Crystallization and Precipitation || Low Temperature Crystallization of Potassium Chloride using the...

Low Temperature Crystallization of Potassium Chloride using the Natural Climate of Saskatchewan: Computer Modelling of a

Pond Crystallizer M. 0. Klein*, Β. K. Sareen**, G. G. Strathdee* and D. K. Storer*

* Potash Corporation of Saskatchewan, Technical Services, Saskatoon, Canada **KS Engineering Inc., Saskatoon, Canada

ABSTRACT

A computer model was developed to investigate the use of the natural climate of Saskatchewan to further depress the terminal temperature of a conventional multi-effect crystallizer circuit effluent in an open pond crystallizer to precipitate additional potassium chloride. The thermodynamics of the pond crystallizer are discussed and economic analyses are presented.

KEYWORDS

Potassium chloride; low temperature crystallization; crystallizers; pond crystallizer; cooling pond model; heat transfer.

INTRODUCTION

A process circuit for recrystallization of potassium chloride to yield refined product consists of two main stages. The first is the thermal dissolution stage at which the brine is contacted with solid potassium chloride of low grade or size at 82-97°C. The second stage is a multistage crystallizer system in which the impregnated brine is cooled adiabatically to cause the crystallization of potassium chloride from solution. The enthalpy in the flashing vapours may be recovered in a counter current fashion in surface or direct heat exchangers as illustrated in Fig.l.

The temperature achieved in the last stage of cooling is governed by the conditions for condensation of the flashing vapours. In most Saskatchewan potash operations this is carried out using reclaim brine cooled in either open reservoirs or in cooling towers. The cooling medium lower temperature limit during the summer months is 30°C. During the colder seasons, however, the terminal temperature may be limited by air leaks into the system which become more pronounced as the difference between the atmospheric and absolute vapour pressure widens. Furthermore with larger vapour volumes to be handled, existing adiabatic equipment may pose another limitation.

CAP - C

21

22 Klein, Sareen, Strathdee and Storer

Plant 1

S t e a m ;

M- • A t m o s p h e r i c COOITTUÇ

Cooling T o w e r a n d / o r P o n d

- F r o m

Fig. 1. Schematic of conventional multiple-effect crystallizer circuit.

Nagy, L. (1983) and Wolf, J. (1987) indicated that surface cooled crystallizers may be utilized for additional cooling of adiabatic crystallizer effluent to produce a soluble grade (99%) potassium chloride with a throughput increase of 25 percent. Wolf, J. (1987) also indicated that at both start-up and steady state the low temperature surface crystallizer must be properly operated to minimize salt scaling on the heat exchanger tube surface on the slurry side. Maintaining low log mean delta T, slurry densities at 25-35 percent by crystal weight, and certain design considerations, will result in five days to four weeks operating cycles between heat exchanger washouts.

The operation of the surface cooled crystallizer may be seasonal or continuous. When reclaim brine is used for a cooling medium, the crystallizer operation is effective only during the colder seasons. With a refrigeration unit the crystallizer becomes operational over the warmer seasons as well.

An alternative for further effluent cooling is the pond crystallizer. It can only be operated on a seasonal basis since it relies totally on the local climate to depress brine temperature. With a median dry bulb temperature of 2.2°C Saskatchewan climate is suited for the pond crystallizer operation.

This paper deals with computer modelling development and application for the open pond case. Pond monitoring, control and behaviour, as well as crystal bed profile variations with climatic changes were simulated. Crystal harvesting methods and the impact of the pond system on the conventional adiabatic crystallizer circuit are discussed as well.

COOLING POND MODEL

The behaviour of solar evaporative, solar energy storage and dissipating heat ponds has been dealt with by several investigators. For the latter case, simulation work does not include ice formation. In general, the heat input eliminates the occurrence of ice (Manganaro, 1985). Evaporative ponds have been used to precipitate carnallite, potassium sulphate and sodium chloride at commercial scale. Work on potassium chloride pond crystallizers has been limited and experimental in scope.

Modelling, Control and Instrumentation 23

The simulation work covered in this paper deals with the fundamental variable governing the thermodynamic state of a pond crystallizer system. The statistical climate variables are provided in terms of dry bulb temperature, relative humidity, cloud cover, wind speed, solar radiation and precipitation as snow and rain. In addition, information on the solubility behaviour of the Na-K-Cl-P^O system and specific gravity has been correlated and provided as part of the input file. Geometrical configuration of the pond has also been selected to ensure pond bank stability. The specific input information deals with desired month of operation, base pond length, width and depth, and brine inflow. Simulation output as a function of time includes the temperature of the discharge brine, daily and monthly potassium chloride precipitate production, water loss to evaporation, etc. The simulation is useful to the pond designer to size the pond for a certain inflow rate and temperature, to the operator to predict the magnitude and profile of the precipitate which will in turn determine its harvesting frequency, and to the process controller to predict the salt concentration in the pond to avoid sodium chloride contamination, the response of the pond to climate changes and in general to achieve closer control for better productivity and product quality.

Assumptions

The thermodynamic model configuration utilized in this paper is illustrated in Fig.2 which includes the general energy and mass flows, upon which the mass and energy balance was developed. The following assumptions were made in developing

the model:

(a) The brine in the pond moves in plug flow (see Fig.3).

(b) The brine velocity remains constant throughout the sections of the pond.

(c) The brine temperature changes along the flow direction only. It remains constant at any cross-section area, i.e. the system is one dimensional.

(d) In any sub-system the temperature gradient is constant along the depth of the pond. Each sub-system moves along the length of the pond in discrete steps at one hour zones.

(e) The heat transfer between the soil mass and the salts and between the soil mass and the brine is negligible for ponds with depth greater than 2 feet (Pancharatham, 1972).

(f) The interference of flotation and other reagents in the inflow brine with the heat transfer between the surface of the brine and the atmosphere is negligible.

(g) Due to their very low concentration in the inflow brine the effect of other constituents, such as calcium and magnesium, on solubility and vapour pressure is negligible.

(h) Snow falling on to the pond surface is at the prevailing ambient temperature. The temperature of the rain water is at 4 degrees Celsius.

(i) Runoffs and snow blowing into the pond are negligible.

(j) Instantaneous climate conditions substituted with average hourly, daily and monthly values depending on the specific situation. The snow falls one hour every day. The monthly average, therefore, would amount to thirty times greater.


(k) The brine seepage into the ground is negligible.

(1) The brine entering the pond is saturated with respect to potassium and sodium chloride.

Fig. 2. Thermodynamic system of pond crystallizer. Schematic diagram.

Fig. 3. Schematic of brine plug-flow through pond.

Modelling, Control and Instrumentation

SYSTEM GOVERNING EQUATIONS

25

System Enthalpies Equations

The sum of the enthalpies entering the pond system is affected by the inflow brine, the snow and the rain water enthalpies. Each was estimated using the equations 1, 2, 2a, 3 and 3a respectively.

H, - (C w *p w * V w + C K * M K + C N A * M N A ) + Μ κ * Δ Η κ + M N A * Δ H N A (1)

where Τ Temperature C of brine C Specific heat V • Volume of water in brine in any sub-system M ss Mass concentration of solids in solution H ss Heat of solution pw = Density of water

subscript W Water Κ Potassium chloride ΝΑ - Sodium chloride Β Brine

%- [c, * ( ° - v

+

where C s - Specific heat of snow

C w ss Specific heat of water

h s , - Latent heat of snow

T A as Mean ambient air for the hour the snow fell T. Mean temperature of brine

M $» Ρ $ * A * X s

where Ρ s Density of snow

A Surface area of sub-system

M s = Mass of snow

X s Hourly snowfall

% - C w * M R * (T B-4)

A * X R

where M, - Mass of rain

(2)

(2a)

(3)

(3a)

X R - Hourly rainfall

System Heat Transfer Equations

The heat transfer between the surface of the residence brine and the surrounding ambient air consists of radiation, convection, evaporation and solar radiation. Equations 4, 5, 6, 7, 7a, 7b, 8 and 9 were used to evaluate the heat transfer rates for each mode.

Ε * Σ * Τ ^ * Α (4)


The value used is 1.4 * 10 4

Ρ = 0.81 * Ρ e (Morrison, 1965) (7a)

V B w S

InP = 24.2779 - 6238.64 (T) - 0.344 ln(T) (Wilhelm, 1976) (7b) w s

where Ρ = Water saturation pressure w S

Q_ = Ε * h * A (8)

Ε F G

QE = Heat dissipation rate due to evaporation

Q c = Heat dissipation rate due to convection (9)

The specific heats for sodium and potassium chloride used in the model were 862 and 677 J/kg Deg.C. The heats of dissolution were 66440 and 230947 J/kg respectively. (Nvylt, 1982).

Q A R = σ * T a

4 * A * (1+0.2Ν 2· 5) * (0.82-0.25 * i o("0.00126*P V B ) ) ( 5 )

where ε = Emissivity from the surface of brine = 0.97 -8 2 4

o" = Stefan-Boltzmann1 s constant 5.66 χ 10 W.m °K

Τ = Air temperature °K A

Τ β = Brine surface temperature °K Ν = Cloud cover

c

P ^ B = Saturation vapour pressure of brine.

Q A R = Rate of radiation from sky to brine surface

Q = Rate of radiation from brine surface to sky

B R J

= (1-r) * I H * (1-N2) * A (6)

where Q S R = Rate of heat energy entering the thermo-

dynamic sub-system due to solar radiation

I H = Solar insolation on horizontal surface

r = Coefficient of reflection

1-r = Coefficient of absorption

N c = Cloud cover if (1-N 2) 0.5, then (1-N 2) = 0 . 5 (assumed)

Ε = N M* U0 - 8 * (P V B-P W A) (Lakshman, 1972) (7)

where Ε = Rate of evaporation per unit area

U = Wind velocity

P V b = Saturation vapor pressure at the

temperature of brine surface

P W A = Water vapour pressure in air

N M = Coefficient of mass transfer and its value -4 -4

measured varied 0.8 * 10 to 1.66 * 10


COMPUTER SIMULATION, SAMPLE CASE AND DISCUSSION

The preceding equations were incorporated into a computer model to simulate the behaviour of the pond crystallizer over the colder months of the year. The model was run using an IBM PC/XT micro-computer. Based on the specified input request, the pond is divided into a number of sections along the brine flow. It is assumed that the pond is always a right-angled rectangle. Each section, except the last one, has a one-hour residence time. Mass and energy balance is calculated for each section in sequence. The temperature and the concentration of each section are calculated iteratively. The program assumes a certain temperature drop in a section at the end of one hour. A mean temperature is calculated. Using the average climatic values for the hour, the heat and mass balance for the section are calculated. The iterative process is repeated as long as the difference between the assumed and the calculated temperature is greater than 0.01°C Upon convergence, the concentration of the potassium chloride brine and the amount of the precipitate for the hour for the particular section is calculated. This process is repeated for all the successive sections of the pond. The process is then repeated for 24 hours followed by a further period of time equal to the residence time of the brine in the pond. Based on the calculated amount of the precipitate a crystal bed profile along the length of the pond is generated.

The computer model was applied to a 1261,5 1/min. crystallizer effluent stream at 29.7°C, saturated with respect to potassium chloride and cooled in ponds exposed to Saskatoon weather conditions. The ponds had the following sizes:

0.3 ha χ 2.3 m 0.4 ha χ 2.3 m 0.5 ha χ 2.3 m 0.6 ha χ 2.3 m 0.7 ha χ 2.3 m

Part of the summary of the computer output information is presented in Table 1. It shows the monthly potassium chloride precipitate temperatures during the months of January, February, March, October, November and December. Over the same months' duration, the amount of precipitate increases with the pond surface as the heat transfer area increases.

TABLE 1. Seasonal Monthly Production of KC1 in Ponds with Surface areas of 0.3, 0.4, 0.5, 0.6 and 0.7 hectares and 2.3 metres in depth

Pond area (ha) 0.3 0.4 0.5 0.6 0.7

January 2766.2 3476.4 4108.3 4644.4 5139.9 February 1786.5 2256.3 2679.1 3038.3 3377.0 March 1816.2 2285.7 2704.7 3051.1 3380.1 October 1123.6 1404.0 1649.8 1849.0 2037.4 November 1857.6 2298.7 2693.1 3037.4 3337.5 December 2808.3 3496.6 4096.6 4617.7 5072.4

Total (tonnes) 12158.4 15217.7 17931.7 20237.8 22344.4


The greatest crystal deposition occurs during January. This is mrinly due to the low mean dry bulb temperature at -17.9°C in comparison to that for October, November, December, February and March at ~5.0°C, -6.3°C, -13.1°C, -14.8°C and -7.5°C respectively and to a lesser extent to the relatively smaller amounts of mean monthly total precipitation as indicated in Table 2.

For the pond designer the cost of building the pond sized for certain levels of brine inflow and the amount of precipitation becomes important. When optimising one must avoid the conditions which will cause sodium chloride precipitation caused by excessive cooling due to evaporation or during mill shutdowns which stop process brine inflows. During unusual and severe subnormal temperatures precipitation of NaCl in the pond may be avoided by the addition of make-up water or unsaturated brine. This addition in the mill at the point of brine diversion towards the pond through the pipeline network will minimize crystal deposition in pipes.

TABLE 2. Mean Snowfall and Rainfall for Saskatoon

Month Snow (mm)

Rain (mm)

Precipitation Total (mm)

January 154.94 15.49 February 142.24 0.50 14.73 March 157.48 1.01 16.76 April 91.44 11.93 21.08 May 30.48 31.24 34.29 June - 59.94 59.94 July - 61.72 61.72 August - 46.22 46.22 September 15.24 32.51* 34.03 October 81.28 10.16 18.28 November 121.92 2.79 14.98 December 162.56 0.50 16.76

Data from SRC Station in Saskatoon for the period 1941 - 1970.

The temperature profile along the pond length is illustrated in Fig.4. The profile of the potassium chloride crystal bed along the length of the pond is outlined in Fig.5. As expected the deposition of the crystal is more rapid at the point of brine entry into the pond as the temperature gradient is the greatest. Flow channelling may occur at this point when the crystal bed reaches a certain height. The quality of the potassium chloride precipitate is expected to be comparable to the soluble grade. As agricultural grade, the precipitate could be mixed with other compaction feed streams or used for refined circuit feed. Continuous or intermittent harvesting may be accomplished by one of several methods including crystal reslurry, floating harvester or front-end loader when the pond is drained. Some of these are already practised in Saskatchewan in sodium sulfate crystallizer ponds.

The results of this computer simulation have shown that the output of a given crystallizer circuit can be increased by about 25 percent (based on the reduction in terminal temperature and phase data) without making significant changes to the existing equipment or plant layout. Moreover, in many cases existing equipment may be capable of processing the additional potassium chloride produced in a crystallizer pond.


SECTIONS

Fig. 4. Temperature profile along the pond length.

DEPTH <M>

SECTIONS

Fig. 5. Crystal bed profile along pond length.

Economics

The economic viability was assessed for 0.5, 0.6 and 0.7 ha χ 2.3 m ponds. The capital requirements and production cost estimates are listed in Table 3. Pond construction, polyethylene conduits, various pumps and motors and adequate temperature and flow monitoring instrumentation were the main capital cost constituents. The main production cost elements are the debt service, manpower and energy. It was assumed that the removal of KC1 precipitate would be carried out intermittently on a contractual basis. The lowest cost per tonne of potassium chloride harvested in the pond was estimated at $15.4.


Series 80, 0.22 m diameter polyethylene, pipe length to pond = 1637 m

Pond area 0.5 0.6 0.7

Polyethylene Pipe Water well Pumps and motors Instrumentation Pond Contingency (20%)

- $ 95,612.0 - 20,000.0 - 10,000.0 - 20,000.0 - 172,180.0 - 63,558.4

$ 95,612.0 20,000.0 10,000.0 20,000.0 206,611.0 70,444.6

$ 95,612.0 20,000.0 10,000.0 20,000.0 241,047.0 77,331.8

Total - $381,350.4 $422,667.6 $463,990.8

Debt @ 12% (11.816) Energy @ 4^/kWh Operators @ $30/hr (50%) KC1 removal and drying Contingency (20%)

- $ 54,072.4 6,540.0

- 65,700.0 - 130,027.0 - 51,267.8

$ 59,930.9 6,540.0

65,700.0 134,268.4 53,287.9

65,790.2 6,540.0

65,700.0 148,195.6 57,245.2

Total - $307,607.2 $319,727.2 $343,471.0

KC1 produced (tonnes) - 17,931.7 20,237.8 22,344.4

Unit cost (ί/tonne) - $ 17.2 $ 15.8 $ 15.4

CONCLUSION

A computer simulation was developed to evaluate the thermodynamic behaviour of a cooling pond used for potassium chloride precipitation from crystallizer effluent. A sample case was presented in which statistical information on the Saskatoon climate was used. The amount of potassium chloride precipitate was proportional to the pond surface area magnitude. Moreover, for equal pond surface area, KC1 production peaked during the month of January. It was found that the integration of a pond crystallizer could increase the conventional crystallizer circuit production by about 25 percent. About 35-40 percent of the low grade process heat introduced in the pond contributes to evaporation.

ACKNOWLEDGMENTS

We would like to thank the Potash Corporation of Saskatchewan for permission to publish. Special thanks are extended to the Technical Services staff.

TABLE 3. Capital and Operating Cost Estimates for the 0.5, 0.6 and 0.7 hectare Pond Crystallizer System


REFERENCES

Lakshman, G.; An Aerodynamic Formula to Compute Evaporation from Open Water Surfaces. Journal of Hydrology, March 1972.

Manganaro, J. L.; Simulation of an Evaporative Solar Salt Pond. Ind. Eng. Chem. Process Pes. Dev. 1985, 24, 1251-58.

Morrison, B.; Vapour Pressure of a Brine Tailings. The Vapour Pressure of a Mixture of Non-Volatile Salt Solutions. Saskatchewan Research Council Report November 1965.

Nagy, J.M.; Low Temperature Crystallization of Potash. Proceedings of Potash f83 (1983), Editor, R.M.McKercher.

Nyvlt, J.; Industrial Crystallization, the State of the Art. Verlag Chemie GmbH 1982.

Pancharatham, S.; Ind. Eng. Chem. Process Pes. Dev. 1972, 11, 287

Wilhelm, L.R.; Numerical Calculation of Psychrometric Properties in SI Units. Transaction of ASAE, 1976.

Wolf, J.H.; Crystallization in Surface Cooled Crystallizers. Proceedings of Industrial Symposium on Crystallization and Precipitation (1987), Editor, G.G.Strathdee.

Crystallization and Precipitation || Low Temperature Crystallization of Potassium Chloride using the...

Documents

Transcript of Crystallization and Precipitation || Low Temperature Crystallization of Potassium Chloride using the...