Dynamic modeling of suspension crystallizers, using experimental data

Eek, R.A.; Dijkstra, S.; Rosmalen, G.M. van

doi:10.1002/aic.690410315

Cited by 60 publications

(24 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using the system identification data, we verified the nonlinear process model described in Eek et al (1995a). It was found that the model with parameters estimated from startup experiments already gave a good description of the data.…”

Section: Comparison With the First-principles Modeling Approachmentioning

confidence: 91%

“…Simulations with the nonlinear first-principles model described in Eek et al (1995a) revealed that stability of the CSD can easily be obtained by applying a SISO PI-control loop, which uses the first principal component of the sensor 2 , output vector y,, as its input and the fines removal rate Q, as its output. The feedback control configuration applied here is depicted in Figure 5.…”

Section: Design Of a Stabilizing Controllermentioning

confidence: 99%

“…Miller and Rawlings (1994) present results on parameter estimation within a firstprinciples model structure, including a method for the estimation of confidence intervals, based on batch crystallization experiments. In earlier work (Eek et al, 1995a), results from first-principles modeling of continuous crystallizers and the estimation of empirical parameter values on the basis of start-up experiments are presented. The experimental data sets were obtained from the free start-up responses of a pilot crystallizer.…”

Section: Introductionmentioning

confidence: 99%

“…March 19% (Eek et al, 1995a). The process considered for identification has three output quantities that directly relate to the population density.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Closed‐loop identification of a continuous crystallization process

1996

View full text Add to dashboard Cite

show abstract

Section: Comparison With the First-principles Modeling Approachmentioning

confidence: 91%

Section: Design Of a Stabilizing Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…March 19% (Eek et al, 1995a). The process considered for identification has three output quantities that directly relate to the population density.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Closed‐loop identification of a continuous crystallization process

1996

View full text Add to dashboard Cite

show abstract

“…For supersaturated conditions, two different kinetic models will be applied: Eek kinetics [1] and Ó Meadhra kinetics [9]. A diffusioncontrolled model previously used by Jager [7] will be applied for undersaturated conditions.…”

Section: Growth and Dissolutionmentioning

confidence: 99%

Modelling the Settling, Dissolution and Non-Uniform Nucleation Kinetics in a 150-Litre Forced Circulation Crystallizer

Bermingham

Neumann

Muusze

et al. 1998

Part. Part. Syst. Charact.

View full text Add to dashboard Cite

Experiments on a pilot-scale 150-litre forced circulation crystallizer with external circulation flow rates of 2 and 3 l/s revealed a high sensitivity of the product crystal size distribution for this operational variable. It is believed that a change in the circulation flow rate influences (1) the nucleation rate, which is mainly caused by the mechanical action of the pump, (2) the degree of internal dissolution in the heat exchanger and (3) the settling of the larger crystals in the crystallizer body. This paper presents a modelling framework which allows for a mechanistic description of growth and dissolution, attrition and secondary nucleation and settling. Such a description is seen as a prerequisite for the development of crystallization models with a predictive value for different operational conditions or for another scale of operation. Growth, attrition and nucleation kinetics are modelled using relationships from both Eek [1] and Ó Meadhra [2], whereas a diffusioncontrolled model is applied to describe size-dependent dissolution kinetics. The settling behaviour of crystals is described using Stokes law combined with Richardson-Zaki's equation for hindered settling. From the simulation results it can be concluded that the modelling framework presented here is capable of qualitatively predicting the effects of a change in the circulation flow rate. The quantitative predictions of the median crystal size are within 15% of the experimental values, whereas the oscillations predicted during start-up show a far larger deviation from the experimental results.

show abstract