figure 2 shows the sequence of mining, at three blocks per year, for Professor Gershon's pit, and Fig. 3, the sequence for a pit under the other block. Table 1 shows the value and discounted value (15%) of Professor Gershon's pit, and Table 2 shows similar values for the second pit. It is apparent that the second pit schedule is more valuable than the first.

Jan 1, 1988

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. 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 F. W. Brackebusch

In the paper presented by F.W. Brackebusch on the "Basics of paste backfill systems," paste fill was presented as a backfill process that offers many advantages over other alternatives such as hydraulic fill and rock fill. It was observed, however, that the mechanics of paste-fill transportation in pipelines is not fully understood and that the success of its implementation in practice depends on the precise control of the proportions of fines, aggregates and water in the mixture. The author emphasized the necessity for laboratory and full-scale testing to determine the suitability of a material to be used as paste fill. Although experimental testing is definitely an important operation in the design of a reliable paste fill, advances in the understanding of the fundamental laws that govern paste flow in pipelines are equally relevant. Ideally, the results of such efforts would provide predictive models for the rheology of the paste and the corresponding pumping-energy requirements. In an attempt to achieve this objective, an ongoing research program has been active at McGill University's Department of Mining and Metallurgical Engineering. Preliminary results showed that the underlying mechanics of paste-fill flow in pipelines may be described in terms of what is known as "plug flow," as depicted in Fig. 1. Although this flow mechanism has been known qualitatively for many years, few attempts managed to offer a comprehensive model (Gandhi, 1987; Duckworth, 1986). In our model, it is assumed that coarse aggregates present in the mixture form a porous core, which is filled with paste (fines and water) and is surrounded by an annular non-Newtonian (Bingham-plastic) lubrication layer, which enables the mixture to flow with pressure losses that are easily overcome by common positive-displacement pumps. In summary, our model predicts the thickness of the annular lubricating layer, which controls the magnitude of the pressure losses. This is done either by collecting data on the apparent viscosity of the Theologically-active fine fraction and using an analytical equation (Bouzaiene, 1994), or is done by measuring the void content of the coarse aggregates and deducing the thickness as a function of the fine- to coarse (weight or volume) fraction ratio in the mixture for a given pipe diameter and solids concentration. Our model predictions showed good agreement with data from Duckworth et al. (1986), as shown in Fig. 2.? References Bouzaiene, R., 1994, "Hydraulic transportation in mining," Ph.D. dissertation in progress, McGill University, Dept. of Mining and Metallurgical Engineering, Montreal, P0, Canada Duckworth, A., Addie, G.R., and Maffei, J.R.,1986, "Mine waste disposal by pipeline using a fine slurry carrier," Proceedings of the 11th International Conference on Slurry Transportation, Slurry Transport Association, Washington DC. Gandhi, R.L., 1987, "Effect of rheological properties of fines fraction on slurry hydraulics," Proceedings of the 12th International Conference on Slurry Technology, New Orleans, LA.

Jan 1, 1996

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

The authors provide a discussion of the paper, ?Coal workers? pneumoconiosis prevalence disparity between australia and the united States,? a peer-reviewed paper that appeared in the technical papers section of the July 2012 issue of Mining Engineering magazine. The original authors, G.J. Joy (gjoy@cdc.gov), J.F. Colinet (jcolinet@cdc.gov) and D.D. Landen (dlanden@cdc.gov), respond.

Jan 1, 2013

By V. Rajaram

R.C. Rex, Jr. V. Rajaram's paper does not accurately reflect the status of Eastern oil shale development as it stands today. Today, there are numerous firms and research organizations pursuing development of the Eastern oil shale resource. Details of the current projects can be found in the symposium proceedings for the 1985 Eastern Oil Shale Symposium held in Lexington, KY, in November 1985. Additionally, the comparison of the Paraho and HYTORT processes is invalid because the HYTORT process design used it not an accurate representation of the HYTORT process. I will briefly address this point. It is disconcerting to see the author reference hydroretorting work conducted at the Institute of Gas Technology (IGT) (circa 1978) in the introduction, which indicates hydroretorting (the HYTORT process concept) yields of up to 250% of the Fischer Assay oil yield, and then turn around and base the remainder of the paper on the 1981 "Synthetic Fuels From Eastern Oil Shale Report," which depicts the HYTORT process as yielding only 115% of Fischer Assay. Indeed, work conducted at IGT to 1981 indicates commercial oil yields for the HYTORT process would be in the range of 200% to 210% of Fischer Assay. A more thorough literature search by the author would have yielded a 1981 publication by Schora et al., entitled "Update on the HYTORT Process" presented at the Symposium on Synthetic Fuels From Oil Shale in Nashville, TN, October 1981. This paper thoroughly discusses the shortcomings of the referenced study with respect to the HYTORT process. For the interested reader, I can also recommend a June 1984 report entitled "An Economic Comparison of Five Process Concepts for Using Eastern Oil Shale," published by Los Alomos National Laboratory (LA-10106-MS, Parkinson et al., NTIS No. DE84-015981). This study applies a realistic HYTORT design (circa 1982) and indicates that HYTORT is the most econom¬ical method of processing Eastern oil shales (about $20/bbl less than Paraho). Additionally, completion of the HYTORT feasibility study in June 1983 by Phillips Petroleum Co., Bechtel Group Inc., HYCRUDE Corp., and IGT has resulted in development of designs that will make the use of HYTORT on Eastern oil shales even more economic. HYCRUDE Corp., a second-tier subsidiary of IGT, is involved in commercialization and licensing of the HYTORT process and is active in efforts to develop the Eastern oil shale resource. As such, I am disappointed to see outdated material that has the potential for adversely affecting development of Eastern oil shale resources published in MINING ENGINEERING. I can only hope that this response will serve to mitigate any negative opinions that may have been formed. Today, activity in commercializing Eastern oil shales dominates the oil shale scene in the US and indicates a realization of the potential for these shales. Reply by V. Rajaram I appreciate the updates on the HYTORT process provided by R.C. Rex, Jr. I hope that Hycrude's work will lead to the funding of a pilot plant to demonstrate that yields of greater than 200% of Fischer Assay can be achieved in a commercial plant using eastern US oil shales.

Jan 9, 1986

By V. Rajaram

R.K. Leininger, N.R. Hasenmueller, and D.D. Carr The content of the paper by V. Rajaram does not fulfill the expectations of the title. But Rajaram submitted the article in October 1983, and he could not have foreseen the numerous developments that would occur before his paper was published more than two years later. Nevertheless, Rajaram failed to mention the interest in oil shale development in southern Indiana beginning in late 1979 and continuing through the present as a result of special financial encouragement of three oil shale projects in May and August 1984 by the Indiana Energy Development Board and the Indiana Corp. for Science and Technology. A session at the 1985 Eastern Oil Shale Symposium in Lexington, KY, Nov. 18-20, 1985, gave the current status of oil shale developments in the eastern United States. Speakers at this session reported on the three Indiana projects. First, Gary D. Aho, Cliffs Engineering Inc., spoke on a feasibility study by Cliffs Engineering and Allis Chalmers for a site-specific pilot plant using the Allis Chalmers process. The plant site is in Clark County, IN, on property of the Midwest Energy Resources Co. The project is funded by $240,908 each from the Indiana Energy Development Board/Corp. for Science and Technology (EDB/CST) and the US Department of Energy (DOE) and $120,454 from the corporate sponsors (total $602,270). Completion is scheduled for mid-1986. Next, Edwin M. Piper, Stone and Webster Engineering Corp., discussed the American Syn-Crude/Indiana Oil Shale Project. This effort followed the completion of two smaller projects funded by the Indiana EDB/ CST: "Testing of Indiana Oil Shale in a Petrosix Pilot Plant" (total funding by EDB/CST at $50,000) and "Assessment of the Petrosix Process for an Indiana Shale Oil Plant" (total funding by EDB/CST at $100,000). The status at the time of the report at the Oil Shale Symposium was that a request for an extension of time for securing nonfederal support had been submitted to the US Synfuels Corp. The proposal included building an 11-m (36-ft) diam retort in southeastern Indiana to process the New Albany Shale and to produce 366 m3 (2300 bbl) of shale oil per day by the PETROSIX process. The Indiana EDB/CST had contracted with Stone and Webster at $401,100 from EDB/CST and $245,835 from Stone and Webster for activities to advance the project in the negotiations with Synfuels Corp. At the time of the report, this project was the only eastern oil shale proposal that was still on the agenda of the Synfuels Corp. As a result of Congressional action in late December 1985, federal support from the Synfuels Corp. is no longer possible. Finally, Victor H. Carr, Eastern Shale Research Corp., described his firm's project, which is jointly supported by DOE ($227,749) and the Indiana EDB/ CST ($73,850) and is entitled "Feasibility Study to Determine Suitability of an In-Situ Process to Recover Hydrocarbons from Eastern Shale." An area in Scott County, IN, had been chosen, but not a specific 9 x 15-m (30 x 50-ft) site. One burn of a small in situ retort is contemplated as part of the project. Besides these three projects, several reports on shale research were presented. Joseph Damukaitis, American Syn-Crude Corp., reported that a pilot plant using the hydrogenation-extraction (H-E) process (described at the 1984 Eastern Oil Shale Symposium) was 94% built and would go through shakedown with oil shale but would then shift mechanical devices to process coal mine waste. Current status of research on the HYTORT process was then presented by Raymond C. Rex, Jr. Oil shale beneficiation research at the University of Alabama/Minerals Research Institute was reported by R. Bruce Tippin. Scott D. Carter discussed continued research on fluidized-bed retort¬ing of shale at the Kentucky Center for Energy Research Laboratory. Carl E. Roosmagi of DOE, Morgantown, reported on the oil shale research at the Morgantown Energy Technology Center (METC) laboratory. Henry J. Gomberg, Ann Arbor Nuclear Inc., discussed "Radiation Combined with Donor Solvents for Extraction and Up-Grading of Kerogen." Aurora M. Rubel and coauthor Eileen Davis presented results of research at the Kentucky Center for Energy Research Laboratory under the title "The Effect of Shale Particle Size on the Products from the Bench Scale Fixed Bed Steam Pyrolysis of Kentucky Sunbury Shale." Lastly, Maria Rockwell, Technical University of Nova Scotia, presented "Processing and Up-Grading of Low Grade Nova Scotia Oil Shale for Potential Use." A review of shale oil prospects by Gerald Parkinson in Chemical Engineering for Feb. 3, 1986, covers both western and eastern projects and includes a report that the US DOE is funding a few relatively small projects; most of the fiscal 1986 budget of $12 million for shale oil is for fundamental research. Projects include a $3.2 million three-year contract with Hycrude Corp. (Chicago) for development of the HYTORT process and a $1.2 million three-year contract with the University of Alabama's Mineral Resources Institute on beneficiation of eastern oil shale by froth flotation. The report incorrectly states that current projects include a total investment of $466 million in a pair of 18-month technical and economic feasibility studies for proposed projects in southern Indiana. The correct figure is $468,657 [$240,908 for the Cliffs Engineering/

Jan 10, 1986

By Y. C. Kim

M.S. Azun The article unfortunately has some serious flaws negating the usefulness of the paper. The authors claim that kriging (linear kriging) is superior to other methods such as polygon. This is not the case. The deterministic methods (referring to polygon, ID, IDS, etc.) should not be compared with the statistical methods (linear kriging, disjunctive kriging, etc.) because they differ not only in their assumptions, but also their tools used in estimation. Thus, they give different results. By comparing the results of deterministic methods and linear kriging, the authors conclude that polygon, IDS, and linear kriging give an average thickness close to the value obtained from realizations. Besides, they argue that linear kriging gives less variance than the others (Fig. 2). The first conclusion is expected, due to the well-known central limit theorem. The second is the result of the statistical properties of different estimators. Thus, the comparison presented in the paper is rather meaningless because the authors have failed to follow basic statistical procedures. The numerical results of different approaches to an estimation problem cannot be generalized. In conclusion, the paper is not a meaningful contribution, and sadly, quite erroneous. Reply by E.Y. Baafi and Y.C. Kim The two key contentions made by M.S. Azun regarding the paper are: deterministic methods should not be compared with statistical methods and, hence, the results are erroneous; and the paper does not make a meaningful contribution. The first contention is an academic one. Most practitioners in ore reserve estimation could care less whether the tool they are using falls under a deterministic or a probabilistic method, so long as it gives the desired answers. It is probably for this reason that, whenever any new tool such as linear kriging is introduced to practioners in the mining industry, they would like to see a comparison test performed between the existing and the more familiar tools with a new and "strange" tool. Only when a new tool passes such a test, the generally conservative mining community would begin to utilize the new tool to its advantage. The second contention, is a subjective one. The final judgment should be left up to the readers within the mining community. If kriging is accepted more among practitioners, partly due to the paper, then the paper makes a practical contribution to the state-of-the art in ore reserve estimation. Finally, M.S. Azun entirely missed two main points in the paper. The first is that any comparative study of kriging vs. Polygonal or IDS should be performed for local estimation and not for global estimation. In the past, kriging was frequently compared with other existing tools in its performance on global estimation. Such results were nearly identical due to the central limit theorem effect, which further prevented the acceptance of kriging by practitioners. The second point is that a single case study using an existing property, as it was frequently performed in the past, is not sufficient because results depend not only on the tool itself, but also on the nature of the mineralization.

Jan 3, 1984

By G. Johnston, P. K. Chatterjee, S. Holguin

M. Gershon The article is an excellent one, providing a basis for the conduct of the major tasks in underground mine planning and scheduling. I object to only one word. Since that word is featured in the title, it is a strong objection. The word used erroneously is optimization. There is no optimization performed in the article. By definition, an optimization is an approach that yields the best of all possible solutions. We can limit this definition to its narrowest sense, the optimization techniques of operations research such as linear programming, or broaden it to include less sophisticated search procedures that find the best mine plan or schedule. No such claim is made in the article. No optimization of any kind is performed. The major tool used is a simulation, which, in truth, is probably more appropriate for this problem than any optimization. But simulation does not optimize. It only allows for quick evaluation of many options, leading to the selection of the best plan "of those tried," not "of all possible plans." This article, of course, is not the first mining paper to make this error. It seems that the word optimization is used more to impress people than to refer to any act of optimizing. It is used in a way that implies "try to optimize"or "come close to optimize," but not to really do it. It is usually appropriate to quietly ignore this error. But when Dr. Chatterjee, who has done so much good work in true optimization projects and whose work I have come to admire, makes such an error, it is time to publicly dispute it. Having discussed this very point with him in the past, I am sure that he will agree. If he can support this position in his response, perhaps people will start to listen and we can reduce the number of false claims of optimization. This should be easy for him in this case since the approach he used, simulation, is the more appropriate one anyway.

Jan 8, 1988

By M. Gershon

The article is an excellent one, providing a basis for the conduct of the major tasks in underground mine planning and scheduling. I object to only one word. Since that word is featured in the title, it is a strong objection. The word used erroneously is optimization. There is no optimization performed in the article. By definition, an optimization is an approach that yields the best of all possible solutions. We can limit this definition to its narrowest sense, the optimization techniques of operations research such as linear programming, or broaden it to include less sophisticated search procedures that find the best mine plan or schedule. No such claim is made in the article. No optimization of any kind is performed. The major tool used is a simulation, which, in truth, is probably more appropriate for this problem than any optimization. But simulation does not optimize. It only allows for quick evaluation of many options, leading to the selection of the best plan "of those tried," not "of all possible plans." This article, of course, is not the first mining paper to make this error. It seems that the word optimization is used more to impress people than to refer to any act of optimizing. It is used in a way that implies "try to optimize" or "come close to optimize," but not to really do it. It is usually appropriate to quietly ignore this error. But when Dr. Chatterjee, who has done so much good work in true optimization projects and whose work I have come to admire, makes such an error, it is time to publicly dispute it. Having discussed this very point with him in the past, I am sure that he will agree. If he can support this position in his response, perhaps people will start to listen and we can reduce the number of false claims of optimization. This should be easy for him in this case since the approach he used, simulation, is the more appropriate one anyway.

Jan 1, 1987