Reactor Residence Time Distribution Research Articles

Assessment of the impact of reactor residence time distribution on non-equilibrium product selectivity of polypropylene pyrolysis using reactive molecular dynamics simulations

Mass residence time distribution (RTD) is considered to be an important factor controlling the product selectivity in the pyrolysis of biomass and plastic wastes along with the pyrolysis chemistry. However, due to the complex pyrolysis chemistry of biomass and plastic waste, the coupling between the reaction chemistry, RTD, and product selectivity is challenging to understand. We introduce a reaction molecular dynamics-based method to examine pyrolysis chemistry and species timescales to assess the impact of RTD on product selectivity and yield. To validate this method, reactive molecular dynamics simulations were conducted for polypropylene pyrolysis and its non-equilibrium product selectivity using 6 different RTDs. We find that the RTD and the reaction chemistry control the peak non-equilibrium product concentrations. The peak monomer (C3H6) concentration during pyrolysis can be increased by up to 25 % by using a narrow RTD in the case of polypropylene pyrolysis. We also find that product selectivity is strongly affected by the average residence time and RTD. This coupling between the reaction chemistry, RTD, and product selectivity highlights the need to understand detailed reaction chemistry to control RTD and optimize non-equilibrium product selectivity during polymer and biomass pyrolysis. The present method provides a new way to design RTD for reactors to reach maximized product selectivity of plastic waste and biomass.

A conceptual multilevel approach to polyolefin reaction engineering

AbstractThis article gives a wide overview of different types of mathematical models that can be used to describe the polymerization of linear olefins with coordination catalysts. We expanded the conventional classification of mathematical models into micro‐, meso‐, and macroscale, to include seven modelling levels: catalysis, polymerization kinetics, thermodynamic equilibrium, particle transport phenomena, particle interactions, reactor fluid dynamics, and reactor residence time distribution. Some of these levels may coexist at the same scale, but they are better treated separately because they make use of distinct modelling approaches. How complex the models in each level need to be, as well as how many modelling levels should beimplicitlyincluded, depends on the type of application intended for the simulations. In this paper, we will argue that the proposed levels of mathematical modelling not only bring to our attention the complexity behind the simulation of laboratory‐ and industrial‐scale olefin polymerization reactors but are also useful conceptual tools to assist us to decide which levels to include and which ones to exclude when we develop simulation packages to describe olefin polymerization processes.

Exploring the use of flow cytometry for understanding the efficacy of disinfection in chlorine contact tanks

A pilot scale chlorine contact tank (CCT) with flexible baffling was installed at an operational water treatment plant (WTP), taking a direct feed from the outlet of the rapid gravity filters (RGF). For the first time, disinfection efficacy was established by direct microbial monitoring in a continuous reactor using flow cytometry (FCM). Disinfection variables of dose, time, and hydraulic efficiency (short circuiting and dispersion) were explored following characterisation of the reactor's residence time distributions (RTD) by tracer testing. FCM enabled distinction to be made between changes in disinfection reactor design where standard culture-based methods could not. The product of chlorine concentration (C) and residence time (t) correlated well with inactivation of microbes, organisms, with the highest cell reductions (N/N0) reaching <0.025 at Ctx¯ of 20 mg.min/L and above. The influence of reactor geometry on disinfection was best shown from the Ct10. This identified that the initial level of microbial inactivation was higher in unbaffled reactors for low Ct10 values, although the highest levels of inactivation of 0.015 could only be achieved in the baffled reactors, because these conditions enabled the highest Ct10 values to be achieved. Increased levels of disinfection were closely associated with increased formation of the trihalomethane disinfection by-products. The results highlight the importance of well-designed and operated CCT. The improved resolution afforded by FCM provides a tool that can dynamically quantify disinfection processes, enabling options for much better process control.

Slurry-phase ethylene polymerization processes: a review on multiscale modeling and simulations

Abstract Slurry polymerization processes using Zeigler–Natta catalysts, are most widely used for the production of polyethylene due to their several advantages over other processes. Significant advancements have been made in the modeling of these processes to obtain high-quality final products. The modeling work in this field has a very wide scope due to the great diversity of the catalyst types, polymerization processes, polymerization conditions, product qualities and microstructures that exist at the commercial scale. In this article, we have reviewed and discussed the slurry polymerization processes for the production of polyethylene and the multiscale modeling and simulation framework in slurry reactors. The multiscale modeling framework mainly comprises of the kinetic model, single-particle diffusion models, multiphase hydrodynamics, phase equilibria, reactor residence time distribution and the overall mass and heat balances. Guidelines to implement the multiscale mathematical modeling and simulation in slurry-phase olefin polymerization processes are proposed. Special focus is given on the need to reduce the computational effort for the simulation of industrial reactors so that the models can be used as an effective tool-kit for optimization studies using state-of-art algorithms.

Development of an Integrated Framework for Multiscale, Multiphase Modeling of Industrial Slurry‐Phase Reactors for Polyethylene Production

AbstractA framework based on the Monte Carlo/random‐pore polymeric flow model is proposed to simulate both single‐particle and continuous slurry reactor industrial polymerizations. The Sanchez–Lacombe equation of state describes the distributions of components in the different phases of these systems. The developed process model is applied to describe heterogeneously catalyzed polymerizations of ethylene in n‐hexane diluent with or without 1‐hexene as a comonomer, but the proposed methodology is applicable to any ethylene/1‐olefin copolymerization in slurry reactors. In addition to the effects of catalyst particle size and reactor residence time distributions, the proposed hybrid model is used to investigate the impact of several catalyst characteristics under different process conditions on polymer yield and microstructure. Particular attention is paid to the catalyst fragmentation process and active center distribution through the particle. These simulations demonstrate the versatility and thoroughness of combining Monte Carlo simulation with single‐particle models to analyze and predict the behavior of commercial polyolefin reactors.

Continuous Solvent/Detergent Virus Inactivation Using a Packed-Bed Reactor.

Continuous virus inactivation (VI) remains one of the missing pieces while the biopharma industry moves toward continuous manufacturing. The challenges of adapting VI to the continuous operation are two-fold: 1) achieving fluid homogeneity and 2) a narrow residence time distribution (RTD) for fluid incubation. To address these challenges, a dynamic active in-line mixer and a packed-bed continuous virus inactivation reactor (CVIR) are implemented, which act as a narrow RTD incubation chamber. The developed concept is applied using solvent/detergent (S/D) treatment for inactivation of two commonly used model viruses. The in-line mixer is characterized and enables mixing of the viscous S/D chemicals to ±1.0% of the target concentration in a small dead volume. The reactor's RTD is characterized and additional control experiments confirm that the VI is due to the S/D action and not induced by system components. The CVIR setup achieves steady state rapidly before two reactor volumes and the logarithmic reduction values of the continuous inactivation process are identical to those obtained by the traditional batch operation. The packed-bed reactor for continuous VI unites fully continuous processing with very low-pressure drop and scalability.

Modification of a pilot-scale continuous flow reactor for hydrothermal liquefaction of wet biomass

A pilot-scale continuous flow reactor (CFR) was modified for hydrothermal liquefaction (HTL) of algae slurry under subcritical conditions to investigate the feasibility of scaling up from batch to continuous processing. Modifications included a novel dual filter system that can remove solids at system pressure and temperature, and undergo in-situ cleaning. Commissioning was carried out to address potential particle settling and clogging problems, and to estimate reactor transport characteristics. CFR performance was evaluated by running 31.4 L algae slurry with solids loadings of 3−5 wt.% under 325−350 °C and 18 MPa for 7 h. C and N elemental yields in HTL aqueous phase reached 39.0 wt.% and 61.8 wt.%, respectively. Future improvements to the CFR system will focus on higher solids loading and addition of in-line HTL liquid upgrading capabilities following the filtration system.•A high-temperature, high-pressure filtration system was designed to remove solids from HTL liquid/gaseous products at near reaction conditions to keep heavy oils in the liquid phase.•Uninterrupted reactor operation was achieved by cycling between the dual filter systems and performing in-situ filter cleaning.•Measured reactor residence time distributions were narrow and close to the calculated theoretical mean time.

A Monte Carlo Method to Quantify the Effect of Reactor Residence Time Distribution on Polyolefins Made with Heterogeneous Catalysts: Part III—Particle Composition Distribution Effects

AbstractPolymer reactor blends, such as bimodal polyethylene or high‐impact polypropylene, are usually produced in multistep processes using two or more reactors in series. Since the polymer particles are subject to reactor residence time distributions (RTD) during the polymerizations, the fractions of the polymer populations made in each reactor will vary from particle to particle. It is shown in the previous publications in this series that reactor RTD has a marked effect on the particle size distribution and on the packing density of polyolefin particles. In this article, the versatile Monte Carlo model is extended to demonstrate how reactor RTD affects particle composition and molecular weight distributions of polyolefin reactor blends made in multistep processes. Increasing the number of reactors in series favors the homogeneity of the product. Moreover, the average fraction of the different polymer populations in the particles depends strongly on the mean reactor residence time and polymerization kinetics.

A Monte Carlo Method to Quantify the Effect of Reactor Residence Time Distribution on Polyolefins Made with Heterogeneous Catalysts: Part IV—Intraparticle Transfer Resistance Effects

AbstractAn integrated Monte Carlo/polymeric multilayer model (MC/PMLM) is developed to predict the polymer particle size distribution (PSD) and microstructures of polyolefins made with heterogeneous catalysts under intraparticle mass transfer limitations. The Monte Carlo model is used to randomly sample particle sizes and residence times from the catalyst PSD and reactor residence time distribution (RTD), respectively, while the polymeric multilayer model is used to describe single‐particle growth considering intraparticle mass transfer resistances. The effect of reactor RTD, catalyst PSD, and polymerization kinetics on polymer PSD and polymer properties is systematically investigated with the MC/PMLM for the first time. The results show that intraparticle mass transfer limitations under various operating conditions may affect polymer PSD and polymer properties. In addition, due to the versatility of the Monte Carlo approach, the proposed MC/PMLM is adequate to describe complex cases, such as reactor systems with arbitrary RTD and catalyst particles having any PSD.

A Monte Carlo Method to Quantify the Effect of Reactor Residence Time Distribution on Polyolefins Made with Heterogeneous Catalysts: Part II ‐ Packing Density Effects

The residence time distribution of reactors used to produce polyolefins commercially has a significant impact on many of their properties. This effect often goes unnoticed, since the concept of reactor residence time is often poorly understood even among chemical engineers. In the first part of this series of articles, it is shown how the reactor residence time distribution has a marked impact on the particle size distribution of polyolefin particles using a new Monte Carlo model. In this article, the Monte Carlo model is combined with a drop and roll algorithm to predict how reactor residence time distribution affects the packing density of the polyolefin particles.

Modelling the synthesis of nanoparticles in continuous microreactors: The role of diffusion and residence time distribution on nanoparticle characteristics

A mathematical model for the liquid-phase synthesis of spherical nanoparticles in continuous flow micro- and milli-reactors was developed, accounting for residence time distributions (RTD). These distributions were derived for the reactants and the particles involved in the synthesis. The kinetic parameters needed to describe the reactions were calculated from experimental data available in the literature from batch reactors, with the aid of population balance modelling. They were subsequently used, without further modification, to simulate the synthesis in flow reactors via population balance modelling, averaging the nanoparticle properties at the reactor outlet using the reactor RTDs. The model was employed to describe the synthesis of silica nanoparticles as a case study, and validated against flow reactor results from the literature. The results demonstrate direct RTD effects and indirect diffusion-induced effects on the evolution of the particle size distribution during the flow synthesis. The former are created by the inherent widening of the RTDs, due to the different residence time experienced by each fluid element, leading to a broadening of the particle size distribution. The latter are induced by the difference in diffusivity between nanoparticles and liquid reactants, which leads to different dispersion processes in the reactor for the different components of the reaction mixture. These effects appear as the major cause of particle size distribution difference between (single phase) flow and batch syntheses.

The Effect of Residence Time Distribution on the Slurry‐Phase Catalytic Ethylene Polymerization: An Experimental and Computational Study

AbstractThis work is focused on the development and validation of a model accounting for the impact of the reactor residence time distribution in well‐stirred slurry‐phase catalytic polymerization of ethylene. Particle growth and morphology are described through the Multigrain model, adopting a two‐site model for the catalyst and a conventional kinetic scheme. Particle size distribution and polymer properties (average molecular weights and polydispersity) are computed as a function of particle size through a segregated model, assuming that neither breakage nor aggregation occur. Reactors are modeled by means of fundamental mass conservation equations. The model is applied to a system constituted by a series of two ideal continuous stirred tank reactors, where the synthesis of polyethylene with bimodal molecular weight distribution is performed, employing the initial catalyst size distribution as the only adjustable parameter. The model provides insights at the single particle scale for each specific size, thus highlighting the inhomogeneity which arises from the synergic effects of chemical kinetics and residence time distributions in both reactors. The satisfactory agreement between model results and experimental data, in terms of particle size distribution and average molecular weights, confirmed the suitability of the model and underlying assumptions.

Modeling residence-time distribution in horizontal screw hydrolysis reactors

The dilute-acid thermochemical hydrolysis step used in the production of liquid fuels from lignocellulosic biomass requires precise residence-time control to achieve high monomeric sugar yields. Difficulty has been encountered reproducing residence times and yields when small batch reaction conditions are scaled up to larger pilot-scale horizontal auger-tube type continuous reactors. A commonly used naive model estimated residence times of 6.2–16.7 min, but measured mean times were actually 1.4–2.2× the estimates. This study investigated how reactor residence-time distribution (RTD) is affected by reactor characteristics and operational conditions, and developed a method to accurately predict the RTD based on key parameters. Screw speed, reactor physical dimensions, throughput rate, and process material density were identified as major factors affecting both the mean and standard deviation of RTDs. The general shape of RTDs was consistent with a constant value determined for skewness. The Péclet number quantified reactor plug-flow performance, which ranged between 20 and 357.

A Monte Carlo Method to Quantify the Effect of Reactor Residence Time Distribution on Polyolefins Made with Heterogeneous Catalysts: Part I—Catalyst/Polymer Particle Size Distribution Effects

AbstractPolyolefins are commercially produced in continuous reactors that have a broad residence time distribution (RTD). Most of these polymers are made with heterogeneous catalysts that also have a particle size distribution (PSD). These are totally segregated systems, in which the catalyst/polymer particle can be seen as a microreactor operated in semibatch mode, where the reagents (olefins, hydrogen, etc.) are fed continuously to the catalyst/polymer particle, but no polymer particle can leave. The reactor RTD has a large influence on the PSD of the polymer particles leaving the reactor, as well as in polymer microstructure and properties, polymerization yield, and composition of reactor blends. This article proposes a Monte Carlo model that can describe how particle RTD in a single or a series of reactors can affect the PSD of polymer particles made under a variety of operation conditions. It is believed that this is the most flexible model ever proposed to model this phenomenon, and can be easily modified to track all properties of interest during polyolefin production in continuous reactors with heterogeneous catalysts.

Evaluation and modeling of a spinning disc photoreactor for degradation of phenol: Impact of geometry modification

Abstract A new spinning disc photoreactor with two different designs employing baffles in its structure for degradation of phenol was studied and compared with conventional ones. TiO2 was successfully immobilized on stainless steel disc and Teflon baffles. X-ray diffraction, scanning electron microscopy, field emission scanning electron microscopy and transmission electron microscopy analysis were performed in order to give information on the crystal phase and structure of both TiO2 coatings and size of particles. The wettability of the photocatalyst film on the disc surface was evaluated by contact angle test. The results have demonstrated that complete phenol removal was achieved using baffles after 180 and 150 min of reaction time, which was 60 and 90 min faster than the reactor with smooth disc under optimum condition of the reactor (rotational speed = 290 rpm, flow rate = 2000 mL/min, disc diameter = 22 cm). Influence of rotational speed for smooth and baffled discs was studied. Results indicated that there was no considerable mass transfer limitation for new designs above approximately 150 rpm. For description of flow regime in the reactor residence time distribution (RTD) measurements was performed experimentally. According to RTD data, reactor was accurately modeled using tanks-in-series model. The estimated equivalent number of tanks-in-series in baffled discs were 8 and 10 compared to 4 for smooth disc. The Langmuir-Hinshelwood (L-H) kinetic model was combined with hydrodynamic model for prediction of degradation of phenol and rate coefficients. Predicted results were in agreement with experimental data.

The Maximum Mixedness Model Applied with Detailed Reaction Mechanisms

Abstract The Zwietering maximum mixedness model (MMM) is extended for use with detailed chemical reaction mechanisms in a combustion setting. Both MMM species and energy balances are offered with a Chemkin-consistent nomenclature. The solution algorithm is discussed. Several reactor residence time distributions are currently offered for use with the MMM program. The MMM is used here to simulate observed literature species concentration data in a turbulent, jet-stirred combustor. For comparison, the results are also compared to simulations from perfectly stirred reactor (PSR) and partially stirred reactor (PaSR) models. The MMM model predicts the observed higher-than-PSR fuel conversions using a residence time distribution based on two unequal CSTRs-in series.

Polymer Reaction Engineering in China

Polymer Reaction Engineering in China

Modeling flow and residence time distribution in an industrial-scale reactor with a plunging jet inlet and optional agitation

The quantified residence time distribution (RTD) provides a numerical characterization of mixing in a reactor, thus allowing the process engineer to better understand mixing performance of the reactor. Many reactors are mixing-limited and/or mass-transfer limited and micro-mixing can be the critical element in contrast to RTD which addresses the macro-mixing. This paper discusses computational and experimental studies to investigate flow patterns in an industrial-scale (110m3) continuous reactor employing a three-stage agitation system with a plunging jet inflow. In operation, the agitation and liquid level are adjusted based on throughput and the specific product being produced. The objective of this study was to quantify RTD under different operating conditions of liquid level, throughput and agitation.Flow in the reactor was modeled with computational fluid dynamics (CFD). A unique coupling of different modeling approaches was developed. The volume of fluid (VOF) method was used to model the plunging jet with transient simulations, while the multiple reference frames (MRF) model was used to model the stirred tank with steady-state simulations. To account for the effect of gas entrainment due to the plunging jet impingement, the two modeling approaches were interfaced by using the plunging jet modeling result as an input boundary condition for the reactor flow simulation. Without mechanical agitation in the reactor, the plunging jet was a dominant feature of the hydraulics. An unexpected anomaly in CFD-predicted flow patterns was tested against and found to be in good agreement with laboratory-scale flow experiments, including local instability when the agitator was not adequately submerged. The reactor RTD was obtained from stochastic particle tracking which tracks residence times of massless tracers through the reactor. The random walk model was used for dispersion due to turbulent eddies. A large number of tracers were used to account for the random effects of turbulence and to ensure statistically significant results. The predicted mean residence times were consistent with the bulk reactor space times.

On the residence time distribution in reactors with non-uniform velocity profiles: The horizontal stirred bed reactor for polypropylene production

Horizontal stirred bed reactors for polypropylene production have a typical axial powder mixing pattern which is unique for polyolefin gas-phase reactors. The polymer, although adhering to the catalyst particles, has a shorter mean residence time and a broader residence time distribution than the catalyst. Both polymer and catalyst residence time distributions, strongly depend on the temporal catalyst activity profile. The powder mixing pattern in a horizontal stirred bed reactor results from two transport effects: the continuously increasing powder net flow in the downstream direction caused by the particle growth, and the simultaneous stirring flows with equal intensity in the up- and downstream directions. Both together lead to a residence time distribution of the reacting catalyst particles between fully backmixed and plug flow. A modelling approach is proposed which describes the axial flow contributions of stirring and polymerisation separately, and which is more accurate and flexible than simple cells-in-series models used in most papers so far. For large-scale reactors, residence time distributions are predicted from experimental pulse–response curves obtained in a miniaturised mixing model without reaction. Residence time distributions equivalent to “three to five” well-mixed reactors in a series reported in the literature are experimentally accessible only with difficulties under polymerising conditions. With the modelling approach proposed in this paper, the “reacting” RTD can be calculated on the basis of the cold-flow experimental data. We compare the proposed modelling concept with simple cells-in-series models by simulating catalyst yields, particle size distributions and catalyst transitions using two model catalysts with different activity profiles. The selection of the right modelling approach has indeed a significant influence on the simulation results, especially if the throughput or the axial velocity profile is changing and the catalyst is not deactivating.

Sample Pulse Broadening in Taylor Flow Microchannels for Screening Applications

AbstractThe effect of different parameters on the residence time distribution of a Taylor flow microreactor was investigated. The reactor residence time distribution was calculated from the tracer residence time distribution of a single unit cell. It was found that generally an increase in Bodenstein number, capillary number or slug length increased the spread of the residence times. A case study comparing the effect of two different sets of design and operating parameters on the distribution spread showed that spreading can be minimized by careful choice of parameters, in particular slug length.