Simulation of Bed Dynamics and Primary Products from Fast Pyrolysis

Article pubs.acs.org/IECR

Simulation of Bed Dynamics and Primary Products from Fast Pyrolysis of Biomass: Steam Compared to Nitrogen as a Fluidizing Agent Pelle Mellin,* Efthymios Kantarelis, Chunguang Zhou, and Weihong Yang KTH Royal Institute of Technology, Division of Energy and Furnace Technology, Brinellvägen 23, SE 100 44 Stockholm, Sweden ABSTRACT: Fast pyrolysis of biomass, using steam as a fluidizing agent, provides several benefits. In this paper, an unsteady multiphase computational fluid dynamics (CFD) model coupled with a comprehensive kinetic scheme for primary pyrolysis is used to obtain the formation rates of primary products and compare the profiles when operating with steam and nitrogen. The model only considers the physical effects of the fluidizing gas at the moment, although a literature review indicates the existence of various chemical and surface-interacting effects. At stabilized pyrolysis reaction rates, the product yields were compared to data found in the literature, which indicated similar yields; this supports the correct implementation of the kinetic model. However, the difference in overall rate and composition is very small when steam is compared to nitrogen. The simultaneous simulation of bed dynamics indicate a shifted formation rate of primary products toward the lower part of the fluidized bed, with an increase in solid−vapor contact time and better temperature distribution as a result. More specifically, total heat flux to the biomass increased by 13% in the lowest part of the reactor. In addition, more heat from the sand is carried through the gas phase when using steam: an increase by 9% in the overall reactor (25% in the lowest part), as indicated by the results. Finally, since no substantial differences in overall product formation rate and composition were found, the considerable effect of steam found in experiments and the literature is mainly (not exclusively) attributed to the chemical and surface-interacting mechanisms. Because of the complex nature of secondary pyrolysis in this process, a comprehensive gas-phase kinetic model is needed to investigate the effects of steam further. Coupling of both is difficult, because of computational constraints, as the present model already is very demanding. The obtained profiles of formation rate of primary products can however be used as an input to another model specifically made for studying homogeneous secondary pyrolysis reactions. Funke and Ziegler6 theorized that water can absorb generated heat and thus act as a buffer to spatial temperature variations. Physical effects are also referenced in steam applications such as deacidification7 and naphthalene cracking to produce olefins,8 but here in relation to operating with no medium. Decap et al.7 argued that the same result can be achieved with an equivalent molar flow rate of nitrogen. The physical effects could be considered well-confined and, in some of these processes, well-understood. However, the effects in fluidized-bed fast pyrolysis of biomass cannot be intuitively derived from knowledge about these processes, since steam also affects the bed dynamics. Hence, the purpose of this paper is to better understand how steam affects this particular process−in this work, in contrast to operating with nitrogen. Upon primary pyrolysis, which is described in detail by the model, it is assumed that steam affects by purely physical means. Further modeling efforts will be aimed at the gas phase, where a complex kinetic scheme involving radicals can be employed to describe the homogeneous chemical effects of steam. In the following section, the background first describes various effects of steam, and then a methodology describes the CFD model as well as the kinetic scheme. After that, results show

1. INTRODUCTION Fast pyrolysis of biomass is a process that, potentially, can supply refinery feedstock, heating oil, and several different chemicals. Fluidized beds are a common choice for pyrolysis, because they provide a fast heating rate, a short residence time, and ease of scaling. Steam as a combined pyrolysis medium and a fluidizing agent was introduced on an experimental basis in Kantarelis et al.1 and steam in combination with catalytic materials in Kantarelis et al.2,3 The objective of this paper is to model the fast pyrolysis fluidized-bed process with steam and nitrogen, using computational fluid dynamics (CFD) coupled with a kinetic scheme for primary pyrolysis. Thereby, formation rate profiles of primary products can be obtained and compared when operating with either steam or nitrogen as a fluidizing agent. The effect of steam on the pyrolysis of solid carbonaceous feedstock is generally considered physical, chemical, and surface-interacting.4 However, in many literature sources, chemical and surface-interacting effects are embodied as mechanisms solely affecting the secondary homogeneous vapor-phase pyrolysis and tar evaporation. Hence, our leading assumption is that steam only provides physical effects (by the thermophysical properties) to the bed dynamics and primary pyrolysis, which permits use of the proposed model. Hot water is similarly known to provide many effects; in hydrothermal carbonization (HTC), water has been described as being able to participate as a catalyst, reactant, and solvent.5,6 It is likely that water also can provide physical effects; for example, © 2014 American Chemical Society

Received: Revised: Accepted: Published: 12129

May 16, 2014 June 26, 2014 June 30, 2014 June 30, 2014 dx.doi.org/10.1021/ie501996v | Ind. Eng. Chem. Res. 2014, 53, 12129−12142

Industrial & Engineering Chemistry Research

Article

At a temperature of 590 °C and in the presence of steam, El Harfi et al.8 found that polycyclic hydrocarbons (hopanes, sterans), pristine and a series of isoalkanes, are absentin contrast to operating with nitrogen as the carrier. These noncatalytic results at 590 °C could point to the lower boundary in temperature for steam reforming. At temperatures up to 500 °C, steam seems to stabilize radicals (polymerization precursors) and prevent decomposition. The effect in this temperature range seems analogous to the effects of hydrogen as discussed in Gopakumar.19 Especially in respect of polycondensation, as a link between inhibition of polymerization and hydropyrolysis is apparent in the work by for example Canel et al.20 Even for ambient pressures of hydrogen, a distinct effect on the pyrolysis oil composition has been found, according to Meesuk et al.21 The effect is possibly analogous to using steam, since steam stabilizes radicals as well as donates and exchanges hydrogen with unsaturated structures. In fact, Dutta et al.4 presented work in the temperature range of 350−530 °C, on steam pyrolysis of coal with aid of deuterated water. The results showed that D readily transfers from the water molecule to the liquid product (far less D transferred to the coke fraction, as a side note). A related study involving biomass is presented by Mettler et al.,22 in which hydrogen exchange is linked to the deoxygenation of levoglucosan. As shown by GC-MS, by Pütün and co-workers,23−25 oils produced in a steam atmosphere contain large portions of lighter hydrocarbons, which could be due to hydrogen donation.25 In terms of hydrogen donation, and especially hydrogen mobility, steam shows similarities to operating with H2 atmosphere, as studied, for example, by Zhang et al.26 2.3. Mild Oxidation. This effect is suggested by Minkova et al.14 to explain the higher concentration of oxygen-containing groups found on the surfaces of remaining char particles. In accordance with this reasoning, steam pyrolysis initially produces a surface with more active sites due the mechanism discussed in section 2.1, which enables oxygen to attach and form functional groups. The source of oxygen could be steam; as discussed by Zanzi,27 this mechanism is utilized at higher temperatures (800−1200 K) after an initial inert pyrolysis step, to produce activated carbon. The mild oxidation causes a progressively developing porous structure. This mechanism is similar and possibly analogous with reforming (or gasification) described in the previous section. At temperatures relevant for fast pyrolysis (∼500 °C), oxidation of char or volatiles will probably not occur to any appreciable extent, since the residence time is very short; in fact, a longer reaction time (by several orders of magnitude) is used in the work by Minkova et al.14 (1−2 h). 2.4. Decarbonylation and Decarboxylation. Funke and Ziegler6 proposed that hydrothermal treatment causes a partial elimination of carboxyl groups; one specific source would be formic acid. Conversely, Zhang et al.26 found that a CO and CO2 atmosphere suppresses decarbonylation and decarboxylation, respectively; at the same time, more acids are found preserved in the liquid, which supports the activity of this mechanism. In Kantarelis et al.,1 increasing amounts of carbon dioxide formed at higher feed ratios of steam to biomass, which is offset by decreasing acid yield. In parallel, the oxygen content decreases, which indicates that instead of dehydration, decarbonylation and decarboxylation, contributed to a larger extent as mechanisms for oxygen rejection, due to steam presence. This is the most noticeable mechanism; it has been considered a chemical effect, since it is presumed to occur homogeneously in the vapor phase.

steam pyrolysis compared to nitrogen fast pyrolysis, which is followed by conclusions.

2. BACKGROUND In previous research, several mechanisms have been linked to the effect of steam on pyrolysis of solid carbonaceous feedstock. The effect on coal has generally been investigated in detail, which, until recently, attracted more attention, compared to biomass. The effects seem analogous in most cases; the mechanisms believed to contribute in fast pyrolysis have been described here under different headlines. Note that this set is not exhaustive, because there might be other subtle and unknown mechanisms. The complexity should be highlighted as well, the mechanisms could interact making them not completely additive; as such, this phenomenological study is more on the explorative side and should be considered in addition to a larger body of research. 2.1. Enhanced Tar Evaporation and Coke Reforming. In the petrochemical industry, steam is often used to dilute the cracking products.9 In the diluted state, the products are less likely to react with each other and form unwanted compounds, such as coke, by polymerization. This suggests that dilution could be achieved with any gaseous solvent. The polarity of solvents are known to homogeneously affect the behavior of a reactant but modeling work such as Lin and Gao10 shows that mainly dense solvents (such as liquids) cause this effect. This is in agreement with the discussion by Mettler et al.,11 where the effect of solvents primarily is related to the passage of tars through the surface film of an intermediate liquid. Instead, penetration of steam into the pores of the biomass particle may contribute to dilute primary pyrolysis products, close to the particle surface, and hence facilitates the evaporation. Based on coal and biomass pyrolysis in a steam atmosphere, Minkova and co-workers,12−14 in both cases, found a facilitated desorption due to steam, leading to a milder pyrolysis with more volatiles intact. This mechanism increases the yield of liquid at the expense of char while rendering the char highly porous. In fact, the tar evaporation from within the pores is an important aspect of pyrolysis. Link et al.15 estimated that the total void fraction in the internal structure of wood is dominated by microporosity (80%), over mesoporosity (15%), and macropores (5%). The micropores are easily clogged by coke during pyrolysis, which results in a drastically reduced specific surface area.14 The enhanced evaporation with aid of steam is used to great effect in gasification, to obtain a more active char, which is converted to gas at a higher rate.16 2.2. Hydrogen Donation and Exchange. In our previous work (see Kantarelis et al.1), steam has been found to reduce oxygen content and acidity of the resulting bio-oil. In ref 1, it is suggested that steam could play a role in the condensation of aromatic rings to polyaromatic hydrocarbons (PAHs). Steam then acts as a hydrogen donor and suppresses polycondensation. This mechanism could be active but in accordance with the discussion by Yang et al.,17 polyaromatic condensation is more important at higher temperatures, i.e. at a later stage in the tar maturation. In contrast, steam is regularly seen as an agent, aiding in the reforming of coke or tarry compounds, as used in, for example, heavy oil refining.8 In gasification, at significantly higher temperatures, steam participates in tar reforming and chargasification, resulting in a cleaner syngas with higher calorific value.16 The steam gasification of char is often distinctly described in numerical models, as it provides a significant impact on the syngas composition (see, for example, Liu et al.18) 12130

dx.doi.org/10.1021/ie501996v | Ind. Eng. Chem. Res. 2014, 53, 12129−12142


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Table 1. Role of Steam in Fluidized Bed Fast Pyrolysis, In Relation to an Inert Gas category

indication

possible mechanism involving steam

surface interaction chemical

affected surface properties of the residual char and higher liquid yield

physical

affected heat flux and fluidized bed dynamics

affected homogeneous vapor phase reactions, most notably less high mw compounds and less acids

(1) enhanced tar desorption by lowering the energy barrier for evaporation of the tar components (2) hydrogen donation and exchange, which stabilizes polymerization precursors (3) decarbonylation and decarboxylation (4) higher heat capacity and heat conductivity

Figure 1. Effects of steam on fast pyrolysis of a solid biomass particle, shown alongside the pyrolysis model suggested by Dufour et al.28

2.5. Enhanced Heat Transfer. Steam, in comparison with other gaseous media, has high thermal conductivity and high heat capacity. The water molecule also absorbs and emits radiation in the infrared spectrum, which could further promote heat distribution. In general, steam is known to provide a uniform temperature field in many applications. For fast pyrolysis, at ∼500 °C, conduction and convection dominates over radiation. Still, this would intuitively give a higher heat-transfer rate to the biomass particles, which could explain the lower char yield obtained when using steam.1 In addition, steam could provide operational benefits as temperature uniformity is improved. This effect is purely physical and is assumed to affect the primary pyrolysis alone, since the media is not permeating the solid biomass structure. Even though this effect might not be substantial in comparison with the other effects in terms of defining the pyrolysis products, the extent is still unknown and a matter of uncertainty. 2.6. Summary. The mechanisms, which are thought to affect the pyrolysis products, have been listed in Table 1; based on findings in the literature reviewed under the previous headlines. Throughout the temperature spectrum, steam seems by no means inert. At higher temperature, this means reforming and gasification, while at lower temperatures the involved hydrogen seems mobile and contributes to saturate different structures and stabilizing radicals. The mechanisms have been assigned to either physical, chemical or surface interacting effects, with an explanation given in the above sections. The mechanisms have been illustrated in Figure 1, which also features the pyrolysis process as suggested by Dufour et al.28 In light of the reviewed work, steam as an inhibitor for polymerization could (1) take effect on surfaces (or inside pores) of the reacting biomass particles, where desorption of

liquid tar is facilitated; or (2) take effect in the vapor phase, where steam can preserve sugars and other macromolecules by stabilizing polymerization precursors.1 The first effect is active close to the surface of a particle and has been assigned to the surface interaction in Table 1. In contrast, the second mechanism is homogeneously active in the vapor phase and has been assigned to the chemical effects of steam. Similarly, we have identified two mechanisms that could cause decreasing char yield (mechanisms 1 and 4). Investigating the impact of each is experimentally difficult but on a model basis, it is possible. This is one of the motives for the CFD work presented in this paper; by estimating the impact of mechanism 4 an indication on the importance of mechanism 1 can be learned. Additionally, some mechanism unique for this process could be revealed; consider for example the unusual hydrodynamic and heat transfer effects that would result from the fluidizing agent locally condensing. The results of the model only renders the physical effect of steam on primary pyrolysis and hydrodynamics of the fluidizedbed process; still the model can be considered comprehensive as it takes into account the three phases, with a complex set of reactions that describe the primary pyrolysis. To provide a more complete picture of steam pyrolysis, the present model could be coupled with a kinetic model for the secondary pyrolysis. However, the computational requirements are prohibitive as such kinetic schemes are very complex and are not considered in this work. In further research work, other effects of steam will be investigated by modeling only the chemistry of the gas phase, in accordance with a step-by-step approach. Simplification such as lumping and reduction of kinetic schemes, as described in Stagni et al.29 could then be an interesting continuation to produce 12131



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Figure 2. Schematic image of the pilot plant as well as the extent of the CFD model, the mesh, the multiphase framework and an example of model results (biomass volume fraction, along the plane Z = 0). Note that the color-map results are given with logarithmic scale.

For a reaction r, which produces a product i with stoichiometric coefficient x, from a reactant j in phase p, the following eq 3 gives the mass source (ṁ ). If the product i is in another phase, the reaction is called heterogeneous. The mass source ṁ also represents user-defined boundary conditions, such as the feeding zone where biomass is continuously added.

smaller chemical mechanisms for secondary pyrolysis, which are easier to apply.

3. METHODOLOGY The CFD model is indicated in the right part of Figure 2, the commercial software ANSYS Fluent 14.5 was used. The multiphase framework is further described in Mellin et al.30 with the some basic description given in this paper. The experiments made earlier were performed in a pilot-scale bubbling fluidized bed setup, using softwood biomass as feedstock and steam as the fluidizing media. The setup also included a hopper, a screw feeding line, fluidizing gas preheater, cyclone and a scrubber; see Figure 2 for a schematic drawing. The simulation uses a fixed time step, transient, second order formulation. QUICK is used for the volume fraction coupling, which corresponds to third-order accuracy. The flow is assumed laminar and, as a result, no turbulence is taken into account. Each time step is considered converged when the residuals fall below 1 × 10−3. The mesh used in the model consists of 158 998 hexagonal cells. The grid size in Y-direction is uniformly 3.9 mm. In both horizontal directions, the cells are, on average, 3.6 mm; however, the size varies for each cell, and the mesh conforms to the cylindrical shape. 3.1. Conservation Equations. The model is based on conservation equations, which are solved for the mixture phase, each individual phase and each individual specie. All these equations are then solved at every iteration in each time step. Equation 1 describes the overall mass balance in the CFD code, which is solved for all phases and the mixture phase (p denotes any phase), and eq 2 describes the species conservation, which is solved for each specie in each phase (i denotes any specie). A simple mass diffusivity of 2.88 × 10−5 m2/s is assumed; however, the focus is on the solid phases in this simulation. ∂ (αpρp ) + ∇·(αpρp vp⃗ ) = ṁ p ∂t

∂ (αpρp Yi ) + ∇·(αpρp vp⃗ Yi ) = ṁ i ∂t

ṁ i = xiMi =

⎛ E ⎞ A r exp⎜⎜ − r ⎟⎟ Mj RTp ⎠ ⎝

αpρp Yj

(3)

The mass exchange, shown in the Eulerian framework in Figure 2, includes drying and reactions. The defined pyrolysis reactions correspond to the scheme developed by Ranzi et al.31 shown in Figure 3, with kinetics proposed by Blondeau and Jeanmart.32 Heat of the reactions is collected from Calonaci et al.33 The different compounds shown in Figure 2 have assigned material properties, which are shown in Table 2. Equations 4 and 5 describe the conservation of energy and momentum, respectively, given as an example for the gas phase. The full set of equations for all phases include the coefficients Hgb, Hgs, Hbs, Kgb, Kgs, and Kbs, which describes the exchange between the phases (subscripts “g”, “b”, and “s” denotes gas, biomass, and sand). This exchange is important for a multiphase simulation and each coefficient is described shortly in the following sections. Note that the heat-transfer coefficients are volumetric and, hence, the volume fraction of the respective phase pairs is considered. ∂ (αgρg hg ) + ∇·(αgρg vg⃗ hg ) ∂t ∂p = − αg + τg : ∇vg⃗ − ∇qg⃗ + Hgb(Tg − Tb) + Hgs(Tg − Ts) ∂t (4) ∂ (αgρg vg⃗ ) + ∇·(αgρg vg⃗ vg⃗ ) ∂t = − αg∇p + ∇τg + αgρg g ⃗ + K gs(vg⃗ − vs⃗) + K gb(vg⃗ − v b⃗ ) + ṁ gbvg⃗

(1)

(5)

(2)

3.1.1. Energy Phase Exchange. Between the biomass phase and the gas phase, the volumetric exchange coefficient (Hgb) is defined according to Ranz and Marshall,34,35 (see eqs 6 and 7). 12132



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Figure 3. Kinetic scheme used for the primary pyrolysis in the model, adapted from Ranzi et al.31

Table 2. Material Properties Phase, Index Gas, Fluid 1 property, unit

N2(g)

H2O(g)

thermal conductivity, W/(m K) heat capacity, J/(kg K) viscosity, kg/(m s) density, kg/m3 particle size, μm

0.0454 e g

0.0670d f h

Biomass, Solid 1

tar

a

0.0176d 1100d 3 × 10−5i Ideal gas

b

c

NCG

wood

0.0176d 1100d 3 × 10−5i

0.104 1150 600 850

char

H2O(l)

0.104 0.104 1150 4180 Granular viscosityj 200 1000 850 850

sand, Solid 2 0.25 830 2650 300

a

Includes CH3HCO, CH3OH, C2H2O2, CH2O, C2H4O2, C2H5OH, C3H4O2, C3H6O, C5H8O4, C6H10O5, C6H5OH, C6H6O3, C9H10O2, and C11H12O4. bIncludes CH4, CO, CO2, H2, and C2H4. cIncludes Cell, CellA, HCell, HCell1, HCell2, LignC, LignH, LignO, and Lign. dData taken from ref 49. ecp = A1 + A2T + A 3T2 + A4T3 + A5T4, where A1 = 979.043, A2 = 0.4179639, AA3 = −0.001176279, A4 = 1.674394 × 10−6, A5 = −7.256297 × 10−10. fcp = A1 + A2T + A3T2 + A4T3 + A5T4, where A1 = 1563.077, A2 = 1.603755, A3 = −0.002932784, A4 = 3.216101 × 10−6, A5 = −1.156827 × 10−9 gμ = μ0(T/T0)3/2(T0 + C)/(T + C), where μ0 = 1.7984 × 10−5, T0 = 273.11, C = 110.56. hμ = C1T3/2/(T + C2), C1 = 1.79 × 10−6, C2 = 632.5606. iData taken from ref 50. jData taken from refs 40 and 43.

Hgb =

6kgαgαbNub db

2

Nub = 2 + 0.6Reb1/2Prg1/3

Hgs =

(6)

6kgαgαsNus ds 2

(8)

(7)

Nus = (7 − 10αg + 5αg 2)(1 + 0.7Res 0.2Pr1/3)

For the volumetric exchange between the gas and sand (Hgs), eq 8 is used with the correlation for Nu (eq 9), following the work by Gunn.36

+ (1.33 − 2.4αg + 1.2αg 2)Res 0.7Pr1/3 12133

(9)



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A distinguished contribution from each phase is required in the Eulerian formulation; hence, the drag force proposed by Mickley and Fairbanks37 (as implemented in CFD by Papadikis et al.38), is modified and used. The modification is done to eliminate the contribution from the gas phase and only account for the sand phase, see the definition of hbs shown by eq 10. The volumetric heat-transfer coefficient (Hbs) is given by eq 11.

The exchange coefficient between the sand and biomass (Kbs) is defined according the work by Syamlal42 and is given in eq 22: Kbs =

πt

(11)

3.1.2. Momentum Phase Exchange. In the case of momentum, the exchange is determined by the coefficient multiplied by the mutual relative velocity. For the gas and biomass phase, the exchange coefficient Kgb (eq 12), by Morsi and Alexander39 is used; the drag coefficient is given in eq 13, alongside constants in eqs 14, 15, 16, and 17. A sphericity (φ) of 0.6 is used to account for additional drag caused by the irregular shape of the biomass particle. ⎛ 18μg ⎞ C Re ⎟ D b |vb⃗ − vg⃗ | K gb = ⎜⎜ 2⎟ ⎝ ρb db ⎠ 24

(12)

C3Reb 24 (1 + c1Rebb2) + Reb C4 + Reb

(13)

C1 = exp(2.3288 − 6.4581φ + 2.4486φ 2)

(14)

C2 = 0.0964 + 0.5565φ

(15)

CD =

Table 3. Cases for Comparison

C3 = exp(4.905 − 13.8944φ + 18.4222φ 2 − 10.2599φ3)

Fluidizing Agent

(16)

C4 = exp(1.4681 + 12.2584φ − 20.7322φ 2 + 15.8825φ3) (17)

For the drag coefficient between the gas and sand phase (Kgs; eq 18), the equations from Syamlal and O’Brien40 is used. Additional coefficients are given in eqs 19, 20, and 21. The coefficients C1 and C2 in eq 21 are tuned in order to accurately predict the experimentally determined minimum fluidization velocity (0.08 m/s at room temperature); thus being set to 9.19 and 0.28, respectively. For additional information on the drag law tuning, see Mellin et al.41 ⎛ Re ⎞ CD⎜⎜ s ⎟⎟|vs⃗ − vg⃗ | K gs = 4vr , s2ds ⎝ vr ,s ⎠

(18)

⎛ CD = ⎜⎜0.63 + ⎝

(19)

A = αg

4.14

(0.06R es)2 + 0.12R es(2B − A) + A2 ) ⎧ αgc1 αg > 0.85 ⎪ B=⎨ ⎪ c 2αg1.28 αg ≤ 0.85 ⎩

gas

flow rate, kg/h

molar flow rate, mol/h

biomass feed rate, kg/h

S/Ba

initial case steam

N2(g) H2O(g)

1.62 1.00

57.86 55.56

2 2

0 0.5

S/B = weight ratio of added steam to biomass.

the experimental feedstock composition and the model feeding rate, in terms of elements and components (cellulose, hemicellulose, and lignin).

( t −0.1t

tanh

ṁ H2O ṁ H2O + ṁ N2

=

90%

)

+ 1.0986 + 1 2

(23)

3.3. Post-processing. Data files were saved regularly during the computation, because the results were evaluated at the end. The computation was stopped when the amount of steam inside the reactor was stabilizing; the wall clock time for the entire simulation effort was ∼4 months. The reaction rates were determined by integrating the reaction rate in each cell over the entire domain (eq 23), and the reaction heat is determined likewise by multiplying the rate by the reaction enthalpy. Equation 24 gives the product formation rate, which was used to determine the pyrolysis oil composition.

vr ,s = 0.5(A − 0.06R es +

case

a

3αsαlρf

⎞2 4.8 ⎟ Res/vr ,s ⎟⎠

|vs⃗ − v b⃗ |

(22)

(10)

⎛ 6α ⎞ Hbs = hbs⎜ b ⎟ ⎝ db ⎠

2π(ρs ds3 + ρb db3)

The work by Lun et al.43 is used to calculate the bulk viscosity for the sand phase. The solid shear viscosity is a sum of two components (frictional viscosity is assumed negligible), which are collisional viscosity (estimated in accordance with Gidaspow et al.44) and kinetic viscosity (according to Syamlal et al.40). Granular temperature is estimated based on kinetic theory, from Syamlal et al.40 3.2. Initial Conditions and Boundary Conditions. In this work, the boundary conditions are the same as those given in the work of Mellin et al.,30 apart from the inlet fraction of steam. The simulation was started with nitrogen as a fluidizing gas; until the results largely stabilized, as an example, the entrainment of solids will stabilize after several minutes. In the beginning seconds, a heterogeneous stiff chemistry solver was used to deal with the complex kinetic scheme used in this simulation. After 14.38 s, a second simulation was started, where the weight fraction of steam was gradually increasing, thus producing two cases: one with nitrogen and one with steam. The gradual increase of steam was determined by eq 22, where t is the elapsed time after 14.38 s and t90% is the time until 90% of the change occurs, which was set to 0.4 s. After ∼0.5 s, the inlet fraction of steam was almost 100%, and a total of 5 s was calculated. During the 5 s, the reactor was almost completely filled with steam. The final flow rate of steam was set in order to retain the same volumetric flow rate (see Table 3). Table 4 gives

αs 2ksρs Cp,s

hbs =

3(1 + esb)(π /2 + Cfr,sbπ 2/8)αsρα ρ (d + db)2 g0,sb s b b s

(20)

Rr = (21) 12134

∫

⎛ E ⎞ A r exp⎜⎜ − r ⎟⎟ dV Mj RTp ⎠ ⎝

αpρp Yj

(24)



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Table 4. Composition of the Experimental Feedstock and the Corresponding Model Feedstock, with the Component Feeding Rate and Elemental Feeding Rate Experimenta

Model

parameter

value, unitb

moisture volatile matter fixed carbon ash HHV

9.80 wt % 83.00 wt %, db 16.60 wt %, db 0.31 wt %, db 20.46 MJ/kg

component (formula)

moisture (H2O) cell (C6H10O5) HCell (C5H8O4) LignC (C15H14O4) LignH (C22H28O9) LignO (C20H22O10) ash (SiO2) Elements carbon (C) 50.70 wt %, dab carbon (C) hydrogen (H) 6.10 wt %, dab hydrogen (H) oxygen (O)c 42.71 wt %, dab oxygen (O) nitrogen (N) 0.18 wt %, dab sulfur (S)

Simulation of Bed Dynamics and Primary Products from Fast Pyrolysis

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