CFD Modelling of the Hydrodynamics and Reaction Kinetics of Chemical Looping Combustion Process in a Fuel Reactor

Professor Xiaogang Yang

5 November 2015

Luming Chena, Xiaogang Yanga,*, Guang Lia, Xia Lib, Colin Snapeb

aInternational Doctoral Innovation Centre (IDIC)The University of Nottingham Ningbo

University Park, Ningbo 315100, P.R. China

bFaculty of Engineering, The University of NottinghamUniversity Park, Nottingham NG7 2RD, UKEmail: xiaogang.yang@nottingham.edu.cn

Contents

BackgroundMathematical ModellingResults and Discussion Concluding Remarks

Background

Chemical looping combustion (CLC) system consists of a fuel reactor and an air reactor

Advantages: (1) High purity of CO2 collection (2) Minimisation of the energy penalty

Performance of fuel reactor directly affects the combustion efficiency and CO2 capture capability

Intrinsic geometry difference when employing 2-D model and 3-D model for cylindrical fuel reactors

Full 3D CFD simulation of CLC fuel reactors is rarely reported and the simulations are limitedly validated by the experimental data

Current study conducts full 3D CFD modelling of the hydrodynamics and reaction kinetics of the CLC in a fuel reactor using CuO/Al2O3 as the oxygen carrier, CH4 as the gaseous reactant

A Typical CLC System

Aims of this investigation

To conduct 3-D simulation of the CLC process in fuel reactor to investigate the hydrodynamics and chemical kinetics in the fuel reactor

To validate the modified kinetic model using the experimental data of Forero et al. (2011)

To propose the correlation parameters to describe the bubble occurrence

Mathematical Modelling

Eulerian-Eulerian (two -fluid) model

( ) ( ) ( )∑=

−=⋅∇+∂∂ n

jijjiiiiii mm

t 1

uρερε

Momentum Balance Equation

Continuity equation

( ) ( ) ))((1

ijij

n

jjijiijjiiiiiiiiiiii mmp

tuuuuguuu ∑

=

−+−++⋅∇+∇−=⋅∇+∂∂ βρετερερε

Energy equation

( ) ( ) iijijiiiiiiiii HmQTkHHt

++∇⋅∇=⋅∇+∂∂ )(uρερε

Species transport equation

( ) ( ) hepiipiiiipiii RYYt

+⋅−∇=⋅∇+∂∂ )J(u ,,, ερερε

Kinetic Theory of Granular Flow (KTGF)

( ) ( ) ( )

gsss

sssgssss

D

kPt

+Φ+−

Θ∇⋅∇+∇+∇−=

Θ⋅∇+Θ∂∂

γ

τρερε )(:23 uIu s

Mathematical Modelling

The modified Syamlal-O’Brien drag model is based on theexperimentally minimum fluidization conditions Eliminate the over/under-prediction of the bed expansion

encountered in the original Syamlal-O’Brien model

gsDpsr

ggs Cdu

uu −= 2,4

3 ρααβ

2

,

Re8.463.0

+=

sr

pD

u

C

( )

+−++−= 22

, )2(Re12.0Re06.0Re06.05.0 AABAu pppsr

14.4gA ε= ( )

( )

≤

≤=

850 850

g

g281

.

..

εεεε

Qg

gPB

tsts

tst

BA ReRe06.01

Re06.0Re++

=

2

2

26.1

8.43

452.28.4Re

−+

=

Ar

ts

2Re43

tDCAr =

Drag Model

Mathematical Modelling

Kinetic Model

molkJHOHCOCuCuOCH

r /178244 224

−=∆++↔+

Overall reaction:

3/200 )1()/exp(3 Xr

RTEkbCdtdX

gm

n

−−

=ρ

CH4

rg (m) 2 × 10−7

𝜌𝜌𝑚𝑚 (mol/m3) 8.06 × 104

b 4k0 (mol1-nm3n-2s-1) 30.0E0 (kJ/mol) 106n 0.5

Oxygen carrier to fuel ratio Experimental value Simulation value （shrinkingcore model）

1.25 0.015 0.009

1.38 0.001 0.0035

1.5 0 0.003

Shrinking Core Model (SCM)with chemical reaction as themain resistance

Mathematic Modelling

Modified Kinetic Model

molkJHOHCOCuCuOCH

r /178244 224

−=∆++↔+

3/200 )1()/exp(3 Xr

RTEkbCdtdX

gm

n

−−

=ρ

<×−−

<≤−−

=20.2/or )/exp(-0.341175.2)1()/exp(3

3/2.20for )1()/exp(3

4_TGA44_TGA4

4_TGA4

CHCHCHCH3/200

CHCH3/200

CCfCCXr

RTEkbC

CCXr

RTEkbC

dtdX

gm

ngm

n

ρ

ρ

Kinetic model is modified based on the experimental data

Oxygen carrier tofuel ratio

Experimental value Simulation value （

shrinking core model）

Simulation value (modified shrinking model)

1.25 0.015 0.009 0.015

1.38 0.001 0.0035 0.035

1.5 0 0.003 0.003

Boundary Conditions

Inlet:Velocity inlet boundary condition Outlet:Pressure outlet boundary condition Wall:Johnson and Jackson’s slip boundary condition

max,

0

63

s

slssc

Ugnε

αρπτ ΦΘ=⋅

max,

2/320

max,

20

4)1(3

63

s

wss

s

slss egUgqn

ααπρ

ααρπθ Θ−

+Φ

=⋅−

Cross-sectional view with mesh 225000

Cross-sectional view with further refined mesh 292000

Central cutting plane view

3-D view

Grid independence is ensured

Operation parameters used in CFD

Width of bed (mm) 50.0

Height of bed (mm) 100.0

Temperature (K) 1023.0

Viscosity of nitrogen (g/cm .s) 2.3 × 10−4

Inlet fuel gas velocity (cm/s) 14.0

Diameter of catalyst (𝜇𝜇𝜇𝜇) 370

CuO content (%) 14.0

Porosity of CuO/Al2O3 (%) 50.5

Density of particle (kg/m3) 1800.0

Minimum fluidization velocity (m/s) 0.056

Initial solid height(m) 0.06

Initial solid volume fraction 0.55

Restitution coefficient (e) 0.9

Wall restitution coefficient (ew) 1.0

Specularity coefficient Φ 0.6

Time interval (s) 10-3 – 10-5

Physical properties and operation parameters

Results and Discussion

Bubble formation and distribution of reactantsand products in the fuel reactor

Instantaneous contours of the volume and mass fractions for solid phaseand gases at t=10.3 s. (a) the volume fraction of the solid phase; (b)mass fraction of CH4; (c) mass fraction of H2O; (d) mass fraction of CO2 .

(a) (b) (c) (d)

The mass fraction of methane is relatively higher in thebubble region (low solid volume fraction)

Results and Discussion

Bubble formation and distribution of reactants and products in the fuel reactor

(a) (b)(a) Instantaneous contour of gas phase volume fraction; (b) velocity vector of gas phase of y-z plane at 10.3s

Large eddies present in the centre of the bubbles in thedense bed, indicating a strong coupling between thebubble formation and the local eddies.

Results and Discussion

Results and Discussion

Variations of reactants and products at the outlet of the fuelreactor

(a) (b)

(a) Time evolution of the mass fraction of a) CH4; (b) gaseous reactant andproducts at the outlet of the fuel reactor at 1023K

Variation of the mass fraction of CH4 falls into a meanvalue around 0.0015 after t=3.8s while H2O and CO2oscillates around the mean values of 0.17 and 0.21,respectively.

Results and Discussion

(a) (b)

Comparison of outlet CH4 concentration at various ratios of the oxygen carrier to fuel with the experimental data of Forero et al. (2011)

The maximum error between the simulation and experimental valuesis smaller than 1.25%.

Simulations reasonably capture the trend that theexperimental CH4 concentration at the outlet decreasesgradually with increase of the ratio of oxygen carrier to fuel,eventually reaching the status of complete combustion.

Results and Discussion

Error Analysis

Small discrepancies of the outlet gasconcentration may exist in the complexchemical reactor such as a CLC unit in thedifferent experimental runs. (Son andKim,2006)

Chemical and physicalchanges of oxygen carrierssuch as attrition and changein grain size can alsocontribute to a certainextent differences (Mattsiionet al.,2003; Leion et al.(2008))

Forero et al.(2009)studied the syngascombustion using thesame Cu-based oxygencarrier in the same CLCunit and revealed that theoutlet gas concentrationin the CLC reactor wasdiluted by N2 from thebottom loop seal.

Results and Discussion

Bubbling characterisation using correlations betweenvelocity fluctuation and local area weighted pressurefluctuation

),,(),(

),(),()(

0002

0,002

0,000,00

hAtuhAtp

hAtuhAtptR

g

g

′′

+′′=

τ

Controlling the bubble formation and bubble size in the dense bed is a cost-effective approach to improve combustion efficiency.

The area-weighted time correlationfor the pressure fluctuation and thelocal gas-phase velocity fluctuationis proposed

Time-dependent correlation relating thebubble formation of x-y plane crosssection with 𝑝𝑝′𝑢𝑢𝑔𝑔′ at z=0.025 m

Results and Discussion

t=8.19s t=8.21s t=8.23s

t=8.27s t=8.79s t=8.85s

t=9.61s t=9.67s

The bubble size at z=0.025m variesover the period of 8.0 to 10.0 s. Thesharp change of the correlationvalues indicates the bubbleformation and rise-up.

t=8.03s t=8.13s t=8.17s

Concluding remarks

The salient features of the bubbles in the dense bed of thefuel reactor were well captured and traced. Formation of fastby-pass bubbles in the dense bed has a negative influenceon the combustion.

Accuracy of the computed outlet concentration of CH4 wasimproved with the modified kinetic model. The CFDmodelling was validated by comparing the simulation resultswith the experimental data.

A correlation parameter, which correlates the fluctuations ofthe local area weighted pressure and gas-phase velocities,can be used for characterising the bubble formation. Thesimulation results indicate that such correlation may be usedto monitor variations of the bubbles because the bubbleformation is highly related to local large eddies.

Acknowledgement

This work was carried out at the InternationalDoctoral Innovation Centre (IDIC). The authorsacknowledge the financial support from NingboEducation Bureau, Ningbo Science and TechnologyBureau (Grant No. 2012B10042), China's MoST andThe University of Nottingham. The work is alsopartially supported by EPSRC (Grant no.EP/G037345/1).

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