Simulation of single- and multiproduct batch chemical plants for optimal design and operation

Rippin, D.W.T.

doi:10.1016/0098-1354(83)85016-9

Cited by 119 publications

(51 citation statements)

References 15 publications

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“…Increased competition has motivated the interest in mathematical modeling, optimization, and advanced process control techniques that enable the operation of flexible high-performance pro-Ž . duction lines Le Lann et al, 1999;Rippin, 1983 . Advanced control techniques have the potential to improve perfor-Ž mance.…”

Section: Introductionmentioning

confidence: 99%

Robust nonlinear model predictive control of batch processes

2003

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Section: Introductionmentioning

confidence: 99%

Robust nonlinear model predictive control of batch processes

2003

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“…6, represents the speciÿc production as a function of the cycle time for a speciÿc control policy. The curve is suitable to determine the maximal performance of batch processes (Rippin, 1983). It can be calculated by simulations, but can also be derived from experiments when the parameters are unknown.…”

Section: Areas Of Optimal Mode Of Operationmentioning

confidence: 99%

Optimal mode of operation for biomass production

Betlem

Mulder

Roffel

2002

Chemical Engineering Science

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The rate of biomass production is optimised for a predeÿned feed exhaustion using the residue ratio as a degree of freedom. Three modes of operation are considered: continuous, repeated batch, and repeated fed-batch operation. By means of the Production Curve, the transition points of the optimal modes of operation are derived. The analytical expressions of these transitions for variable bioreaction kinetic parameters are determined. The key measures "degree of di culty of conversion" and "degree of exhaustion" are introduced to deÿne the optimal modes in more general terms. The "degree of di culty" describes the e ect of the kinetic parameters and the feed substrate concentration on the conversion; the "degree of exhaustion" describes the desired ÿnal condition. In fed-batch operation, the proposed constant feed policy approximates the optimal feed policy closely. ?

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“…Axial dispersion is due to molecular diffusion, turbulence and nonuniformity of the velocity profile. It is thus a key factor when reactions with selectivity issues are considered [15,16]. This dimensionless number quantifies the difference between a perfect stirred reactor and a plug flow reactor.…”

Section: Rtd Experimentsmentioning

confidence: 99%

Pressure drop and axial dispersion in industrial millistructured heat exchange reactors

Moreau

Raimondi

Sauze

et al. 2015

Chemical Engineering and Processing: Process Intensification

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A B S T R A C THydrodynamic characterization by means of pressure drop and residence time distribution (RTD) experiments is performed in three millistructured heat exchange reactors: two Corning reactors (further referred to as Corning HP and Corning RT) and a Chart reactor. Pressure drop is measured for different flow rates and fluids. Fanning friction factor is then calculated and its evolution versus Reynolds number is plotted for each reactor, showing the influence of the geometrical characteristics of the reactors on this parameter. From RTD experiments, axial dispersion coefficients that allow calculating Péclet numbers are identified by solving the convection-dispersion equation. The results highlight plug flow behavior of these reactors for the range of flow rates studied. Péclet number in Corning HP remains constant in the range of Reynolds number studied. Its specific pattern is designed to generate mixing structures that allow homogenization of the tracer over the cross-section. It explains the plug flow behavior of this reactor even at low Reynolds number but generates high pressure drop. Péclet number in Corning RT and Chart ShimTec 1 increases with Reynolds number. This evolution is encountered for straight circular pipes in turbulent regime and confirms the pressure drop analysis.

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Simulation of single- and multiproduct batch chemical plants for optimal design and operation

Cited by 119 publications

References 15 publications

Robust nonlinear model predictive control of batch processes

Robust nonlinear model predictive control of batch processes

Optimal mode of operation for biomass production

Pressure drop and axial dispersion in industrial millistructured heat exchange reactors

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