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ABSTRACT: Previously, Ward et al. [Ward, J. D.; Doherty, M. F.; Yu, C. C. Plantwide Operation and Control of Processes with Crystallization. AIChE J. 2007, 53, 2885−2896] published a novel shortcut method for predicting how process operation will be affected by the choice of control structure for a plant with reaction, crystallization, and recycling. The analysis assumed the presence of a continuous filter but did not model its operation. In this article, we introduce an analogous dimensionless model for a continuous rotary drum filter and show that a similar methodology can be used to predict the behavior of a combined crystallizer and filter, and a reactor, crystallizer, filter, and recycle circuit. We show the effect of the crystallizer operating policy on the operation of the filter and show that the overall operation of the combined plant can be predicted for a given choice of controlled variables. This facilitates the screening of control structures by rapid elimination of control structures that are likely to lead to infeasible or uneconomic modes of operation.
05/2010;
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ABSTRACT: Recently Ward et al. [Ward, J. D., Doherty, M. F., & Yu, C. C. (2007). Plantwide operation and control of processes with crystallization. AIChE Journal, 53, 2885–2896] presented new shortcut expressions for the steady-state operation of plantwide processes with crystallization. The method allows the engineer to predict the steady-state gain between the production rate and certain other key process variables for various choices of controlled variables. The result is a simple analytical model that shows how the process operates for various choices of control structure. The previous work of Ward et al. considered only steady-state process operation. In this contribution we apply the method and results from our previous work to develop plantwide control structures, and test the structures using a rigorous non-linear dynamic process model. We demonstrate that the method produces workable plantwide control structures, and that the steady-state behavior of the dynamic process is consistent with the predictions of our previous work.
Computers & Chemical Engineering. 01/2010;
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ABSTRACT: Simple analytical expressions are developed to model the steady-state operation of a chemical plant with a continuous crystallizer. The equations show analytically how uncontrolled variables change with the changing production rate depending on the values of key kinetic parameters and the choice of controlled variables. Because the results are derived, their validity and limitations are more apparent than heuristics that are suggested based on case studies. Furthermore, because the equations are simple and analytic, it is possible to develop insight and understanding about the behavior of the process. Finally, these results can be readily taught to process engineers and used to rapidly screen alternative control structures for operability problems. Results are illustrated with a case study process to produce adipic acid. © 2007 American Institute of Chemical Engineers AIChE J, 2007
AIChE Journal 10/2007; 53(11):2885 - 2896. · 2.26 Impact Factor
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ABSTRACT: In this work we develop, demonstrate, and distribute the code for a new Simulink block that models the dynamic evolution of the population density function for a physical system which can be modeled by a population balance equation. The name of the block is PCSS, for population balance modeling using the conservation element/solution element method in Simulink. The block interfaces with an auxiliary user-defined function that allows the user to specify arbitrary expressions for growth and generation/loss terms, as well as an arbitrary number of inputs, outputs and auxiliary states for the block. The versatility of the block allows a wide variety of physical systems to be modeled, and the implementation in Simulink facilitates rapid model development and permits the use of pre-existing MATLAB/Simulink packages for system identification and control.
Computers & Chemical Engineering.
