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Agglomeration in Spray Drying Installations (The EDECAD Project):Stickiness Measurements and Simulation ResultsR. E. M. Verdurmenab; G. van Houwelingenb; M. Gunsingb; M. Verschuerenb; J. Straatsmaba Numico Research, Wegenigen, The Netherlands b Processing Division, NIZO Food Research, BA Ede,The Netherlands

To cite this Article Verdurmen, R. E. M. , van Houwelingen, G. , Gunsing, M. , Verschueren, M. and Straatsma, J.(2006)'Agglomeration in Spray Drying Installations (The EDECAD Project): Stickiness Measurements and Simulation Results',Drying Technology, 24: 6, 721 726

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Agglomeration in Spray Drying Installations (The EDECADProject): Stickiness Measurements and Simulation Results

R. E. M. Verdurmen,1,2 G. van Houwelingen,2 M. Gunsing,2 M. Verschueren,2

and J. Straatsma2

1Numico Research, Wegenigen, The Netherlands2NIZO Food Research, Processing Division, BA Ede, The Netherlands

Spray drying is used for the manufacture of many consumer andindustrial products such as instant dairy and food products, laundrydetergents, pharmaceuticals, ceramics, and agrochemicals. During

spray drying, agglomerates of powder particles are formed thatdetermine the instant properties of the powder. Agglomeration dur-ing spray drying is considered to be a difficult process to control.The main cause of this is the complex interaction of the process vari-ables: the atomization process, the mixing of spray and hot air, thedrying of suspension droplets, and the collision of particles, whichmight lead to coalescence or agglomeration. As a consequence,agglomeration during spray drying is operated by trial and error.In an EC-sponsored project, named the EDECAD project and coor-dinated by NIZO food research, an industrially validated computermodel, using CFD technology, to predict agglomeration processes inspray drying machines is developed. A Euler-Lagrange approachwith appropriate elementary models for drying, collision, coalesc-ence, and agglomeration of the dispersed phase is used. The mainresult of the EDECAD project is a so-called design tool, which

establishes relations between the configuration of the drying instal-lation (geometry, nozzle selection), process conditions, product com-position, and final powder properties. The design tool has beenvalidated on pilot plant scale and industrial scale. This article pre-sents the setup and results of dynamic stickiness tests and someCFD simulation and validation results.

Keywords Agglomeration: Computational fluid dynamics;Stickiness; Modeling; Spray drying

INTRODUCTION

Spray drying is an essential unit operation for the manu-facture of many products with specific powder properties.It is characterized by atomization of a solution or suspen-

sion into droplets, followed by subsequent drying of thesedroplets by evaporation of water or other solvents. Spraydrying is used for the manufacture of many consumerand industrial products such as instant food products,laundry detergents, pharmaceuticals, ceramics, and agro-

chemicals. The best known example of an instant foodproduct is milk powder. Consumers desire a quick dissol-ution or dispersion of such powders in water or milkwithout the formation of lumps. But manufacturers also

have their wishes. They require free-flowing powdersand absence of dust in such a way that it facilitates thehandling of the powders. Both requirements are met byapplying agglomeration of food powders.[13]

Agglomeration is a size enlargement process of powders,where small particles combine to form large relatively per-manent masses, in which the original particles are stillidentifiable; see also Figure 1. In this way, the characteris-tics of a single particle are maintained while the bulk pow-der properties are improved by the creation of the largeragglomerates.

In a spray dryer, agglomeration can take place withinthe spray of an atomizer, between sprays of various atomi-zers, and between sprays and dry material being introducedinto the drying chamber (e.g., by fines return; see Fig. 2).The latter technique is often the most effective way toachieve and control agglomeration in spray dryers.

Correspondence: Dr. M. Verschueren, NIZO Food Research,P.O. Box 20, 6710 BA Ede, The Netherlands; E-mail: Maykel.Verschueren@nizo.nl

FIG. 1. SEM photograph of spray-dried and agglomerated powder.From Verdurmen et al.[4]

Drying Technology, 24: 721726, 2006

Copyright# 2006 Taylor & Francis Group, LLC

ISSN: 0737-3937 print/1532-2300 online

DOI: 10.1080/07373930600684973

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Agglomeration takes place when two sticky particles, ora sticky and a dry particle, collide and form a liquid bridgethat is strong enough to resist mechanical deformations,while the integrity of the particles is maintained. Variousresearchers have calculated the critical viscosity for stickingduring contact times of a few seconds by applying variousmodels. As a result, the critical viscosity appears to be inthe range of 106108 Pa s. This value has been confirmedexperimentally by various investigators.[59] At lower visco-sities, the particles will coalesce upon collision, at higherviscosities the particles will not stick together (see also nextchapter).

The critical viscosity occurs at a temperature that is

called the sticky point temperature. Roos and Karel[10]

related the sticky point temperature to the glass transitiontemperature, which is characteristic for each material. Forskim milk solids, for example, the stickiness and cakingzone is positioned at about 10C or higher above the Tgmeasured by DSC.[11,12] Sticky points can further deviatefrom glass transition points, for instance, because alsothe dynamics of colliding particles are also relevant. Itwould therefore be better to measure sticky points directlyunder dynamic conditions. However, the classical measure-ment techniques[13] are not very accurate and show poorreproducibility when the examined powder is not free-flowing.

Agglomeration during spray drying is considered to be adifficult process to control. The main cause of this is thecomplex interaction of the process variables: the atomi-zation process, the mixing of spray and hot air, the dryingof suspension droplets, and the collision of particles, whichmight lead to coalescence or agglomeration. As a conse-quence, agglomeration during spray drying is operated bytrial and error. In 2001, an EC-sponsored project started,coordinated by NIZO food research, entitled EDECAD

(Efficient DEsign and Control of Agglomeration in sprayDrying machines, www.edecad.com). The EDECADproject aimed at developing an industrially validated com-puter model, using computational fluid dynamics (CFD)technology, to predict agglomeration processes in spray-drying machines.

This article presents the setup and results of static and

dynamic stickiness tests and some CFD simulation andvalidation results.

STICKINESS MEASUREMENTS AND SPRAYDRYING MODELING

Stickiness Measurements

The sticky point of a powder (i.e., the combination oftemperature and relative humidity of the outer layer ofthe powder, leading to sticky particles) can be measuredusing a stagnant layer of powder. This so-called staticsticky point is of relevance for storage of powders and to

determine when buildup of a powder layer can occur atthe chamber wall or cone of spray dryers.

The static sticky point is determined by filling an opencontainer (d 85 mm) with some powder (h 5 mm). Thiscontainer is exposed to a constant temperature in a con-trolled air cabinet. The relative humidity of the circulatingair will be step-wise increased (leaving at least 6 h betweensuch steps) until an optical change in powder structure isobserved. This change in structure is regarded as the staticsticky point. By repeating this procedure at different tem-peratures, a static stickiness line can be constructed.

The dynamic sticky point of a powder is determined byfluidizing a powder in an experimental fluid bed. [14] This

fluid bed is composed of a sintered distributor plate anda cylinder; see Figure 3. The air that is fluidizing the

FIG. 3. Schematic setup of the test rig to determine the dynamic stickypoint.

FIG. 2. An industrial two-stage spray dryer with fines return (courtesyof Anhydro A=S).

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powder can be heated up to 100C and the maximum airhumidity is 50 g kg1. Air pressure, temperature, and rela-tive humidity are measured below the sintered distributionplate. Also, the powder temperature is measured. The press-ure is measured every 5 s and the temperatures and relativehumidity every 5 min. The amount of powder added is500 g. At a constant air flow (adjusted to achieve sufficient

fluidization) and temperature, the relative humidity of theair is step-wise increase every 5 min until the fluidizationcharacteristics are changed (visual observation). To deter-mine the dynamic sticky point, visual observations andmeasurements of air pressure and powder temperature areused. By repeating this procedure at different temperatures,a dynamic stickiness line can be constructed.

Modeling of Spray Drying

Predictive computer models are helpful tools to maxi-mize the production capacity of available installations, tominimize fouling of equipment, and to reduce energy con-

sumption. These models also reduce the number of costlyand time-consuming production trials needed for the devel-opment of new products or processes. Verdurmen et al. [4]

have given an overview of how different modelingapproaches can be applied to spray drying equipment. Cur-rently, CFD is regarded as on of the best approaches tosimulate spray-drying process in detail.[4,1520] The air flowfield, the local temperature (see Fig. 4 as an example), andthe local humidity (see Fig. 5 as an example) inside thespray dryer can be computed by using CFD techniques,taking into account the coupling for mass, momentum,and energy. The difference from standard (e.g., diesel

sprays used in the automotive industry) spray calculationsmainly concerns the drying part: stickiness primarily dependson the drying state of the outer layer of the particles.Additional sub-models for moisture diffusion inside the par-ticles[16] and for the relation between the drying state andstickiness[11] are therefore required to be able to computethe drying and fouling behavior of spray-drying systems.

Some powder properties (e.g., insolubility) can berelated to the moisture content and the temperature-timehistory of the particles.[21] For these properties, the model-ing techniques described above can be used. The majorityof relevant powder quality properties, however, are related

to the degree of agglomeration.The aim of the EDECAD project has been to develop an

industrially validated CFD model, a so-called design tool,to predict agglomeration processes in spray-dryingmachines. The project has focused on agglomeration thattakes place at the upper part of the spray chamber, i.e.,between sprays and between sprays and fines return. Themodeling technique used is an extension of the Euler-Lagrange model for the drying and fouling behavior ofspray dryers described above.

The initial spray conditions were measured and the sub-models for drying, collision, and agglomeration weredeveloped and validated by the academic partners in theproject.[2226] For a detailed description of the CFD modeland its sub-models and pilot plant validation work carriedout by the industrial partners, we refer to Verdurmen et al.[4]

RESULTS AND DISCUSSION

The results of both the static and dynamic stickinessmeasurements for skim milk powder are presented inFigure 6 as a function of relative humidity of the air in

FIG. 4. Simulation of temperature profiles (C). Co-current spray dryerusing three peripheral high pressure nozzles (top center) and fines re-injec-

tion in the center. Chamber diameter is 4.3 m. The air inlet is positioned atthe top center, the air outlet at the right side of the cone. Copyright fromVerdurmen et al.[29] Reproduced with permission from EDP Sciences.

FIG. 5. Simulation of an air humidity profile (kg m3). The configur-

ation is identical to Figure 4. Copyright from Verdurmen et al.[29] Repro-duced with permission from EDP Sciences.

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the fluid bed. The glass transition temperature of skim milksolids as determined by DSC is also plotted in Figure 6 andis taken from literature.[27] These results confirm earlierobservations[1012] that the sticky point temperature andglass transition temperature are related, also when stickypoints are measured under dynamic conditions. The aver-age offset between the glass transition temperature andthe static sticky point is 13C, whereas the average off setbetween the glass transition temperature and the dynamicstatic point is 18C. These observations are also in line witha recent study by Paterson et al.,[28] who found that for

amorphous lactose, being the dominating carbohydrate inskim milk solids, a temperature exceeding the glass tran-sition temperature by 25C or more leads to instantaneousstickiness, even under very short contact times, such asthose experienced in industrial fluid bed dryers. The stickypoint curves obtained are used as input for the agglomer-ation sub-model of the design tool, as is described byVerdurmen et al.[4]

Figure 7 shows a typical simulation result for the par-ticle trajectories in the pilot plant dryer, which was alsoused for the validation trials. The size of the particlesshown in Figure 7 is a measure for the particle diameter.The results clearly show that the smaller particles (fines)

leave the dryer through the air outlet, whereas the majorityof the larger particles leave the dryer through the bottomof the dryer. The results also show a large recirculationpattern in the dryer, which is not unusual especially forrelatively small particles.

Figure 8 shows the initial particle size distribution at thenozzle and the computed size distribution at the bottom ofthe dryer corresponding to the calculation shown inFigure 7. Two cases have been simulated: production of

infant formula without and with fines return. An increasein the particle size of the powder is observed when usinga fines return configuration. This is in correspondence withexperimental observations. In Table 1 the experimental andsimulated average particle sizes are compared. It can beconcluded that the simulations are giving results in the cor-rect order of magnitude. On the other hand, there is still aneed for further optimization. Special attention is to bepaid on the correct prediction of viscosity during the dryingprocess, as this is an essential parameter for the agglomer-ation model.

FIG. 7. Simulated particle trajectories (the shown size is a measure ofthe particle diameter and the colours represent the particle temperature

in K). Copyright from Verdurmen et al.[29] Reproduced with permissionfrom EDP Sciences.

FIG. 6. Results of the static and dynamic stickiness measurements ofskim milk powder (dashed and dotted lines, respectively), as compared

to the glass transition temperature (solid line).

FIG. 8. Particle size distribution at the nozzle (measured) and at thebottom of the dryer (simulated). Copyright from Verdurmen et al.[29]

Reproduced with permission from EDP Sciences.

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CONCLUSIONS

The development of models for the food industry is anongoing process. By choosing an approach as used in theEDECAD project, agglomeration in spray dryers cannow also be simulated, although there is still a need forfurther optimization. The resulting design tool establishesrelations between process parameters, degree of agglomer-ation (e.g., particle size distribution, porosity), and finalpowder properties by combining information on materialproperties (e.g., sticky point) and computational fluiddynamics. This can be used by the industry for improveddesign and optimization of spray-drying and agglomer-ation equipment, to improve the quality of products, andto increase the productivity of such equipment.

ACKNOWLEDGEMENTS

This work is sponsored by the European Commission inthe frame of the EC Fifth Framework Programme withinthe research programme Competitive and SustainableGrowth (contract G1RD-CT-2000-00340, http:==www.edecad.com). The authors thank the other project partnersArmor Proteines, Royal Numico, Anhydro A=S, Univer-sity of Manchester, Bremen University, TU Darmstadt,and Martin-Luther-Universitat Halle-Wittenberg for theirparticipation and for supplying the products studied.

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TABLE 1Comparison of powder particle size distributions of simulations and validating spray drying trials

SimulationsMeasured directly

at dryerMeasured aftertransportation

Without fines return average diameter d (v, 0.5) in mm 95 103 92Without fines return span 1.02 2.7 2.0

With fines return average diameter d (v, 0.5) in mm 130 164 103With fines return span 0.6 2.3 2.0

Copyright from Verdurmen et al.[29]. Reproduced with permission from EDP Sciences.Relative span is defined as [d (v, 0.9) fd (v, 0.1)]=d (v, 0.5).

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