Fluidized Bed Reactor Model Research Articles

Performance Evaluation of Fluidised Bed Biomass Gasifier Using CFD

Biomass gasification is one of the effective thermo-chemical methods to extract energy from biomass. This study mainly focuses on 2D modelling and simulation of biomass gasification in a bubbling fluidized bed gasifier using computational fluid dynamics (CFD) solver ANSYS FLUENT 15.0. Separate phases are used for biomass (saw dust), sand and gases and all the phases are solved using Eulerian- Eulerian approach. The effect of turbulence on computational fluid dynamics modelling of fluidized bed reactors is analyzed by comparing the results obtained from laminar and turbulent cases. The developed model is used to predict the effect of equivalence ratio, steam to biomass ratio, steam temperature and air preheating on product gas composition. It is found that when equivalence ratio is increased from 0.15 to 0.4, H2 concentration is decreased by 72% and the variation of steam to biomass ratio from 0.5 to 1.5 enhanced the H2 concentration by 87%.

Modelling of binary fluidized bed reactors for the sorption‐enhanced steam methane reforming process

ABSTRACTA 1 m high laboratory‐scale and a 4 m high industrial‐scale sorption‐enhanced steam methane reforming (SE‐SMR) fluidized bed reactor were simulated using a three‐fluid model. The performance of the SE‐SMR process was compared with the steam methane reforming (SMR) process. The influences of the superficial gas velocities and the solid loading (packed bed heights) on the reactor performance (hydrogen purity) were studied. The simulation results show that a higher purity of the hydrogen product can be obtained in a SE‐SMR reactor. The superficial gas velocity is an important parameter. In the present study, it has been found that the binary sorbent‐catalyst particles are well mixed when the bed is operated at m/s. The sorbent can adsorb CO steadily, thus the dry mole fraction of the hydrogen product can get above 0.95 in the 1 m laboratory‐scale bed, and above 0.97 in the 4 m industrial‐scale bed. However, when the laboratory scale bed is operated at a lower superficial gas velocity of m/s, the binary sorbent‐catalyst particles are segregated. When the bed is operated at a higher superficial gas velocity of 0.3 m/s, the process work load is increased, and the gas residence time in the reactor is decreased. Therefore, the hydrogen product purity is further decreased. The simulation results also show that there is an optimal bed height limit for the 4 m industrial‐scale bed, at which further increase of the packed bed height cannot increase the hydrogen purity.

Hydrodynamic modeling of an industrial turbulent fluidized bed reactor with FCC particles

This study presents a CFD modeling of the hydrodynamics in an industrial turbulent fluidized bed reactor with FCC particles. Considering the mesoscale structure of particle clusters and the impact of reactor temperatures, a gas-solid drag model based on the equivalent diameter of particle clusters is proposed. A CFD model is developed, the model parameters are evaluated, and the gas-solid flow behaviors are explored. Compared with the conventional drag models, the proposed model gives a reasonable hydrodynamic prediction in the industrial turbulent fluidized bed reactor. The hydrodynamics show more sensitive to the drag models than to the flow types, the kinetics theories and the restitution coefficients. There exist two coexisting flow regions in the industrial turbulent fluidized bed: a bottom dense, bubbling region and an upper dilute, dispersed flow region. Moreover, the bed density in the dense phase is much lower than those in the cold experiments. In the dilute phase, particles ascend in the center and descend near the wall, showing a core-annulus flow. In the bottom dense phase, some vortex flows appear, leading to the non-uniform distribution of particle velocity and solid holdup. With increasing the superficial gas velocity, the bed surface rises; and the bed density decreases in the bottom dense phase and increases in the upper dilute phase.

Modeling and simulation of bubbling fluidized bed reactors using a dynamic one-dimensional two-fluid model: The sorption-enhanced steam–methane reforming process

A dynamic one-dimensional multicomponent model for two-phase flows which includes heat- and mass transfer processes are studied in the Euler framework. The model is intended for reactive gas–solid flows in bubbling fluidized bed reactors. A model is desired that allows for a more complex description of the fluidized bed reactors (e.g. prediction of the bed expansion) relative to the conventional fluidized bed reactor models such as, e.g., Kunii–Levenspiel type of models. The model should not predict details in the flow as the two- and three-dimensional Euler two-fluid models in order to ensure reasonable simulation costs. In particular, the two- and three-dimensional Euler two-fluid models challenges the current available computational capacity for studies of reactive flows.The novel sorption-enhanced steam methane reforming (SE-SMR) technology is simulated in the bubbling bed regime. Simulation results of the one-dimensional Euler two-fluid model is compared to both a two-dimensional Euler model and a conventional fluidized bed model consisting of mass and heat balances. Furthermore, a sensitivity study to operation conditions and transport coefficients is performed for the one-dimensional Euler two-fluid model.The present simulation results reveal that the chemical process performance of the reactor is to a large extent determined by the imposed temperature in the reactor. Further, the one-dimensional Euler model provides an improvement of the simpler conventional fluidized bed reactor models by prediction of the bed expansion. Compared with the two-dimensional Euler model, cross-sectional averaging results in a significant reduction in the computational time but on the cost of loss of flow details.

One dimensional steady-state circulating fluidized-bed reactor model for biomass fast pyrolysis

A one dimensional (1-D) steady-state biomass fast pyrolysis reactor model is developed for integration with a biomass pyrolysis plant system model. A state-of-the-art biomass pyrolysis kinetic mechanism is combined with the 1-D Eulerian fluid dynamics and heat transfer description. Simulations are performed for a small scale reactor (0.023kg/s) with four different biomass feedstocks (pine, wheat straw, olive husks, organic fraction of MSW). Results show that biomass particles are heated to pyrolysis temperature of 786K in 0.3s and 99% biomass conversion is reached in 0.9s from entering the reactor. Comparison of pyrolysis products yields against available literature data shows that the employed reaction mechanism generally gives good predictions. However, water yield is under predicted. Fluid dynamics and heat transfer results are compared with averaged results from a 2-D, transient reactor model developed in Multiphase Flow with Interphase eXchanges (MFIX). Comparison of the 1-D and the 2-D model results shows flow patterns and reasonably similar values of flow parameters, with the average relative error between the gas velocities of 10%. The solids velocity predictions from the 1-D model carry a larger error since particle clustering is neglected in the plug flow approximation. The 1-D model is still considered attractive because of a reasonable agreement with the averaged experimental results.

Catalytic NOx Reduction in a Novel i-CFB Reactor: I. Kinetics Development and Modeling of Reduction Zone

A model was developed for the hydrocarbon selective catalytic reduction (HC-SCR) of NOx in a fluidized bed reactor. For the kinetics, the reaction was divided into two submodels: (i) NO oxidation and adsorption; (ii) hydrocarbon oxidation and NOx reduction. The kinetic parameters were obtained from fitting a fixed bed model to fixed bed experimental data. Mass transfer between solids and gas phases was also considered in this fixed bed model with the reaction term being embedded into the solids phase mass balance equation. Comparing with fixed bed experimental data, the model showed an average error of about 7% for NOx conversion and about 5% for HC conversion. The fitted kinetics was then incorporated into a fluidized bed reactor model, which included gas flow in the bubble phase, gas flow in the dense phase and solids flow in the dense phase. The fluidized bed reactor model was compared to the fluidized bed experimental data. The model showed acceptable agreement with measured NOx conversion, but poor agreement with observed HC conversion data. Suggestions were proposed to further improve the model and experimental data. The fluidized bed model was then applied to simulate NOx reduction in the reduction zone of the internal circulating fluidized bed (i-CFB) reactor. The simulation results showed that NOx conversion could be improved if NOx is fed into the reactor via the solids phase, the same as what happens in the reduction zone of an i-CFB reactor. Also, for the reduction zone of the i-CFB reactor, a higher solids circulation rate is preferred if NOx feed rate is kept at a constant. These simulations could provide good suggestions for the i-CFB design and operation.

Modeling and design of anaerobic fluidized bed reactor with recycling for denitrification of reverse osmosis concentrates

Reverse osmosis is a widely used technology in wastewater treatment, water purification, water reclamation and reuse. A major concern is production of brine concentrates containing high levels of ammonia or nitrogen. This work addresses biological denitrification of brine concentrates in anaerobic fluidized bed reactor (AFBR) systems. Previous publications (Ersever et al., 2007a, 2007b) described the first phase: process development, feasibility evaluation, and reaction optimization. This paper describes the second phase involving process modeling for performance prediction, simulation, and design with upscaling implications. Laboratory-scale studies provided data for AFBR process evaluation and model verification under different conditions, including media characteristics, hydraulic residence times, and influent nitrate levels. Model simulations facilitated process design and upscaling, and further projected that among different parameters the Monod yield coefficient and maximum specific growth rate significantly influenced process dynamics. Transient-state dynamics provided insight into process induction and acclimation besides process recovery after upsets.

Modeling phosphorus removal and recovery from anaerobic digester supernatant through struvite crystallization in a fluidized bed reactor

The cost associated with the disposal of phosphate-rich sludge, the stringent regulations to limit phosphate discharge into aquatic environments, and resource shortages resulting from limited phosphorus rock reserves, have diverted attention to phosphorus recovery in the form of struvite (MAP: MgNH4PO4·6H2O) crystals, which can essentially be used as a slow release fertilizer. Fluidized-bed crystallization is one of the most efficient unit processes used in struvite crystallization from wastewater. In this study, a comprehensive mathematical model, incorporating solution thermodynamics, struvite precipitation kinetics and reactor hydrodynamics, was developed to illustrate phosphorus depletion through struvite crystal growth in a continuous, fluidized-bed crystallizer. A thermodynamic equilibrium model for struvite precipitation was linked to the fluidized-bed reactor model. While the equilibrium model provided information on supersaturation generation, the reactor model captured the dynamic behavior of the crystal growth processes, as well as the effect of the reactor hydrodynamics on the overall process performance. The model was then used for performance evaluation of the reactor, in terms of removal efficiencies of struvite constituent species (Mg, NH4 and PO4), and the average product crystal sizes. The model also determined the variation of species concentration of struvite within the crystal bed height. The species concentrations at two extreme ends (inlet and outlet) were used to evaluate the reactor performance. The model predictions provided a reasonably good fit with the experimental results for PO4–P, NH4–N and Mg removals. Predicated average crystal sizes also matched fairly well with the experimental observations. Therefore, this model can be used as a tool for performance evaluation and process optimization of struvite crystallization in a fluidized-bed reactor.

One-dimensional modelling of chemical looping combustion in dual fluidized bed reactor system

Chemical looping combustion (CLC) is an emerging combustion technology with an inherent separation of the greenhouse gas CO2. The technique typically employs a dual fluidized bed reactor system where a metal oxide is used as a solid oxygen carrier that transfers the necessary oxygen from air to the fuel combustion. In this work, a comprehensive simulation tool for the investigation of a CLC system consisting of two interconnected fluidized bed reactors is introduced. One-dimensional, dynamic fluidized bed reactor model is implemented into the Matlab/Simulink environment. The model is based on the conservation of mass and energy, and semi-empirical correlations are used for the calculation of reaction kinetics, hydrodynamics, and heat transfer. The main outputs of the model are the global solids circulation rate, the conversion of the carrier and the gas composition at the reactor exit, the vertical profiles of temperature, reaction rates and gas concentrations, and the distribution of solids in the reactors. For validating and evaluating the capabilities of the model, a reference case based on the operation of a 120kWth CLC test rig was defined and simulated. Good agreement was observed between the experiments and simulations, and the model structure and submodel forms turned out to be appropriate to describe the studied process.

Simulations of Steam Methane Reforming/Sorption-Enhanced Steam Methane Reforming Bubbling Fluidized Bed Reactors by a Dynamic One-Dimensional Two-Fluid Model: Implementation Issues and Model Validation

Multiphase flows and in particular dispersed flows are frequently encountered in a variety of important process facilities in the chemical industry; herein, the fluidized bed reactors. Whereas the internal and external solid fluxes in the fluidized bed reactors are generally determined by empirical correlations or prescribed in the Kunii–Levenspiel type of models, the two-fluid models serve as highly relevant in the progress of commercial reactors for processes such as the novel sorption-enhanced steam methane reforming (SE-SMR) technology because the solid flux incorporated in the two-fluid model allows for dynamic modeling of interconnected fluidized bed reactors. Nevertheless, the two- and three-dimensional two-fluid models are yet too computationally demanding for chemical process evaluation studies due to the complexity of the gas–solid flow in the bed. Hence, these models are not efficient for studies of the processes such as the SE-SMR technology where the solid particles are transported between reactor units for utilization and recovery of the characteristic solid property, i.e. CO2-capture and CO2-release. Thus, the aim of the present study is to derive a model that allows for a more complex description of the fluidized bed reactors relative to the frequently used Kunii–Levenspiel type of models. On the other hand, the model should not predict details in the flow, as the two- and three-dimensional two-fluid models, in order to ensure reasonable simulation costs. Hence, in this study, the classical SIMPLE algorithm is extended to compressible two-phase reactive flows. The governing equations are cross-sectional averaged to smooth out the details in the flow. The suggested dynamic one-dimensional Eulerian–Eulerian two-fluid model is applied to investigate the reactive gas–solid flows of the SMR and SE-SMR processes; and moreover, the simulation results are compared with the results of the more complex two-dimensional model with a solid stress closure based on kinetic theory of granular flow. The one-dimensional model predictions of the chemical process performance are in good agreement with the corresponding profiles predicted with the two-dimensional model. The deviations are larger comparing the internal flow details but these do not owe significant impact on the chemical process which to a large extent is determined by the imposed temperature in the reactor.

Modeling of fluidized bed reactor for ethylene polymerization: effect of parameters on the single-pass ethylene conversion

Abstract Background In this study, we present the developments in modeling gas-phase catalyzed olefin polymerization fluidized bed reactors (FBR) using chromium catalyst technique. The model is based on the two-phase theory of gas-solid fluidization: bubble phase and emulsion phase. The model has proved to be the suitable model in many of past studies. In the proposed model, the bed is divided into several sequential sections. The effect of important reactor parameters such as superficial gas velocity, catalyst injection rate, catalyst particle growth, and minimum fluidization velocity on the dynamic behavior of the FBR has been discussed. The conversion of product in a fluidized bed reactor is investigated and compared with the actual data from the plant site. Results A good agreement has been observed between the model predictions and the actual plant data. It has been shown that about 0.28% difference between the calculated and actual conversions has been achieved. Conclusions The study showed that the computational model was capable of predicting the hydrodynamic behavior of gas-solid fluidized bed flows with reasonable accuracy.

Application of the flowsheet simulation concept to fluidized bed reactor modeling. Part I: Development of a fluidized bed reactor simulation module

In the present work a simulation module is developed for the description of a bubbling fluidized bed reactor and for the riser reactor of a circulating fluidized bed which is suitable for use in the framework of a flowsheet simulation system. A population balance approach is used to determine the particle size distribution within the reactor in steady-state. The model allows to describe the individual fate of particles in terms of attrition (abrasion and shrinkage) and transport effects. The fluidized bed reactor model is one-dimensional. Models of fluid mechanics are combined with kinetic approaches for the description of the local reaction. The implementation within the framework of a simulation package for solids processes allows for the flexible coupling of process models, e.g. of the fluidized bed reactor with one or more cyclone stages for gas cleaning or with other fluidized beds in fluidized bed systems.

Application of the flowsheet simulation concept to fluidized bed reactor modeling. Part II—Application to the selective oxidation of n-butane to maleic anhydride in a riser/regenerator system

In part I of this paper a new fluidized bed reactor module was presented for the simulation of a bubbling fluidized bed and of the riser of a circulating fluidized bed with the flowsheet simulation tool SolidSim so that several process models can easily be coupled. In the present part II the newly developed fluidized reactor modules are connected to existing cyclone modules to simulate a complex coupled fluidized-bed process, the selective oxidation of n-butane to maleic anhydride in a riser–regenerator system [1,2]. The calculation results for a laboratory setup are found to be in good agreement with experimental data from the literature. The subsequent simulation of an industrial scale sized plant shows that a high solids recirculation rate is needed to achieve satisfying maleic anhydride yield. The usefulness of flowsheet simulation is demonstrated by further process simulation calculations with varied solids recovery systems.

Adsorption and Ozonation Kinetic Model for Phenolic Wastewater Treatment

A three phase fluidized bed reactor was used to investigate the combined effect of adsorption and oxidation for phenolic wastewater treatment. Aqueous solutions containing 10 mg·L −1 of phenol and ozone were continuously fed co-currently as upward flow into the reactor at constant flow rate of 2 and 1 L·min −1, respectively. The phenolic treatment results in seven cases were compared: (a) O 3 only, (b) fresh granular activated carbon (GAC), (c) 1st reused GAC, (d) 2nd reused GAC, (e) fresh GAC enhanced with O 3, (f) 1st reused GAC enhanced with O 3, and (g) 2nd reused GAC enhanced with O 3. The phenolic wastewater was re-circulated through the reactor and its concentration was measured with respect to time. The experimental results revealed that the phenolic degradation using GAC enhanced with O 3 provided the best result. The effect of adsorption by activated carbon was stronger than the effect of oxidation by ozone. Fresh GAC could adsorb phenol better than reused GAC. All cases of adsorption on GAC followed the Langmuir isotherm and displayed pseudo second order adsorption kinetics. Finally, a differential equation for the fluidized bed reactor model was used to describe the phenol concentration with respect to time for GAC enhanced with O 3. The calculated results agree reasonably well with the experimental results.

Optimal hybrid modeling approach for polymerization reactors using parameter estimation techniques

The dynamics of polymerization catalytic reactors have been investigated by many researchers during the past five decades; however, the emphasis of these studies was directed towards correlating process model parameters using empirical investigation based on small scale experimental setup and not on real process conditions. The resulting correlations are of limited practical use for industrial scale operations. A statistical study for the relative correlation of each of the effective process parameters revealed the best combination of parameters that could be used for optimizing the process model performance. Parameter estimation techniques are then utilized to find the values of these parameters that minimize a predefined objective function. Published real industrial scale data for the process was used as a basis for validating the process model. To generalize the model, an artificial neural network approach is used to capture the functional relationship of the selected parameters with the process operating conditions. The developed ANN-based correlation was used in a conventional fluidized catalytic bed reactor (FCR) model and simulated under industrial operating conditions. The new hybrid model predictions of the melt-flow index and the emulsion temperature were compared to industrial measurements as well as published models. The predictive quality of the hybrid model was superior to other models. The suggested parameter estimation and modeling approach can be used for process analysis and possible control system design and optimization investigations.

Complementarity of CFD, experimentation and reactor models for solving challenging fluidization problems

Experimentalists, numerical modellers and reactor modellers need to work together, not only just for validation of numerical codes, but also to shed fundamental light on each other's problems and underlying assumptions. Several examples are given. Experimental gas axial dispersion data provide a means of choosing the most appropriate boundary condition (no slip, partial slip or full slip) for particles at the wall of fluidized beds. CFD simulations help to identify how close “two-dimensional” experimental columns are to being truly two-dimensional and to representing three-dimensional columns. CFD also can be used to provide a more rational means of establishing assumptions needed in the modelling of two-phase fluidized bed reactors, for example how to deal with cases where there is a change in molar flow (and hence volumetric flow) as a result of chemical reactions.

Artificial Neural Network Modeling of an Inverse Fluidized Bed Bioreactor

The application of neural networks to model a laboratory scale inverse fluidized bed reactor has been studied. A Radial Basis Function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. In the proposed model, the trained neural network represents the kinetics of biological decomposition of pollutants in the reactor. The neural network has been trained with experimental data obtained from an inverse fluidized bed reactor treating the starch industrywastewater. Experiments were carried out at various initial substrate concentrations of 2250, 4475, 6730 and 8910 mg COD/L and at different hydraulic retention times (40, 32, 24, 26 and 8h). It is found thatneural network based model has been useful in predicting the system parameters with desired accuracy.

Biosorption of RBBR by Trichoderma harzianum WL1 in stirred tank and fluidized bed reactor models

A lab scale stirred tank and fluidized bed reactor models were employed for the removal of RBBR from aqueous solution using autoclaved biomass of Trichoderma harzianum WL1. In batch mode, the effect of contact time and initial dye concentration, adsorbent dosage was investigated and optimal experimental conditions were ascertained. Dye decolorization experiments were carried out at pH 2.0, since the reactive dye uptake was favored at higher acidic environment. Equilibrium time was attained at 150 and 135 min in stirred tank and fluidized bed reactors respectively for the dye concentrations of 25–100 mg/L. The maximum percent color removal at equilibrium was observed from stirred tank reactor as 89.3–71.4% (25–100 mg/L). The adsorbent dosage of 1.5–2.0 g/50 mL was found to be optimum for increased dye uptake. The experimental data were analyzed by Langmuir and Freundlich isotherms and adsorption kinetics were determined. Both the Langmuir and Freundlich isotherms could describe the adsorption equilibrium of the adsorption system. The adsorption capacity ( Q 0) of 4.59 and 4.51 mg/g was recorded for RBBR removal by stirred and fluidized bed reactors, respectively. Kinetic studies showed that dye adsorption onto fungal biomass fitted well with second-order kinetic model. Stirred tank reactor showed a better adsorption capacity than fluidized bed reactor.

Simulation of gas-solid fluidized bed reactor for F-T synthesis

Using the lumping method, CH4, C3H8, C10H22, and C22H44 were chosen as the model products, and CO as the key component. The mathematical model of a gas-solid fluidized bed reactor was established based on some hypotheses. The consumption kinetic model of CO was investigated, and the parameters were estimated by Universal Global Optimization with the Marquardt method. Residual error distribution and a statistical test show that the intrinsic kinetic models are reliable and acceptable. A model of carbon chain growth probability was established in terms of experiments. Coupled with the Ander-son-Schulz-Flory (ASF) distribution, the amount of specific product could be obtained. Large-scale cold model experiments were conducted to investigate the distribution of the gas (solid) phase and determine the function of the voidage with the location of the catalytic bed. The change tendencies of the components in the catalytic bed at different temperatures were computed and figured out. The calculated value computed by the model established for the Fe-based F-T synthesis catalyst fit the experimental value very well under the same operating conditions, and all the absolute values of the relative deviations are less than 5%.

Comparison of fluidized bed flow regimes for steam methane reforming in membrane reactors: A simulation study

An important decision in the design of fluidized bed reactors is which of several flow regimes to choose. Almost all fluidized bed reactor models are restricted to a single flow regime, making comparison difficult, especially near the regime boundaries. This paper examines the performance of fluidized bed methane reformers with three models—a simple equilibrium model and two kinetic distributed models, based on different assumptions of varying sophistication. Membranes are incorporated to improve reactor performance. Eighteen cases are simulated for different flow regimes and membrane configurations. Predictions for the fast fluidization and turbulent flow regimes show that the rate-controlling step is permeation through the membranes. Bubbling regime simulations predict somewhat less hydrogen production than for turbulent and fast fluidization, due to the effects of interphase crossflow and mass transfer. Overall reactor performance is predicted to be best under turbulent fluidization operation. Practical considerations also affect the advantages, shortcomings and ultimate choice of flow regime.