Designing a lactose crystallization process based on dynamic metastable limit

Journal of Food Engineering 111 (2012) 642–654

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Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng

Designing a lactose crystallization process based on dynamic metastable limit Shin Yee Wong a, Rajesh K. Bund b, Robin K. Connelly a,b,1, Richard W. Hartel a,b,⇑ a b

Department of Biological Systems Engineering, University of Wisconsin, Madison, 460 Henry Mall, Madison, WI 53706, United States Department of Food Science, University of Wisconsin, Madison, 1605 Linden Drive, Madison, WI 53706, United States

a r t i c l e

i n f o

Article history: Received 22 January 2012 Received in revised form 27 February 2012 Accepted 1 March 2012 Available online 20 March 2012 Keywords: Lactose Cooling crystallization Metastable zone Computational fluid dynamics Secondary nucleation Encrustation

a b s t r a c t In the dairy industry, lactose crystallization during refining typically generates a large number of fines (<100 lm), which greatly reduces the efficiency of downstream processes. To overcome this problem, a strategy to minimize fines production was developed. On lab scale units, lactose crystals were produced from three crystallizers (draft-tube baffled, anchor and paddle) operated with three cooling profiles (at different region inside metastable zone (MSZ)). Computational fluid dynamics was used to simulate the flow profile. Among all combinations investigated, anchor crystallizer (lowest shear) operated at slow cooling rate (in upper MSZ) produces the largest crystals with minimal fines. Then, the design strategy was applied in industrial scale crystallizer. The 13 h cooling profile created for operation in the medium MSZ region successfully produced crystals with 28% less fines than the typical process. Therefore, depending on the crystallizer design and operational region (in MSZ), production of fines can be minimized. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction Lactose is produced from whey permeates obtained after the production of cheese and/or whey proteins. The three main steps in lactose production are concentration, crystallization and separation. The concentration process involves the evaporation of water in whey permeate to increase lactose concentration. Concentrated whey permeate has about 65–70% total solids, with about 80% of the total solids as lactose. The mixture is then cooled during the crystallization process where the lactose is separated as a-lactose monohydrate crystal. Crude/food grade lactose is obtained after two stages of centrifugation, and final drying. Pharmaceutical grade lactose is produced by a subsequent refining process, which includes a series of washing, evaporation, drying and centrifugation steps to remove trace impurities. Among all processing steps, crystallization is the most important separation step, but the crystallization process in the dairy industry is far from optimized. The filling of the tank takes about 6 h, followed by gradual cooling and crystallization that lasts for 14–18 h, which means the crystallization process lasts for 20– 24 h (Shi et al., 2006). The process is usually carried out in a large Abbreviations: MSZ, metastable zone; ML, metastable limit; MSZW, metastable zone width; CFD, computational fluid dynamics. ⇑ Corresponding author at: 1605 Linden Drive, Madison, WI 53706, United States. Tel.: +1 608 263 1965; fax: +1 608 262 6872. E-mail address: [email protected] (R.W. Hartel). 1 Current address: Solae LLC, 4300 Duncan Avenue, St. Louis, MO 63110, United States. 0260-8774/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jfoodeng.2012.03.003

stirred tank cooling crystallizer. As the solution is gradually cooled, the supersaturation increases and lactose crystals are formed. The growth of crystals is typically accompanied by secondary nucleation, so the final product has a lot of small crystals, as shown in Fig. 1a. The resulting crystal size distribution makes the downstream processes (e.g., filtration, washing, drying, etc.) difficult. This results in low quality product, large product loss and low efficiency. To overcome these production problems, the crystallization process could be greatly improved by operating at conditions that promote growth and minimize secondary nucleation, leading to the production of a narrow distribution of larger crystals. The ideal operating conditions can be selected by examining the lactose ‘‘supersolubility’’ diagram (Wong et al., 2011) as reproduced in Fig. 1b. In Fig. 1b, the metastable zone width (MSZW) is defined as the region between the solubility and supersolubility lines. The region between forced crystallization and supersolubility lines was reported by Hunziker (1926) as the optimum region for mass crystallization in condensed milk. Recently, the metastable zone width (MSZW) was refined by Wong et al. (2011), with additional reference lines: 1) TD is the temperature at the detection of the first nuclei (via microscopy test) at various lactose solution concentrations. Therefore, seeded crystallization operations in the upper metastable limit (ML) defined by the region between solubility and TD lines have minimum secondary nucleation.

S.Y. Wong et al. / Journal of Food Engineering 111 (2012) 642–654

(a)

nucleation through impact (agitation) (Wong et al., 2011), shear damage to crystals, and impact on agglomerate formation/breakup (Tung et al., 2009). For energy transport, fluid mixing affects the rate of heat transfer through the jacket wall. In terms of mass transport, proper blending of the solution to the molecular level is required to achieve uniform supersaturation or to promote reactive crystallization (Tung et al., 2009). The flow profile in a crystallizer can be analysed using computational fluid dynamics (CFD). CFD is a numerical method that predicts parameters such as velocity, temperature, and pressure (among others) by solving the associated governing equations describing fluid flow, which are the mass, momentum and energy conservation equations (Bird et al., 2007). CFD is widely used to help describe a variety of fluid motion in mixing (Paul et al., 2004). For lactose crystallization, Wood-Kaczmar (2006) used CFD to reveal the poor circulation regions below the impeller in a crystallizer. When designing a lactose crystallization process, the operating regions and fluid mixing are the two most important parameters. Therefore, the objective of this study was to examine the correlation between fluid mixing and the operating conditions along different regions in the lactose ‘‘supersolubility’’ diagram (Fig. 1b). Then, based on this understanding, an optimized solution suitable for industrial operation was proposed.

(b) 80

Temperature (oC)

70

UNDERSATURATED ZONE

60 50 LABILE ZONE

40 30

Extrapolated T TD D 0.5% ΔTr

20

2. Materials and methods

1% ΔTr Industrial operation

10 0.1

643

0.2

0.3

0.4

0.5

0.6

Lactose solution concentration (g g-1) Fig. 1. (a) Polarized light microscope image of the lactose crystals obtained after an industrial cooling crystallization process. (b) Lactose ‘‘supersolubility’’ diagram (TD – temperature at the detection of the first nuclei; 0.5, 1% DTr – temperatures at 0.5% and 1% change in the transmittance relative to the initially seeded lactose solution; Lactose solution concentration (g g1) = mass of anhydrous lactose/mass of solution).

This study was split into four parts. The first three parts were lab scale studies (Sections 2 and 3), while the last part involved industrial verification and plant trials (Section 4). For the lab scale studies, lactose crystallization experiments with three distinct cooling profiles were first conducted using three crystallizer types/impellers with different flow profiles. Then, a model capable of predicting the concentration profile according to the cooling profile and initial lactose solution concentration was developed. Finally, the fluid flow profiles were analysed via CFD simulations. 2.1. Crystallizer design

2) The other two reference lines, 0.5% and 1% DTr, indicate the temperatures at different levels of transmittance change (DTr) (via spectroscopy test) when lactose solution was cooled at 1 °C/min. Higher changes in transmittance (relative to the seeded lactose solution) suggests the presence of higher numbers of nuclei in the solution and, thus, higher extent of secondary nucleation. The upper ML, defined by the region between solubility and 0.5% DTr or 1% DTr lines, have low or medium levels of secondary nucleation, respectively. Typical operating conditions for an industrial lactose refining operation (Shi et al., 2006) are also shown in Fig. 1b. The bulk of the operation operates in the lower ML between forced crystallization and the supersolubility lines, which is a region prone to secondary nucleation under agitated conditions. Therefore, commercial operating conditions result in the production of lactose crystals with wide range of size and numerous small crystals (Shi et al., 2006), as shown in Fig. 1a. In short, for a seeded crystallization process, the ideal operating region would be the upper metastable region, which is characterized by the area between the solubility and the TD, 0.5% DTr or 1% DTr lines, depending on the tolerance to the extent of secondary nucleation. In addition, fluid mixing during the crystallization process is also important in all aspects of transport properties, including momentum, energy and mass. A few areas of concern for momentum transport include the homogeneity of crystal slurry, secondary

In this study, three crystallizers with different types of impellers, shown in Fig. 2, were used. The first design (Fig. 2a) was a draft tube baffle (DTB) crystallizer. It consisted of a tall form 250 ml beaker, a polycarbonate draft tube baffle set, and a three blade propeller attached to a stainless steel shaft. The crystallizer was placed in a water bath (Haake DC30) and the temperature of the crystallization process was controlled by the bath temperature. The draft tube baffle system was constructed so that both mother liquor and suspension were well mixed. This system allowed axial flow (of solution) inside the crystallizer: flow was down inside the draft tube and up in the annular region. However, a minimum rotational speed of 440 rpm was required to suspend the crystals, resulting in significantly higher shear rate (around the impeller region) compared to the other two designs. The second and third designs had close-clearance impellers, with diameters nearly the same size as crystallizer tank diameter to provide macro-scale blending of liquids at low shear (Paul et al., 2004). The clearance between the impeller and the crystallizer (bottom and side) wall was ca. 3 mm. Due to the close clearance, the rotational motion of the impeller sweeps the wall and prevents build-up of encrusted crystals on the wall. In addition, this also improves heat transfer through the jacket. The anchor crystallizer (Fig. 2b) consisted of a tall form 250 ml jacketed beaker and an anchor stirrer. The temperature of the crystallization process was controlled by the circulating water bath (Thermo Electron Neslab RTE7) connected to the jacketed beaker.

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speed ≈ 95 rpm

speed ≈ 440 rpm

speed ≈ 110 rpm

Baffle

Draft tube

Propeller Total Volume = 206 ml

Total Volume = 206 ml

(a) Draft tube baffle (DTB)

(b)Anchor

Total Volume = 300 ml

(c) Paddle

Fig. 2. Schematic diagram of all crystallizers.

The paddle assembly configuration (Fig. 2c) was similar to the anchor stirrer, with additional two-blade propellers at the top and bottom of the assembly. This crystallizer consisted of a 350 ml beaker and the paddle assembly. Similar to the DTB crystallizer, the paddle crystallizer was placed in the same water bath (Haake DC30). The working volumes of the three crystallizers were 206, 206 and 300 ml, respectively. The three crystallizers were selected to represent different mixing profiles and impeller designs, which can be further examined through CFD simulations.

average rate of 0.031 °C/min, which is a long cooling time for the industry. The medium cooling profile (MEDIUMC) had similar cooling time (14 h) as an industrial cooling crystallizer (Shi et al., 2006) with an average cooling rate of 0.055 °C/min. As the solution gradually cooled, the supersaturation increased and lactose crystals were formed. The concentration profile of the crystallization process changes as a function of the cooling profile and the crystallization rates. These three different cooling profiles allowed the crystallization operation to be investigated in different operational regions as outlined in Fig. 1b.

2.2. Cooling profile 2.3. Experimental setup Three cooling profiles, representative of fast, medium and slow cooling, were selected. The lactose solution was cooled from a high temperature of 76 °C to 25 or 30 °C in a given period of time, as shown in Fig. 3. The fast cooling profile (FASTC) had a cooling time of 2.2 h with an average cooling rate of -0.43 °C/min. The slow cooling profile (SLOWC) had a total cooling time of 25 h with an

75 70

Temperature (o C)

65 60 55 50 45 40 35 30 25 0

2

4

6

8

10

12

14

16

18

20

22

24

Time (hr) Fig. 3. Three cooling profiles investigated (SLOWC, MEDIUMC and FASTC are cooling profiles with cooling rates of 0.031, 0.055 and 0.43 °C/min, respectively).

Supersaturated lactose solution (58%) was prepared by dissolving pharmaceutical grade lactose (310, Foremost Farms USA) in deionized water. The solution was heated to 80–85 °C to make sure all the lactose crystals were dissolved. At the start of the experiment, seed crystals were added to achieve the following objectives reported in previous studies: (1) to create a number of initial nuclei that are in fast growing state, so that secondary nuclei do not survive when there is a balance between the growth rate of existing crystals and the rate of change from clusters to crystals (in the supersaturated solution) (Shi et al., 2006); and (2) to improve the yield (Vu et al., 2003). In industrial operation, multiple crystal nuclei are often already present in the concentrated whey permeate during filling and prior to the onset of cooling. Therefore, the solution was seeded. The seed lactose crystals were prepared by sieving pharmaceutical grade lactose through sieve sizes of 250–90–45 lm; crystals collected on the sieve size of 45–90 lm (Vu et al., 2003) were used. The crystallizer was first filled with a fixed volume of supersaturated lactose solution. At the start of the experiment (t = 0 min), the supersaturated solution (at T = 76.5 °C) was seeded with 25 mg of lactose seed crystals (Shi et al., 2006). The temperature of the crystallization process was controlled by either the circulating water bath (Thermo Electron Neslab RTE7) connected to the jacketed beaker (Anchor crystallizer) or the water bath (Haake DL30-V26/B) (DTB and Paddle crystallizer). The crystallizer was cooled to 25 or 30 °C via the three different cooling profiles, as shown in Fig. 3. The cooling profile was implemented by controlling the set point of the circulating water bath with a modified Labview program.

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Lactose crystals were produced as cooling progressed. The concentration of the lactose solution was measured following every 10 °C drop in temperature. For this measurement, a small volume (1 ml) of lactose slurry was first filtered through a Whatman GD/X syringe filter. The refractive index of the filtrate was measured (refractometer, Bausch and Lomb) and converted into lactose concentration using pre-calibrated standard curve. At the end of the cooling cycle, the crystallizer was emptied and the lactose crystals were separated by vacuum filtration (Whatman No. 42 filter paper, 2.5 lm). The crystals were washed with 2-propanol (nonsolvent) and dried overnight in a 60 °C oven. The crystal size distribution (CSD) was measured by laser diffraction via Malvern MasterSizer 2000 (Wong et al., 2010). In addition, the crystal shape characteristic was examined by microscope (Nikon Labophot-2) with 40 magnification. The encrustation amount (g) and yield (g) were also measured. Encrustation is defined as the coating/scaling of lactose crystals on the surface of the crystallizer assembly (wall, baffles, and draft tube). To measure the level of encrustation, the emptied crystallizer (after vacuum filtration of the slurry) was dried in a 60 °C oven overnight and the weight of encrusted lactose crystals measured. The yield of the crystallization process was calculated by two approaches. The recovery percentage (Eq. (1)) denotes the ratio of lactose crystals produced and the amount of lactose initially present in the solution. This is the approach commonly used in the lactose refining industry.

Recovery ð%Þ ¼

Experimental yield ðgÞ initial mass of lactose in solution ð@t ¼ 0ÞðgÞ

V I  ð1  C I Þ ¼ V F  ð1  C E Þ þ 0:05  M crystal

ð4Þ

The value of Mcrystal was determined by solving both Eqs. (3) and (4) simultaneously. The theoretical yield (%) can be calculated via Eq. (5):

Theoretical yield ð%Þ ¼

Experimental yield ðgÞ  100 ðMcrystal þ M seed Þ ðgÞ

ð5Þ

To investigate the crystallization operation in different regions along the lactose ‘‘supersolubility’’ diagram, crystallization experiments were conducted for all three crystallizer designs (Fig. 2) and three cooling profiles (Fig. 3). There were a total of 3  3 experiments, with all experiments repeated at least twice. 2.4. Modeling the concentration profile For a batch cooling crystallization process, the mass conservation equation for all species (water, dissolved lactose and a-lactose monohydrate crystals) can be written as: Water concentration (x1) (kg water/m3 solution),

dx1 dx3 ¼ 0:05 dt dt

ð6Þ

Lactose concentration (x2) (kg lactose/m3 solution),

dx2 dx3 ¼ 0:95 dt dt

ð7Þ

Suspension density of a-lactose monohydrate crystals (x3) (kg lactose crystal/m3 solution),

 100 ð1Þ Theoretically, the maximum yield (Mcrystal) is limited by the saturation concentration of lactose (Cs) at the final cooling temperature (TF). The lactose crystallization process is defined as:

dx3 qpNGx24 ¼ dt 2

ð8Þ

Average diameter of crystals (x4) (m), 22 dx4 ¼ G ¼ 3:2  109 eRðTþ273Þ ðS  1Þ2:4 =a1 dt

ð9Þ

Number concentration of crystals of a-lactose monohydrate, N (#/m3 solution). 0.95 Lactose 0.05 H2O (Dissolved in solution) VI  CI VI  (1  CI) VF  CS VF  (1  CS)

Lactose H2O

Initial Mseed Final Mcrystal (Equilibrium + Mseed @ TF) Used VI  CI  VF  CS VI  (1  CI)  VF  (1  CS)

Here, VI and VF are the initial and final volumes (ml) of the lactose solution. CI and CS are the initial and saturation (equilibrium at TF) concentrations (g lactose/ml solution) of the lactose solution. Cs can be calculated from (Eq. (2)) (Visser, 1982). Mseed is the mass of seed added initially (=25 mg). Mcrystal is the maximum yield (g) of crystals if the system achieves equilibrium at TF. Cg ¼

12:23þ0:3375T þ0:001236T 2 þ0:00007257T 3 þ5:188107 T 4 ð100þ12:23þ0:3375T þ0:001236T 2 þ0:00007257T 3 þ5:188107 T 4 Þ ð2Þ

The overall mass balance of each species in the reaction can be written as: Mass balance of lactose,

V I  C I ¼ V F  C E þ 0:95  Mcrystal Mass balance of water,

ð3Þ

11:4 dN ¼ B ¼ 1:2  1018 eRðTþ273Þ ðS  1Þ1:5 x3 =a2 dt

ð10Þ

These equations were revised from the study of Vu et al. (2003) assuming (1) constant density (q = 1150 kg/m3); and (2) nucleation and growth of lactose crystals were the dominant mass transfer mechanisms (minimal aggregation or encrustation). Here, the growth (G) and nucleation (Bo) rates models were obtained from Liang et al. (1991) with the addition of model parameters, a1 and a2. Different from the study of Vu et al. (2003), Eqs. (6)–(10) included the effect of secondary nucleation by incorporating the nucleation rate model (Eq. (10)) developed by Liang et al. (1991). Crystals of a-lactose monohydrate were produced (Eq. (8)) from 95% of dissolved lactose (Eq. (7)) and 5% of water (Eq. (6)). G is the growth rate (m/min), as described by (Eq. (9)). At the start of the batch process (t = 0 min), N (Eq. (10)) is the total number concentration of particles (number/ml solution) added as seed crystals. Due to nucleation, N, changed during the crystallization process. The rate of evolution of the particles can be described as the nucleation rate (Bo) (#/ml-min) (Eq. (10)). It is known that crystallization kinetics change with different types of crystallizers and operating conditions. Therefore, the factors (a1, a2) in both Eqs. (9) and (10) were added to determine the kinetic expression for this study. These factors (a1, a2) were estimated using the experimental concentration profile of FASTC for anchor crystallizers. For this purpose, an iteration loop that scanned all combinations of both parameters (a1, a2) in the range of (1–300) (interval size = 1) was setup in Matlab R2008a. The parameter combination

S.Y. Wong et al. / Journal of Food Engineering 111 (2012) 642–654

with the smallest sum of error between eight experimental and modeled concentration was determined as a1 = 39, a2 = 258. After that, the performance of the model (Eqs. (6)–(10)) was also validated with experimental concentration for SLOWC and MEDIUMC. As cooling progressed, the temperature (T) decreased, giving an increase in the supersaturation (S). S of the a-lactose solution was calculated by a model developed by Visser (1982), as shown in Eqs. (11)–(13).

S¼

C C s  FK m ðC  C s Þ

F ¼ exp

  2374:6 þ 4:5683 Tk

K m ¼ 0:002286T þ 2:6371

ð11Þ

75

Modeled Experimental (Anchor) Experimental (DTB) Experimental (Paddle)

65

Temperature (oC)

646

55

45

35

ð12Þ 25 0.2

ð13Þ

0.3

0.4

0.5

0.6

Lactose solution concentration (g g-1)

Given the cooling profiles (Fig. 3), all equations were solved simultaneously by the ODE solver in Matlab R2008a to predict solution concentration and yield as function of time and temperature.

(a) SLOWC (25 hr) 75

2.5. CFD simulation approach

Modeled Experimental (Anchor) Experimental (DTB) Experimental (Paddle)

ND2 q

l

3. Results and discussion 3.1. Experimental concentration profile The concentration profiles measured experimentally for the crystallization operation with all three cooling profiles (SLOWC, MEDIUMC and FASTC) are shown in Fig. 4. From Fig. 4a, for anchor and paddle crystallizer, crystallization in SLOWC occurred in the region between 0.5% and 1% DTr initially. When the temperature dropped below 65 °C, the operation transitioned into the region between TD and 0.5% DTr, and moved closer to TD after 46 °C. The experimental concentration profile of MEDIUMC (Fig. 4b) is similar to the profile of SLOWC. However, the operation transitioned to the region between TD and 0.5% DTr only after 55 °C, which is 10 °C lower than the operation in SLOWC, and therefore might experience higher degree of secondary nucleation. When the cooling rate was very high (FASTC, Fig. 4c), the crystallization process was operating in the labile zone throughout, with high degree of secondary nucleation.

45

25 0.2

ð14Þ

Here, N is the impeller speed (rev/s) and D is the impeller diameter (m). For all crystallizers, the modified Reynolds numbers (Re) were greater than 5000, which indicated that all flows were in the turbulent regime. Thus, the Reynolds stress model (RSM) (Deen, 1998) was used to model the relationship between the turbulent fluxes and the smoothed field variables. The cooling profile for FASTC (Fig. 3) was used for the CFD simulation. The profile was implemented as temperature boundary conditions to the side and bottom wall of the crystallizers. The time step size for the unsteady simulation was 60 s, and the total number of time steps was 130, which was equivalent to a total simulation time of 130 min (2.17 h).

55

35

0.3

0.4

0.5

0.6

Lactose solution concentration (g g-1)

(b) MEDIUMC (14hr)

75

Modeled Experimental (Anchor) Experimental (DTB) Experimental (Paddle)

65

Temperature (oC)

Re ¼

Temperature (oC)

65

To better correlate the differences between fluid flow profiles and the crystallization process output, CFD simulations were conducted. Three 3D, pressure-based, implicit, unsteady state simulations were setup in Fluent 6.3.26 for each crystallizer (Fig. 2). In the CFD model, the time-smoothed continuity, momentum and energy transport equations (Bird et al., 2007) were solved for lactose solution (q = 1150 kg/m3, l = 2cP, Cp = 3470 J/kg-K, k = 0.6 W/m-K). For mixing, the modified definition of Reynolds number (Paul et al., 2004) was used:

55

45

35

25 0.2

0.3

0.4

0.5

0.6

lactose solution concentration (g g-1)

(c) FASTC (2hr) Fig. 4. Experimental and calculated concentration profile for crystallization operation in (a) SLOWC (25 h); (b) MEDIUMC (14 h); (c) FASTC (2 h). (TD – temperature at the detection of the first nuclei; 0.5%, 1% DTr – temperatures at 0.5%, 1% change in the transmittance; ‘‘Modeled’’ – concentration profile estimated by Eqs. (6)–(13)).

From Fig. 4, the concentration profiles predicted from the crystallization model were close to the experimental profiles at all cooling rates for the anchor and paddle crystallizers even though crystallization kinetics were predicted based on the FASTC cooling profile. This suggests that the kinetic models used here adequately fit lactose crystallization kinetics over a broad range of conditions.

S.Y. Wong et al. / Journal of Food Engineering 111 (2012) 642–654

However, in Fig. 4a and b, the experimental concentration profiles of DTB crystallizer deviated from both the modeled and experimental (anchor and paddle) concentration profiles. This is most likely due to the high extent of encrustation (Fig. 6) observed only in the DTB crystallizer, which will be discussed in the next section. For crystallization operation with minimal encrustation, all modeled concentration profiles for all cooling conditions are summarized in Fig. 5. As discussed in Section 1, the extent of secondary nucleation increases as the operation moves further away from the TD line towards the supersolubility line. Therefore, to limit the generation of small nuclei (extend of secondary nucleation), it is desirable to operate closer to TD. However, the cooling time increases significantly as the operation moves in the reverse direction (from supersolubility line towards TD). For example, there is an 11 h difference between the cooling times based on MEDIUMC and SLOWC. The model (Eqs. (6)–(13)) provided a quick estimate of process output corresponding to process input (initial lactose concentration) and operational parameters (cooling profile). With the availability of the model, the lactose refiner can customize their cooling profile by balancing the available resources (operational time) and the desired operational efficiency (product quality, recovery, etc.). This will be demonstrated in the next section.

SLOWC

75

MEDIUMC FASTC

Temperature (oC)

65

55

Increased cooling time

45 Increased extent of secondary nucleation

35

25 0.2

0.3

0.4

0.5

0.6

Lactose solution concentration (g g-1) Fig. 5. Calculated temperature-concentration profiles of the three operating conditions investigated (for crystallization processes with minimal encrustation).

Fig. 6. Encrustation observed experimentally for crystallization operation at SLOWC (25 h).

647

3.2. Crystallizer outputs The yield and encrustation amount for all experiments are summarized in Table 1. Among the three crystallizers (at all operating conditions), the DTB crystallizer had the lowest yield and highest amount of encrustation. That means most of the lactose was lost as encrusted crystals (as high as 67% for operation in SLOWC) while only a limited quantity were recovered as the final product crystals. Fig. 6 shows a snapshot comparing encrustation level in all three crystallizers after operating in SLOWC. For the DTB crystallizer, severe encrustation was observed on the baffles, draft tube assembly, and a portion of the crystallizer wall. However, the anchor and paddle crystallizers were almost free from encrustation (Fig. 6), and the amounts of encrustation were less than 5% of the total amount observed in DTB crystallizer (Table 1). Clearly, to obtain optimum yield, the DTB crystallizer design is not suitable for lactose refining. For both anchor and paddle crystallizers, where encrustation levels were minimal, operation in SLOWC gave the highest yield followed by MEDIUMC and FASTC. From Fig. 5, the horizontal difference between the final concentration of operation in FASTC and the solubility line (the residual supersaturation at the end of the cooling cycle) is greater than the same distance for operation in SLOWC and MEDIUMC; therefore, the lower yields observed for FASTC are expected. The crystal size distributions (CSD) of the lactose crystals obtained from the three crystallizers at end of the three operating conditions are shown in Figs. 7–9. The corresponding microscopic photos of all product crystals are shown in Fig. 10. In Fig. 10, a distinct crystal shape characteristic can be observed for all crystals obtained from experiments operating in FASTC. The lactose crystals primarily were found as large aggregates, accompanied by the presence of numerous small crystals. The DTB crystallizer had the largest number of small crystals, with 55.9% (of all crystals) smaller than 100 lm, as shown in Fig. 7. In Fig. 9, although a higher proportion of larger crystals were obtained for FASTC operation using the paddle crystallizer, the aggregated crystals (Fig. 10) were not favorable as a final product (Shi et al., 2006). So, operation in this region should be avoided. In general, among all operating conditions, the crystals produced from operation in SLOWC had the highest average size (Figs. 7–9). However, there were no distinct differences between the CSD profiles for operation in SLOWC and MEDIUMC in all crystallizers. Most of the crystals produced in SLOWC and MEDIUMC were shaped as segregated tomahawk crystals with minimal aggregation (Fig. 10). Among all 6 experiments (first two columns in Fig. 10), operation in SLOWC & MEDIUMC of DTB crystallizer produced the largest lactose crystals, with ca. 3% of fines (<100 lm), whereas the anchor and paddle crystallizers yielded ca. 5.4% and 18.1% fines, respectively. From Figs. 7–9, it is evident that the extent of secondary nucleation increased as the operating condition moved from the metastable regions defined by TD (Fig. 1b), from SLOWC ? MEDIUMC ? FASTC. In addition, if the rate of secondary nucleation was not controlled/limited, the presence of high number of nuclei centers promoted the formation of aggregates, as shown in column 3 of Fig. 10. From these results, the production of fines can be minimized by operating within the upper ML defined between the 0.5% DTr and solubility lines. Based on the experimental data, operation in SLOWC using the anchor crystallizer produced the most optimized combination with a reasonable level of fines (4.4%) and high yield (90% Theoretical yield). The use of CFD will help clarify the flow profiles to better document the differences between crystallizer designs.

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Table 1 Experimental yield and encrustation amount from all crystallizers at different operating conditions. Operating conditions

Recovery (%) (Eq. (1))

Theoretical yield (%) (Eq. (5))

Encrustation amt (g)

DTB crystallizer

SLOWC MEDIUMC FASTC (Tf = 27 °C)

0.18 0.43 1.61

0.20 0.49 1.82

80.31 76.20 48.69

Anchor crystallizer

SLOWC MEDIUMC FASTC (Tf = 25 °C)

78.80 74.29 54.33

90.34 85.17 60.68

1.50 2.51 2.42

Paddle crystallizer

SLOWC MEDIUMC FASTC (Tf = 27 °C)

82.66 82.04 39.33

94.77 94.06 44.38

1.95 1.79 3.93

Fig. 7. Crystal size distribution of crystals obtained from the draft tube with baffles (DTB) crystallizer at three operating conditions.

Fig. 8. Crystal size distribution of crystals obtained from the anchor crystallizer at three operating conditions.

3.3. CFD flow profile analysis The 3D flow patterns inside the crystallizers can be visualized using path lines. Path lines follow the trajectories that would be

Fig. 9. Crystal size distribution of crystals obtained from the paddle crystallizer at three operating conditions.

imposed by mass-less particles seeded at the plane y = 0 inside the crystallizer domain. The path line plots of all crystallizers (colored by velocity (m/s)) are shown in Fig. 11. These path lines were generated with 200 steps of (size) 0.005 m, which means each particle had advanced through a distance of 1 m inside the crystallizer. From Fig. 11a, the baffles in the DTB crystallizer converted the swirling motion (of the propeller) into top-down or axial fluid motion that helped to lift and suspend the crystals (Paul et al., 2004). It had upward z-directional flow in the annular region between the draft tube and crystallizer wall, and downward z-directional flow inside the draft tube (Fig. 12a). This arrangement allows the optimal mixing in the axial (z) direction. In contrast, a radial flow pattern dominated in both anchor and paddle crystallizers (Fig. 11b and c). As shown in Fig. 12b, the anchor impeller provided minimal axial flow and there was no distinct region of dominant upward (positive) or downward (negative) axial movement. Therefore, the larger particles had a tendency to settle at the bottom of the crystallizer; however, bottom encrustation was prevented by the close clearance between the impeller and the crystallizer wall. The presence of the top and bottom center propellers in the paddle impeller assembly helped to enhance axial mixing. Similar to the axial flow pattern inside the DTB crystallizer, particles moved upward in the region between the paddle impeller and crystallizer wall and downward inside the impeller in the paddle crystallizer (Fig. 12c). However, the extent of axial mixing in the paddle crystallizer was less than that of the DTB crystallizer.

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SLOWC (25 hr)

MEDIUMC (14 hr)

FASTC (2.2 hr)

Draft tube baffle (DTB) Crystallizer

Anchor Crystallizer

Paddle Crystallizer

Fig. 10. Microscopic images of the lactose crystals obtained from different crystallizers under different operating conditions.

Fig. 11. Path lines plots (colored by velocity (m/s)) of mass-less particles released from plane y = 0 for all crystallizers (Step size = 0.005 m, number of steps = 200, equivalent to a tracked distance of 1 m). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

During the crystallization process, the driving force (supersaturation) required for the production of crystals is created by cooling. The mixing profiles will have an impact on the temperature and, thus, the local supersaturation profile inside the crystallizers (Tung et al., 2009). The simulated temperature profiles at 1 h into the cooling profile for FASTC operation are shown in Fig. 13. Due to the presence of axial flow profile, the temperatures were mostly uniform in DTB and paddle crystallizers. The highest average temperature was found inside the anchor crystallizer, where the heat transfer from the center of the crystallizer to the wall is the slowest. Note that, the maximum temperature difference between the wall and the center was less than 0.4 °C for any of the crystallizer configurations.

In the DTB crystallizer, the presence of low velocity (<0.01 m/s) zones (Fig. 14) might be a significant factor that leads to the high encrustation level. The low velocity zones overlap with the locations of the encrusted crystals, as shown in Fig. 6. The encrusted crystals were mostly present in the annular region between the draft tube and the crystallizer wall. Inside the annular region, the flow was mostly slow and unidirectional (vertical) (Fig. 11a), with no turbulent eddies to lift any particles settled at the side walls/ baffles. Therefore, once in the low velocity zones, particles settle and accumulate (at the same location) over time, leading to higher level of encrustation as operational time increased (Table 1). The influence of shear on secondary nucleation has been reported in the literature (Koscher and Fulchiron, 2002; Paul et al.,

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Fig. 12. Axial velocity (m/s) profile at the center plane of all crystallizers.

Fig. 13. Temperature distribution (1 h into the cooling cycle with FASTC operation) at the cross sectional plane (x = 0 or y = 0) of all crystallizers.

2004; Soos et al., 2008; Tung et al., 2009; Wong et al., 2010). In general, the rate of secondary nucleation, which in turn determines the number of nuclei formed, increases following shear treatment. In a stirred tank, the high shear rates are generated in the immediate vicinity of the impeller (Paul et al., 2004). Fig. 15 shows the contours of wall shear stress on the impeller assembly for each crystallizer. The wall shear stress is defined as the force acting tangential to the surface due to friction. It is proportional to the velocity (gradient) parallel to the wall and, thus, the highest shear stresses are found at the tips of the impellers. Among all crystallizers, the highest wall shear stress was observed in the propeller of DTB crystallizer (Fig. 15a), since it had the highest rotational speed. The lowest shear stress was found in the anchor crystallizer (Fig. 15b). Although the paddle impeller had an intermediate level of shear stress, it had the highest surface area of high shear stress zones (non-blue region) (Fig. 15c). That means there will be higher probability of (high shear) collisions between the lactose slurry and the paddle impeller assembly.

The overall mixing process is described by the combination of shear rate and the volume (Paul et al., 2004). The volume-averaged shear rate of all crystallizers is summarized in Table 2. In Fig. 15, although the propeller in DTB crystallizer had the highest wall shear stress, the volume of this region is relatively small and, therefore, any given fluid volume will experience the high shear for a small amount of time. This results in intermediate volumeaveraged shear rate. In contrast, the paddle assembly has nearly the same size as the crystallizer; thus, it had the highest volumeaveraged shear rate. It is logical that the magnitude of the volume-averaged shear rate may be correlated to the amount of fines generated in each crystallizer. In Table 2, the volume-averaged shear rate in the anchor crystallizer was the smallest, resulting in the production of less than 6% fines (<100 lm). The largest number (24%) of fines was produced by the paddle crystallizer with the highest volume-averaged shear rate. The impact of shear on CSD is twofold. First, it increases the rate of secondary nucleation. Also, when large additional num-

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Fig. 14. Velocity (m/s) contour plot in the lower velocity range (0–0.01 m/s) of the DTB crystallizer (All colored zones are prone to encrustation).

Fig. 15. Wall shear stress (Pa) on the impeller assembly of all crystallizers.

Table 2 Flow properties of all crystallizers (⁄The cumulative volume fraction (%) of fines was calculated as the sum of the volume fraction (%) of all crystals of size less than 100 lm). DTB crystallizer

Anchor crystallizer

Paddle crystallizer

Rotational speed (rpm) Tip speed (m/s) Volume-averaged shear rate (1/s)

440 0.58 15.71

95 0.25 4.83

110 0.38 18.77

Cumulative volume fraction (%) of fines (<100 lm) for operation in SLOWC MEDIUMC FASTC

3.53 2.31 50.39

4.41 6.31 21.07

17.80 18.36 18.59

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Fig. 16. CFD analysis on Industrial scale crystallizer (a) Path lines plot of mass-less particles released from plane y = 0; (b) Wall shear stress (Pa) on the impeller assembly of the crystallizers (c_ is the volume average shear rate).

Fig. 17. Proposed and existing industrial cooling and concentration profiles (The proposed (13 h) profile is proposed by establishing a cushion of 1 °C higher than the concentration profile of 0.5% DTr).

bers of crystal units are introduced, the available supersaturation is divided equally among crystals, which results in less growth for individual crystals (Hartel, 2001). Despite the large volume-averaged shear rate, only 4.4% fines were produced in DTB crystallizer. This is most likely due to the high level of encrustation, since the secondary nuclei that were generated might be entrapped as encrusted crystals, resulting in lower recovery of smaller crystals. Therefore, for DTB crystallizer, no conclusive remark on shear rate and the extent of secondary nucleation can be made.

4. Industrial validations From the lab scale (200–300 ml) study, a good understanding of the crystallizer designs, and the appropriate regions of operation were established with model lactose in water solution systems. However, in the dairy industry, lactose is produced in an industrial scale crystallizer (2.6  107 ml) from whey permeate that contains other components (e.g., residual whey protein, minerals, riboflavin, etc.). To verify the applicability of this study in industrial

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(b) (a)

Typical process 13 hr plant trial

Fig. 18. (a) Polarized light microscope images; (b) Cumulative crystal size distribution (CSD) of the lactose crystals obtained from 13 h industrial trial (The typical process is representative of the current industrial operation with 14 h cooling profile).

operation, the same design strategy was applied to an industrial scale crystallization process. The objective of this part of the work was to apply the design strategy directly onto existing industrial crystallizer without the need of high capital investment. Therefore, a ‘‘soft’’ modification, which would only require modification in processing parameters, was developed. As shown in the lab scale study, the two most important criteria in optimizing/designing a lactose crystallization process are (1) crystallizer design, and (2) concentration profile (along MSZW). The ‘‘soft’’ processing parameters corresponding to these two factors are the impeller’s agitation rate and cooling profile, respectively. 4.1. Industrial scale crystallizer (7000 gal) An industrial scale lactose crystallizer with a height of 5.5 m and an internal diameter of 2.6 m was used. Similar to the anchor crystallizer (Fig. 2b), the industrial scale crystallizer had a close clearance impeller that swept the wall and prevented build-up of encrusted crystals on the wall. Currently, the typical lactose crystallization process at this facility takes 12 h for filling and 14 h for cooling. To examine the design and to determine the appropriate agitation rate for the industrial crystallizer, a computational fluid dynamics (CFD) simulation was created. 4.2. CFD analysis A CFD analysis was conducted based on the agitation rate (14.5 rpm) of the industrial crystallizer during cooling. The path line plots of the industrial crystallizer are shown in Fig. 16a. Compared to the anchor crystallizer, the impeller in the industrial crystallizer allows better axial mixing. The tip speed of the industrial crystallizer (1.84 m/s) is 7.4 times higher than that of the lab-scale anchor crystallizer (0.253 m/s). However, even though the tip speed of industrial crystallizer is significantly higher, the volume-averaged shear rate inside the industrial crystallizer is only approximately 10% of the same shear rate of anchor crystallizer, as shown in Fig. 16b. Based on the low volumeaveraged shear rate, agitation in the industrial crystallizer is satisfactory and should not by itself cause excessive secondary nucleation.

4.3. Plant trial Given the low volume-averaged shear rate estimated from the CFD analysis, it is possible to design a crystallization operation close to the 0.5% DTr line, as shown in Fig. 1b. However, it may not be ideal to operate directly on the 0.5% DTr reference line. Thus, a cushion of +1–2 °C was included to provide additional protection against secondary nucleation. The cooling profile required to achieve the desired concentration profile was calculated using Eqs. (6)–(13) via a Matlab R2008a routine. In this routine, the temperature was first divided into 5 °C grids. Then, the holding time required at each temperature interval (to achieve a minimum difference between calculated and desired profile) was estimated. A 13 h cooling profile based on a concentration–temperature profile that avoided the secondary nucleation zone was estimated and applied to the industrial scale crystallization process. The concentration and cooling profile of the 13 h plant trial is shown in Fig. 17. A microscopic image of the lactose crystals obtained from the plant trial is shown in Fig. 18a. Compared to the lactose crystals obtained in a typical industrial process (Fig. 1a), the crystals obtained from the 13 h plant trial are larger, with 28% less fines than the typical process, as shown in Fig. 18b. The 13 h plant trial sample had an L50 of 360 lm, compared to 250 lm obtained from a typical industrial process. Thus, given a good crystallizer design, large crystals can be obtained from a commercial crystallizer simply by using an appropriate cooling and agitation profile. 5. Conclusions The results from this study showed that the characteristics of the crystal products can be controlled by careful selection of operation region in the lactose ‘‘supersolubility’’ diagram and crystallizer design. Among all the conditions tested, the operation in the anchor crystallizer along the upper metastable limit (ML), closest to the first detection temperature (TD) produces the least number of fines (<100 lm). In addition, the practicability of the approach established using the lab scale crystallizer was tested successfully with an industrial scale crystallizer in whey permeate concentrate system. To summarize, the two key factors in designing a cooling lactose crystallization process are the cooling profile and the crystallizer

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design. To minimize secondary nucleation or the production of fines, the cooling profile should be selected such that the concentration profile of the crystallization process lies within the upper metastable limit as depicted in Fig. 1b. Once the cooling profile is selected, the crystallization process should be conducted in a crystallizer with optimal mixing profile, heat transfer efficiency (to avoid encrustation) and minimal shear. Acknowledgement This project was supported by National Research Initiative Grant #2007-55503-18448 from the USDA Cooperative State Research Education and Extension Service. References Bird, R.B., Stewart, W.E., Lightfoot, E.N., 2007. Transport phenomena, 2nd edn. J. Wiley, New York. Deen, W.M., 1998. Analysis of transport phenomena. Oxford University Press, New York, pp. 597. Hartel, R.W., 2001. Crystallization in foods. Aspen Publishers, Inc., Gaithersburg, Maryland, pp. 192–232. Hunziker, O.F. 1926. Condensed Milk and Milk Powder, fourth ed. In: Otto F. Hunziker, La Grange, Illinois.

Koscher, E., Fulchiron, R., 2002. Influence of shear on polypropylene crystallization: morphology development and kinetics. Polymer 43 (25), 6931–6942. Liang, B., Shi, Y., Hartel, R.W., 1991. Growth-rate dispersion effects on lactose crystal size distributions from a continuous cooling crystallizer. Journal of Food Science 56 (3), 848–854. Paul, E.L., Atiemo-Obeng, V.A., Kresta, S.M., 2004. Handbook of industrial mixing: science and practice. Wiley-Interscience, Hoboken, NJ, pp. 1377. Shi, Y., Liang, B., & Hartel, R.W. (2006). Crystal refining technologies by controlled crystallization. (US 2006/0128953 A1). Soos, M., Moussa, A.S., Ehrl, L., Sefcik, J., Wu, H., Morbidelli, M., 2008. Effect of shear rate on aggregate size and morphology investigated under turbulent conditions in stirred tank. Journal of colloid and interface science 319 (2), 577–589. Tung, H., Paul, E.L., Midler, M., McCauley, J.A., 2009. Crystallization of organic compounds: an industrial perspective. Wiley InterScience, Hoboken, NJ. Visser, R.A., 1982. Supersaturation of alpha-lactose in aqueous-solutions in mutarotation equilibrium. Netherlands Milk and Dairy Journal 36 (2), 89–101. Vu, T.T.L., Hourigan, J.A., Sleigh, R.W., Ang, M.H., Tade, M.O., 2003. Metastable control of cooling crystallization. European Symposium on Computer Aided Process Engineering 13, 527–532. Wong, S.Y., Bund, R.K., Connelly, R.K., Hartel, R.W., 2011. Determination of the dynamic metastable limit for a-lactose monohydrate crystallization. International Dairy Journal 21 (11), 839–847. Wong, S.Y., Bund, R.K., Connelly, R.K., Hartel, R.W., 2010. Modeling the crystallization kinetics of lactose via artificial neural network. Crystal Growth & Design 10 (6), 2620–2628. Wood-Kaczmar, M. (2006). Process for crystallizing lactose particles for use in pharmaceutical formulations. (WO 2006/086130 A2).