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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

By M. Lonoff

G. Campbell The paper by M. Lonoff looks at the importance of byproduct prices on copper production. The paper develops several interesting points on this topic, but there are some points in the theoretical discussion that could use further development. A couple of these theoretical topics will be considered here using the paper's framework of assumptions without concern about how realistic the assumptions are for the copper industry. Lonoff's theoretical model is based on a static, homogenous world where all copper/byproduct deposits are identical, and these deposits are the main source of these metals. Due to the importance of the byproducts to the production decision, the term coproducts will be substituted for the term byproducts to reflect more accurately this condition. The conclusion is drawn that a rise in coproduct prices necessitates a decrease in copper prices because copper production is increased as a consequence of increased coproduct production. The observation that real world behavior does not always follow this pattern is dismissed as "speculation." However, it can be easily shown that within this simple framework market forces might create the observed behavior. The key question to be answered is what causes coproduct prices to rise. Three possible cases will be used as illustrations. The first case is the one implicity assumed by Lonoff. Here, the demand for coproducts increases at all prices (an outward parallel shift of the demand curve) with the demand for copper remaining constant. As reported in the paper, the results are higher coproduct prices, an increase in coproduct production, and lower copper prices due to the resulting increase in copper production. The second case is when the supply of coproducts are constrained-leading to higher market prices. Copper production, as required by the simple model, is also reduced which Reply by M. Lonoff Campbell's comments give me an opportunity to clarify a few points in "Copper and Its Byproducts." That paper examined the affect of byproducts on the copper market and considered the relative riskiness of multi-metal deposits from an investment standpoint. That brief note made no attempt to be exhaustive. Nevertheless, Campbell's comments miss the point of the paper and necessitate a response. My "theoretical model" was static and I freely conceded after introducing the assumption of identical deposits that "none of the assumptions hold." These simplifying assumptions allowed me to bound the possible effects of higher byproduct prices on the copper price by assuming identical deposits and computing average price effects. I took great pains to subsequently explain that since deposits are not identical the identity of the marginal deposit might change due to byproduct price changes. In this case, average price affects will overstate the affect of byproducts on copper prices. According to Campbell, I dismiss as speculation any "real world behavior that does not always follow this pattern" (of metals prices moving in opposite directions). In the byproducts paper I noted that gold, copper, and silver price movements often parallel each other on an intra-day or day-to-day basis. Such movements are largely due to market anticipation of or reaction to changes in interest rates that affect carrying costs of metals stocks. Other movements may be due to anticipated changes in available supply or physical requirements. I loosely grouped these effects as speculative. To distinguish this statement from the main thrust of the paper, I contined "In the long run if gold and silver prices remain high the equilibrium copper price will be lower." The paper set out long run equilibrium conditions rather than attempting to explain price movements on a daily basis or on a year-to-year basis.

Jan 11, 1983

By M. G. Ayat, B. C. Scott

J. Dasher Having an interest in coal slurry pipelines from a decade of arguments with Ed Wasp and crew at Bechtel about pumping thicker slurries slower, I immediately read this article and found nothing in it pertinant to the title. Ayat and Scott pumped five unidentified coals at 9% solids (50%-60% is the area of interest) in a 25-mm (1-in.) pipe around two square elbows through a 76-mm (3-in.) cyclone for up to 60 minutes and sized a large number of samples of unstated size on an unidentified wet screening device. They did not measure power consumption, discharge pressure, flow rate, or give pump tip speed or impeller diameter. They siad the cyclone had a "high" pressure drop (unmeasured) and did much of the degradation (measured) but more or less per unit of energy expended? Hargrove was not measured, so there are no data as to whether it would correlate with degradation. The authors conclude, with no attempt, correlation is "hard to establish." Please experiment before concluding. I am at a loss to know what "increasingly smaller size" means, much less what theory says such particles take "exponentially larger quantities of energy," which the authors neglected to measure. If such experiments without pertinent data or justified conclusions must be published, please attach a pertinant title. reply by M. G. Ayat The first and the last criticism of this paper is that the work is not pertinent to the title. Anybody who reads this article will immediately realize that the work describes the breakage of coal particles to finer sizes in coal slurry pipes and pumps. If this is so, why not title the work "Degradation process in coal slurry pipelines"? What could be more pertinent to this title than the investigation concerning the degradation phenomenon of coal particles in a pipe carrying a coal slurry? Mr. Dasher complains that he does not understand the meaning of the term "increasingly smaller size." The first sentence of this article defines the degradation process as "the breakage of coal particles to increasingly finer sizes." The term "increasingly finer sizes" here means successive breakage of a fine particle to finer and finer sizes. According to Hukki (Hukki, 1975), the probability of breakage is high for large particles and rapidly diminished for fine sizes. We apologize for being brief about some of these definitions. The degradation process, breakage of particles to increasingly finer sizes, is so widespread in the mineral industry that we did not feel it necessary to bore the reader with lengthy definitions of some simple terms. Mr. Dasher states that the coals examined and their original size consist are unidentified. Please look at Table I and Table 2 in the paper again where you will find the original size consist of the coals examined and their full specifications. We only named the coals A, B, C, D, and E to avoid identifying the coal seams that were more susceptible to degradation. Not identifying the name of the wet screening device used in this work has also been criticized. In our opinion, wet screening operation is such a routine and standard procedure that naming the device by which the screening is performed would serve no purpose but to promote a sales approach. This was not our intention. We did not conclude that the correlation between the degradation process and Hardgrove Grindability Index is hard to establish as Mr. Dasher writes in his letter. We stated, not concluded, that "It is reasonable to assume that some relationship between the extent of degradation and its physical properties, such as Hardgrove Grindability Index, does exist. However, any definite correlation is difficult to establish." This statement is based on other researchers work, which are clearly referenced in the article. The conclusions of this paper were based solely on the findings of the experimental work. As for the theory of comminution that Mr. Dasher asks, we would like to refer him to some basic comminution books and articles where various theories are clearly described. For example, Hukki (Hukki, R.T.,"The Principles of Comminution; An Analytical Summary," Eng. Min. 176, 106, 1975) suggests that the relationship between energy and particle size is a composite form of three laws (Bond's law, Kick's law, and Rittinger's law). A comprehensive analysis of coal breakage processes is also performed by Broadbent and Callcott (S.R. Broadbent, and T.G. Callcott, "Coal Breakage Processes, I. - A New Analysis of Coal Breakage Processes;" and "Coal Breakage Processes, II. - A Matrix Representation of Breakage," Journal of the Institute of Fuel, pp. 524-539, December 1956). These and many other relevant publications explain the relationship between the particle size and energy much better that what can be said in this short reply. We will, however, agree with Mr. Dasher on one particular point. We, too, believe that if the investigation concerning the degradation process in coal slurry pipeline were to be pursued further, one could choose to determine one or more of the variables available in the process, such as discharge pressure, power consumption, percent solid, pipe diameter, etc.

Jan 1, 1989

By M. G. Ayat, B. C. Scott

H. P. Ferri I refer to the article "Degradation Process in Coal Slurry Pipelines" by M.G. Ayat and B.C. Scott in the September 1988 issue of Mining Engineering. I would like to congratulate Dr. Ayat and his colleague on a very interesting and valuable piece of work. This article is an excellent one, describing a real phenomenon that has been ignored for so long. I do, however, have an objection. The article fails to address the degradation process when coal is processed or transported in other ways than slurry form, particularly those employed in this work. Could, for example, screening (wet or dry) have contributed to the extent of degradation? Perhaps scanning electron micrographs of the samples examined and after screening would have helped to clarify this. I would like to point out that degradation is also observed in pneumatic conveying systems, mechanical conveying, and other means of transportations employed by the mineral industry. Reply by M. G. Ayat We gratefully acknowledge Dr. Fern's comments on the subject paper. As he so rightly points out, the degradation process is a real problem, not only in coal slurry pipelines, but also in many handling and processing equipment employed by the coal and mineral industry. Scanning Electron Microscopic examination of samples may offer very little information about the extent of degradation for several reasons. One is that preparing a representative sample that has undergone degradation will be extremely difficult if not impossible. This problem is exacerbated by the fact that SEM requires only very small amounts of material for testing. Secondly, there is a sample preparation step involved in the SEM examination and, as such, it would be very difficult to associate the extent of degradation to either sample preparation or handling and processing operations. Finally, it is probably worth mentioning that degradation is a multi-faceted phenomenon involving many natural and man-made factors. The logical approach to this problem would, therefore, seem to be a "one-step-at-a-time" approach.

Jan 2, 1989

By P. L. Webster, S. D. Thompson

Sevim and Wang (1988a) have presented a model for designing haulage systems in underground coal mines. The authors contend that their model uses a heuristic algorithm to optimize various haulage system parameters. In reality, it would be nearly impossible to optimize a haulage system, because mining plans are uncertain and often change with respect to time. Therefore, haulage system design poses both a stochastic and a dynamic design problem, and its optimization appears to be well beyond the scope of heuristic algorithms. In regard to the authors' design model and its practical significance, a number of additional issues warrant further discussion and clarification. These issues include: l) their model's alleged advantage over simulation models, 2) the correctness of their belt network design, 3) the correctness of their bunker design, 4) the necessity of their proposed bunker clearance policies, 5) the correctness of their shaft-bottom bin design, and 6) the

Jan 1, 1991

Dunn has written an excellent paper providing a wealth of advice on what is often the most costly consumable in the mineral processing plant. As he pointed out, grinding media selection and quality control can play a major role in successful plant operation. Owing to the economic importance of this topic, there are some important factors related to media sizing that I believe merit further comment. Dunn made reference to a slightly simplified version of the Azzaroni (1981) equation and pointed out its successful use for the Henderson SAG and Climax ball mills.

Jan 1, 1991

By P. Malozemoff

Discussion by P. Malozemoff I have no objection to using mathematics in the value appraisal of properties. The factor that is not emphasized in the paper is that very few important properties have a lifetime that reflects the initial ore reserves of the property divided by the rate of production adopted. In the majority of cases, major properties mine out several times the initial reserves. How much more will be mined out is not known, and only exceptionally gifted geologists can predict that additional reserves will be found. There is the further factor of metals price, which, over the long term, is not predictable. Another factor vitiating making calculations on initially established ore reserves is the speculative nature of exploration success. In my judgment, the life of a property, in addition to an established ore reserve, should include ample time for exploration to find additional reserves. The likelihood of additional reserves is based on the geological promise of the general area where the mine is established. This is especially important because of various risk factors associated with small orebodies, the economic life of which is about five to seven years. In underground mines, it is not economic to develop reserves beyond a certain depth, so the life of initially established reserves must be limited. In these cases, it is especially important to have a good geological understanding of the orebody and its continuity. To accommodate these concepts and present proof of economic soundness for a mining enterprise, a mathematical analysis should yield a life long enough to allow exploration and the development of additional reserves that would ensure a longer mine life and a more profitable result.

Jan 1, 1994

By G. Le Bel

Discussion by G. Le Bel The paper proposes three methods to determine optimum lifetime of a mining project 1. The conclusion is that the three methods arrive at the same optimum production rate (by coincidence). It is also stated that: "The stochastic and option pricing models, in addition to providing a more realistic optimum mine life than the traditional NPV (net present value) calculation, showed that the example project has the potential for substantially higher return. By explicitly considering a project's potential risks, the stochastic or option pricing techniques can more accurately describe its probable investment performance." This discussion is intended to demonstrate that: •It is no coincidence that the three methods arrive at the same optimum production rate. • The stochastic and option pricing models do not provide a more realistic optimum mine life than the traditional NPV calculation. •The potential for a substantially higher return is misrepresented. First, a review of investment decision theory in mining is needed. Net present value is the preferred performance measure because of the flexibility offered when comparing various alternatives. However, it presents the following disadvantages: • The discount rate selection is not straightforward. • The NPV obtained represents a deterministic characterization of the variables included in the cash flow calculations, i.e. a single-point estimate. Discount rate selection The opportunity cost of capital represents the rate of return that would be obtained if the capital was instead invested in other opportunities considered to exist. Such opportunities must be bypassed if the available capital is invested in the project studied 2. If these other opportunities carry risk similar to the project under analysis (for example, if they are other mining projects), there is no need to add incremental [ ] risk factors. On the other hand, if these opportunities are represented by the acquisition of government bonds yielding 7%, a risk premium factor must be included. The types of risks associated with a mining venture are shown in Table 1. Together they represent the "business risk" of being a mining company. The individual project risk is important to investors if it differs substantially from the business risk of the company and that of the other investments in mining ventures that we must pass up to invest in this particular project. A risk premium or discount would then be required. This can be illustrated by the following example. Consider that a company has two investment alternatives: one is the Cavender hypothetical project located in Nevada, and the other is the same project located in a civil war zone of central Europe. The second project requires a risk premium factor on the discount rate. Conversely, a project showing highly uncertain returns that are negatively correlated with the returns of the firm's other assets may decrease the company's corporate risk. Deterministic character of NPV calculation The cash flows used in NPV calculations are obtained from a set of variables. These variables are estimated using one parameter obtained from the engineering studies. Each parameter is thus a single value that is often termed a "realistic" or "best estimate" as opposed to "optimistic" or "pessimistic." However, considering that each variable can assume a range of values between the

Jan 1, 1994