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

Spray drying is used for the manufacture of many consumer and industrial products such as instant dairy and food products, laundry detergents, pharmaceuticals, ceramics, and agrochemicals. During spray drying, agglomerates of powder particles are formed that determine the instant properties of the powder. Agglomeration during spray drying is considered to be a difficult process to control. The main cause of this is the complex interaction of the process variables: the atomization process, the mixing of spray and hot air, the drying of suspension droplets, and the collision of particles, which might 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 coordinated by NIZO food research, an industrially validated computer model, using CFD technology, to predict agglomeration processes in spray drying machines is developed. A Euler-Lagrange approach with appropriate elementary models for drying, collision, coalescence, and agglomeration of the dispersed phase is used. The main result of the EDECAD project is a so-called design tool, which establishes relations between the configuration of the drying installation (geometry, nozzle selection), process conditions, product composition, and final powder properties. The design tool has been validated on pilot plant scale and industrial scale. This article presents the setup and results of dynamic stickiness tests and some CFD simulation and validation results.     

Simulation of Agglomeration in Spray Drying Installations: The EDECAD Project

Spray drying is used for the manufacture of many consumer and industrial products such as instant dairy and food products, laundry detergents, pharmaceuticals, ceramics, and agrochemicals. During spray drying, agglomerates of powder particles are formed which determine the instant properties of the powder. Agglomeration during spray drying is considered to be a difficult process to control. The main cause of this is the complex interaction of the process variables: the atomization process, the mixing of spray and hot air, the drying of suspension droplets and the collision of particles which might 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 projects, an industrially validated computer model, using CFD technology, to predict agglomeration processes in spray drying machines is developed. An Euler-Lagrange approach with appropriate elementary models for drying, collision, coalescence and agglomeration of the dispersed phase is used. The main result of the EDECAD project is a so-called “Design Tool,” which establishes relations between the configuration of the drying installation (geometry, nozzle selection), process conditions, product composition and final powder properties. The Design Tool is being validated on pilot-plant scale and industrial scale. It will provide an advanced tool for improved design and optimization of spray drying and agglomeration equipment, to improve the quality of products and to increase the productivity of such equipment. This article introduces the background and approach of the project and some preliminary results.     

New Engineered Particles from Spray Dryers: Research Needs in Spray Drying

This article reviews developments in the simulations of spray dryer behavior, including the challenges in modeling the complex flow patterns inside the equipment, which are often highly transient and three-dimensional in nature. There appears to be considerable scope for using CFD simulations for investigating methods to reduce the rates of wall deposition and of thermal degradation for particles by modifying the air flow patterns in the chamber through small changes in the air inlet geometry. Challenges include building particle drying kinetics and reaction processes, as well as agglomeration behavior, into these simulations. The numerical simulations should be valuable supplements to pilot-scale testing, enabling more extensive and accurate optimization to be carried out than hitherto possible. New understanding of reaction processes and materials science, in combination with recent knowledge of the application of CFD to these problems, may enable new engineered powder products to be developed from the one-step spray-drying process.     

Spray Drying and Agglomeration of Instant Bayberry Powder

Optimum technology of spray-dried bayberry powder was studied using D-optimal experimental design. The operating conditions were varied within the following ranges: inlet air temperature 140-160°C, outlet air temperature 65-85°C, maltodextrin DE values 12 and 19, and feed concentrations of 7-17°B. The spray-dried bayberry powder was analyzed for moisture content and color. Moisture content of spray-dried powder was determined mainly by the inlet and outlet air temperatures, DE value, and the feed concentration. The inlet and outlet temperature had important effects on powder color. Finally, instant bayberry powder for beverages was produced by agglomeration of the spray-dried product.     

Spray Drying and Agglomeration of Instant Bayberry Powder

Optimum technology of spray-dried bayberry powder was studied using D-optimal experimental design. The operating conditions were varied within the following ranges: inlet air temperature 140–160°C, outlet air temperature 65–85°C, maltodextrin DE values 12 and 19, and feed concentrations of 7–17°B. The spray-dried bayberry powder was analyzed for moisture content and color. Moisture content of spray-dried powder was determined mainly by the inlet and outlet air temperatures, DE value, and the feed concentration. The inlet and outlet temperature had important effects on powder color. Finally, instant bayberry powder for beverages was produced by agglomeration of the spray-dried product.     

Droplet-Droplet Interactions in Spray Drying by Using 2D Computational Fluid Dynamics

A 2D axisymmetric model of the spray drying process is presented. The two-phase flow theoretical model is based on a combined Eulerian-Lagrangian approach and takes binary interactions (coalescence or bouncing) between spray droplets into consideration. Validation of the model (incorporated in FLUENT 6.3.26) demonstrated good agreement and consistency with the literature data. The results of transient simulations showed that droplet-droplet interactions displace the region of heat and mass transfer from the central core toward the periphery of the drying chamber. It was also found that insulation of the spray dryer can substantially affect temperature and humidity patterns, whereas its influence on the velocity flow field is less marked.     

Surface Stickiness of Drops of Carbohydrate and Organic Acid Solutions During Convective Drying: Experiments and Modeling

Abstract

Drying kinetics of low molecular weight sugars such as fructose, glucose, sucrose and organic acid such as citric acid and high molecular weight carbohydrate such as maltodextrin (DE 6) were determined experimentally using single drop drying experiments as well as predicted numerically by solving the mass and heat transfer equations. The predicted moisture and temperature histories agreed with the experimental ones within 6% average relative (absolute) error and average difference of ± 1°C, respectively. The stickiness histories of these drops were determined experimentally and predicted numerically based on the glass transition temperature (T _g ) of surface layer. The model predicted the experimental observations with good accuracy. A nonsticky regime for these materials during spray drying is proposed by simulating a drop, initially 120 µm in diameter, in a spray drying environment.     

Surface Stickiness of Drops of Carbohydrate and Organic Acid Solutions During Convective Drying: Experiments and Modeling

Drying kinetics of low molecular weight sugars such as fructose, glucose, sucrose and organic acid such as citric acid and high molecular weight carbohydrate such as maltodextrin (DE 6) were determined experimentally using single drop drying experiments as well as predicted numerically by solving the mass and heat transfer equations. The predicted moisture and temperature histories agreed with the experimental ones within 6% average relative (absolute) error and average difference of ± 1°C, respectively. The stickiness histories of these drops were determined experimentally and predicted numerically based on the glass transition temperature (T_g) of surface layer. The model predicted the experimental observations with good accuracy. A nonsticky regime for these materials during spray drying is proposed by simulating a drop, initially 120 µm in diameter, in a spray drying environment.     

An Experimental Investigation of Lime Juice Drying in a Pilot Plant Spray Dryer

One of the major problems in spray drying of fruit juices such as lime juice is stickiness and thermoplasticity of their compositions. Lime juice consists of invert sugars and citric acid, which have low glass transition temperatures. Due to this characteristic, the particles stick on the dryer wall upon their collision with it. As a result, drying of these materials is very difficult. In order to solve this problem, various percent of silicon dioxide and maltodextrin (DE5), based on total soluble solid content of lime juice, have been used to reach a suitable drying condition. A cool chamber wall spray dryer was used in this investigation in order to decrease the probability of particles stickiness on the wall. Our investigation revealed that an addition of 10% silicon dioxide and 20% maltodextrin (DE5) to lime juice is the optimum amount for a complete and successful drying of lime juice. Sampling of particles from different longitudinal distances in the dryer tower is carried out to find the particle moisture contents as they fly downward in the dryer. The results show a very fast decrease in entrance moisture contents. Based on our experimental data, the variation of moisture contents are presented as a function of radial distance from central line and longitudinal distance from the entrance region.     

Validation of the Lagrangian Approach for Predicting Turbulent Dispersion and Evaporation of Droplets within a Spray

The accuracy of the Lagrangian approach for predicting droplet trajectories and evaporation rates within a simple spray has been addressed. The turbulent dispersion and overall evaporation rates of droplets are modeled reasonably well, although the downstream velocity decay of the larger droplets is underpredicted, which is attributed to a poor estimate of the radial fluctuating velocity of these droplets at the inlet boundary. Qualitative agreement is found between the predicted and experimental evolution of the droplet size distribution downstream of the nozzle. These results show that smaller droplets evaporate preferentially to larger droplets, because they disperse more quickly toward the edge of the jet, where the entrainment of fresh air from the surroundings produces a significant evaporative driving force. Droplet dispersion and evaporation rates are highly influenced by the rate of turbulence generation within the shear layer. This work demonstrates the potential of the Lagrangian approach for analyzing particle trajectories and drying within the more complex spray dryer system.     

Challenges of Simulating Droplet Coalescence within a Spray

This article reports various challenges that have been encountered in the process of developing validated Lagrangian and Eulerian models for simulating particle agglomeration within a spray dryer. These have included the challenges of accurately measuring droplet coalescence rates within a spray, and modeling properly the gas-droplet and droplet-droplet turbulence interactions. We have demonstrated the relative versatility and ease of implementation of the Lagrangian model compared with the Eulerian model, and the accuracy of both models for predicting turbulent dispersion of droplets and the turbulent flow-field within a simple jet system. The Lagrangian and Eulerian droplet coalescence predictions are consistent with each other, which implies that the numerical aspects of each simulation are handled properly, suggesting that either approach can be used with confidence for future spray modeling. However, it is clear that considerable research must be done in the area of particle turbulence modeling and accurate measurement of particle agglomeration rates before any Computational Fluid Dynamics tool can be employed to accurately predict particle agglomeration within a spray dryer.     

Challenges of Simulating Droplet Coalescence within a Spray

Abstract

This article reports various challenges that have been encountered in the process of developing validated Lagrangian and Eulerian models for simulating particle agglomeration within a spray dryer. These have included the challenges of accurately measuring droplet coalescence rates within a spray, and modeling properly the gas–droplet and droplet-droplet turbulence interactions. We have demonstrated the relative versatility and ease of implementation of the Lagrangian model compared with the Eulerian model, and the accuracy of both models for predicting turbulent dispersion of droplets and the turbulent flow-field within a simple jet system. The Lagrangian and Eulerian droplet coalescence predictions are consistent with each other, which implies that the numerical aspects of each simulation are handled properly, suggesting that either approach can be used with confidence for future spray modeling. However, it is clear that considerable research must be done in the area of particle turbulence modeling and accurate measurement of particle agglomeration rates before any Computational Fluid Dynamics tool can be employed to accurately predict particle agglomeration within a spray dryer.     

Spray Drying of Skim Milk Mixed with Milk Permeate: Effect on Drying Behavior, Physicochemical Properties, and Storage Stability of Powder

The possibility of using milk permeate (MP) to lower the protein level of skim milk powder (SMP) in producing powders of 34% and lower protein is explored. Skim milk suspensions with various levels of MP were prepared by mixing SMP and MP powder (MPP) at the ratios of 1:0, 7:3, 3:7, and 0:1: from 34 to 5.3% protein. The suspensions were dried in a spray dryer with inlet and outlet temperatures of 180 and 80°C, respectively. Increasing permeate concentration in the mixture showed a greater tendency to stickiness manifested by lowered the cyclone recovery of the powder as more powder stuck on the wall of the dryer. Increasing permeate concentration in the resultant powder did not significantly affect the bulk density but led to a reduction in the particle size and also made the powder slight green and yellowish in color. It also found to lower the glass transition temperature (T_g) of the skim milk powder (SMP) and induce crystallization of lactose at lower water activity (a_w ≥ 0.328 for SMP:MPP of 3:7 and 0:1 compared to a_w ≥ 0.0.432 for SMP:MPP of 1:0 and 3:7). Addition of MP in SMP lowered the T_g values of the resulting powders. The permeate fraction in spray-dried SMP/MPP mixtures found to lower the critical a_w and moisture content, suggesting the SMP mixed with MPP is more likely to become sticky than SMP alone (at 34% protein) when stored at a similar water activity and moisture content.     

Evolution of particle properties during spray drying in relation with stickiness and agglomeration control

Spray drying consists in atomizing a solution into liquid drops in a hot air flow to get dry solid particles after solvent evaporation. The convective drying at the drop surface leads to a very fast evolution of temperature and water content due to initial high differences of temperature and water vapour pressure between the drop surface and the drying air. During drying, the drop surface viscosity is increasing due to potentially amorphous polymers reaching a rubbery state. The drop surface is becoming sticky with consequences on wall deposit. This sticky behaviour which appears in the range of 10 to 30 °C above the glass transition temperature Tg, may be utilized in a positive way for agglomeration of drying particles with dry powders, either recycled fines or new dry powder, to improve instant properties.The evolution of water content of drops along drying, is deduced from measurements of air temperature and relative humidity, at different places in the dryer and used to predict the drying and sticky behaviour of two maltodextrin solutions (DE12 and DE21) with different Tg. The studied parameters in a co-current spray dryer were the inlet air temperature (144, 174, 200 °C) and flow rate (80 and 110 kg h^− 1), the liquid flow rate (1.8, 3.6 and 5.4 kg h^− 1) and the rotation speed of the wheel atomizer. The results on particle water content combined with the evolution of Tg showed that particles are sticky close to the atomiser for the two maltodextrins, and also along the chamber for maltodextrin DE21 due to its lower Tg. The introduction of dry particles at different places in the chamber allowed validating the method to control agglomeration.     

The Influence of the Spray Drying Process on Product Properties

Uniform and repeatable product characteristics are critical in the performance and acceptance of consumer products, and the spray drying process can have a major influence on achieving these characteristics. This article shares experiences in the Spray Drying of powdered detergent granules in Procter & Gamble. It looks at the influence of both process operation and process equipment design on product characteristics. Procter & Gamble (P&G) is a major global producer of consumer products in the areas of fabric and home care; personal and beauty care; health care; and snacks and beverages. Whilst different drying operations, and product quality measuring tools are mentioned by Genskow (Genskow, L.R.¹ Considerations in Drying Consumer Products, Proceedings of 6th International Drying Symposium, Versailles, September, 1988; Keynote lecture, 39-46.) as being involved in all of the categories of Company production, I will concentrate on the counter-current Spray Drying process and controls, used in the manufacture of most of the detergent granules business of P&G. This area is the oldest and largest of the Company's core business activities. Innovative technology development is critical in continuing to satisfy the consumer need for performance and value. Use of modeling in the spray drying process is helping the Company to move faster in delivering these advanced technologies. And, through better understanding of the process, it is possible to minimize capital expenditure, and improve trouble-shooting ability across the global production facilities.     

The Influence of the Spray Drying Process on Product Properties

Abstract

Uniform and repeatable product characteristics are critical in the performance and acceptance of consumer products, and the spray drying process can have a major influence on achieving these characteristics. This article shares experiences in the Spray Drying of powdered detergent granules in Procter & Gamble. It looks at the influence of both process operation and process equipment design on product characteristics. Procter & Gamble (P&G) is a major global producer of consumer products in the areas of fabric and home care; personal and beauty care; health care; and snacks and beverages. Whilst different drying operations, and product quality measuring tools are mentioned by Genskow (Genskow, L.R.¹ Considerations in Drying Consumer Products, Proceedings of 6th International Drying Symposium, Versailles, September, 1988; Keynote lecture, 39–46.) as being involved in all of the categories of Company production, I will concentrate on the counter-current Spray Drying process and controls, used in the manufacture of most of the detergent granules business of P&G. This area is the oldest and largest of the Company's core business activities. Innovative technology development is critical in continuing to satisfy the consumer need for performance and value. Use of modeling in the spray drying process is helping the Company to move faster in delivering these advanced technologies. And, through better understanding of the process, it is possible to minimize capital expenditure, and improve trouble-shooting ability across the global production facilities.     

Spray Drying of Biopharmaceuticals: Stability and Process Considerations

Spray drying represents an elegant one-step process for producing biopharmaceutical formulations with unique particle characteristics. However, the full potential of spray drying of therapeutic/proteins/peptides has yet to be fully exploited. The reluctance of utilizing spray drying for formulation development may stem from the fact that the process oftentimes subjects the therapeutic actives to temperatures in excess of 100°C, which is a concern for thermally labile drugs as spray drying was performed primarily on co-current spray dryer in a single-stage mode. In this review we discuss the respective dehydration mechanisms of spray drying and the appropriate formulation strategies that can be taken to minimize detrimental effects on biomolecules.     

Partial Crystallization Behavior during Spray Drying: Simulations and Experiments

Simulations of crystallization behavior in a spray dryer have been performed using modifications to a model developed by previous workers and applied to a Buchi-290 laboratory-scale dryer. The potential crystallization behavior has been modeled using Williams-Landel-Ferry kinetics. Explorations using the model have suggested that the air inlet temperature is an important variable affecting crystallization in the dryer. The explorations suggested drying conditions that permitted reasonable drying while controlling the degree of crystallization. These conditions were examined and tested experimentally, also showing that the apparent degree of crystallinity was affected by the inlet air temperature over the range of inlet temperatures from 134°C (∼55% crystalline) to 210°C (∼76% crystalline). The simulation also predicted the trends in the experimental results from previous workers where their experimental results are considered in terms of the measurement techniques used in each case, suggesting that the simulation is a reasonable tool for developing operating conditions for drying equipment to give low or high degrees of crystallinity in the products.     

Spray Drying and Process Optimization of Unclarified Pomegranate (Punica granatum) Juice

In this study, production of pomegranate juice powder using a spray dryer was investigated. To prevent stickiness, maltodextrin dextrose equivalent 6 (DE6) was used as a drying agent. While feed flow rate, feed temperature, and air flow rate were kept constant, air inlet temperature (110–140°C), percentage maltodextrin (MD; maltodextrin dry solids/100 g feed mixture dry solids; 39.08–64.12%), and feed mixture concentration (19.61–44.11 °Brix) were chosen as the independent variables. Product properties investigated included moisture content, hygroscopicity, anthocyanin content, color change, solubility, bulk density, total phenolics content, antioxidant capacity, and sensory properties. The products were produced with high yield (86%) and high antioxidant activity (77%). MD and drying temperature were found to be the most important variables in production of pomegranate juice powders. Because total color change (ΔE), bulk density, antioxidant capacity, and powder yield were affected strongly by the independent variables, these parameters were used in optimization of the process. The optimum temperature, feed mixture concentration, and percentage maltodextrin were 100°C, 30.8 °Brix, and 53.5% MD, respectively. This study revealed that by applying these optimal conditions, pomegranate juice powder with a 55% dry solids yield, 9.78 total color change, 0.35 g/mL bulk density, and 57.8% antioxidant capacity were produced.     

Hygrothermal and Quality Properties Applicable to Drying. Data Sources and Measurement Techniques

ABSTRACT

The efficient dryer design and the optimization of existing drying processes require both effective drying models and hygrothermal properties. Following extensive research during the previous decades, today's existing models for the drying process are mostly adequate. Thus.most of the requirements for appropriate process design and operation depend on the existence of data for the various properties. The correct estimation of properties is of fundamental importance for the design.optimization and control of the process. The existing knowledge is adequate regarding the hygrothermal properties of the drying medium (air). Most of the efforts should address the problem of finding and standardizing appropriate measuring techniques and selecting and compiling the existing data, concerning hygrothermal and quality properties of the product being dried. The article identifies those areas, where adequate data not exist and future research is needed or data banks should be created.