Reactor Network Research Articles

Equivalent Reactor Network Model for the Modeling of Fluid Catalytic Cracking Riser Reactor

Modeling description of riser reactors is a highly interesting issue in design and development of fluid catalytic cracking (FCC) processes. However, one of the challenging problems in the modeling of FCC riser reactors is that sophisticated flow-reaction models with high accuracy require time-consuming computation, while simple flow-reaction models with fast computation result in low-accuracy predictions. This dilemma requires new types of coupled flow-reaction models, which should own time-efficient computation and acceptable model accuracy. In this investigation, an Equivalent Reactor Network (ERN) model was developed for a pilot FCC riser reactor. The construction procedure of the ERN model contains two main steps: hydrodynamic simulations under reactive condition and determination of the equivalent reactor network structure. Numerical results demonstrate that with the ERN model the predicted averaged error of the product yields at the riser outlet is 4.69% and the computation time is ∼5 s. Contrast to...

Effect of Steam Addition on the Flow Field and NOx Emissions for Jet-A in an Aircraft Combustor

AbstractThe steam injection technology for aircraft engines is gaining rising importance because of the strong limitations imposed by the legislation for NOx reduction in airports. In order to investigate the impact of steam addition on combustion and NOx emissions, an integrated performance-CFD-chemical reactor network (CRN) methodology was developed. The CFD results showed steam addition reduced the high temperature size and the radical pool moved downstream. Then different post-processing techniques are employed and CRN is generated to predict NOx emissions. This network consists of 14 chemical reactor elements and the results were in close agreement with the ICAO databank. The established CRN model was then used for steam addition study and the results showed under air/steam mixture atmosphere, high steam content could push the NOx formation region to the post-flame zone and a large amount of the NOx emission could be reduced when the steam mass fraction is quite high.

Adiabatic reactor network synthesis using coupled genetic algorithm with quasi linear programming method

In this paper a new approach is presented for synthesis of adiabatic reactor networks (ARNs) using genetic algorithm (GA) coupled with quasi linear programming (LP) method. In most cases reactor network (RN) synthesis leads to mixed integer non-linear programming (MINLP) problems or complicated non-linear programming (NLP) problems. In the suggested method to prevent complexity, GA is used to find the best configuration while continuous variables are handled using a quasi LP formulation. In quasi LP model continuous variables are regrouped into (a) normal variables such as concentration, temperature and flow rate (b) variables which make the equations nonlinear such as conversion in each reactor, split ratio of streams, recycles and exit temperatures from coolers or heaters. To optimize continuous variables the quasi LP consists of two nested loops. In the outer loop variables of group (b) are optimized while variables of group (a) are obtained using known values of group (b) in the inner loop. Therefore the complex MINLP or NLP model is converted to a quasi LP which is much easier to solve. Although in the RN only continuous stirred tank reactors (CSTR) and plug flow reactors (PFR) are used. The cases studied showed that this method can reach near optimum and in some cases better solutions compared to the literature.

ChemInform Abstract: Integrated Network of Continuous Reactors for the Decontamination of Gaseous Streams in Heterogeneous Catalytic Gas‐Liquid‐Solid Systems

AbstractReview: 60 refs.

Optimization of reactor network design problem using Jumping Gene Adaptation of Differential Evolution

Detailed working principle of jumping gene adaptation of differential evolution (DE-JGa) is presented. The performance of the DE-JGa algorithm is compared with the performance of differential evolution (DE) and modified DE (MDE) by applying these algorithms on industrial problems. In this study Reactor network design (RND) problem is solved using DE, MDE, and DE-JGa algorithms: These industrial processes are highly nonlinear and complex with reference to optimal operating conditions with many equality and inequality constraints. Extensive computational comparisons have been made for all the chemical engineering problems considered. The results obtained in the present study show that DE-JGa algorithm outperforms the other algorithms (DE and MDE). Several comparisons are made among the algorithms with regard to the number of function evaluations (NFE)/CPU- time required to find the global optimum. The standard deviation and the variance values obtained using DE-JGa, DE and MDE algorithms also show that the DE-JGa algorithm gives consistent set of results for the majority of the test problems and the industrial real world problems.

Prediction and Validation of Major Gas and Tar Species from a Reactor Network Model of Air-Blown Fluidized Bed Biomass Gasification

The thermochemical conversion of biomass via gasification offers a promising approach to producing fungible substitutes for petroleum-derived fuels and chemicals. The kinetic study of the gas-phase reactions of biomass gasification is key to understanding fluidized bed biomass gasification (FBBG). Under typical operating conditions for air-blown FBBG (700–1000 °C), tars exist in the product gas in significant quantities (2–50 g/Nm3). Predicting the formation and evolution of tars in a FBBG reactor model is particularly important as they introduce several operational and cleanup challenges in practice. However, such predictions require implementation of detailed chemical kinetic mechanisms due to the large number of species and competing conversion pathways involved. A detailed gas-phase mechanism has been proposed by the CRECK modeling group at Politecnico di Milano encompassing the secondary pyrolysis, cracking, and oxidation reactions of the devolatilization species of biomass, as well as the oxidation and combustion reactions of the resultant gas-phase hydrocarbon species. In this work, a one-dimensional reactor network model (RNM) of an air-blown fluidized bed gasifier utilizing this detailed chemistry model is developed and validated for the prediction of major gas-phase species and tar compounds. It is found that this RNM is able to accurately predict the syn-gas production and total tar concentration given a modification of water gas shift and/or CO oxidation kinetics to account for catalytic effects of the biomass ash and char. Additionally, validation of the predicted tar composition is attempted against available experimental measurements. Good agreement is achieved for single-ring aromatic and oxygenated tar compounds, while it is found that polycyclic aromatic hydrocarbons are underpredicted by more than an order of magnitude. Finally, the conversion pathways of representative devolatilization products of biomass—levoglucosan, xylofuranose, and p-coumaryl—are analyzed in the context of syn-gas and tar formation routes.

A multi-compartment population balance model for high shear granulation

This work extends the granulation model published by Braumann et al. (2007) to include multiple compartments in order to account for mixture heterogeneity encountered in powder mixing processes. A stochastic weighted algorithm is adapted to solve the granulation model which includes simultaneous coalescence and breakage. Then, a new numerical method to solve stochastic reactor networks is devised. The numerical behaviour of the adapted stochastic weighted algorithm is compared against the existing direct simulation algorithm. Lastly, the performance of the new compartmental model is then investigated by comparing the predicted particle size distribution against an experimentally measured size distribution. It is found that the adapted stochastic weighted algorithm exhibits superior performance compared to the direct simulation algorithm and the multi-compartment model produces results with better agreement with the experimental results compared to the original single-compartment model.

Equivalent Reactor Network Model for Simulating the Air Gasification of Polyethylene in a Conical Spouted Bed Gasifier

Plastic waste gasification is one of the most promising techniques to use nondecomposable solid waste and to produce syngas. A CFD-based Equivalent Reactor Network (ERN) model was developed for simulation of polyethylene gasification in a designed pilot-scale conical spouted bed gasifier. The CFD-based ERN model was established through two steps: (i) hydrodynamics simulations with CFD software and (ii) the equivalent reactor network built in the Aspen Plus simulator with gasification reactions taken into account through external FORTRAN modules. The model predictions were in very good agreement with experimental data of a lab-scale conical spouted bed gasifier used for steam gasification of polyethylene. The developed CFD-based ERN model was then used to investigate the effect of gasification temperature and equivalence ratio on the gasification performance of polyethylene in such a pilot-scale conical spouted bed reactor. It was found that the proper values of temperature and ER for air gasification were...

Numerical and experimental investigation on emission performance of a fuel staged combustor

The low NOx emission technology has become an important feature of advanced aviation engine. A wide range of applications attempt to take advantage of the fact that staged combustion under lean-premixed-prevaporized (LPP) conditions can significantly cut down emission and improve combustion efficiency. This paper proposes a scheme with fuel centrally staged and multi-point injection. The mixing of fuel and air is improved, and the flame temperature is relative low in combustion zone, minimizing the formation of nitrogen oxides (NOx), especially thermal NOx. In terms of the field distribution of equivalence ratio and temperature obtained from Computational Fluid Dynamics (CFD), a chemical reactor network (CRN), including several different ideal reactor, namely perfectly stirred reactor (PSR) and plug flow reactor (PFR), is constructed to simulate the combustion process and predict pollution emission. The influences of the pilot equivalence ratio and percentage of pilot/main fuel on NOx and carbon monoxide (CO) emission were investigated by CRN model. The effects of the pilot fuel and primary fuel on pollution emission were investigated experimentally. Finally, the effects of pilot equivalence ratio and pilot fuel proportion on NOx emission were discussed in detail by comparing predict of CRN and experimental results.

Minimum entropy generation for isothermal endothermic/exothermic reactor networks

It was shown in an earlier work by us that entropy generation and energy (hot utility or cold utility) consumption of isothermal, isobaric reactor networks depend only on the network's inlet and outlet stream compositions and flow rates and are not dependent on the reactor network structure, as long as the universe of realizable reactor units and network outlet mixing units are either all endothermic interacting with a single hot reservoir, or all exothermic interacting with a single cold reservoir, respectively. It is shown that when the universe of realizable reactor/mixer units, of isothermal, isobaric, continuous stirred tank reactor networks, consists of both endothermic units interacting with a single hot reservoir and exothermic units interacting with a single cold reservoir, the network's net (hot minus cold) utility consumption depends only on the network's inlet and outlet stream compositions and flow rates (and does not depend on the network's structure). In contrast, the network's entropy generation depends on the network's inlet and outlet stream compositions and flow rates, and the network's hot utility (or cold utility) consumption. The latter, in general, depends on the network structure, thus making entropy generation also, in general, depend on network structure. Thus, the synthesis of isothermal, isobaric reactor networks, with fixed inlet and outlet stream specifications, is equivalent to the synthesis of minimum hot (or cold) utility consuming such networks. The Infinite DimEnsionAl State‐space conceptual framework is used for the problem's mathematical formulation, which is then used to rigorously establish the above equivalence. A case study involving Trambouze kinetics demonstrates the findings. © 2014 American Institute of Chemical Engineers AIChE J, 61: 103–117, 2015

An integrated methodology for the modeling of Fluid Catalytic Cracking (FCC) riser reactor

Modeling description of the riser reactor is a highly interesting issue in the development of FCC process. However, one of the challenging problems in the modeling of FCC riser reactors is that sophisticated flow-reaction models with high accuracy need long computational time, while simple flow-reaction models give rise to results with fast computation but low accuracy. This dilemma requires new type of coupled flow-reaction models. The goal of this study was to propose a novel integrated model with time-efficient computation and acceptable accuracy. The integrated model, named equivalent reactor network (ERN) model, was established based on Aspen Plus simulator with considering gas–solid hydrodynamics via built-in modules and catalytic reactions via external FORTRAN subroutines, as well as lump mixtures characterized by real components. Through comparing with pilot-scale experimental data and industrial plant data in two case studies, the developed ERN model was justified to be capable of precisely and quickly modeling FCC riser reactors. Furthermore, the proposed methodology is expected to be readily applied to studies on the dynamic simulation, optimization, and control of FCC units in future studies.

Experimental Simulation of a Two-Dimensional Attainable Region and Its Application in the Optimization of Production Rate and Process Time of an Adiabatic Batch Reactor

Attainable region analysis is a graphical optimization technique which enables design engineers to synthesize optimal reactor networks to achieve a given objective. This is accomplished if a given system of reactions with known reaction kinetic models and feedstock is available. This paper shows experimentally how the geometry of a two-dimensional attainable region can be generated by reaction and mixing as the only fundamental processes occurring in the reactor of a hydrolysis process without taking the reaction kinetic model of the process into consideration. The experiment was conducted using an adiabatic batch reactor fitted with a thermistor for temperature measurement. The results were used to develop a novel technique to run the adiabatic batch reactor by applying the attainable region analysis. From the analysis the production rate of the product and the process time of the adiabatic batch reactor were optimized by graphical techniques, and it is shown that the maximum production rate increased by 72% as compared with the standard method of operating the batch reactor and the corresponding minimized process time was reduced to 0.36 h compared with 1.26 h of the standard batch operation. It is also shown that the limit of the optimization process generated the optimal process configuration required for a continuous operation to achieve the highest production rate in a minimum time possible.

A novel approach to the design and operation scheduling of heterogeneous catalytic reactors

A number of studies have been conducted to reduce the overall level of catalyst deactivation in heterogeneous catalytic reactors, and improve the performance of reactors, such as yield, conversion or selectivity. The methodology generally includes optimization of the following: (1) operating conditions of the reaction system, such as feed temperature, normal operating temperature, pressure, and composition of feed streams; (2) reactor design parameters, such as dimension of the reactor, side stream distribution along the axis of the reactor beds, the mixing ratio of inert catalyst at each bed; and (3) catalyst design parameters, such as the pore size distribution across the pellet, active material distribution, size and shape of the catalyst, etc. Few studies have examined optimization of the overall catalyst reactor performance throughout the catalyst lifetime, considering catalyst deactivation. Furthermore, little attention has been given to the impact of various configurations of reactor networks and scheduling of the reactor operation (i.e., online and offline-regeneration) on the overall reactor performance throughout the catalyst lifetime. Therefore, we developed a range of feasible sequences of reactors and scheduling of reactors for operation and regeneration, and compared the overall reactor performance of multiple cases. Furthermore, a superstructure of reactor networks was developed and optimized to determine the optimum reactor network that shows the maximum overall reactor performance. The operating schedule of each reactor in the network was considered further. Lastly, the methodology was illustrated using a case study of the MTO (methanol to olefin) process.

A chemical reactor network for oxides of nitrogen emission prediction in gas turbine combustor

This study presents the use of a new chemical reactor network (CRN) model and non-uniform injectors to predict the NOx emission pollutant in gas turbine combustor. The CRN uses information from Computational Fluid Dynamics (CFD) combustion analysis with two injectors of CH4-air mixture. The injectors of CH4-air mixture have different lean equivalence ratio, and they control fuel flow to stabilize combustion and adjust combustor’s equivalence ratio. Non-uniform injector is applied to improve the burning process of the turbine combustor. The results of the new CRN for NOx prediction in the gas turbine combustor show very good agreement with the experimental data from Korea Electric Power Research Institute.

Influence of Pressure and Steam Dilution on NOx and CO Emissions in a Premixed Natural Gas Flame

In the current study, the influence of pressure and steam on the emission formation in a premixed natural gas flame is investigated at pressures between 1.5 bar and 9 bar. A premixed, swirl-stabilized combustor is developed that provides a stable flame up to very high steam contents. Combustion tests are conducted at different pressure levels for equivalence ratios from lean blowout to near-stoichiometric conditions and steam-to-air mass ratios from 0% to 25%. A reactor network is developed to model the combustion process. The simulation results match the measured NOx and CO concentrations very well for all operating conditions. The reactor network is used for a detailed investigation of the influence of steam and pressure on the NOx formation pathways. In the experiments, adding 20% steam reduces NOx and CO emissions to below 10 ppm at all tested pressures up to near-stoichiometric conditions. Pressure scaling laws are derived: CO changes with a pressure exponent of approximately −0.5 that is not noticeably affected by the steam. For the NOx emissions, the exponent increases with equivalence ratio from 0.1 to 0.65 at dry conditions. At a steam-to-air mass ratio of 20%, the NOx pressure exponent is reduced to −0.1 to +0.25. The numerical analysis reveals that steam has a strong effect on the combustion chemistry. The reduction in NOx emissions is mainly caused by lower concentrations of atomic oxygen at steam-diluted conditions, constraining the thermal pathway.

Effect of fuel injection velocity on MILD combustion of syngas in axially-staged combustor

The role of fuel injection velocity on MILD (Moderate or Intense Low-oxygen Dilution) combustion of coal-derived syngas was examined in an axially staged combustor, where the secondary air was mixed with the flue gases from the gas generation zone to produce hot and diluted oxidant prior to its mixing with the secondary fuel. The global flame signatures, OH∗ radicals distribution, and exhaust emissions were obtained through experimental measurements, while the mixing behavior between the secondary fuel and oxidant was numerically studied. Higher secondary fuel injection velocity within 199–299 m/s facilitated the earlier entrainment of oxidizer into the secondary fuel and increased the flame lift-off height, resulting in a lower flame temperature, a more distributed reaction zone and reduced NOx emissions, but higher pressure loss and CO formation. The MILD regime yields lower NOx emissions compared to the traditional diffusion combustion mode, and the N2O-intermediate mechanism dominates the NO production in the syngas MILD flame with adiabatic flame temperature lower than 1565 K according to the prediction of the chemical reactor network model.

An experimental and modeling study of NOx and CO emission behaviors of dimethyl ether (DME) in a boiler furnace

NOx and CO emission behaviors of dimethyl ether/air premixed flame in a boiler furnace were studied by experimental and modeling approaches in this paper. Five excess air ratios (1.05, 1.15, 1.30, 1.45 and 1.60) and two thermal loads (high load (about 270kW) and low load (about 130kW)) were involved to investigate their effects on the emission behaviors. Besides, a chemical reactor network was constructed on the basis of CFD solutions to calculate NO and CO emissions. A detailed chemical mechanism of dimethyl ether combined with the San Diego NOx chemistry which includes thermal, prompt, N2O and NO2 pathways was used. The research indicated that NO in the flame base was formed via a combination of thermal, prompt and N2O pathways. The thermal pathway dominated in the high-temperature (above 1800K) flame zone. NO in intermediate-temperature (1000–1600K) regions was generated via the NO2 pathway. Besides, a considerable amount of NO was converted to NO2 in the low-temperature (below 1000K) zones. Emission indices of NO and CO both decreased with the increment of excess air ratio. They became rather small if the excess air ratio was maintained above 1.30 and 1.15 respectively. The effect of thermal load on the NO emission index was insignificant. The CO emission index increased considerably under the high load.

Model-based optimization of sulfur recovery units

Multi-scale process modeling is very appealing methodology for process optimization since it highlights certain issues that remain unexplored with conventional methodologies and debottlenecks certain potentialities that remain unexploited in chemical plants. In this work, a kinetic model with 2400 reactions and 140 species is implemented in a proper reactor network to characterize the thermal furnace and the waste heat boiler of sulfur recovery units; the network with detailed kinetics is the kernel of a Claus process simulation that includes all the unit operations and the catalytic train. By doing so, reliable estimation of acid gas conversion, elemental sulfur recovery, and steam generation is achieved with the possibility to carry out an integrated process-energy optimization at the total plant scale.

Influence of ash agglomerating fluidized bed reactor scale‐up on coal gasification characteristics

To study the influence of fluidized‐bed reactor scale‐up on coal gasification characteristics, a model of the ash agglomerating fluidized‐bed reactor has been developed using an equivalent reactor network method. With the reactor network model, the scale‐up effects of a gasifier were studied in terms of the characteristics of the chemical reactions in the jet zone, the annulus dense‐phase zone and the freeboard zone. Results showed that the changes occurred in the inequality proportion of the volume of the jet zone during the reactor scale‐up. Taking into consideration the utilization of a portion of the backflow gas, the expansion of the jet zone volume and the coal particle residence time, the temperature of the jet zone was increased from 1592 to 1662 K. Also, both the annulus dense‐phase zone temperature and the freeboard zone temperature decreased, causing subsequent decrease in the carbon conversion efficiency. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1821–1829, 2014

Detailed Emissions Prediction for a Turbulent Swirling Nonpremixed Flame

This paper describes the validation of a previously described CFD-CRN method (computational fluid dynamics–chemical reactor network) for emissions predictions for the laboratory benchmark TECFLAM S09c flame. It details CFD simulation, solution strategy, validation using, CRN generation, detailed emissions predictions and reaction pathway studies. Steady-state 3D CFD models of a 45° sector of the combustor, employing standard numerical techniques; steady-state k–ω SST turbulence, P1 radiation, finite-rate eddy-dissipation turbulence-chemistry interaction, and a three-step methane combustion mechanism, were created in ANSYS FLUENT v14. Steady-state models were used as they are of interest to industrial researchers, who are often limited to their use by extremely complex geometries. The models differ in their handling of pressure-velocity coupling and discretization of the momentum equation. The solution which uses SIMPLE coupling and second-order upwind discretization of the momentum equation was generally found to give better results. Satisfactory agreement with experimental profiles for velocity, turbulent kinetic energy, temperature, and species mass fractions has been achieved. Some errors are seen in temperature and CO mass fractions at the highest temperatures (T > 2000 K) and are due to the fact that the highly simplified three-step kinetic mechanism employed due to practical limitations on computational resources, underestimates CO2 dissociation. The results compare satisfactorily with the state-of-the-art. Nonzero concentrations of CO are predicted in the external recirculation zone, which has not been achieved in previous modeling efforts. The validated solution was used as the basis to generate a CRN using the CFD-CRN method. The CFD-CRN method uses user-defined criteria to divide the CFD domain into a set of interconnected perfectly stirred reactors (PSRs) (i.e., a CRN). This CRN is then solved using detailed chemical kinetic mechanisms in the Kinetic Post-Processor (KPPSMOKE) solver. CRN size-independence studies are performed, and it is determined that 5000+ PSRs were needed to adequately capture pollutant formation in the complex recirculating flow field. Validation of CFD-CRN predictions of major species show similar accuracy to steady-state CFD simulation, with improvements over state-of-the-art CFD in CO profile predictions. Satisfactory agreement with previously published experimental NOx contour plots is also seen. The CFD-CRN is used to study NOx formation pathways in the swirling, turbulent environment of the S09c diffusion flame. As expected, NOx is seen to form primarily in the high-temperature internal recirculation zone (IRZ). The prompt pathway is predicted to be of greatest importance in this area. Significant NOx reburning is seen in the low temperature fuel–air jets immediately adjacent to the IRZ. Overall, the prompt pathway is responsible for 77% of NOx leaving the system, with 12% due to thermal and 11% due to N2O intermediate.