Environ. Sci. Technol. 1997, 31, 2534-2539
Numerical Modeling of the Temperature Distribution in a Commercial Hazardous Waste Slagging Rotary Kiln
cannot be measured due to cost, equipment configuration, or operating permit limits. A model can also provide insights into the physical processes taking place in a kiln. A secondary goal of the study was to determine whether an exit-plane gas temperature measurement is a good surrogate for bed temperature when comparing laboratory, pilot-scale, and fullscale data for the mass transfer rates and equilibrium partitioning of volatile metals in rotary kiln incinerators.
JOHN M. VERANTH, GEOFFREY D. SILCOX,* AND DAVID W. PERSHING Department of Chemical Engineering, University of Utah, Salt Lake City, Utah 84112
Physical System
The gas, wall, and bed temperatures in a hazardous waste incineration kiln were studied using a commercially available, CFD-based, reacting flow code, which included radiation heat transfer. The model was compared to field measurements made on a co-current flow, 35 MW slagging rotary kiln. Cases were run to determine the sensitivity of the predictions to changes in the model assumptions and to simulate the normal variation in combustion inputs. The model predictions of the peak bed temperature, of the axial temperature profile, and of the gas temperature at the exit-plane were consistent with the measurements at a fullscale waste incinerator during normal operation. The model and the field observations both indicate that the peak bed temperature occurs near the middle of the kiln and that the difference between the peak bed temperature and the exit-plane gas temperature depends on the inlet flows. The geometry of the transition between the kiln and the secondary combustion chamber and the fuel-to-air equivalence ratio have the greatest effect on the calculated temperature distribution. Modeling studies provide useful information such as the relationship between available measurements and the temperature at inaccessible locations inside a full-scale kiln.
Introduction A field study at a commercial co-current flow slagging hazardous waste rotary kiln (1) showed that the peak bed temperature occurs near the middle of the kiln and not at the discharge. Observations suggested that certain combustion conditions, referred to as “short flame,” resulted in both extremely high actual bed temperature and a relatively low exit-plane gas temperature measured by a radiation pyrometer. Conversely, “long flame” conditions appeared to raise the exit temperature measurement while lowering the actual peak bed temperature. The relationship between the local bed temperature and measurements made at an accessible location is important for the design and operation of incineration kilns since exit-plane sensors are commonly used for plant records and for permit compliance (2). This study was initiated to determine whether calculations based on heat transfer and fluid flow fundamentals could reproduce the field observations. A computational fluid dynamics-based (CFD-based) reacting flow model that provides reasonable agreement with available measurements can provide estimates of the temperature at conditions that * Corresponding author phone: 801-581-8820; e-mail: geoff@ tempest.che.utah.edu.
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Figure 1 shows the rotary kiln and secondary combustion chamber (SCC) that were the subject of both the modeling and field studies. Details of the facility operation and of the field temperature measurement techniques were previously reported (1). The modeling study focused on the kiln and the transition section below the SCC burners, as shown in Figure 2. Several physical features of the incinerator are especially relevant to the model formulation. Molten slag and hot, unmelted materials drop from the end of the kiln into a water-filled tank (Figure 1, item f) where they are quenched and removed by a chain conveyor. The transition between the SCC floor and the deslagger water surface forms a sump. The lower portion of the sump wall (item h) is a stainless steel plate, which is exposed to ambient conditions on the outside. The combination of the evaporation from the water surface, the steam and spray from quenching the molten slag, and the low thermal resistance of metal sump walls create a heat sink directly below the kiln discharge. Air enters the system at many points. Dampers control the air that enters under positive pressure though the burners. However, the kiln and SCC are maintained at a negative pressure and a substantial portion of the total air flow is inward leakage through the rotary seals (item g). Additional air enters through the view ports and more infiltrates through the SCC walls (item d) since there is not an air-tight shell around the SCC. Two burners (item j) are mounted in the SCC and are used to raise the temperature of the gas to the range specified in the permit. These burners create a radiation source above the kiln exit. A system heat balance, made as part of the field study, indicated that approximately 90% of the thermal energy goes to heating the major combustion products, water vapor, and excess air. About 5% goes to wall loss and 5% goes to heating the non-combustible portion of the waste into a molten slag. The batch feeding of containers and bulk solids causes short duration flare-ups, and changes in feed composition cause longer duration excursions from the average combustion conditions. Tumbling, slumping, and sliding motions are all observed in the kiln bed depending on the feed material and on the local temperature. The majority of the bed material is located near the bottom but shifted slightly toward the ascending side of the kiln. Several techniques were used to measure the temperature inside the kiln during the field study. Slag samples were collected, and the melting range, determined in a laboratory furnace, was compared to observations of slag flow in the kiln. Assemblies containing pellets with a known melting point were passed though the kiln and recovered from the deslagger discharge (3). Thermocouples were inserted through the kiln lining at four axial locations. Gas temperature at the exit was measured with both the permanent plant instruments and with thermocouples that were inserted through available ports in the SCC.
Model Formulation Models based on FLUENT have been developed by Leger et al. (4) and by Khan et al. (5). Jakway et al. (6) described
S0013-936X(96)00947-9 CCC: $14.00
1997 American Chemical Society
FIGURE 1. Incineration system cross section: a, front wall multi-fuel burner; b, stationary front wall; c, refractory lined rotary kiln; d, SCC refractory wall; e, hot duct to gas cleaning; f, wet deslagger; g, kiln end seal; h, sump wall, metal shirt; i, air inlet ducts; j, SCC burners; k, view port and test access; l, air-atomized fuel and liquid waste spray lances; m, burner tile; n, bluff body flame holder; and o, solids feed chute.
FIGURE 2. Computational grid. Nodes are at the intersection of the lines, and inactive wall nodes are not shown. For this study, the bed temperature was defined as the wall temperature along the line of nodes marked X. improvements to Leger’s model that included radiation heat transfer, a more accurate geometry, and a better fitting grid. These three studies emphasized the gas velocity field and gas temperature results, not wall and bed temperatures. Banff is a commercially available CFD-based reacting flow code originally developed to study pulverized coal combustion (7). Several texts describe the fundamentals for numerically solving the coupled non-linear equations for fluid flow (8), for radiation heat transfer (9), and for combustion (10) as they are applied in Banff. Descriptions of earlier versions of the three-dimensional code used in this study (11, 12), of the development of the radiation submodel (13, 14), and of using the code as a design tool (15) are available. Banff solves the continuity and Navier-Stokes equations in an Eulerian framework using the SIMPLERC algorithm and the k- turbulence model. The gas phase chemistry is determined assuming local equilibrium based on the mixture
fraction of two independent reactant streams. Radiation heat transfer calculations are performed using the S-4 approximation of the discrete-ordinates method (16). User Inputs. This study was conducted with the userspecified inputs and submodel options available in Banff, and no custom programming was done. Spark (17), which has a graphical user interface, was used for input of the system geometry. Interactive visualization of the model output was done using Fieldview (18). The active nodes of the 15 000 node grid (40 × 25 × 15) are shown in Figure 2. Since the bed solids remain near the kiln bottom, this study used the steady-state wall temperature along the indicated line of nodes as the surrogate for the bed temperature. The use of a uniform Cartesian grid with an irregular shape resulted in many inactive nodes. Non-uniform Cartesian grids are an option in Banff but were not used in this study. Prior experience indicated that adding a fictitious chimney beyond the furnace volume of interest avoids convergence problems due to recirculation at the exit-plane. The mass flow rate and reactant properties are specified for the primary and secondary inlets. The primary inlet was used for the front wall burner. A secondary inlet was used to represent the moisture released from the solids feed and the air flow through the solids feed chute and through the front wall seals. Another secondary inlet was used to represent the evaporation from the wet deslagger and the air entering through the discharge end seals. Banff determines the gasphase composition from the mixture fraction of two reactants, which are typically multicomponent mixtures (e.g., air). Reactant 1 was a mixture of air and methane, and reactant 2 was a mixture of air and water vapor. Reactant 1 was used to represent the air and fuel entering though the primary inlet. Reactant 2 was used for the flows through both secondary inlets. This assignment of variables allowed simulating the effect of changing the split of air flow between the feed and discharge ends of the kiln and allowed simulating
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the effect of a high moisture and high ash feed. This choice of variables also introduced computational artifacts. The reaction model is based on local equilibrium not on kinetics, so Banff calculated an artificially high temperature for the premixed fuel and air at the primary inlet. Also, since reactant 2 contained both water and air, the leakage through the kiln seals, the release of steam from the bed, and steam from the deslagger were artificially coupled. These were not serious limitations for modeling the relationship between the kiln bed and exit gas temperatures, which was the emphasis of this study.
Results of Numerical Experiments Initial cases were run to determine what geometrical features, inlet flows, and transfer processes must be included in the computational model to produce realistic simulations of the kiln temperature. This was followed by a series of cases that simulated the normal range of operating conditions in a commercial incinerator. The numerical experiments were conducted using two-level factorial designs (19), which provided sufficient data to measure the single-variable effects and to screen for interactions between variables. The differences between cases were quantified by comparing the peak temperature along the line of wall nodes that was used to represent bed temperature, the axial location of this peak temperature, and the difference between the peak bed temperature and the gas temperature at the node corresponding to a physical thermocouple used during the field study. Effect of Model Design. The maximum bed temperature was observed near the middle of the kiln in both the field study and in all computational cases that included the sump geometry and the sump inlet flow. Omission of the sump shifted the peak bed temperature to the discharge end. The model indicated that the cold region formed by the sump and wet deslagger is the cause of the observed bed temperature decrease near the kiln discharge. The incinerator used for this study and the site studied in the previously cited kiln modeling papers (6) both have a sump below the kiln discharge. A sump at the kiln discharge was included in the modeling study by Leger (4) but was not included by Khan or Jakway (5, 6). The sump was included in all subsequent cases of this study. The kiln operators adjust the temperature distribution in the kiln by manipulating the fuel and air flows. The short and long flame conditions achieved by the operators were represented in the model by a flame mixing variable that changed the distribution of the inlet air. The total air flow input for a case was calculated based on the desired thermal input and the equivalence ratio, but both the amount of air premixed with the fuel in reactant 1 and the split of secondary air between the front wall and the sump were changed to represent the two levels of the mixing variable. This flame mixing variable changed the shape of the gas temperature and composition contours. Flame mixing was retained as an input variable in subsequent cases even though the difference between the two model input levels was less than the full range of apparent flame length, from a compact ball near the front wall to fire extending beyond the kiln discharge, that was visually observed in the field study. Including water vapor in reactant 2 reduced the adiabatic flame temperature and lowered the peak bed temperature. Water vapor was an input variable in subsequent cases. A kiln bed flame was simulated by adding 20% of reactant 1 through inlet nodes located along the first one-third of the kiln bottom centerline. This simulated bed flame had little effect on the bed temperature distribution and was omitted from all subsequent cases. Including convection heat transfer to the walls had a negligible effect on the results. Changing from adiabatic walls to walls with a realistic value for thermal resistance reduced
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TABLE 1. Combinations of Combustion Inputs Used To Simulate Normal Operating Variation run
thermal input, q (MW)
flame mixing, f
equivalence ratio, e
water, w (kg/s)
qew q qfe qfw e w few f
23.4 23.4 23.4 23.4 14.7 14.7 14.7 14.7
long long short short long long short short
0.7 0.5 0.7 0.5 0.7 0.5 0.7 0.5
0.38 0 0 0.38 0 0.38 0.38 0
FIGURE 3. Peak bed temperature. The peak bed temperature, predicted from cases using reasonable combinations of operating inputs, is consistent with the range of peak bed temperature estimated from field measurements taken under varying operating conditions. Test pellets: Lower and upper bound on the peak temperature reached inside a metal pipe. Data from 1 day with long flame (day 2) and 2 days with short flame (days 3 and 4). Slag melting: Bars show the range of initial deformation (id) and fluid point (f) temperature measured using seven samples collected over 5 days. Model cases: Maximum temperature along the line of wall nodes indicated in Figure 2. Table 1 lists the input variables for the eight cases. Cases w and qew were run on grids with two, four, and six times (qew only) the nodes of the base model shown in Figure 2. the peak bed temperature but had little effect on the bed temperature distribution. Wall convection and finite wall resistance were included in all subsequent cases since they are physically present and these submodels impose a small computational burden. The radiation from the gas and walls above the SCC burners was simulated by constraining the walls of the fictitious exit chimney to be at 1420 K. Replacing this specified wall temperature with adiabatic walls had little effect since the gas temperature in the SCC was close to 1400 K. The specified wall temperature for the exit transition was retained in all subsequent cases. Effect of Operating Variation. Normal operation of a commercial hazardous waste kiln involves batch feeding of multiple streams of highly variable wastes. Since the field data was collected under normal operation, a series of eight cases was run using combinations of combustion inputs that spanned a reasonable range of inlet flow rates and compositions. Table 1 lists the combinations of thermal input, equivalence ratio, flame mixing, and water that were used for each case. Each case was named using the initials of the variables that were at the plus condition.
FIGURE 4. Axial temperature profile. The model predictions for the wall temperature at the gas-wall interface (squares showing cases and dashed line showing average of the cases) are higher than the measurements at the inside face of the brick lining (mean and range bars). The agreement is improved when the model includes the temperature gradient in a slag layer with constant thickness (solid line). Field data are the overall mean and the range of daily means obtained over 6 days that included both “long flame” and “short flame” operating conditions. The model levels for thermal input were 14.7 and 23.4 MW as compared to hourly averages of 15-26 MW reported for the kiln during the facility trial burn. The model exit oxygen levels were 5.65 and 9.58% as compared to a mean of 7.7% and a standard deviation of 1.5% measured at the SCC exit. The high water flow was based on a moist soil as the kiln bulk waste feed plus the measured deslagger makeup flow. Figure 3 compares the pellet assembly and slag melting point estimates of the peak bed temperature from the field study with the peak bed temperature from the model. The calculated range of peak bed temperatures is consistent with the range of peak bed temperature estimated by phase-change observations made under varying operating conditions. The operators were requested to produce a long flame on days 1 and 2 and a short flame on days 3 and 4. No pellet assemblies were recovered on day 1. The peak temperature was bracketed by the rating of the last melted pellet and the first unmelted pellet. On the days when all pellets melted, including the 1644 K pellet, the upper bound estimate of 1700 K was based on the unmelted carbon steel pipe and stainless steel spacers. Since slag is a mixture, its melting behavior in a laboratory furnace is described by the temperature range from initial deformation to a fully fluid condition. Observation of flowing slag in the kiln on all test days indicated that the bed temperature along part of the kiln length was above the slag fluid point. The range shown for the initial deformation and fluid condition temperatures by the bars in Figure 3 is the variation between samples due to the changing composition of the non-combustible portion of the waste feed. Figure 4 compares the model results for the axial bed temperature profile to field measurements made with thermocouples that were inserted through kiln lining. Banff calculates the temperature of the gas-wall interface, but the
FIGURE 5. Kiln exit gas temperature. The exit gas temperatures predicted from cases using reasonable combinations of operating inputs overlap the range of exit gas temperature measured with test thermocouples installed through view ports in the secondary combustion chamber (item k in Figure 1). Data are the average and range (edited for noise) during a single 4-h period of normal commercial operation. By request, the operators adjusted flame length once during this testing period. thermocouples were inserted into the lining brick and were covered by unknown and variable thicknesses of frozen and flowing slag. A 1.7 K/mm gradient across a 0.1 m layer of slag was assumed to include the difference between the inside surface temperature and the brick face temperature in the model. The solid line on Figure 4 shows that the average of the eight model cases agrees with the range of field measurements when the temperature gradient in the slag layer is included in the model. Grid Sensitivity. The effect of changing the grid was studied by running cases qew and w on uniform grids with 30 000 and 60 000 nodes (referred to as 2× and 4×). Case qew was also run on a 90 000 node grid (6×). As shown in Figure 3, the change in peak bed temperature between different grids was less than the change when the fuel and air model inputs were varied over the operating range. Knowledge of actual field conditions and the normal plant operating variation, not numerical effects, limits the accuracy of current model predictions. Less than 8 h was required to converge each case on an Silicon Graphics Indigo 2 Extreme workstation when using the 15 000 node grid shown in Figure 2. This grid provided sufficient detail to predict the general shape of the temperature distribution observed in the field and was used for all other phases of this study. Gas Temperature and Flow. The gas temperatures predicted in this modeling study are compared to field thermocouple data in Figure 5. The field data are the mean and range for test thermocouples that were mounted 0.6 m inside the SCC ports indicated by Figure 1, item k. The flame pattern was adjusted during the data period so the temperature range includes both short and long flame conditions as practiced by the operators. The model predictions overlap the range of the field data. The difference between the model and the measurements for the lower side wall location may be due to the inability of the coarse grid to accurately represent an area of steep temperature gradients.
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FIGURE 6. Predicted difference between peak bed temperature and an exit-plane gas temperature measurement. Model results confirm that changing the fuel and air flows in the kiln can increase the actual peak bed temperature and also increase the difference between the bed temperature and the measured gas temperature. Exit temperature was evaluated at the node corresponding to the test thermocouple at the upper side wall port.
and a concurrent study by Mehrotra and Silcox include a one-dimensional model of heating of the solids as they move through a kiln. Predictions are also affected by the simplified representation of inlet conditions such as using a single secondary inlet to represent the distributed air flow through the seals at each end of the kiln. The sump at the bottom of the transition between the kiln and the secondary combustion chamber affects gas flow and radiation heat transfer. Omission of the sump from the model for this facility led to predictions of the temperature profile that did not match the field data. There are many practical incinerator design and performance evaluation problems for which the current model can provide useful estimates of bed, wall, and gas temperatures. Many refinements to the model could be made within the current capabilities of Banff, but the complexity of the simulation must be balanced against the accuracy of the input data and the level of detail needed to answer the engineering questions that are within the project scope.
Acknowledgments The gas temperature contours and the flow vectors calculated by Banff were similar to those reported by Jakway using a model based on FLUENT (6). Both studies show a flow of lower temperature gas along the bottom of the kiln at the ends. Both models predict a hot gas flow near the top, but this study showed a more asymmetrical temperature pattern and a more defined jet of hot combustion products at the kiln exit plane. Predicted Difference between Bed and Gas Temperature. Figure 6 shows the model predictions for the difference between the peak bed temperature and the gas temperature at the node closest to the upper side wall thermocouple location. The four cases with low equivalence ratio have a small difference between the peak bed temperature and the gas temperature. The four cases with high equivalence ratio have a higher bed temperature but also have a larger difference between the bed and the gas temperatures. The model supports the field evidence that certain combustion conditions result in a high bed temperature without a proportional increase in the gas temperature measured at the kiln exit plane. Comparison of the Model to Field Measurements. General trends can be observed by examining the data points in Figures 3 and 4, which are labeled with the case names. Equivalence ratio (variable e) was found to have the greatest effect on the temperature distribution. At constant equivalence ratio, the total thermal input (q) had little effect on bed temperature. These results are consistent with the overall system heat balance, which shows that most of the energy goes to heating the gas. The effect of water vapor (w) in the inlet flows was less than the effect of changing the equivalence ratio, and the flame mixing variable (f) had the least effect. Available data is insufficient to determine whether the changes observed in the field study between long flame and short flame conditions were due primarily to changes in the equivalence ratio inside the kiln or whether mixing patterns were equally important but are not accurately simulated in the current model. Overall agreement between the model predictions and the field data is considered good, considering the many simplifying assumptions in the current model. A thermocouple more than 25 mm below the rotating surface will approach a constant temperature since the kiln rotation period of 3-4 min is less than the characteristic time for transient heating. The current model calculates the steadystate temperature for a stationary cylinder. It excludes regenerative heat transfer due to wall rotation, heat transfer by the axially-moving solids and slag, and temperature variation within the sliding or slumping bed. The heating of bed solids and the evaporation of water from the bed were not included in this study; however, a previous paper (20)
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Assistance in the modeling was received from P. J. Smith of the University of Utah and M. J. Bockelie of Reaction Engineering International. Financial support for this work was provided by the Advanced Combustion Engineering Research Center. Funds for this center are received from the National Science Foundation, the State of Utah, 25 industrial participants, and the U.S. Department of Energy.
Supporting Information Available Three tables comparing the recent hazardous waste kiln modeling studies to our model; detailing the dimensions, material properties, and inlet flow rate used; and describing the cases that were used to evaluate alternative model inputs and two figures showing the model predictions for circumferential temperature variation on a stationary wall and the gas temperature contours for one case (8 pp) will appear following these pages in the microfilm edition of this volume of the journal. Photocopies of the Supporting Information from this paper or microfiche (105 × 148 mm, 24× reduction, negatives) may be outlined from Microforms Office, American Chemical Society, 1155 16th St. NW, Washington, DC 20036. Full bibliographic citation (journal, title of article, names of authors, inclusive pagination, volume number, and issue number) and prepayment, check or money order for $19.50 for photocopy ($21.50 foreign) or $12.00 for microfiche ($13.00 foreign), are required. Canadian residents should add 7% GST. Supporting Information is also available via the World Wide Web at URL http://www.chemcenter.org. Users should select Electronic Publications and then Environmental Science and Technology under Electronic Editions. Detailed instructions for using this service, along with a description of the file formats, are available at this site. To download the Supporting Information, enter the journal subscription number from your mailing label. For additional information on electronic access, send electronic mail to
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Literature Cited (1) Veranth, J. M.; Gao, D.; Silcox, G. D. Environ. Sci. Technol. 1996, 30 (10), 3053-3060. (2) Monsanto Research Corp. Engineering Handbook for Hazardous Waste Incineration; Vol. SW-889 PB81-248163; U.S. Environmental Protection Agency, Office of Research and Development: Washington, DC, 1981. (3) Veranth, J. M.; Silcox, G. D.; Pershing, D. W. Bed Temperature in Slagging Hazardous Waste Rotary Kilns: Field and Computational Investigations. In Proceedings of the International Conference on Incineration and Thermal Treatment Technologies; University of California: Irvine, CA, 1997. (4) Leger, C. B.; Cundy; V. A.; Sterling, A. M. Environ. Sci. Technol. 1993, 27 (4), 677-690.
(5) Khan, J. A.; Pal, D.; Morse, J. S. Hazard. Waste Hazard. Mater. 1993, 10 (1), 81-95. (6) Jakway, A. L.; Sterling; A. M.; Cundy, V. A.; Cook, C. A. Environ. Sci. Technol. 1996, 30 (5), 1699-1712. (7) Reaction Engineering International. Theoretical Overview of REI Simulation Software; Reaction Engineering International: Salt Lake City, UT 1994. (8) Patankar, S. V. Numerical Heat Transfer and Fluid Flow; Hemisphere Publishing Co.: Bristol, PA, 1980. (9) Modest, M. F. Radiative Heat Transfer; McGraw-Hill: New York, 1993; Chapter 15, The Method of Discrete Ordinates. (10) Smoot, L. D.; Smith, P. J. Coal Combustion and Gasification; Plenum Press: New York, 1985. (11) Hill, S. C.; Smoot, L. D. Energy Fuels 1993, 7, 874-883. (12) Sikorski, K.; Ma, K.-L.; Smith, P. J.; Adams, B. R. Energy Fuels 1993, 7, 902-905. (13) Jamaluddin, A. S.; Smith, P. J. Combust. Sci. Technol. 1988, 59, 321-340. (14) Adams, B. R.; Smith, P. J. Combust. Sci. Technol. 1995, 109, 121140.
(15) Smith, P. J.; Sowa, W. A.; Hedman, P. O. Combust. Flame 1990, 79, 111-121. (16) Fiveland, W. A. ASME J. Heat Transfer 1984, 106, 699-706. (17) ACERC. Spark Users Manual; Combustion Computations Laboratory, Brigham Young University: Provo, UT, 1994. (18) Fieldview. Fieldview User’s Manual; Intelligent Light: Lyndhurst, NJ, 1994. (19) Box, G. E. P.; Hunter, W. G.; Hunter, S. J. Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building; John Wiley & Sons: New York, 1978. (20) Silcox, G. D.; Pershing, D. W. J. Air Waste Manage. Assoc. 1990, 40 (3), 337-344.
Received for review November 8, 1996. Revised manuscript received April 10, 1997. Accepted May 12, 1997.X ES960947U X
Abstract published in Advance ACS Abstracts, July 1, 1997.
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