Nonlinear model reduction of a continuous fluidized bed crystallizer, Journal of Computational and Applied Mathematics (2015), http://dx.
AbstractThis work considers a system of a fluidized bed crystallizer and a ultrasonic attenuator, which separates an enantiomer from a liquid solution. A population balance model of the system shows autonomous oscillations over a wide range of operation conditions. Proper orthogonal decomposition is applied to obtain nonlinear reduced models of low order. An a posteriori error estimator is used to assess the quality of the reduced model during run time.
Continuous selective crystallization using mixed suspension mixed product removal (MSMPR) crystallizers is an attractive method for separating enantiomers. Recent experimental results confirm the feasibility of the approach, but also indicate that the operation conditions for nominal operation lie in a rather small window. A systematic analysis and an optimal design are needed to exploit the full potential of the method. In this contribution, a mathematical process model based on population balance equations is presented. In contrast to other studies in literature, the considered crystallizer is not a stirred tank, but has a conical shape that requires a spatially distributed model formulation. Parameter studies identify the key operation and design parameters for maximizing the mass of the product crystals and for shaping their size distribution. The proposed model focuses on geometrical and fluid-dynamic aspects, but at the current stage does not include purity aspects.
In the process design of chemical production plants, dynamic simulation plays an important role. This paper gives a short introduction to the process modeling tool ProMoT and the simulation tool Diana. Both are open‐source programs intended for the dynamic analysis of chemical engineering and biological systems. They support the implementation and analysis of large nonlinear differential algebraic systems. An overview is given on the functionality of ProMoT and Diana. The use of the tools is illustrated by their application to an innovative fluidized bed crystallization process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.