Optimal design and control of a spray drying process that manufactures hollow micro-particles
Year: 2006
Type: dissertation
Abstract: Spray drying processes have a wide variety of applications in industries from the manufacture of food to pharmaceuticals and more recently hollow polymeric microparticles. In spite of the wide uses of the spray drying process the approach to the design of the spray dryer has remained experiential. One reason for this is that the spray drying process itself exhibits certain characteristics, such as rapid heat and mass transfer and a distributed nature, that are challenging from a first-principles modeling perspective. Additionally, the control of these processes is difficult since direct on-line realtime measurements of the product quality (e.g., particle size) are not available. \n \n In the spray drying process, a liquid spray is brought into contact with a heating gas to evaporate the solvent present in the solution. The product is in particle form. The contact between the heating gas and liquid spray may be achieved in either a cocurrent or a counter-current manner. In the design of the spray dryer, the residence time of individual particles inside the spray dryer is important. A particle should remain in the spray dryer long enough for complete evaporation of the solvent but not too long to cause product degradation, e.g., by charring. \n \n In this research, a rigorous first-principles based model of the spray dryer is developed and presented. The model is in two parts: the first, studies the changes occurring to a single droplet as it is exposed to the heating gas; the second, tracks individual particles and calculates the total heat and mass transfer between the droplet phase and the heating gas. The first part of the model consists of a coupled set of parabolic partial differential equations with a moving boundary condition. This model is solved using the Gradient Weighted Moving Finite Element Method. To solve the second part of the model, a Lagrangian framework is used to track the individual droplets. The flow rate of the heating gas is calculated from empirical equations available in the literature. The model's results are validated against an existing experimental laboratory scale spray drying unit. The validated model is used to develop an optimal design of the spray drying system. \n \n A control structure to regulate the spray dryer's product properties is developed. The two important property variables to be controlled are the mean particle size (diameter of the particles) and the residual solvent concentration in the product. Reliable and efficient on-line, realtime measurements of these variables are difficult to obtain. Therefore, these variables must be estimated from available measurements such as the temperature of the heating gas measured at points along the length of the spray dryer. Applying the method of Principal Component Regression, inferential models are developed to estimate the particle size and residual solvent concentration from the heating gas temperature measurements. Using these estimates an appropriate control strategy is developed and tested in the presence of expected disturbances. \n \n Finally, the coupling of design and control that exists naturally due to the interconnection of unit operations and the recycle of material and energy is addressed. Traditionally, process design and controller synthesis have been treated as distinct tasks with the controller synthesis following process design flowsheet generation. This serial approach ignores the effects the process design decisions has on the control structure synthesis. Thus, the achievable control performance if a function of the process design. In this work, a novel bi-level optimization strategy is used to optimize both the process design and controller synthesis. The bi-level strategy operates at two levels. At the first level, the combined design and control problem is solved subject only to the constraints of the design problem. At the second level, the control problem is solved parameterized by the design solution. The solutions found from the bi-level and serial approaches are compared and analyzed.
Author: Vikram S. Shabde
Language: English
Subfield: Food Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2289111183