Computational Fluid Dynamic Simulations of a Pilot-Scale Transport

Nov 18, 2013 - In this study, a pilot-scale transport gasifier was simulated by employing .... and then recycle back to the mixing zone via an aerated...
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Computational Fluid Dynamic Simulations of a Pilot-Scale Transport Coal Gasifier: Evaluation of Reaction Kinetics Tingwen Li,*,†,§ Kiran Chaudhari,†,‡ Dirk VanEssendelft,† Richard Turton,†,‡ Philip Nicoletti,†,§ Mehrdad Shahnam,† and Chris Guenther† †

National Energy Technology Laboratory, Morgantown, West Virginia 26507, United States West Virginia University, Morgantown, West Virginia 26506, United States § URS Corporation, Morgantown, West Virginia 26501, United States ‡

ABSTRACT: The U.S. Department of Energy’s National Energy Technology Laboratory has developed a software platform titled Carbonaceous Chemistry for Computational Modeling (C3M) that can be used to seamlessly connect the reaction kinetics typically found in the gasification process to various computational fluid dynamic (CFD) packages, including MFIX, ANSYSFLUENT, and BARRACUDA, for advanced gasifier simulation. In this study, a pilot-scale transport gasifier was simulated by employing the C3M platform to incorporate various kinetics into the CFD simulation. It was found that appropriate chemical kinetics for gasification reactions are key to the numerical prediction of syngas composition and the kinetics from Niksa Energy Associate’s PC Coal Lab yielded reasonable agreement to the experimental data. Using the C3M platform, different chemistry kinetics for coal devolatilizationgenerated by METC Gasifier Advanced Simulation (MGAS), Niksa Energy Associate’s PC Coal Lab (PCCL), Chemical Percolation Model for Coal Devolatilization (CPD), and Advanced Fuel Research’s FunctionalGroup, Depolymerization, Vaporization, Cross-linking (FG-DVC)were evaluated for the transport gasifier simulation. Results showed that the effect of devolatilization kinetics on the transport gasifier simulation is considered to be secondary comparing to the char gasification reactions because of the relatively long residence time of coal particles in the system.

1. INTRODUCTION Environmentally clean energy is of vital importance throughout the world, especially in light of climate change, CO2 emissions, and the limited availability of fossil fuels coupled with the rapidly rising global demand for energy. Considering the abundant storage and wide distribution of coal around the world,1 increasing effort has been put into developing the most effective technologies for efficiently utilizing coal as a clean source of energy. One such technology is coal gasification, a flexible, reliable, and clean energy technology that uses heat, pressure, and steam to convert coal into synthesis gas (syngas)a mixture of CO and H2with high coal conversion efficiency and low environmental impacts. Three main types of reactors are generally used to gasify coal: moving bed, fluidized bed, and entrained flow reactors.2 For fluidized bed gasifiers, many variations in design configurations and features have been developed based on fluidization and chemical reactor principles, test observations, and empirical rules, as well as conventional engineering practices.3,4 Despite gasification’s long history and wide application, detailed scientific knowledge is still lacking about the complex interactions between the gasification reactions and the hydrodynamics in the gasifier. Computational fluid dynamic (CFD) modeling is believed a valuable tool to understand the gasification process from both hydrodynamic and chemical basis.5,6 For modeling the gas−solids flow inside a gasifier, the Lagrangian−Eulerian (LE) method, and the Eulerian−Eulerian (EE) method or twofluid model (TFM), are the most widely used approaches.6 Differences between these two methods are mainly in the treatment of the solids phase. The LE method tracks the solids © XXXX American Chemical Society

phase at a particle scale by solving the motion of each individual particle or swarm of particles. The EE method treats the solid particles as a continuum by solving the conservation equations of mass, momentum, and energy, which are derived based on appropriate averaging techniques. The former approach is usually used for modeling entrained gasifiers with a relatively dilute solid flow,7−10 while the latter approach is often used for dense flow in fluidized bed gasifiers.11−13 CFD modeling of the gasification process is a challenging task because of the complex hydrodynamics of gas−solids flow within the reactor, as well as the different types of chemical reactions taking place simultaneously. Numerous numerical studies have reported investigations of flow hydrodynamics in various gas−solids fluidized bed systems. With the acceleration in computer speed and the availability of powerful computing resource, as well as the rapid development in advanced numerical algorithms, more and more CFD simulations have been reported for predicting gas− solids flow, which makes the accurate simulation of a gasifier more feasible. Nevertheless, successful CFD predictions of the coal-gasification process require a detailed and accurate description of the chemical reactions taking place inside the gasifier, in addition to proper prediction of the flow hydrodynamics.14 Numerous reactions, both homogeneous and heterogeneous, occur in a coal-fed gasifier.15 Most homogeneous gas-phase reactions, which take place between pure components, are well-known (with the exception of the water-gas shift reaction Received: September 19, 2013 Revised: November 14, 2013

A

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occurring at high pressure16). The heterogeneous reactions (e.g., the initial devolatilization and subsequent tar cracking and char gasification reactions) are far more difficult to model when the effects of temperature, heating rate, pressure, coal structure, and particle properties are included.15,18,19 Usually, the chemical kinetics describing heterogeneous reactions must be determined by laboratory testing. Unfortunately, it is difficult to conduct comprehensive laboratory tests due to the chemical diversity of coals and the variety in operating conditions. Different mathematical modeling approaches have been proposed to describe the gasification of coal and its behavioral changes under varying operating conditions and processes, depending on the coal’s individual properties.20−23 However, additional work and knowledge are needed to incorporate the chemical kinetics predicted by a mathematical model into a CFD simulation of the gasification process. To reduce the amount of time and effort required for gathering and incorporating the appropriate kinetic information into a numerical simulation of the gasification process, the U.S. Department of Energy’s National Energy Technology Laboratory (DOE/ NETL) has developed the software platform Carbonaceous Chemistry for Computational Modeling (C3M) that can be used to seamlessly connect a variety of reaction kinetics typically found in the gasification process to various high-fidelity, reacting, multiphase CFD packages for advanced gasifier simulations. Through interfacing with various leading sources of kinetic information including NETL’s METC Gasifier Advanced Simulation (MGAS), Niksa Energy Associate’s PC Coal Lab (PCCL), Fletcher’s Chemical Percolation Devolatilization (CPD), Advanced Fuel Research’s Functional-Group, Depolymerization, Vaporization, Cross-linking (FG-DVC), and NETL’s in-house kinetic data, C3M can be used as a virtual kinetic laboratory for gasification to compare different kinetic modeling results. The kinetic models extracted by C3M can be directly incorporated into NETL’s open-source multiphase CFD software MFIX, commercial software FLUENT from ANSYS Inc., and commercial software BARRACUDA from CPFD Software LLC for gasifier simulations. In this paper, a series of CFD simulations of a pilot-scale transport gasifier are presented. With the aid of C3M, chemical kinetics from different sources are evaluated in the numerical simulations with respect to the composition of the exit syngas. Specifically, chemistry kinetics for coal devolatilization predicted by MGAS, PCCL, CPD, and FG-DVC are evaluated in the CFD simulations using the C3M platform as well as the char gasification kinetics taken from MGAS and PCCL, respectively.

Figure 1. Schematics of (a) the KBR transport gasifier (from24) and (b) numerical simulation.

suited for low-rank, high-moisture, high-ash coals due to its low-temperature operation and high circulation rate, which has been tested and proven at the Power Systems Development Facility (PSDF) in Wilsonville, Alabama, an engineering-scale demonstration unit that evaluated the transport gasifier over a series of tests and under a wide variety of conditions and feed stocks.24 In the current study, only the riser and mixing zone of the gasifier is simulated, as schematically shown in Figure 1(b), where majority of coal gasification reactions take place. The geometry and operating conditions are taken from the PSDF facility. A mixture of air and steam is fed through the bottom. Air for the primary burner is present below the recycle feed, and additional air is fed into the mixing zone from various locations between coal and recycle inlets; this arrangement evenly distributes heat generated from the partial combustion of the circulating solids. Fresh Powder River Basin (PRB) subbituminous coal is fed near the top of the mixing zone. A detailed coal analysis is provided in Table 1. The PRB coal Table 1. Coal Analysis of PRB Coal under Tests proximate analysis fixed carbon (%) volatile matter (%) moisture (%) ash (%)

2. KBR TRANSPORT GASIFIER In this study, the transport gasifier (also known as TRIG Transport Integrated Gasification) developed by KBR and Southern Company, together with DOE, is assessed. The KBR transport gasifier is a circulating fluidized bed reactor that operates in either air or oxygen blown modes. The design of the transport gasifier is based on fluidized catalytic cracking (FCC) technology developed for refinery gasoline production in the 1940s, which consists of a mixing zone, riser, disengager, cyclone, standpipe, loop-seal, and J-leg as shown in Figure 1(a).24 The transport gasifier has higher superficial gas velocities, riser densities, and solids circulation rates than most conventional circulating fluidized bed reactors, resulting in higher syngas throughput and enhanced mixing, as well as high heat and mass transfer rates. The KBR transport gasifier is particularly well

ultimate analysis 43.2 35.5 15.9 5.4

carbon (%) hydrogen (%) oxygen (%) nitrogen (%) sulfur (%)

59.2 3.7 15.8 0.8 0.3

is first crushed and then pulverized to a mean particle size of 168 μm with a standard deviation of 22 μm.25 Cyclones collect the solids leaving the riser through the top exit, and then recycle back to the mixing zone via an aerated loop-seal, standpipe, and J-leg arrangement. The whole recycling loop is simplified in the simulation as continuous feeding of recycled solids through the J-leg inlet. During steady-state operation, the circulating solids consist mainly of ash and a small amount of carbon, for which detailed solids chemical and physical analyses have been reported.25 Although the carbon content in the B

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Table 2. Major Operating Parameters Used for Numerical Simulationsa run no. TC20−69 TC20−70 R02−30b a

outlet temperature (°F)

outlet pressure (psig)

coal feed rate (lb/h)

air feed rate (lb/h)

oxygen feed rate (lb/h)

nitrogen feed rate (lb/h)

steam feed rate (lb/h)

1710 1660

160 160

2040 3760

800 2580

1940 2270

6570 6970

3510 2000

Data are collected from.25 bNo data available in the public domain.

Figure 2. Architecture of C3M. ⎞ ⎛ ∂Θ 3 εmρ ⎜ m + vm⃗ ·∇Θm⎟ = ∇·qΘ⃗ + Sm: ∇vm⃗ − εmρm Jm + m ⎠ 2 m ⎝ ∂t

circulating spent solids is low, the high circulation rate which is typically two-order of magnitude higher than the coal feed rate ensures sufficient heat generation to maintain gasifier temperatures. Three PSDF tests, TC20-69, TC20-70, and R02−30, are simulated in this study with major operating parameters listed in Table 2. Cases 1 and 2 are similar except that the latter has a higher coal feed rate and gas flow rate but a lower steam feed rate. The operating parameters for the third case, R02-30, are not given here for proprietary reasons. In the PSDF transport gasifier, gas flow is required to fluidize the solids recycle sections of the unit and to ensure that the circulating solids flow properly. The main difference is that syngas is used for the aeration of the recycled solids, as opposed to nitrogen in the other two cases. More detailed information on the PSDF gasifier and related tests can be found in the report.25

⎛ ∂T ⎞ εmρm Cpm⎜ m + vm⃗ ·∇Tm⎟ = −∇·qm⃗ + ⎝ ∂t ⎠ ∂ (εmρm X ml) + ∇· (εmρm X mlvm⃗ ) = R ml ∂t

∂ (εmρm vm⃗ ) + ∇·(εmρm vm⃗ vm⃗ ) = ∇· Sm + εmρm g ⃗ + ∂t

n

(5)

chemical reaction rate of the lth species of the mth phase; S mis the stress tensor; Tm is temperature; vm⃗ is the velocity vector; Xml is the mass fraction of the lth species in the mth phase; γmn is the coefficient of heat transfer between phases m and n; εmis the volume fraction; ΠΘm is the dissipation of granular energy due to interaction with gas; ρm is density; and Θm is granular temperature. These equations must be closed with constitutive relations for the momentum and energy exchange, as well as the plastic stresses, heat capacities, and heat fluxes. MFIX has been widely used to study the flow hydrodynamics in various gas−solids systems, including circulating fluidized bed.27,28 Details on the theory, numerical techniques, and basic models are provided in online documentation for MFIX.29−31 3.2. C3M. NETL developed C3M to support detailed kinetic models within high-fidelity reacting multiphase CFD software. C3M is free chemistry management software focused on computational modeling of reacting systems. It started with the development of MGAS, which was NETL’s first attempt to produce a validated set of kinetics for gasification and was based on several experiments conducted by NETL.32 Figure 2 presents the architecture of C3M. With continuous development, the C3M graphical user interface now allows users to exercise various kinetic models from leading kinetic packages, such as PCCL, CPD, FG-DVC, and NETL’s Co-pyrolysis package to graphically evaluate the effect of different fuels and/or gasifier operating conditions on gasification kinetics along with the yield of

(1)

∑ Imn⃗

n

where m and n represent phases, l represents a species in a phase, and Cpm represents heat capacity at constant pressure; ΔHrm is the heat of ⃗ is the momentum exchange between phases m and n; Jmis reaction; Imn the collisional dissipation of granular energy; g ⃗ is the gravitational acceleration; q⃗m is heat flux; q⃗Θm is granular heat flux; Rml is the

Nm l=1

∑ γmn(Tn − Tm) − ΔHrm (4)

3.1. MFIX. The present study used the continuum flow solver in the open-source code MFIX (available at https://mfix.netl.doe.gov), which is a multifluid EE code, with each phase treated as an interpenetrating continuum. The mixture of coal particles and recycled solids are represented as a granular phase, which colocates with the gas phase to form a multiphase mixture, with the volume fraction εm giving the amount of phase m at each spatial location. The governing equations for the solid phase are closed by kinetic granular theory.26 MFIX solved the governing equations, including the mass, momentum, energy, and species-mass balances for each phase, gas (m = g) or solids (m = s) that fully accounts for the spatial and temporal variations in gas and solids volume fractions, velocities, and temperatures with any associated phase change and chemical reactions.

∑ R ml

Θm

(3)

3. MODEL DESCRIPTION

∂ (εmρm ) + ∇·(εmρm vm⃗ ) = ∂t

∏ (m ≠ g)

(2) C

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product species.33,34 C3M directly exports the selected kinetic models to CFD solvers MFIX, Fluent, and Barracuda through customized user defined subroutines. With this functionality, C3M derives a unified global kinetic model for the specified CFD solver from the outputs of various kinetic packages and automatically completes the unit conversion, molecular weights, and formation heat calculations. Users can easily operate C3M in a stand-alone mode as well, to exercise C3M as a virtual kinetic laboratory for gasification, to compare C3M output to their own experimental kinetic information, or to use the output from C3M to implement gasification kinetics into any numerical model. These kinetic expressions describe the fundamental steps taking place in the gasification of coal/petcoke/biomass, namely: devolatilization, tar-gas chemistry, soot formation, and the subsequent heterogeneous and homogeneous gasification and combustion reactions. The following sections briefly describe the fundamental principles and technical aspects of each of the kinetic packages included in C3M. 3.2.1. METC Gasifier Advanced Simulation (MGAS). MGAS was developed at NETL to describe the transient operation of coflow, counter flow, or fixed bed gasifiers.32 MGAS considers both the heterogeneous and homogeneous reactions encountered in most gasification processes. In MGAS, all light hydrocarbons are lumped into CH4 and minor species such as H2S and NH3 are ignored, resulting eight gas species, O2, CO, CO2, CH4, H2, H2O, N2, and tar. Coal is treated as material containing four pseudospecies: ash, moisture, volatile matter, and fixed carbon. The rate expressions for gasification and combustion reactions were taken from the literature,35 and the associated reaction kinetics were experimentally determined or calibrated specifically for four types of coal only: Pittsburgh No.8 (bituminous), Arkwright Pittsburgh (bituminous), Illinois No. 6 (bituminous), and Rosebud (subbituminous). A fifth type of coal, North Dakota Lignite, was added in the latest version of MGAS. MGAS has been implemented into MFIX, and Fluent, and has been successfully applied to modeling the transport gasifier from the PSDF pilot-scale facility and entrained gasifier.7,36−39 Despite its success during the past decade, the kinetic parameters for coal gasification kinetics in MGAS are limited to five types of coal. In addition, the devolatilizaiton kinetics does not consider the effect of heating rate or pressure on devolatilization yield. Several other limitations of MGAS triggered the development of C3M to allow incorporation of more accurate gasifier chemistry information so that a wider variety of fuels could be simulated using CFD. 3.2.2. PC Coal Lab (PCCL). PC Coal Lab is commercial software developed by Niksa Energy Associates LLC to predict a solid fuel’s pyrolysis and gasification behavior by simulating processes as they would occur in laboratory test facilities.40 PCCL can predict the kinetics and product composition from primary pyrolysis, tar cracking, secondary pyrolysis, and gasification reactions for over 2000 coals along with biomass and pet coke. For a wide variety of coals, PCCL’s predictions are in good agreement with experimental results obtained from laboratory measurements. The predictions give the yields of all major primary pyrolysis products (CO2, H2O, CO, CH4, C2H4, C2H6, C3H6, C3H8, H2, H2S, HCN, tar, and char) as well as the molecular weights of tar and char. It also predicts the subsequent secondary pyrolysis of primary volatiles into CO2, H2O, CO, H2, CH4, C2H2, and soot. PCCL describes char combustion from ignition throughout the later stages of burnout based on the expanded version of Hurt’s Carbon Burnout Kinetics (CBK) Model.41 It also describes char gasification by H2O, CO2, and H2 with a newly expanded version of CBK called CBK/G. 3.2.3. Chemical Percolation Model for Coal Devolatilization (CPD). The CPD model is well-known for predicting coal pyrolysis.21,42−44 The model describes the pyrolysis behavior of rapidly heated coal based on the chemical structure of the parent coal. CPD predicts pyrolysis via a bridge-reacting mechanism, percolation lattice statistics, a vapor−liquid mechanism, and a cross-linking mechanism. It successfully predicts the effects of pressure on tar and total volatiles yields observed in heated grid experiments for coals. Predictions of the amount and characteristics of gas and tar from many different coals compare well with available data.44

3.2.4. Functional-Group, Depolymerization, Vaporization, Crosslinking (FG-DVC). The FG-DVC model is a comprehensive code for predicting the yield and composition of coal and biomass pyrolysis products (gas, tar, and char) developed at Advanced Fuel Research, Inc. The FG-DVC model combines two previously developed models by Solomon and his research group, a Functional Group (FG) model and a Depolymerization, Vaporization, Cross-linking (DVC) model.45 The FG subroutine is used to describe gas evolution and the elemental and functional group compositions, whereas the DVC subroutine is employed to determine the amount and molecular weight of macromolecular fragments. The model is particularly useful in modeling high heating rate processes, where experimental data are difficult to collect along with the pressure effects. 3.3. Simulation Setup. The computational domain, as depicted in Figure 1(b), was discretized using a cylindrical coordinate which leads to 240K computational cells. To simplify the geometry for CFD simulation, only the major feed ports as shown in the schematics are considered. Inlets for coal feed, recycled ash, and various gas streams were simulated with proper boundary conditions specified based on the operating conditions from PSDF. As not all operating conditions were available for setting up the CFD simulation, assumptions on certain flow parameters, such as exact temperature and pressure at each feed inlet, were made based on the best knowledge of PSDF. A pressure outflow boundary condition was used at the top exit through which solids and gas are free to leave the computational domain. The system was initialized with a mixture of recycled ash and air at elevated temperature and pressure. Relevant information, such as coal proximate and ultimate analysis, operating pressure, and temperature, was provided to C3M for running different chemical packages to extract appropriate chemical kinetics. For simplification, minor species of sulfur and nitrogen measured in the coal analysis were ignored in the modeling. In the current study, all kinetics for moisture release, devolatilization, tar cracking, steam gasification, CO2 gasification, hydrogasification, char combustion, hydrogen combustion, carbon monoxide combustion, and methane combustion are considered. To evaluate the effect of coal devolatilization reaction, different kinetic expressions derived from MGAS, PCCL, CPD, and FG-DVC were incorporated into the gasifier simulation through C3M. For the char gasification, that is, steam and carbon dioxide gasification and methanation, chemical kinetics from MGAS and PCCL were also briefly evaluated. The computation was conducted on a high-performance computing (HPC) system with 192 Xeon quad-core CPU running at 2.83 GHz. Transient simulation of 40 s of real time was conducted for each case, which takes 3 days on 16 cores. Solids inventory and exit gas flow were monitored to determine if the simulation reached the statistically steady state. The results reported in this paper are time-averaged over the last 25 s of numerical results.

4. RESULTS AND DISCUSSION 4.1. Comparison with PSDF Experiment. The gas−solids flow inside the reactor was highly unsteady with clusters continuously forming and breaking up, and falling down close to the wall. This leads to the typical core-annular flow pattern: a dilute, rapidly rising core flow surrounded by a dense, slowly falling flow adjacent to the wall, as observed in most circulating fluidized beds. Penetrations of the coal jet and various feed streams into the bulk flow were also predicted. Consistent with the results reported in the literature,46,47 separation of coal particles and the transporting gas in the riser cross-flow was observed. Pressure profiles predicted by the CFD simulation were compared against the proprietary PSDF experimental data measured at four elevations along the riser for all three cases. Generally, the CFD simulation yielded reasonable agreement with the measurements. Computational results are compared against the PSDF experimental data with respect to the axial temperature profile as shown in Figure 3. In Figure 3, the mean temperature D

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presentation. The jet formed by the cold gas mixture, which is fed through the bottom, penetrates to a certain height leading to low temperature along the axis in the lower region. In the lower portion of the mixing zone, where the collected solids reenter the gasifier and combust to provide the heat necessary for the gasification reactions, the inner flow field temperature rises rapidly. Strong solids back-mixing exists in the mixing zone, which explains the high wall temperature in that region. The low temperature, due to cold feed of burner gases and coal, is evident in the temperature profile along the wall. Above the coal inlet, the temperature decreases slightly due to coal drying and devolatilization. In the upper region of the riser, the temperature profile is very flat and the overlap of wall and central axial temperature profiles indicates excellent heat transfer within the system. Overall, the CFD simulations yield reasonable agreement to the PSDF temperature measurements for all three operating conditions. Comparison of the exit syngas composition is presented in Figure 4, where the mole fractions of major gas components of interest are shown (scale is not provided for proprietary reasons). Numerical results based on chemical kinetics for devolatilization and char gasification from MGAS and PCCL are compared against the experimental data. It can be seen that all numerical simulations using MGAS kinetics overpredict the mole fraction of H2O but under-predict those of CO and H2, compared to the PSDF experimental data. The discrepancy between CFD simulation using MGAS kinetics and the experimental measurement is mainly attributed to the low steam gasification rate used in MGAS as discussed in the previous study.36 The steam gasification rate in MGAS was derived by Wen et al.35 based on the experiments with hydrodynamically different conditions than the PSDF transport gasifier. A parametric study of pre-exponential factors suggested that a higher steam gasification rate is needed for the transport gasifier conditions. However, arbitrarily adjusting the gasification rates to match the experimental measurement is not desirable. While the simulations based on the PCCL kinetics predict much improved results compared to MGAS. Both the previous studies by Guenther et al.36,37 and the current work illustrate the need for appropriate and accurate chemical kinetics for gasification process modeling. The C3M software platform was developed for this purpose, so that more accurate chemical kinetic models can be incorporated into CFD simulations. The differences between CFD predictions and experimental data might attribute to the chemical kinetics and assumptions in geometry and boundary conditions used in the simulation. It should be noted that the chemical kinetics predicted by PCCL has strong dependence on many operating conditions such as pressure, temperature, heating rate, and coal properties. In the current simulations, the estimated overall operating conditions were used to derive the kinetics using PCCL. An advanced algorithm to account for the variation of these major parameters is under-development which will yield more accurate chemical kinetics for complex gasification systems and improve the numerical prediction. Clearly, differences between numerical results observed in Figure 4 are due to the different kinetics for devolatilization and gasification used in these simulations. Further investigation is reported in the next section to compare the numerical predictions by incorporating different devolatilization kinetics to identify the leading order kinetics for numerical simulations of a transport gasifier. 4.2. Devolatilization Kinetics by Different Models. Coal devolatilization (or pyrolysis) is the first stage in coal

Figure 3. Comparison of axial temperature profiles along axis and wall with experimental data (a) TC20-69; (b) TC20-70; (c) R02-30.

profiles obtained over the last 25-s simulation along the wall and central axis are compared against the PSDF experimental data for three operating conditions. Without detailed information on where the experimental measurement was taken, it is assumed that the temperatures were measured close to the wall. For the wall temperature profile, an average is applied over the circumference. In this figure, the height and temperature are nondimensionalized by the experimental exit temperature and the gasifier total height, respectively, for E

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and operating conditions. Here the higher hydrocarbons are lumped into CH4 and minor species such as NH3 and H2S are ignored. This assumption is introduced to facilitate direct comparison among various kinetic models as different product gas species are predicted by different kinetic models. No significant impact by this assumption is expected as the current study focuses only on the composition of major syngas species. Further the contribution to measurable properties by such species in the gasification is minimal due to the very low concentrations. The devolatilization rate equation suggested by Wen et al.35 is used, which has the following form: rate = kd exp( −Ed /R gTs)εsρs XVM

(7)

where values of frequency factor, kd, and activation energy, Ed, are fitted parameters. Rg and Ts are universal gas constant and solids temperature and εs, ρs, XVM are solids volume fraction, bulk density, and mass fraction of volatile matter in the solids phase. Different devolatilization kinetics are derived from MGAS, PCCL, CPD, and FG-DVC through C3M. For each model, the program was executed with appropriate inputs including operating conditions, coal structure, and material properties. Output from the execution was fitted with an appropriate algorithm to derive the above rate eq 7. The stoichiometric coefficients were calculated based on the yield of each product gas. C3M completed all these steps automatically with no user interference needed. For the PSDF runs, rate constants by different models are listed in Table 3 and the stoichiometric coefficients are compared in Figure 5. Table 3. Devolatilization Kinetic Rate Constants by Different Models kd (1/s) Ed (cal/g-mole)

MGAS

PCCL

CPD

FG-DVC

75 000 18 700

169.10 4929.25

240.01 10 511.36

98.8 9058.21

Figure 4. Composition of exit syngas (a) TC20-69; (b) TC20-70; (c) R02-30.

combustion or gasification. Devolatilization occurs as the raw coal is heated in an inert or oxidizing atmosphere. The released volatiles mainly consist of CO, CO2, CH4, H2O, H2, tar, and higher hydrocarbons. Coal devolatilization is a very complex process affected by the thermal history, pressure, temperature, particle size, and coal structure and constituents. Various models with different complexities have been proposed to predict the yield and reaction rate of this process17 and the kinetics for devolatilization have profound influences on certain gasifier simulation.48 In this study, the devolatilization reaction is written as follows:

Figure 5. Stoichiometric coefficients of coal devolatilization by different models.

Differences in stoichiometric coefficients and reaction rate constants suggest that various chemical models predict distinct chemical kinetics given the same coal and operating conditions. In addition to chemical kinetics, the model selected also affects the total devolatilization yield. For example, the total yield of devolatilization in MGAS is based on the proximate analysis. However, it has been reported that higher heating rates and temperatures increase the total devolatilization product yield as well as the rate itself.49,50 On the other hand, an

volatile matter → αd tar + βdCoCO + βdCO2CO2 + βdCH4 CH4 + βdH2 H 2 + βdH2OH 2O

(6)

where α and β are the respective stoichiometric coefficients for the products as mass fractions determined by a phenomenological model based on coal proximate and ultimate analysis F

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increase in pressure inhibits devolatilization rate, ultimately reducing volatile yield. Depending on the operating conditions, higher or lower volatile yields (compared to the volatile matter reported in the standard ASTM proximate analysis) have been observed. For example, the ultimate yields of volatile matter predicted by CPD and FG-DVC are 0.48 and 0.4074, respectively, which are higher than the mass fraction of volatile matter of 0.355 from proximate analysis. 4.3. Effect of Devolatilization Rate. As illustrated in the previous sections, the chemical kinetics for coal devolatilization from various chemical kinetic packages are very different with respect to both product yield and reaction rate. It is of interest to evaluate how the reaction rate itself affects the numerical simulation compared to the final product yields, that is, stoichiometric coefficients. Figure 6 compares the reaction rates

Figure 7. Mass fractions of CO, CH4, and H2 in the exit syngas predicted by different devolatilization rates for TC20-69.

believed to be controlled by the slow char gasification reactions. Certainly, the devolatilization rate has a significant impact in the areas local to the coal injection sites. However, for these large-scale, long residence time reactors, the speed of this reaction appears to be of secondary importance to the exit syngas compositions. The system would appear to be dominated by gasification rates and (to a lesser extent) devolatilization product gas yields and/or rates. 4.4. Effect of Different Devolatilization Yields. Finally, all devolatilization kinetics predicted by MGAS, PCCL, CPD, and FG-DVC are incorporated into the PSDF transport gasifier simulation of TC20-69. This was done primarily to evaluate the impact of different devolatilization yields on the numerical prediction of exit syngas because the devolatilization rate was shown to have little to no impact on the exit syngas composition for this system. The differences in devolatilization kinetics from the various sources were mainly observed to mainly affect the coal jet region. The influence is relatively local and does not appear to change the global flow behavior. In addition, its impact on the temperature field is moderate in the mixing zone and coal feed region. In the upper region, the temperature discrepancy predicted by runs with different devolatilization kinetics is less than 10 K. The exit syngas compositions are shown in Figure 8 for different models. As the comparison

Figure 6. Devolatilization rates predicted by different kinetic models (the shaded area represents varying reaction rates over 4 orders of magnitude).

predicted by different kinetic models, demonstrating the differences among the models. To separate the effects of reaction rate and product yield, a parametric study was conducted to vary the devolatilization rate derived from PCCL by increasing/ decreasing the reaction rate by a factor of 10 or 100, shown as the shaded area. This range of rates covers most of the variation in devolatilization rates from all kinetic models. In addition, instead of feeding the fresh coal, an artificial coal absent of volatile matter is used with the volatile matter converted to volatile gases to mimic the extreme scenario that devolatilization completes upon coal entering the gasifer. Finally, one test with the reaction rate set to zero was conducted to simulate the extremely slow devolatilization process. The product yields of devolatilization for all tests remained unchanged. For the rest of reactions, such as char gasification, the kinetics predicted by PCCL were used. Figure 7 compares the mass fractions of syngas components in the exit syngas predicted by different devolatilization rates. Here only the mass fractions of H2, CO, and CH4 are shown. These species are of primary interest as they determine the lower heating value of syngas. Except for the extreme case in which the coal devolatilization process is turned off, the change in devolatilization rate has only a minor effect on the syngas composition, especially when the devolatilization rate is increased. This observation can be explained by the fact that devolatilization usually occurs over a short time period, and the resident time of coal particles in a transport gasifier is long. As the residence time of the coal in the gasification system is significantly longer than the time needed to reach ∼100% conversion of the volatile matter, the syngas composition is

Figure 8. Mass fractions of CO, CH4, and H2 in the exit syngas predicted by using different devolatilization kinetics for TC20-69. (The error bar indicates the variation in products when varying the devolatilization reaction rate over 4 orders of magnitude).

shows, different devolatilization kinetics predicted by various chemical models only slightly affect the exit syngas composition of the transport gasifier simulations. The variations in exit syngas composition when varying the devolatilization reaction rate over 4 orders of magnitude are shown as error bars in G

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endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

Figure 8. As the error bars due to variation in devolatilization reaction rate are comparable to the variation in syngas composition due to different models, it is hard to comment the priority of reaction rate and devolatilization yield from Figure 8. In contrast to the comparison shown in Figure 4 which includes changing gasification kinetics, deviation among the results by different devolatilization kinetics is moderate. Overall, this analysis suggests that the effect of different devolatilization kinetics is of less importance comparing to the char gasification reactions for transport gasifier simulation.

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5. SUMMARY AND CONCLUSIONS In this study, numerical simulations of a pilot-scale KBR transport gasifier are reported by coupling the newly developed software platform, C3M, to the open-source code MFIX. The gasifier simulation was first conducted using chemical kinetics from MGAS and PCCL. Three operating conditions were simulated and numerical results were compared against the PSDF experimental data. Significant differences between different chemical kinetic models were observed and the simulation using the reaction kinetics from PCCL provided reasonable agreement to the experimental measurement of syngas composition. The deviation between different chemical kinetic models revealed in the current study suggests the importance of incorporating appropriate reaction kinetics in the gasifier simulation. To further identify the leading order chemical reaction kinetics in the transport gasifier simulation, detailed comparison of different chemical kinetics for coal devolatilization from various kinetic packages were conducted with the aid of C3M. The effect of both reaction rate and final yields of coal devolatilization were investigated for transport gasification process modeling with respect to the exit syngas composition. It was found that the effect of devolatilization kinetics on the transport gasifier simulation is considered to be secondary comparing to the char gasification reactions because of the relatively long solids residence time. Hence, more effort should be devoted to adopting accurate kinetics for char gasification reactions.

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REFERENCES

AUTHOR INFORMATION

Corresponding Author

*(T.L.) Phone: +1-304-285-4538. E-mail: tingwen.li@contr. netl.doe.gov, [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This technical report was produced in support of the National Energy Technology Laboratory’s ongoing research in advanced numerical simulation of multiphase flow under the RES contract DE-FE0004000. This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its H

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