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A Quantitative study of the performance of
commercial radiation models for predicting
behaviour of oxy-coal combustion
P. Edge, R. Porter, M. Pourkashanian & A. Williams,
Centre for Computational Fluid Dynamics, University of Leeds, UK
P. O’Nions, J. Smart & P. Stephenson, RWE npower, UK
IEA GHG 1st Oxyfuel Conference, Cottbus, Germany
8-11 September 2009
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Introduction
CFD Modelling for air-coal and oxy-coal presents many challenges;
radiation modelling is particularly difficult.
Accurate CFD modelling can aid design
Increased computational capabilities makes complex CFD models more
feasible
Results of CFD model compared to experiments conducted by RWE npower
on their 0.5MW test rig for air and oxy-coal.
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Challenges
In order to use as a predictive and analytic tool, must be capable of precise prediction.
Chemistry-complex homogeneous and heterogenous reaction mechanisms are not fully
understood and currently very computationally expensive to implement
Turbulence-Incorporating LES into coal combustion modelling will make it possible to
account for unsteady velocity field, however this is very time-consuming and expensive
Radiation-Radiative properties of particles found in air-coal can only be very coarsely
represented due to lack of knowledge and lack of commercially available sophisticated
models. RTE is incredibly time-consuming to solve in a complex 3D physical case
In order to extend to larger furnaces and incorporate full-plant models computational times
must be reasonable
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Combustion chemistry
Hard to implement complex reaction mechanisms which exist for difficult fuels
such as coal combustion
For air- and oxy-coal combustion, mechanisms involving heterogeneous reaction
with CO2 / H2O could have high impact
Reaction impacts on particle temperatures which have a high influence on
radiation in the furnace
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Turbulence
RANS – Reynolds Averaged Navier Stokes
very efficient BUT loses instability effects – how important are these?
LES - Large Eddy Simulation
instead flow is spatially averaged, fully resolving bulk flow and modelling smallest scales
gives a more realistic prediction but still computationally expensive.
In this case RANS + Eddy Dissipation: with some preliminary LES results
Cover-up
RANS LES - average LES - instantaneous
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Radiative Heat Transfer
Propagation of each ray through the domain depends on it’s wavelength, position,
direction, and the absorptive, emissive and scattering properties of gas and particles
in its path.
“Radiation Model” in this paper refers to the combination of
1. Method of solving the RTE
2. Representation of radiative properties of the participating gas and particles.
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Solution Methods Considered
DOM DOM DTM P1
No. of discrete directions
considered
2x2 5x5 2x2 X
Spectral models compatibility √ √ X X
Particle radiation compatibility √ √ X √
Parallel processing compatibility √ √ X √
Relative CPU effort* MED HIGH LOW* LOW
Additional validity issues of
method
CPU intensive
in large
enclosures
High optical
thicknesses
required
*considered as calculation runtime on same system. Ray-tracing pre-processed and not included.
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Representation of combustion gases and particles
Only commercially available gas radiation model is grey WSGGM
(Weighted sum of grey gases), which is used here with Beer’s Law to calculate
the absorption coefficient.
Full spectrum k-distribution method recently incorporated into commercial code–
see poster (R. Porter et al…)
In commercial codes, particle radiation interaction is ultimately dependent on a
constant absorptivity/emissivity and scattering factor.
High level of uncertainty in the literature: in general coal is assumed highly
forward scattering & coal, soot, char have high emissivity; however the
emissivity of ash particles is probably much lower.
Weighting coefficients: Smith et al. (1982)
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Combustion chamber: 4m by 0.8m square with slightly arched roof, fitted with IFRF 0.5MW burner
Experiments
These were undertaken using the RWE npower combustion test facility at Didcot
power station site, UK.
Measurements consisted of optical flame studies using high-speed cameras and
surface incident radiation on the walls.
Furnace and Burner Geometry
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Overview of cases studied
Defined in terms of recycle ratio (RR): Oxygen enrichment applied to secondary
stream in order to achieve 3% v/v O2 at the exit.
Russian high-volatile bituminous coal used (80% carbon daf)
Mass flow rate was kept constant at 68kg/h
Case Oxidant % Inlet O2
Mass flow rate Primary Secondary
Air 730 kg/h 23.15 23.15
65% RR 523 kg/h 16.20 34.80
75% RR 755 kg/h 16.20 22.10
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Furnace and burner mesh:
A fully structured, hexahedral mesh was used, taking advantage of quarter symmetry
of the domain.
Total number of mesh elements: 400K
71mm
400mm
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Computational effort
Relative time savings
obtained via parallel processing
0
10
20
30
40
50
60
Serial Parallel0
1
2
3
4
Time (s) per continuous iteration
Serial: 64-bit windows with 8GB RAM Parallel: 32-bit linux with 4 processors
Discrete transfer has fastest runtime on a desktop PC; Discrete ordinates
with 5x5 discretisation is significantly slowest
P1 model offers the highest efficiency on a parallel machine
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Deviation from exit temperatures (°C)
1000
1100
1200
1300
1400
1500
Air 65% Recycle Ratio 75% Recycle Ratio
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Surface incident radiation (kW/m2) air-firing case predictions against measurements
0
100
200
300
400
500
600
700
800
0 1 2 3 4
Distance from burner (m)
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Surface incident radiation (kW/m2) 75% recycle ratio case predictions against measurements
0
100
200
300
400
500
600
700
800
0 1 2 3 4Distance from burner (m)
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Surface incident radiation (kW/m2) 65% recycle ratio case predictions against measurements
0
100
200
300
400
500
600
700
800
0 1 2 3 4Distance from burner (m)
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Large Eddy Simulation
Preliminary indications: 75% recycle ratio case with DOM 2x2
Temperature field: higher maximum temperatures in
unsteady flow-field
RANS LES - average
50 300 800 1300 1700°C
LES - instantaneous
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Absorption coefficient
RANS LES
Lower in-flame absorption in unsteady
predictions
0.17 0.186 0.203 0.22 0.236 0.252 0.269 0.28/m
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Surface incident radiation (kW/m2) 75% recycle ratio case – RANS vs LES
Distance from burner (m)
RANS LES
0
100
200
300
400
500
600
700
800
0 1 2 3 4
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Conclusions
Between DOM, P1 and DTM, there is no clear winner. All have benefits and drawbacks and
must be selected on a case by case basis; in this case P1 has best trade-off between accuracy
and effort, however for more precise results DOM with >2x2 discretisation should be
considered. Question of applicability of DTM as particle radiation interaction cannot be
included.
A spectral radiation model is required in order to avoid overprediction of gas radiation
contribution in oxyfuel cases – despite high computational requirement from additional
equations. (see poster)
Particle radiation contribution is inadequate and is contributing to the incorrect curve shape in
which incident radiation peaks too late: improvements under development (see poster)
LES can provide a more realistic view of the unsteady natures of turbulent combustion
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Acknowledgements
This project forms part of the ECO-COPPS project funded by DTI. PE
thanks -TSB- for financial support, RP thanks EPSRC.