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Particle-Laden Spray Dryer Flowfield Analysis
Spray dryers are widely used in the food, mineral, chemical processing, and pharmaceutical industries to dry wet particles (or droplets) through a heat transfer process in a tank. The particles are generally injected at the top of the tank by a spray cone injection process, while warm air is also introduced into the tank through an annulus region adjacent to the particle spray. A representative spray dryer geometry is shown in Figure 1.
The flowfield in the spray dryer consists of the warm air flow and the particles, which represents a multi-phase flow situation. The continuous gaseous phase will be solved in the standard Eulerian frame of reference, while the discrete particles will be modeled using the Lagrangian method. The particle sizes can be described by using a Gaussian like distribution, or alternatively, with specified size groups. Each size group indicates the behavior of particles of that particular size. Based on the local balance of drag force, gravity, pressure, and flow momentum, the Lagrangian particle tracking will record instantaneous particle velocity, location, and trajectory for each particle group. Additional physical models for particles, such as evaporation and condensation, are included in the analysis to better describe the evaporated particle mass transfer process during the drying process.
One key issue in dryer operation is flow stability, i.e., avoiding a highly unsteady flow pattern in the dryer. When particles enter the dryer, unsteady flow can lead to excessive particle deposition on the dryer walls, a condition which may cause machine clogging or frequent maintenance shutdowns. Another possible problem is incomplete drying of the particles. With the help of CFD analysis, the particle-laden flow in the dryer can be examined in detail, to identify not only flow stability issues, but also the amount of particles deposited on the dryer walls, especially at the dryer exit region. This provides critical information on the dryer effectiveness and efficiency. Exploring these design issues with CFD analysis prior to prototype testing will significantly reduce the time and cost for dryer design and testing. It will also result in a high efficiency dryer, with reduced operational risks, such as clogging.
The CFD consultants at CAE Associates are very familiar with techniques necessary to get fast, accurate solutions for spray dryer behavior. We use the ANSYS suite of CFD software, including CFX and Fluent, to ensure high-fidelity solutions. As an example, we performed a CFD analysis of the dryer shown in Figure 1, where water droplets at room temperature are injected into the dryer at a spray cone angle of 60 degrees through an injection port on top of the dryer. The warm air enters the dryer at an annulus region surrounding the droplet injection port at 400ºK.
Figure 2 shows the temperature distribution at two cross-sections, which indicate that the droplet temperature rises 50ºK prior to leaving the dryer. Some of the warm air also rises to the top surface of the dryer. During the drying process, some of the droplets will evaporate to become vapor. Figure 3 shows streamlines (mean flow pattern) in the dryer. The streamlines are colored by the vapor concentration. The flowfield in the dryer is quite stable. There are recirculation regions in the dryer, but no clear unsteadiness is observed in the solutions. Figure 4 shows the particle trajectory (path) and residual time, which is an indication of where the particles travel to, and how long each group of particles stays in the dryer. This parameter can help in understanding the effectiveness of the dryer design and in determining appropriate particle injection methods, including port geometry, spray cone angle, particle flow rates, etc.
The results produced by the CFD analysis gave a complete picture of the expected dryer performance and were used to help guide the design before any costly prototypes were built and tested. The result was an efficient design and significantly lower development time and cost.
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