A two-fluid model simulation of an industrial moving grate waste incinerator

Waste Management 104 (2020) 183–191

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Waste Management journal homepage: www.elsevier.com/locate/wasman

A two-fluid model simulation of an industrial moving grate waste incinerator Zihong Xia a, Peng Shan a, Caixia Chen a,⇑, Hailiang Du b, Jie Huang b, Li Bai b a b

Department of Energy and Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China Waste Incineration Tech & Equipment National Engineering Laboratory, Shanghai SUS Environment Co., LTD, Shanghai 201703, China

a r t i c l e

i n f o

Article history: Received 25 July 2019 Revised 17 December 2019 Accepted 13 January 2020

Keywords: Moving grate incinerator TFM-KTGF simulation Direct simultaneous in-bed/over-bed coupling Realistic grate geometry

a b s t r a c t CFD modelling and simulation is an effective means of optimizing the design and operation of moving grate waste incinerators. Conventional approach models the grate combustion and the furnace combustion separately by using an in-bed/over-bed coupling procedure. In this paper, a comprehensive two-fluid reacting model that integrates the gas-solid grate incineration and the gas turbulent combustion in one scheme is developed for industrial incinerators. Realistic grate geometry and direct simultaneous coupling of the fuel bed and the freeboard gas phase are realized. According to different treatments of the solid phase, the whole incinerator is divided into three regions, namely the packed bed region, the fall region and the furnace region. The kinetic theory of granular flow (KTGF) is introduced to describe the rheological properties of waste particles, and the Ergun model is used for the gas-solid drag. Thermal conversion of wastes is characterized by the heterogeneous reactions of moisture evaporation, devolatilization, char-O2 combustion and the homogeneous reactions of hydrocarbons combustion. Distributions of temperatures and gas species are predicted and validated by measurements. Particle properties are calculated to reveal the grate incineration characteristics. Effects of waste throughput on the incineration are also investigated. Overall, the present model provides a new methodology of in-bed and over-bed integration for the moving grate incinerator simulation. Ó 2020 Published by Elsevier Ltd.

1. Introduction Municipal solid wastes (MSW) incineration is gaining popularity in China encouraged by the ‘‘13th Five-Year” national urban solid waste disposal facilities construction plan (National Development and Reform Commission, 2016). By the end of 2020, more than a half of MSW will be disposed of by incineration, and the incinerator capacity is preferably over 300 tons per day. In the past decades, several moving grate incineration technologies have been introduced into China, such as Hitachi Zosen Inova, JFE Hyper Stoker and Mitsubishi Martin. However, these incinerators do not operate satisfactorily limited by the high moisture and low heating value of the input wastes. The smooth operation and further equipment modification of incinerators require an indepth understanding of the combustion process. Since the common experimental method is restricted by the large waste variations, violent combustion conditions and complicated boiler structures, Computational Fluid Dynamics (CFD) provides an effective alternative. ⇑ Corresponding author. E-mail address: [email protected] (C. Chen). https://doi.org/10.1016/j.wasman.2020.01.016 0956-053X/Ó 2020 Published by Elsevier Ltd.

MSW incinerator is usually composed of a moving bed stoker and an over-bed combustion chamber. The waste solids are first heated by the over-bed radiation and the primary air after being pushed onto the grate, and go through the drying, pyrolysis, and char burnout processes. Combustibles of wastes are released into the furnace freeboard and continue to combust with the excess air to form a high temperature zone. Correspondingly, the whole incineration is divided into the in-bed moving grate combustion and the over-bed gas turbulent combustion. And this makes the standard multiphase flow models hardly used for the whole incinerator simulation. Efforts have been made in the bed models focusing on the hydrodynamics of gas-solid flow and thermal conversion of MSW. The flow pattern on the grate is a typical moving packed bed with considerable differences of phase properties. Several inhouse bed codes are developed in the 2D frame. For example, FLIC (Fluid Dynamic Incinerator Code) solves the phase properties along the bed height, then conducts a time-space transformation by projecting the transient variations onto the grate length (Yang et al., 2002, 2005). Gu et al.(2019) developed BASIC (Bulk Accumulated Solids Incineration Code) by correcting boundary conditions for the bedtop, homogeneous reations and calculation method for

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Nomenclature

Roman letters a absorption coefficient, m
1 C empirical coefficient Ci gas molar concentration, kmol/m3 C 1e ; C 2e ; C 3e constants, 1.42, 1.68, 1.3 cp specific heat capacity, J/(kg K) gas diffusivity, m2/s Di ds particle diameter, m ess coefficient of restitution production of turbulent kinetic energy, W/m3 Gk,g g acceleration of gravity, 9.81 m/s2 g0,ss radial distribution function Hevap latent heat of evaporation, J/kmol heat transfer coefficient, W/(m2 K) hpq I2D second invariant of the deviator of the strain tensor for solids phase, 1/s2 J mass flux, kg/(m2 s) k turbulent kinetic energy, m2/s2 kd gas diffusion rate, kg/(m2 s Pa) Kgs interphase momentum exchange coefficient, kg/(m3 s) kgs covariance of the velocities of the gas phase and the dispersed phase kr kinetic rate, kg/(m2 s Pa) Nu Nusselt number P pressure, Pa Pr Prandtl number R universal gas constant, 8.3145 J/(K mol) Rchar reaction rate of char combustion, kmol/(m3 s) reaction rate of devolatilization, kmol/(m3 s) Rdevol Revap reaction rate of evaporation, kmol/(m3 s) RCmHn reaction rate of CmHn combustion, kmol/(m3 s)

pyrolysis products. But in these models, the solid phase is treated as the porous medium and its velocity is pre-assigned as the grate moving speed. Inter-particle interactions and particle movements are also greatly simplified. The porous medium alone is not enough to describe the bed compaction resulted from fuel consumption. Lin et al. (2009) employed the dynamic mesh technique to simulate the coal combustion on the traveling grate. Gómez et al. (2014) proposed a cell collapse mechanism model, which produced a mass (volume) exchange between cells with the consequent mass grouping to describe the bed contraction. Thresholds were defined to control the compaction procedures by emptying the higher cells and filling the lower cells. Using a similar collapse method, Hermansson and Thunman (2011) predicted the channeling phenomenon. Naser group investigated the effect of moving grate bars on the reciprocating grate biomass combustion (Karim and Naser, 2018a), and verified the biomass thermal conversion under different air/oxyfuel conditions (Karim et al., 2020). In order to give detailed descriptions of particle movements, Ismail et al. (2014) and Sun et al. (2016a, 2016b) incorporated the kinetic theory of granular flows (KTGF) into bed combustion. Comparison of their simulations with experimental data showed more accurate results than FLIC (Ismail et al., 2014). The discrete particle model (DPM) is also an option since it enhances the particle-particle collisions and frictions by assuming the whole bed as an ensemble of representative particles. Mehrabian et al. (2012, 2014) employed DPM in the packed bed biomass combustion to track each representative particle’s trajectory along the grate. Wissing et al. (2017) proposed a DEM/CFD

RCO Rhet Ri Re S Sh T t Dt U v wc wi Yi

reaction rate of CO combustion, kmol/(m3 s) heterogeneous reaction rate, kg/(m3 s) homogeneous reaction rate, kg/(m3 s) Reynolds number source term Sherwood number temperature, K time, s time step, s velocity, m/s velocity, m/s molecular weight of carbon, 12 kg/kmol species molecular weight, kg/kmol mass fraction of species

Greek letters a volume fraction e turbulent dissipation rate, m2/s3; emissivity / angle of internal friction u stoichiometric coefficient k bulk viscosity, Pa s l viscosity, Pa s q density, kg/m3 r Stefan-Boltzmann constant s stress-strain tensor, Pa 2 2 H granular temperature, Hs ¼ 13 ðv 02 s Þ,m /s Subscripts g gas phase p particle s solid phase t turbulent

coupling method to investigate the effects of waste properties, grate and furnace design. But the computational cost is overwhelming for solving the Newton’s second law of motion, and external coupling of bed and furnace is still needed. Accurate modelling of MSW thermal conversion is also key to bed modelling. Thermally thick and thermally thin particle models are usually used. In the former model, the distinct gradient development and simultaneous progress of different conversion stages are described in detailed sub-models. Four layers inside the particle, which are the wet fuel layer (moisture layer), the dry fuel layer (volatile layer), the char layer and the ash layer are defined to simulate the variations of the solid properties. For example, Gómez et al. (2014, 2018) introduced six user defined scalars to characterize the radial variations in each layer: (1) solid temperature, (2) solid fraction, (3) density of wet wastes, (4) density of dry wastes, (5) density of char, and (6) particle characteristic volume. Mehrabian et al. (2012) first combined the layer model with DPM to track the conversion of a single particle, and then extended to multiple particles (2014). As for the thermally thin model, no gradients are present inside the particle, and the conversion stages take place sequentially in such a manner as the FLIC work. It is convenient to apply in the industrial waste incinerator, since the global conversion is predicted with a relatively low computational cost. For the high-moisture MSW, the evaporation process dominates the grate combustion process, then the pyrolysis and char burnout have to take place afterwards. When combining bed models with furnace combustion, a strong coupling link exists between the bed and the freeboard, which is the incident radiation of furnace. The radiation heat flux plays a

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critical role in the drying process, the ignition front propagation and the fuel consumption on the grate (Karim and Naser, 2018b; Karim et al., 2018). For example, FLIC assumes an artificial surface where the mass and energy exchanges occur. To ensure the surface exchanges are modelled accurately, a 2D FLIC/FLUENT coupling procedure has to be adopted, and several iterations are needed to make the incident radiation flux over the bed top unchanged (Xia et al., 2014; Yang et al., 2002, 2005). Moreover, the existing proposed models are mostly validated in the fixed bed or packed bed reactors. The realistic grate geometry is not considered, and its effect is ignored. When applying these models to the moving grate, especially with the fall regions between two stages of grate in this paper, the dynamic variations of mesh are hard to control due to the complicated grate structure. To the best of our knowledge, a comprehensive multiphase model that could compute both the gas-solid moving grate incineration and the gas turbulent combustion in one scheme is not reported in the open literature. In this paper, we proposed a 3D two-fluid model for the industrial moving grate incinerator that integrated the gas-solid grate incineration and the gas turbulent combustion in the platform of ANSYS FLUENT 14.0. Simulations of a realistic grate geometry with a direct simultaneous coupling of the fuel bed and the freeboard gas phase were realized in this model. The rheological properties of the solid phase were described by the kinetic theory of granular flow (KTGF), and the gas-solid drag on the grate were expressed by using the Ergun model (Ergun, 1952). Thermal conversion of MSW was predicted by taking into account the heterogeneous reactions of moisture evaporation, devolatilization, char-O2 combustion and the homogeneous reactions of hydrocarbons combustion. Distributions of temperatures and gas species concentrations were predicted and compared with measurements. In-bed particle properties were calculated, and effects of waste throughput were investigated.

2. Modeling and simulation methods 2.1. The benchmark MSW incinerator Fig. 1(a) shows the schematic diagram of the 750 t/d MSW incinerator located in Ningbo, Zhejiang Province. The moving grate is subdivided into three consecutive sections: primary air zone 1, 2 and 3. The length is 14.83 m and the width is 8.8 m. The residence time of wastes on the grate stoker is 1.75 h (6300 s). And the initial bed height is 1.2 m. The combustion air is split into primary and the secondary air streams with a ratio 1.3:0.25 and a total fuel stoichiometric ratio of 1.55. The primary air is preheated to 453 K, and fed from six wind boxes below the grate. The secondary air is kept at 300 K, and injected from nozzles located in the throat of incinerator. Note that the nozzles are staggeredly arranged at the front arch and the rear arch, and their numbers are not equal. The detailed arrangement of secondary air nozzles is shown in Fig. 1 (b). Nine temperature measurement points (evenly arranged in three rows at Y = 15.0 m, Y = 12.2 m, and Y = 8.8 m) are distributed in the first chamber. The properties of wastes are listed in Table 1. The present two-fluid modelling includes two phases: a gas phase and a solid phase. The gas phase consists of CO, CO2, CmHn (m = 4.144, n = 11.645 in this case), H2O, O2 and N2 gases. The solid phase is made up of moisture, volatile, char and ash. As shown in Fig. 1(a), the incinerator is divided into three regions according to different treatments in the solid phase movement: the packed bed region, the fall region and the furnace region. In the packed bed region, wastes are conveyed by the moving chains, therefore the x-direction and y-direction velocities for the solid phase are kept constant and calculated by projecting the average grate speed (grate length/residence time) to the corre-

sponding direction, and the z-direction velocity is solved by the momentum equation. In the fall region, wastes fall down onto the next grate due to gravity, then the solid phase velocity is simplified as the free-falling velocity. The furnace region is free of particles for the modelling simplification; thus, the momentum equation is not solved for the solid phase, and only the turbulent (reacting) gas flow is simulated. 2.2. Hydrodynamics of gas-solid flows The constitutive equations for the gas-solid hydrodynamics are similar to our previous modelling in the fluidized bed coal gasification (Xia et al., 2015, 2016). Therefore, only general equations are listed in this section. The continuity equations for the gas and solid phases are expressed as:

@
! ðag qg Þ þ r  ðag qg v g Þ ¼ Sgs @t

ð1Þ

@
! ðas qs Þ þ r  ðas qs v s Þ ¼ Ssg @t

ð2Þ

where a represents the volume fraction. The source terms Sgs andSsg represent the mass exchange between phases due to heterogeneous reactions:

Ssg ¼
Sgs ¼ wi

X

ð3Þ

Y i Rhet;i

The momentum equations for the gas and solid phase (only zdimensional velocity of the solid phase is solved, x and y velocities are defined by the average moving speed of grate) are expressed as Eq. (4) and Eq. (5), respectively:

@
!
!
! ðag qg v g Þ þ r  ðag qg v g v g Þ @t !
!
! ¼
ag rp þ r  sg þ ag qg g þ Rgs þ Sgs v gs

ð4Þ

@
!
!
! ðas qs v s;z Þ þ r  ðas qs v s;z v s;z Þ @t

!
!
! ¼
as rp
rps þ r  ss þ as qs g þ Rsg þ Ssg v sg ð5Þ

where

sg and ss are the stress-strain tensors for each phase:



2 3

sg ¼ ag qg ðr
! v g þ r
! v g Þ
ag lg ðr 
! vq Þ I T



2 3



ss ¼ as qs ðr
! v s þ r
! v s Þ þ as ks
ls r 
! vs T

ð6Þ ð7Þ

For the solids bulk viscosity ks (Lun et al., 1984):

ks ¼

 12 4 H as qs ds g 0;ss ð1 þ ess Þ s 3 p

ð8Þ

For the shear viscosityls , it is a combination of the kinetic (ls;kin ), the collisional (ls;col ) and the frictional contribution (ls;f ), and the corresponding expressions are listed from Eq. (9) to Eq. (11), where a coefficient of restitution (ess ) of 0.92 is introduced to account for the energy loss due to particle collisions.

ls;kin ¼

1 pffiffiffiffiffiffiffiffiffiffi 1 pffiffiffiffiffiffiffiffiffiffi 10 Hs pqs ds g 0;ss ð1 þ ess Þa2s þ Hs pqs ds as þ 15 6 96 pffiffiffiffiffiffiffiffiffiffi qs ds  Hs p ð1 þ ess Þg 0;ss 4

H

1 2

ls;col ¼ as qs ds g 0;ss ð1 þ ess Þð s Þ es 5 p

ð9Þ

ð10Þ

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Fig. 1. Schematic structure of waste incinerator.

Table 1 Properties of MSW.

where the radial distribution function g 0;ss is introduced to modify the probability of particle collisions (Ma and Ahmadi, 1986):

Parameters

Value

Proximate analysis:

wt.(%)

Moisture (M) Volatile matter (V) Fixed carbon (FC) Ash (A) Ultimate analysis (daf, wt.%): Carbon (C) Hydrogen (H) Oxygen (O) Nitrogen (N) Sulfur (S) Chlorine (Cl) Lower heating value (LHV, kJ/kg) Particle density (kg/m3, mass weighted average) Bulk particle density (kg/m3) Mean particle size (cm, estimated)

P sin/ 2 I2D

ls;f ¼ spffiffiffiffiffiffi

46.50 25.50 8.00 20.00

61 þ 2:5000as þ 4:5904as þ 4:515439as 7 g 0;ss ¼ 1 þ 4as 6 5 4  3 0:67802 as ½1
as;max  2

In Eq. (13), as;max is calculated as

37

ð13Þ

qbulk qs .

Drag force has been proven to be a dominant interaction force
! for gas-solid momentum exchange, and is modeled by the term Rgs .

60.39 8.60 28.30 1.40 0.06 1.25 7000 1556

2
! X
!
! Rgs ¼ K gs ð v g
v s Þ

ð14Þ

p¼1

where K gs represents the interphase momentum exchange coefficient, and the Ergun model (Ergun, 1952) is employed in the computations, i.e.:

350 7





as 2 lg qg as 
! v s

! vg  K gs ¼ 150 þ 1:75 2 d s ag ds ð11Þ

Solid pressure (ps ) represents the normal solid-phase forces due to particle-particle interactions:

ps ¼ as qs Hs þ 2qs ð1 þ ess Þas 2 g 0;ss Hs

3

2 density (kg/m3, Xia et al. 2014) 1000 1500 2300 2630

ð12Þ

ð15Þ

The kinetic theory of granular flow (KTGF) model is to provide closures for the rheological properties of the fluidized particles. In analogy to the thermodynamic temperature for gases, the granular temperature (Hs ) is introduced as a measure of the particle velocity fluctuations. In this work, an algebraic expression of granular temperature equation is used:

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2


! 12ð1
peffiffiffi ss Þg 0;ss ffi 0 ¼ ð
rps I þ sS Þ : r v s
qs a2s H3=2 s ds p

ð16Þ

The dispersed renormalization group (RNG) k
e turbulence model is used. And the k and e equations are written as follows, respectively. @ ðag qg kg Þ @t

    l
! þ r  ag qg v g kg ¼ r  ag rt;g rkg k

þag Gk;g
ag qg eg þ ag qg Pkg

    l
! þ r  ag qg v g eg ¼ r  ag rt;ge reg   e þag kgg C 1e Gk;g
C 2e qg eg þ ag qg Peg

2.4. Reaction models

ð17Þ

ð18Þ

The overall incineration process is classified into moisture evaporation, devolatilization, combustion of volatile gases and char burnout. Rates for each individual process are described below. Moisture evaporation is controlled by a two-step mechanism. When the temperature is below the saturation temperature, the evaporation rate depends on the convective mass transfer. When the temperature is higher than the saturation temperature, any temperature increase is consumed by the evaporation process.

ð19Þ

Revap ¼

ð20Þ

where hw ¼

@ ðag qg eg Þ @t

where Pkq , Peq are defined as following:

Pkg ¼

M  X K gs 
!
! kgs
2kg þ v gs  v dr p¼1

Peg ¼ C 3e

ag qg

eg

Pkg

kg

work, the evaporation heat is assumed to be taken from the solid phase in a way that it is cooled down. As for the combustion, 20% of combustion heat is distributed to the gas phase, and the rest to the solid phase. These modifications are shown to give a realistic temperature field compared with the default settings.

hw  ðC w;s
C w;g Þ when T s 6 100 C 6ds

Revap ¼

2.3. Species transport and energy conservation equations The ith species transport equation in phase q is expressed as:


! @
! ðaq qq Y i;q Þ þ r  ðaq qq v q Y i;q Þ ¼
r  aq J i;q þ aq Ri;q þ Rhet;i @t

ð21Þ

ð22Þ

The term hpq in Eq. (22) is the gas-solid heat transfer coefficient, and the Wakao correlation (Wakao and Kaguei, 1982) suitable for the packed bed, is used.

hpq ¼

6kq ap aq Nup 2

ds

Nup ¼ 2:0 þ

1=3 1:1Re0:6 p Pr

ð23Þ ð24Þ

Radiation plays an important role to ignite the wastes combustion, and P-1 model (Cheng, 1964; Siegel and Howell, 1992) in Eq. (25) is used to solve the incident radiation of the mixture of both gas and solid phases. Then the enthalpy sources due to radiation (Sq ) are distributed to each phase according to Eq. (26):

1 r  ð rGÞ
aG þ 4arT 4 ¼ 0 here a ¼ ag ag þ as as 3a

ð25Þ

Sq ¼ aq aq ðG
4rT 4q Þ

ð26Þ

where aq is the absorption coefficient. The weighted-sum-of-graygases model (WSGGM) is used for the gas phase, and for the solid phase, the absorption coefficient is calculated by Eq. (27):

as ¼


lnð1
eÞ ds

1=3 DH2 O ð2:0 þ 1:1Re0:6 Þ p Pr ds

T s
T ev ap qw cp;w Hev ap 4 t

ð29Þ 

when T s > 100 C

ð30Þ

For the devolatilization, a single-step global reaction kinetic model of Arrhenius expression (Pyle and Zaror, 1984) is adopted to reduce the computational cost:

  69000 Rdevol ¼ 3000 exp
qs Y v ol RT s

The energy conservation equation is in the enthalpy form:

@
! ðaq qq hq Þ þ r  ðaq qq v q hq Þ @t @p
! þ sq : r v q þ hpq ðT p
T q Þ þ Sq þ Sr ¼
aq @t

ð28Þ

ð27Þ

The enthalpy sources due to evaporation and char combustion (Sr ) are specified by UDF (User-Defined Functions) to redistribute the reaction heat. The default treatment in FLUENT is to distribute the total reaction heat to the gas phase in the form of an energy source, and the solid phase is heated or cooled by the interfacial thermal convection instead of receiving the heat directly. In this

ð31Þ

The compositions of volatile gases released from the solids are assumed to be 33% CmHn (m = 4.144, n = 11.645), 28% CO2 and 39% H2O by volume based on mass and energy balances (Yang et al., 2002, 2005). The two-step global reaction model is used for CmHn combustion:

C m Hn þ

m 2

þ

n n O2 ¼ mCO þ H2 O 4 2

ð32Þ

1 CO þ O2 ¼ CO2 2

ð33Þ

In the packed bed region, the combustion rates of CmHn and CO are controlled by mixing between the combustible gases and the under-grate air supply, and given by Eq. (34). While in the furnace, the finite rate/eddy-dissipation model is used for the gas turbulent combustion. The Arrhenius type rate constants and the reaction rates are shown in Eqs. (35)–(36).

(

Rmix ¼ C mix qg 150

Dg ð1
ag Þ2=3

ds ag  C fuel C O2 ;  min Sfuel SO2 2

12

RC m Hn ¼ 2:345  10

U g ð1
ag Þ1=3 þ 1:75 ds ag

1:7  105  exp
RT g

)

ð34Þ !  C 0:5 C m H n  C O2

! 1:7  105 0:5  C CO  C 0:25 RCO ¼ 2:239  10  exp
O2  C H2 O RT g 12

ð35Þ

ð36Þ

For the char combustion, the rate is controlled by the surface reaction rate (Desai et al., 1978) and the gas diffusion rate.

C þ O2 ¼ CO2

ð37Þ

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Rchar ¼ 

P O2

1 kd

kd ¼

þ k1r



uShwc DO2 RT m ds

kr ¼ 0:871  expð
20000=1:987=T p Þ

ð38Þ

ð39Þ ð40Þ

The particle diameter varies with the reaction, and is predicted based on the ash mass conservation by Eq. (41).

ds ¼ ds;0

 1 Y ash;0 3 Y ash

ð41Þ

2.5. The initial and boundary conditions A 3D hexahedral mesh was generated with a total number of 1,412,439 cells as a compromise of the simulation accuracy and the computational cost. No significant variations of simulation results were found when a finer grid size (twice the current cell number) was used. The waste inlet, under-grate primary air inlet and secondary air inlet were treated as mass flow inlets. Since no leak air flow was considered in the simulation, only wastes were fed onto grate through the waste inlet at a constant mass flow rate as the waste throughput (the corresponding inlet velocity is 0.00229 m/s) and at a room temperature of 300 K. The flow rates of primary and secondary air were calculated by their excess air ratios. The walls below the throat were treated as adiabatic, while the other walls were set as fixed temperatures estimated from our in-site operating experiences. Standard wall functions were used for the near-wall treatments, and the y+ values are in the range of 50–300. A no-slip wall boundary condition was set for the gas phase and a partial slip boundary condition for the solid phase (Johnson and Jackson, 1987) with a specularity coefficient of 0.5. For the furnace outlet, a pressure outlet was used. In the real furnace, the onset of waste combustion is achieved by adding auxiliary fuel oil to combust with air to increase the furnace temperature to 1123 K. While in the simulation, the initial conditions were simplified as: the incinerator was full of nitrogen and free of wastes particles, temperatures were set as 1123 K for both the gas and solid phases to ignite the incineration. The Phase-Coupled SIMPLE algorithm was used for solving the pressure-velocity couple momentum equations, in combination with the phase weighted mass continuity. The QUICK scheme was used for the volume fraction, and the Second Order Upwind scheme was for the rest of variables (momentum, turbulence, energy and species). A time step 1 s was used for solving a first order implicit transient integration with a maximum number of 20 inner circle iterations for each time step. No significant variations of simulation results were found when smaller time steps were used. The simulation lasted for 6300 s of the real physical time, which was the residence time of wastes on the grate. And the TFM simulation was run on a workstation with 8 AMD 6376 16-CPU processors for 2000 s physical time per day. 3. Results and discussion 3.1. Results of benchmark case Fig. 2(a) and (b) show the gas and solid temperature distributions at the center plane of incinerator. Heated by the primary air and the furnace radiation, moisture evaporation occurs at primary air zone 1, and both temperatures near the inlet are almost unchanged. Along with the rapid release of steam, the remaining wastes warm up. At the end of zone 1, volatiles start to pyrolyze,

and the released hydrocarbons combust with primary air. In the middle of primary air zone 2, a high-temperature zone of 1500 K is formed above the bed. Upon mixing with the secondary air, the gas temperature rises to a peak of about 1570 K. The high temperature also promotes the char combustion, and the solid temperature rises to its maximum of 1200 K. When the wastes are conveyed onto primary air zone 3, only char residues burn with the primary air, then gas and solid temperatures reduce to 1000 K. Fig. 2(b) also shows the solid temperature distribution along the bed height. Here, the top surface of bed is defined with a contour surface of solid volume fraction of 0.01. The vertical distribution is non-uniform, and the temperature at the bed top is much higher than at the bottom. This indicates the radiation heat flux propagates onto the upper surface of the solid packed bed and the thermal conversion starts from the bed top. Fig. 2(c) presents a uniform temperature distribution at the throat cross section. Our previous simulations show that a highly non-uniform temperature distribution is formed by the inappropriate injection of the secondary air (Xia et al., 2014). In this work, the secondary air from the front and rear walls is injected into the furnace staggeredly, and the injection speed (35 m/s for each) is high enough to achieve a more uniform temperature and velocity distribution above the throat. Contours of incident radiation at the central plane are presented in Fig. 2(d). Within the high temperature zones, there are two strong radiation zones. One is near the bed top of wastes at primary air zone 2, where hydrocarbon and char combustions mainly occur. The other is above the throat due to the secondary air feeding. The Reynolds number of the freeboard gas flow based on the equivalent diameter of the throat cross section (6.2 m) is calculated. The Re value below the throat is less than 1e+05, while the value at the throat is about 1e+07. This indicates that the secondary air promotes the gas mixing and combustion. Fig. 2(e) indicates the variation of solid volume fraction along the grate. At primary air zone 1, change in the bed height is small, though particle size decreases by 20%. This is because the particle movement is pre-assigned by the average grate speed in the packed bed region (shown in Fig. 1). Conversion of wastes is mainly reflected in the reduction of solid volume fraction. One half of solid volume fraction is decreased, which corresponds to the remaining total mass at the end of zone 1 in Table 2. After being moved onto primary air zone 2, the volatile gases are ignited and char combustion occurs, the solid volume faction continues to decrease, and the bed height reduces to 0.8 m (two-third of the initial height). Residual particles continue to combust with the primary air at zone 3, which further reduces the bed height to 0.3 m. The bed heights at each zone are almost unchanged restricted by the assumptions of the packed bed region that x-direction and y-direction velocities for the solid phase are pre-assigned. Particle properties also change significantly along the grate. Table 2 shows the calculated particle properties at the end of primary air zone 1, 2 and 3. Drying dominates at the first part of grate, and moisture is completely evaporated at the end of zone 1. Average particle size decreases from 7 cm to 5.6 cm. One-third of volatile matter is consumed at zone 1, and the rest is entirely pyrolyzed at zone 2. Particle size reduces to 4.5 cm. At zone 3, only residual char burns out, and the particle size further reduces to 4.2 cm. Changes in the particle density also prove that evaporation and devolatilization dominate at zone 1 and zone 2. At the end of zone 3, wastes are almost converted, and only ash remains. Distributions of gas species mass fractions are shown in Fig. 3. The mass fraction of steam is highest near the inlet, which corresponds to the moisture evaporation at primary air zone 1, and decreases along the grate. The released steam flows into the furnace and moves mainly along the front wall. In the middle of furnace, steam is produced by the hydrocarbon combustion,

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Fig. 2. Simulation results of benchmark case: (a) gas temperature (K) at the center plane, (b) solid temperature (K) at the center plane, (c) gas temperature (K) at the throat cross section, (d) incident radiation (W/m2) at the center plane, and (e) solid volume fraction at the center plane.

Table 2 Calculated particle properties at the end of primary air zone 1, 2 and 3. Zone No.

Total mass (%)

M (%)

V (%)

FC (%)

A (%)

Density (kg/m3)

Particle size (cm)

1 2 3

54.2 29.0 22.2

0.52 0.00 0.00

43.77 3.45 0.00

15.85 27.59 11.00

39.86 68.97 89.00

2074 2548 2590

5.6 4.5 4.2

but the concentration is much lower. CmHn is mainly concentrated above the second stage where devolatilization occurs. After passing through the throat, CmHn decreases quickly due to sufficient combustion with the secondary air. CO is produced by the hydrocarbon combustion, and takes a similar distribution as CmHn. CO2 is produced by both the gas phase hydrocarbon and the char combustion, and its distribution above the throat is uniform with the help of secondary air. O2 is almost unreacted at primary air zone 1 where the temperature is quite low due to the high moisture content in the wastes, and consumed completely at primary air zone 2. In the primary air zone 3, few amounts of O2 react with char. It needs to be pointed out that the CO2 and O2 concentrations have some distortions in the ash hopper region. In reality, the bottom of ash hopper is an outlet for ash removal, but in the modelling, this bottom is assumed as a wall for the simulation convenience. Thus, the unburnt O2 accumulates together in this region, which leads to the sharp decrease of CO2. Comparisons of simulated temperatures and gas species concentrations with measurements are presented in Table 3. Due to the large variations in the input wastes, the single temperature measurement point has huge fluctuations, thus the averaged values of three points are calculated for each row. Area-weighted average of simulation results are used for comparison correspondingly. The deviations are within 3%. The simulated gas species concentrations at the furnace outlet are also area averaged, and reasonable agreements are shown.

The simulation has continued for another 3000 s after 6300 s. The results of incineration profiles (volume fractions, species, and temperatures) do not change in time significantly, suggesting the solution has reached a steady state. 3.2. Effects of waste throughput on the waste incineration Simulations were performed to examine the influence of waste throughput on the incineration. The 60% and 110% throughputs of the MCR benchmark case were selected, and the remaining operating parameters (air temperatures, air ratios, residence time) were unchanged. The area-averaged radiation heat fluxes over the bed top (The bed top surface is defined with a contour surface of solid volume fraction of 0.01) were compared with the benchmark case, as shown in Fig. 4. When loading rises from 100% to 110%, the peak location of radiation heat flux holds identical, and the corresponding grate length is 6.45 m. Due to the input increase, the magnitude of peak radiation rises slightly by 14%. When loading is reduced from 100% to 60%, the peak location moves backwards by 0.5 m, and the magnitude decreases significantly. Fig. 5 shows the gas temperature distributions inside the incinerator. Both cases demonstrate the ignition and combustion of wastes mainly occur at primary air zone 2, and two hightemperature zone exists. This is consistent with the MCR case. The peak temperature in the 110% case is 300 K higher than the 60% case, suggesting the increased heat input leads to the violent combustion.

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Fig. 3. Distributions of gas species mass fractions at the center plane: (a) H2O, (b) CmHn, (c) CO, (d) CO2, and (e) O2.

Table 3 Validations of simulation results with measurements.

Simulation Measurements

Y = 8.8 m (K)

Y = 12.2 m (K)

Y = 15.0 m (K)

O2 (wet gas base, vol %)

CO2 (wet gas base, vol %)

H2O (vol %)

1262 1225

1222 1211

1191 1172

6.8 6.7

9.5 8.6

23.2 20.5

Fig. 4. Effects of waste throughputs on the radiation heat flux over the bed top. Fig. 5. Contours of gas temperature (K) at the center plane: (a) 60% waste throughput, and (b) 110% waste throughput.

4. Conclusions A comprehensive two-fluid model that integrates both the gassolid grate incineration and the furnace gas turbulent combustion in the platform of ANSYS FLUENT 14.0 is presented. Realistic grate geometry and direct simultaneous coupling of the fuel bed and the freeboard gas phase are realized in this model. According to different treatments of the solid phase, three regions are defined in the simulation, which are namely the packed bed region, the fall region

and the furnace region. The rheological properties of the solid phase are described by the kinetic theory of granular flow (KTGF), and the gas-solid momentum exchanges are expressed by using the Ergun drag model. Thermal conversion of MSW is described by the heterogeneous reactions of moisture evaporation, devolatilization, char-O2 combustion and the homogeneous reactions of hydrocarbons combustion. Results show that moisture evaporation occurs at primary air zone 1, devolatilization and the

Z. Xia et al. / Waste Management 104 (2020) 183–191

subsequent gaseous combustion occur at primary air zone 2. A high-temperature zone near the bed top in the middle of grate is thus formed, which promotes the char combustion. The unburnt flue gases continue to combust with the secondary air and a uniform temperature distribution above the throat is shown. Variations of particle properties are predicted to reveal the in-bed incineration process. Effects of waste throughput on the incineration are also investigated. One main feature of this work is that the exchange profiles between the grate combustion and the furnace combustion are updated internally, and there is no need to carry out external coupling calculations between the in-bed and over-bed combustions. The newly developed two-fluid model provides insights for the smart operation and intelligent control of the similar moving grate incinerators due to the simultaneous feedback of the combustion status. Its applicability of other types of incinerators will be studied in our future work. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement The authors acknowledge the financial support by the National Natural Science Foundation of China (21908062) and Shanghai SUS Environment Co., LTD (SUS17K-605-01). References Cheng, P., 1964. Two-dimensional radiating gas flow by a moment method. Am. Instit. Aeron. Astron. 2 (9), 1662–1664. DeSai, P.R., Wen, C.Y., Bissett, L.A., 1978. Computer Modeling of the Morgantown Energy Research Center’s Fixed Bed Gasifier. US Department of Energy, Technical Information Center. Ergun, S., 1952. Fluid flow through packed columns. Chem. Eng. Prog. 48 (2), 89–94. Gómez, M.A., Porteiro, J., Patiño, D., Míguez, J.L., 2014. CFD modelling of thermal conversion and packed bed compaction in biomass combustion. Fuel 117, 716– 732. Gómez, M.A., Porteiro, J., Chapela, S., Míguez, J.L., 2018. An Eulerian model for the simulation of the thermal conversion of a single large biomass particle. Fuel 220, 671–681. Gu, T., Yin, C., Ma, W., Chen, G., 2019. Municipal solid waste incineration in a packed bed: A comprehensive modeling study with experimental validation. Appl. Energy 247, 127–139. Hermansson, S., Thunman, H., 2011. CFD modelling of bed shrinkage and channelling in fixed-bed combustion. Combust. Flame 158, 988–999.

191

Ismail, T.M., Abd El-Salam, M., El-Kady, M.A., El-Haggar, S.M., 2014. Three dimensional model of transport and chemical late phenomena on a MSW incinerator. Int. J. Therm. Sci. 77, 139–157. Johnson, P.C., Jackson, R., 1987. Frictional-collisional constitutive relations for granular materials, with application to plane shearing. J. Fluid Mech. 176, 67– 93. Karim, M.R., Naser, J., 2018a. CFD modelling of combustion and associated emission of wet woody biomass in a 4 MW moving grate boiler. Fuel 222, 656–674. Karim, M.R., Naser, J., 2018b. Numerical study of the ignition front propagation of different pelletised biomass in a packed bed furnace. Appl. Therm. Eng. 128, 772–784. Karim, M.R., Bhuiyan, A.A., Naser, J., 2018. Effect of recycled flue gas ratios for pellet type biomass combustion in a packed bed furnace. Int. J. Heat Mass Transfer 120, 1031–1043. Karim, M.R., Bhuiyan, A.A., Sarhan, A.A.R., Naser, J., 2020. CFD simulation of biomass thermal conversion under air/oxy-fuel conditions in a reciprocating grate boiler. Renewable Energy 146, 1416–1428. Lin, P., Ji, J., Luo, Y., Wang, Y., 2009. A non-isothermal integrated model of coal-fired traveling grate boilers. Appl. Therm. Eng. 29, 3224–3234. Lun, C.K.K., Savage, S.B., Jeffrey, D.J., Chepurniy, N., 1984. Kinetic theories for granular flow: inelastic particles in Couette flow and slightly inelastic particles in a general flow field. J. Fluid Mech. 140, 223–256. Ma, D., Ahmadi, G., 1986. An equation of state for dense rigid sphere gases. J. Chem. Phys. 84 (6), 3449–3450. Mehrabian, R., Zahirovic, S., Scharler, R., Obernberger, I., Kleditzsch, S., Wirtz, S., Scherer, V., Lu, H., Baxter, L.L., 2012. A CFD model for thermal conversion of thermally thick biomass particles. Fuel Process. Technol. 95, 96–108. Mehrabian, R., Shiehnejadhesar, A., Scharler, R., Obernberger, I., 2014. Multi-physics modelling of packed bed biomass combustion. Fuel 122, 164–178. National Development and Reform Commission, 2016. The ‘‘13th Five-Year” national urban solid waste disposal facilities construction plan. Pyle, D.L., Zaror, C.A., 1984. Heat transfer and kinetics in the low temperature pyrolysis of solids. Chem. Eng. Sci. 39 (1), 147–158. Siegel, R., Howell, J.R., 1992. Thermal Radiation Heat Transfer. Hemisphere Publishing Corporation, Washington DC. Sun, R., Ismail, T.M., Ren, X., Abd El-Salam, M., 2016a. Effect of ash content on the combustion process of simulated MSW in the fixed bed. Waste Manage. 48, 236–249. Sun, R., Ismail, T.M., Ren, X., El-Salam, M.A., 2016b. Influence of simulated MSW sizes on the combustion process in a fixed bed: CFD and experimental approaches. Waste Manage. 49, 272–286. Wakao, N., Kaguei, S., 1982. Heat and Mass Transfer in Packed Beds. Gorden and Breach, New York. Wissing, F., Wirtz, S., Scherer, V., 2017. Simulating municipal solid waste incineration with a DEM/CFD method–influences of waste properties, grate and furnace design. Fuel 206, 638–656. Xia, Z., Li, J., Wu, T., Chen, C., Zhang, X., 2014. CFD simulation of MSW combustion and SNCR in a commercial incinerator. Waste Manage. 34 (9), 1609–1618. Xia, Z., Fan, Y., Wang, T., Guo, X., Chen, C., 2015. A TFM-KTGF jetting fluidized bed coal gasification model and its validations with data of a bench-scale gasifier. Chem. Eng. Sci. 131, 12–21. Xia, Z., Chen, C., Bi, J., Li, K., Jin, Y., 2016. Modeling and simulation of catalytic coal gasification in a pressurized jetting fluidized bed with embedded high-speed air jets. Chem. Eng. Sci. 152, 624–635. Yang, Y., Goh, Y., Zakaria, R., Nasserzadeh, V., Swithenbank, J., 2002. Mathematical modelling of MSW incineration on a travelling bed. Waste Manage. 22, 369– 380. Yang, Y.B., Lim, C.N., Goodfellow, J., Sharifi, V.N., Swithenbank, J., 2005. A diffusion model for particle mixing in a packed bed of burning solids. Fuel 84, 213–225.