Abstract—This paper presents the prediction of air flow, humidity and temperature patterns in a co-current pilot plant spray dryer fitted with a pressure nozzle using a three dimensional model. The modelling was done with a Computational Fluid Dynamic package (Fluent 6.3), in which the gas phase is modeled as continuum using the Euler approach and the droplet/ particle phase is modelled by the Discrete Phase model (Lagrange approach). Good agreement was obtained with published experimental data where the CFD simulation correctly predicts a fast downward central flowing core and slow recirculation zones near the walls. In this work, the
effects of the air flow pattern on droplets trajectories, residence time distribution of droplets and deposition of the droplets on the wall also were investigated where atomizing of maltodextrin solution was used.
I. INTRODUCTION
SPRAY dryer is an essential unit operation for the manufacture of many products with specific powder properties, e.g. chemical, ceramic, food; pharmaceuticals etc.
In spite of the wide uses of the spray dryers, they are still designed mainly on the basis of experience and pilot experiment [1]. One of the big problems facing spray dryer designer and operators is the complexity of the spray/air mixing process in spray chamber [2] where the air flow patterns existing inside the spray dryer is considered as one of the primary factors that influence the residence time of droplet
/ particle, in turn the equality of the product produced by the dryer such as moisture content, size distribution, and bulk density. The particle residence time and surrounding air temperature are particularly important in the spray drying of
thermal sensitive products, such as milk, where product degradation can occur if the particles remain in an air stream for too long, or experience an air stream is too hot [3].
A very important phenomenon of spray dryer operability is the particle wall deposition which is affected by the temperature and humidity patterns inside the dryer when moist particles contact the spray dryer wall. Such depositions can lead to a build up large amounts of product on the wall. These depositions may be dangerous, as they can fall and cause damage to the chamber walls, or they can char,
resulting in a potential explosion hazard [4].
Application of computational fluid dynamic (CFD) techniques in analyses of spray dryers have been carried out successfully and reported by [5], [6] and others. Most of these earlier works assume the flows in the dryers are two dimensional and axisymmetric in order to reduce the demand on computational resources. There is clear experimental evidence to demonstrate three dimensional behavior in this
type of equipment suggesting that numerical simulations of spray dryers need to include the three-dimensional nature of the flows [7]. Previous two-dimensional, axi-symmetric simulations can only be regarded as indicative, at best, since they do not reproduce the basic physics that are involved [8].
As explained above, it is apparent that in order to avoid wall build up and insufficient residence time of particle which influences the product quality, we must able to model of the complexity of the spray/air mixing and including the proper drying model , therefore the objective of this paper is to perform two phase simulations of a co-current spray dryer in order to examine what current computational fluid dynamics techniques are capable of achieving when simulating such a system and to understand what happened inside the spray dryer?
II. MODELLING APPROACH
In order to simulate the spray drying process in a rigorous way, it is necessary to gain insight into the flow pattern, local temperature and local moisture content of the air and the temperature-time history of drying particle.
The first important aspect in modelling of spray dryer is prediction of the flow pattern of air which depends on the geometry of the dryer and the location and design of the air inlet and air outlet channel. The trajectories followed by the drying particles depend not only on the air flow pattern but also on the position and method of atomisation.
The second important aspect is the need to include the proper modelling of the drying behaviour of the droplet to ensure that the prediction of the droplet behaviour in the dryer is correct. The above considerations will be discussed in more detail as follows.
A. TWO PHASE FLOW SIMULATION
The flow in a spray dryer is turbulent and two-phase (gas and droplets or gas and particles). There are two commonly used approaches for modelling two-phase flow[9]. Firstly, one can treat the disperse phase as an extra fluid with its own
flow field (Euler/Euler approach). In the case of spray drying, with rather concentration of particles, one usually use the second approach, the Euler/ Lagrange approach. In this approach the gas field is calculated first (Euler). This is done
by calculating solutions of the Navier-Stockes and continuity equation on a grid of control volumes. Subsequently the particles are tracked individually (Lagrange). Along the particle trajectories the exchange of mass, energy and momentum with the continuous phase is calculated. These transfer terms are added to the source terms of the Navier-Stokes equations of the gas flow calculation. After the particle tracking, the air flow calculation pattern is recalculated, taking the transfer terms into account. This cycle of airflow calculation followed by particle tracking is repeated until convergence is reached. This scheme is called the Particle-In-Cell model [10].
The droplet field is established by integrating the differential equations for droplet motion to determine droplet velocities and, with further integration, droplet trajectories. At each time step along the trajectory, droplet size and temperature history are calculated using the equations for droplet mass and heat transfer rates. These equations can be found in [11]. Since space is limited, they are not repeated
here. The effect of turbulence on the droplet motion is modelled by the turbulent stochastic model. Turbulent stochastic tracking of droplets admits the effect of random velocity fluctuations of turbulence on droplet dispersion to be
accounted for in prediction of droplet trajectories [12].
B. DROPLETS DRYING
In this modelling approach, the drying kinetics are included and the concept of a characteristic drying curve has been used here [13]. This essentially empirical approach has been widely used for the modelling of single particle drying,
where it was based on the assumption of two distinct periods of drying, namely, the constant rate period which is then followed by the falling rate period. The approach relies upon first identifying an unhindered drying rate which may correspond to the rate in the first/constant drying period, and may mathematically expressed as :
The relative drying rate, , is then defined
Where is the drying rate and is the unhindered drying rate.
N Nˆ is a function of the characteristic moisture content,
defined as :
The drying curve can be fitted by a simple expression of the form [14]:
According to [15],the value of n for maltodextrin is 3.22. Where x is the volume-averaged moisture content, xcr is the critical moisture content and xeq is the solid moisture content which would be in equilibrium with the surrounding gas and
can be predicted from correlation of sorption isotherms of the dried material such as the one proposed by [16].
Where xeq is the equilibrium moisture content on a dry basis
(in kg water/kg dry material), xeq T is the temperature of the gas
(in K), and is the relative humidity of the gas (a fraction from 0 to 1), c1 , c2 and m are constants with the values 0.000405, -187.962 and 1.169 respectively.
The characteristic drying curve for a given material is unique and independent of external drying conditions. Furthermore, it is hypothesized that the drying-rate curves for the same material at different operating conditions will be geometrically similar, i.e., the normalized drying rate curve characterizes the drying of a given material[17], therefore it can be assumed that the critical moisture content is the same as the initial moisture content.
The concentration of vapour at the droplet surface is evaluated by Raoult’s Law , where the partial pressure of the vapour at the surface is equal to mole fraction of the water (Xs ) multiplied by the saturated vapour pressure, Psat at the
droplet temperature, Td :
The concentration of vapour in the bulk gas is calculated by :
III. CASE STUDY
For CFD simulation, the spray dryer used in this article is a co-current pilot plant spray dryer by Niro Atomizer as shown in Fig. 1. The geometry and air inlet size are the same as those used by [6]. The nozzle atomizer is located at the top of the drying chamber; hot drying air enters the chamber through an annulus with the nozzle as its centre. The outlet of the spray dryer is a pipe mounted through the wall of the cone section of the chamber, bent downwards in the centre of the chamber.
This type of spray dryers is a more complex geometry than the simple box configuration, which requires an unstructured mesh for accurate representation using 84000 tetrahedral mesh elements (Fig. 2). To check whether the solution was
dependent on the mesh which had chosen, the mesh was refined to 160000 elements. For each element of original mesh, the value of axial, radial and tangential velocities was compared with the corresponding values in refined mesh.
