Plantwide operation of processes with crystallization

Ward, Jeffrey D.; Yu, Cheng‐Ching; Doherty, Michael F.

doi:10.1002/aic.11308

Cited by 16 publications

(20 citation statements)

References 15 publications

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“…The inspiration for this approach is that comprehensive knowledge and experiences are available for controlling the major unit operations. Control design for special unit operations has been the subject of academic and industrial research, (e.g., Ward, et al 2007;Ward, et al 2010;Skogestad 1988Skogestad , 2007Hori and Skogestad, 2007). Although the approach based on combining unit-wise control structures for individual unit operations ignores the plant-wide interactions among them, still this method has wide industrial applications.…”

Section: Complexity Reduction Based On Process Componentsmentioning

confidence: 99%

Integration of process design and control: A review

Sharifzadeh

2013

Chemical Engineering Research and Design

116

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There is a large variety of methods in literature for process design and control, which can be classified into two main categories. The methods in the first category have a sequential approach in which, the control system is designed, only after the details of process design are decided. However, when process design is fixed, there is little room left for improving the control performance. Recognizing the interactions between process design and control, the methods in the second category integrate some control aspects into process design. With the aim of providing an exploration map and identifying the potential areas of further contributions, this paper presents a thematic review of the methods for integration of process design and control. The evolution paths of these methods are described and the advantages and disadvantages of each method are explained. The paper concludes with suggestions for future research activities. KeywordsIntegrated design and control, Sequential design and control, Control structure selection, Simultaneous optimization of a process and its controllers, inversely controlled process model, controllability.

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Section: Complexity Reduction Based On Process Componentsmentioning

confidence: 99%

Integration of process design and control: A review

Sharifzadeh

2013

Chemical Engineering Research and Design

116

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“…Other related quantities must use the same basis for consistency; i.e., the volumetric flow rate out of the crystallizer q must have units of (kg solvent)/ s, (m 3 clear solution)/s, or (m 3 suspension)/s, respectively. The previous results of Ward et al 6 do not depend on any particular basis and will work regardless of basis as long as that basis is used consistently. In the present work, however, the equation for the filter model is only strictly valid if the volume of clear solution is used as a basis, as demonstrated in the following derivation of eq 14.…”

Section: Appendix A: Note On Concentration Basis and Filter Model Equmentioning

confidence: 88%

“…More details can be found in Ward et al 6 and in the Webpublished supplement to that paper. Table 8 shows certain key process parameters related to the operation of the crystallizer and filter.…”

Section: Appendix B: Adipic Acid Case Studymentioning

confidence: 94%

“…The resulting sensitivity parameter k sen is shown in Table 2 for changes in the production rate, Table 3 for changes in the average crystal size, and Table 4 for changes in clear liquid flow rate. Figure 3 shows the steady-state behavior of the adipic acid process (Ward et al 6 ) for changes in the production rate, average crystal size, and clear liquid flow rate. When the expected behavior is nonlinear, the linear approximation is shown by a dashed line.…”

Section: Filter Operationmentioning

confidence: 99%

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Analytical Design and Operation of Systems with Crystallization, Filtration, and Recycling

Ward

Doherty

2010

Ind. Eng. Chem. Res.

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Previously, Ward et al. [Ward, J. D.; Doherty, M. F.; Yu, C. C. Plantwide Operation and Control of Processes with Crystallization. AIChE J. 2007AIChE J. , 53, 2885AIChE J. -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.

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“…The system’s steady state in population balance models is frequently studied for nucleation and crystal growth processes . In the cell duplication context, cell cycle phases may reach steady state with respect to the percentage of cells in each phase ( G % , S % , M % ) but not in the phases themselves (G, S, M) as the absolute count will increase over time as a result of doubling.…”

Section: Model Definitionsmentioning

confidence: 99%

Selecting a Differential Equation Cell Cycle Model for Simulating Leukemia Treatment

Fuentes-Garí¹,

Misener²,

Georgiadis³

et al. 2015

Ind. Eng. Chem. Res.

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This manuscript studies three differential equation models of the leukemia cell cycle: a population balance model (PBM) using intracellular protein expression levels as state variables representing phase progress; a delay differential equation model (DDE) with temporal phase durations as delays; and an ordinary differential equation model (ODE) of inter-phase progression. In each type of model, global sensitivity analysis determines the most significant parameters while parameter estimation fits experimental data. In order to compare models based on the output of their structural properties, an expected behavior was defined, and each model was coupled to a pharmacokinetic/pharmacodynamic model of chemotherapy delivery. Results suggest that the particular cell cycle model chosen highly affects the simulated treatment outcome, given the same steady state kinetic parameters and drug dosage/scheduling. The manuscript shows how cell cycle models should be selected according to the complexity, sensitivity and parameter availability of the application envisioned.2

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Plantwide operation of processes with crystallization

Cited by 16 publications

References 15 publications

Integration of process design and control: A review

Integration of process design and control: A review

Analytical Design and Operation of Systems with Crystallization, Filtration, and Recycling

Selecting a Differential Equation Cell Cycle Model for Simulating Leukemia Treatment

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