Low-density Polyethylene Autoclave Reactor Research Articles

CFD modeling for the prediction of molecular weight distribution in the LDPE autoclave reactor: Effects of non-ideal mixing

A commercial Low-density polyethylene (LDPE) reactor was modeled to investigate the effects of highly nonlinear hydrodynamics in an industrial-scale autoclave reactor on the polymer Molecular weight distribution (MWD). To reduce the extremely high computational burden of Computational fluid dynamics (CFD) runs and detailed MWD calculations, a combination of the CFD multicompartment model and probability generating function transformation is proposed. The validity of the proposed model was verified by a comparison with experimental data on industrial equipment. The computation time was shown to be only 37% of the actual operation time. The proposed model showed that strong downflow and weak reverse-flow coexisted to form circulation flow between the disks in the autoclave. Polymerization mainly occurred in the strong downflow region of the tubular regime. The circulation flow increased the accumulation of dead polymers to enhance the chain transfer to polymer, which produces long-branched living polymer chains and termination by recombination for a broad MWD with bimodality. Further analysis based on the simulation without the circulation flow showed a narrow MWD and no bimodality. These results indicate that the flow pattern must be properly controlled to produce polymers with desired properties in large-scale polymerization reactors.

Computational Fluid Dynamics Simulations and Experimental Validation of Macromixing and Flow Characteristics in Low-Density Polyethylene Autoclave Reactors

The macromixing and flow characteristics of a low-density polyethylene autoclave reactor stirred with 32 impellers were investigated by experiments and computational fluid dynamics simulations. The simulation results were validated using the experimental data. The mixing curves show an excellent agreement with the experimental results. The flow field, distribution of velocity, and mass flux obtained from the simulations were further analyzed, and the results show that the reactor can be divided into two reaction zones. In each reaction zone, two axial flows form a big circulation loop. The downward flows near the reactor wall decrease along the flow direction, while the upward flows near the shaft increase. In each big circulation loop there are many small radial circulation loops that are similar to those encountered in continuous stirred-tank reactors. Finally, a more accurate macromixing model was proposed, which is helpful to reveal the multizone phenomenon and flow characteristics in reactors.

Unscented Kalman filter based nonlinear model predictive control of a LDPE autoclave reactor

This paper presents a multivariable nonlinear model predictive control (NMPC) scheme for the regulation of a low-density polyethylene (LDPE) autoclave reactor. A detailed mechanistic process model developed previously was used to describe the dynamics of the LDPE reactor and the properties of the polymer product. Closed-loop simulations are used to demonstrate the disturbance rejection and tracking performance of the NMPC algorithm for control of reactor temperature and weight-averaged molecular weight (WAMW). In addition, the effect of parametric uncertainty in the kinetic rate constants of the LDPE reactor model on closed-loop performance is discussed. The unscented Kalman filtering (UKF) algorithm is employed to estimate plant states and disturbances. All control simulations were performed under conditions of noisy process measurements and structural plant–model mismatch. Where appropriate, the performance of the NMPC algorithm is contrasted with that of linear model predictive control (LMPC). It is shown that for this application the closed-loop performance of the UKF based NMPC scheme is very good and is superior to that of the linear predictive controller.

Mixing effects on performance and stability of low‐density polyethylene reactors

AbstractImperfect initiator mixing greatly affects the stability and efficiency of low density polyethylene (LDPE) autoclave reactors. A combined simulation technique utilizing compartment models and computational fluid dynamics extends previous work in the literature by providing a physically detailed picture of imperfect mixing. Analysis indicates that the effective volume for chain propagation in the autoclave reactor can expand and contract in a continuous fashion as operating conditions change. As mixing becomes poor, the effective reactive volume decreases, causing a reduction in initiator efficiency, but an expansion in the stable operation region. Examples demonstrate that accurate prediction of the effective reaction volume is crucial for predicting LDPE autoclave reactor behavior. A new mixing model that represents the feed plume by a series of interconnected tanks with geometrically increasing volumes provides a favorable tradeoff between accuracy and model complexity. © 2005 American Institute of Chemical Engineers AIChE J, 2005

Prediction of Polymer Properties in LDPE Reactors

AbstractSummary: A new analysis tool is presented that uses the governing kinetic scheme to predict properties of low‐density polyethylene (LDPE) such as the detailed shape of the molecular weight distribution (MWD). A model that captures mixing details of autoclave reactor operation is used to provide a new criterion for the onset of MWD shouldering. Kinetic effects are shown to govern the existence of MWD shoulders in LDPE reactors, even when operation is far from perfectly‐mixed. MWD shoulders occur when the mean reaction environment has a relatively high radical concentration and has a high polymer content, and is at a low temperature. Such conditions maximize long chain formation by polymer transfer and combination‐termination, while limiting chain scission. For imperfectly‐mixed reactors, the blending of polymer‐distributions produced in different spatial locations has a small effect on the composite MWD. However, for adiabatic LDPE autoclaves, imperfect mixing broadens the stable range of mean reactor conditions, and thereby increases the possibility for MWD shouldering.Polymer MWD produced in an LDPE autoclave reactor by various kinetic mechanisms.magnified imagePolymer MWD produced in an LDPE autoclave reactor by various kinetic mechanisms.

A Study of Macrosegregation in Low-Density Polyethylene Autoclave Reactors by Computational Fluid Dynamic Modeling

ADVERTISEMENT RETURN TO ISSUEPREVAddition/CorrectionNEXTA Study of Macrosegregation in Low-Density Polyethylene Autoclave Reactors by Computational Fluid Dynamic ModelingGüray Tosun and André BakkerCite this: Ind. Eng. Chem. Res. 1997, 36, 9, 4013Publication Date (Web):September 2, 1997Publication History Published online2 September 1997Published inissue 1 September 1997https://doi.org/10.1021/ie9708438Copyright © 1997 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views162Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (51 KB) Get e-Alerts Get e-Alerts

Simultaneous optimization of mixing patterns and feed distribution in LDPE autoclave reactors

In this work, a model for simultaneous optimization of mixing patterns and feed distribution in LDPE (Low Density PolyEthylene) reactors is presented. The formulation is based on a a novel technique for optimizing mixing patterns in chemical reactors, resulting in an optimal control formulation which is solved as an NLP. The kinetic model is based on representing the molecular weight distribution by statistical moments.

A Study of Macrosegregation in Low-Density Polyethylene Autoclave Reactors by Computational Fluid Dynamic Modeling

Flow and reaction in a typical commercial scale autoclave LDPE reactor were modeled by a three-dimensional computational fluid dynamic (CFD) k-e model in order to shed light on the macrosegregation effects that can occur in these reactors. It is shown that the CFD model predicts significant differences from CSTR behavior. Results are discussed in terms of the effects of macro- and microscale inhomogeneities of concentration and temperature on free radical polymerization kinetics. The observed nonidealities in terms of minima in the initiator consumption curves and multiple steady states are explained on the basis of competing turbulent transport and chemical kinetics. Microsegregation effects are shown to be negligible in comparison to macrosegregation effects. Given the fact that the CFD model is based on reactive scalar and energy balances without adjusted parameters in the three-dimensional flow field of the entire reactor, it is tentatively concluded that commercial-scale LDPE vessel reactors can have significant macrosegregation effects beyond a certain steady-state adiabatic operating temperature that is specific to the initiator being used.

Modeling and control of an LDPE autoclave reactor

A two-compartment four-cell model is developed for the adiabetic slim type autoclave reactor for free radical polymerization of low density polyethylene (LDPE). It is possible to determine not only the reactor performance represented by the monomer conversion and the reaction temperature but also the properties of the polymer product characterized by the average molecular weight and the polydispersity. It turns out that the reactor performance predicted is in good agreement with the plant data and the properties of the polymer product are estimated within reasonable ranges of actual values. The steady state multiplicity is found to exist and is examined by constructing the bifurcation diagram. The effects of various operation parameters on the reactor performance and the polymer properties are investigated systematically to show that the temperature distribution plays the central role for the properties of the polymer products. Therefore, it is essential to establish a good control strategy for the temperature in each compartment. The adaptive pole-placement control algorithm is applied to the temperature control of the adiabatic slim type autoclave reactor. The recursive least square method is used for the model identification. To accomplish a satisfactory control, the estimator and controller are initialized during the period of start-up. It is shown that the reactor system can be adaptively controlled by the pole-placement control algorithm, especially when the reactor temperature distribution is changed.

Dynamic flowsheet modeling of polymerization processes using POLYRED

Some of the features of the dynamic flowsheeting package, POLYRED, are described. To demonstrate some of the capabilities of the package, POLYRED is used to formulate models and to estimate model parameters from both batch and continuous process data. Examples include the complications of imperfect micromixing which require mixing models. Both kinetic and micromixing parameters are estimated from data. Results for a low-density polyethylene autoclave reactor are provided as an illustration.