Spray drying
In many areas in industry, the product of a process is a liquid containing a valuable solid material in either dissolved or suspended form. In many cases it is advantageous to separate the solid material from the solvent in order to obtain the dry material. The objective for this can be to save on shipping costs, or because the material has better properties in dry form than when dissolved. This is for instance the case in the preservation of foods.

Spray drying is a process for converting a liquid feed into a powder by evapo-ration of the solvent. Compared to other evaporation processes, spray drying has the great advantage that products can be dried without much loss of volatile or thermal labile compounds. These advantages are especially important in the production of food stuffs such as milk powder and instant coffee. The volatiles in these processes are aromas; the thermal labile compounds are for example proteins.

Spray dryers are widely used in industry. Although they are mostly found at the end-point of a plant, they have an important place in the whole process, not in the least because of their capital investment, size (heights of 20–30 meters are not uncommon), and operating costs.

The basic principle of the spray drying process is the extensive contacting of the liquid with the drying medium, usually air. The air provides the energy for the evaporation and ‘absorbs’ the solvent vapour (usually water). Four stages can be discerned in the spray drying process. The first stage takes place at the core of the process: the atomiser (see figure). The liquid stream is broken up by the atomiser into an enormous number of tiny droplets. (Droplets are referred to as particles in this thesis.) The particle sizes range from less than ten to a few hundred microns. Commonly used atomisers are the rotary disk atomiser, the pressure nozzle, and the twin fluid nozzle. In pressure nozzles, like the one used in this project, the feed is forced through a small hole (orifice). A liquid conical sheet is formed after the orifice; this sheet breaks up into particles.

The second stage is the dispersion of the particles in the air (spray-air mixing). The extent of spray-air mixing has great influence on the drying of the particles. The drying itself is considered the third stage.

Collecting the powder is the last stage. This usually comprises the removal of powder from the walls (air brooms, sweepers, hammers, vibrators, etc.) and the separation of powder from the exhaust air, usually by cyclones.

Spray dryers come in various shapes (tall forms, wide bodies) and types (co-current, counter-current or mixed flow). The co-current type is mostly used where thermal degradation and aroma retention are of concern. This is the type of spray dryer considered in this study.

Description of the problem
One of the problems associated with the spray drying process is that it is very difficult to predict the quality of the product. Here, product quality consists of parameters such as moisture content, thermal degradation, aroma retention, shape and size of the particles, stickiness, etc. How can the modelling of these parameters be approached? A first step is to recognise that a quality parameter in the end product is the result of what a particle experiences (e.g. temperatures, humidities) in the spray dryer and how it reacts to that (e.g. evaporation rate, thermal degradation rate). The combination of factors that address the environment of a particle (e.g. air temperature, air humidity) is called the equipment model, while the set of factors that address the responses of a particle is called the feedstock model. The equipment model thus comprises the influence of the spray drying process on the quality of the product, and is the subject of study in this project; a feedstock model reported in literature is used (Meerdink, 1993).

Several equipment models have been developed in the past decades. Most of them are based on crude assumptions of what takes place in the spray drying chamber, especially with respect to spray-air mixing. In most models, variations in air temperature and residence times are neglected; the flow of air and particles is not considered. The problem associated with this approach becomes apparent when one considers a handful of product. It consists of thousands of particles; a measure of the overall quality of that sample is the average of those thousands of particles, each having a different size, a different residence time and a different air temperature and air humidity history. Further, many properties are non-linear in the composing parameters, for example the amount of moisture to be evaporated is of the power of three in particle diameter, the surface through which the evaporation takes place, is of the power of two in diameter, the moisture content is strongly non-linear in time, etc.

Since the introduction of powerful computers in the 1980s, it is possible to approach the spray-air mixing problem on a more fundamental level, taking the flow of air and particles into account: the computational fluid dynamics (CFD) approach. In a nutshell, in the CFD approach the spray-air mixing is addressed by combining airflow and particle trajectories, yielding temperature and humidity patterns in the drying chamber, which in turn, when combined with the particle trajectories, result in the air temperature and humidity histories of the particles.

Some studies of the CFD approach are reported in literature. Those studies were mostly focused on only one aspect, such as the airflow or temperatures and humidities. In the 1990s CFD and the CFD packages have matured, and now a more integrated study is feasible that considers several aspects and the integration of various models in the CFD model. The project described in this thesis is the first of this type of research.

The objective of this research project
Initially, the objective of this research project was the development of a funda-mental model for predicting product quality in spray drying. This is a very comprehensive objective and was therefore redefined: concentration on the integration of models in the CFD approach, on the testing of the approach and on the assessment of the value of the use of CFD in product quality predictions.

Throughout all subjects studied, we have focused on two aspects: not only the modelling of phenomena but also the validation of the models is of principal concern.

Outline of this thesis
As described above, the CFD approach consists of a number of components. The basis of the approach is the airflow pattern. The modelling and measurement of the airflow pattern is discussed in chapter 2. In this chapter the airflow is simpli-fied: spray and swirl are omitted.

For the measurement of the temperature and humidity pattern, a special measuring device had to be developed. This device is described in chapter 3.

In chapter 4, the modelling of the temperature and humidity pattern is discussed: when particles are tracked through the air and when the drying rate is calculated along the trajectories, temperature and humidity patterns in the drying chamber can be obtained. For this, it is necessary to integrate a drying model in the CFD model. The modelling results were compared with measurements of temperatures and humidities in the dryer. These measurements are described in this chapter as well. Further, in contrast with chapter 2, the simplification with respect to the swirl angle is omitted in the modelling work as well as in the measurements.

Unfortunately, direct measurement of particle trajectories is impossible. On the other hand, it is possible to measure the particles’ end-points in time as well as space. This is described in chapter 5, which is concerned with residence time distributions of the particles and addresses product deposition on the walls. Furthermore, the topic of residence time distributions in spray dryers is an important subject on its own: they are of key importance for the design of spray drying processing and —as will be shown in chapter 6— have great influence on product quality.

By combining particle trajectories with the air temperature and humidity pattern, air temperature and humidity histories can be calculated. It was our intention to validate these air temperature and humidity histories by using a temperature time integrator (TTI). A TTI is a chemical or biochemical compound that is converted under increased temperatures with known conversion rate. An example of a TTI is the enzyme a-amylase, which was used in this project. Unfortunately, the accuracy of this approach to validation was too small and the objective shifted to the prediction of thermal degradation using basic and the more advanced CFD models. This is described in chapter 6.

Finally, the findings of these chapters are summarised in the conclusion, chapter 7. In this chapter the advantages and drawbacks of the CFD approach as well as the application of CFD in industrial practice are discussed.