Place for a photo
(no lines around photo)
Measurement methods for
validation of time-averaged
CFD modelling of CFBs
Liekkipäivä 30.01.2014, Tampere, Finland
Sirpa Kallio, Juho Peltola
VTT Technical Research Centre of Finland
Jouni Elfvengren, Jari Kolehmainen, Pentti Saarenrinne
Tampere University of Technology
CFD Modelling of Fluidization Processes
Gas-solid flow in fluidized beds is
dominated by fluctuations of
velocities, solids concentration and
chemical components.
The effects of these fluctuations
have to be included in the model!
Alternatives:
1. Detailed transient simulations that
resolve the fluctuations
2. Filtered modelling (time or spatial
filtering)
Real CFB
Simulation results
Detailed
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Filtered
2
The Filtered Approach
Spatial filtering (coarse grid) and temporal filtering
As the mesh resolution of a transient simulation decreases, the
sub-grid closure models approach the steady-state models.
At VTT focus is on time-averaged CFD modelling of fluidization
Simulation of a long time period avoided
Less sensitive to mesh resolution
coarser mesh allowed
Fast simulation of industrial furnaces possible
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Time-Averaged Simulation Approach
Time-averaged form of the continuity and momentum
equations used in the transient simulations for phase q are:
q
q
q
q
Uq = 0
Uq Uq =
M
q
q
( 1)
q
(
qs
q
1)
g
q
K gs u g
p
q
us
Time-averaged drag
u
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U
qu / q
uq " uq Uq
p
qs
q
ps
q
q
q
u"q u"q
”Reynolds stresses”
instantaneous velocity
phase-weighted average velocity
velocity fluctuation
4
Time-Averaged Simulation Approach:
Model Development
Based on high resolution, Eulerian transient simulations:
All the terms in the momentum equation are individually
averaged
Evaluation of the relative importance of each term in
different conditions
Simulation data is used to develop of the closure models for
the steady-state simulations
>120 simulations have been carried out
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Time-Averaged Simulation Approach:
Model Development
Experimental work is required to support and validate the
simulations!
Both the transient and the time-averaged simulations
Simultaneous measurement of velocity and concentration
• A requirement for validation of time-averaged simulations!
Satisfactory measurement methods are available for small scale
2D rigs
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6
Lab scale experiments at Åbo Akademi
University
Pseudo 2D units :
CFB
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BFB
7
0.4 m X 0.015 m X 3 m CFB and 0.9 m x 0.015 m x 2 m BFB
Pseudo 2D: Image-based velocity
measurements
Co-operation between VTT, Åbo Akademi and Tampere
University of Technology
Simultaneous measurement of instantaneous:
Particle velocity: Particle Image Velocimetry
(PIV), Particle Tracking Velocimetry (PTV)
Solids volume fraction: Absorbtion of light,
correlations of image Greyscale value
Particle size distribution: Greyscale gradient
direction matching with a circular mask
Gray scale volume fraction estimate.
0.2
0.18
5
0.16
10
0.14
15
0.12
0.1
20
0.08
=
25
0.06
30
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0.04
0.02
35
5
10
15
20
25
30
35
40
45
50
0
8
Lab scale 2D units vs. industrial scale
2D lab scale
Good visual access allows accurate optical methods
Flow behavior is affected by the front and back walls
Small size: entrance and exit effects affect most of the riser
Industrial fluidized beds
Extremely limited visual access
Local measurements with probes
Measurement methods differ from the ones used in 2D units
Larger cold models
Compromise between full scale and 2D
More realistic flow fields than in 2D
Better visual access than industrial scale
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Experiments at Chalmers cold CFB rig
0.7 x 0.12 x 8.0 m
The bed material is glass
beads.
Measurements:
Velocity and solids
concentration with optical
probe
Pressure profile
Circulation rate
Velocity measurement with
PIV was tested
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The Optical probe
Provided by Chalmers
Two fiber optical sensors
Measures the amount of light
reflected from particles
Time delay between the signals can be
determined by cross-correlating the
signals
Solids velocity measurement
Emitter
Detector
Ideally:
A high frequency measurement of solids velocity and volume fraction
Usable in industrial conditions with cooling
Calibration procedure of Rundqvist et al. 2003 for solids volume
fraction
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Optical probe measurements at Chalmers
Vertical alignment of sensors: Measures the vertical velocity.
Time delay detection by cross-correlation
Sampling:
Frequency 5000 Hz, sampling: 512 blocks with 80% overlap.
Normalized and median-filtered.
The measured velocity can be offset by several factors:
Too low solids volume fraction
Large non-vertical velocities
Very low velocities are not detected.
If the suspension is uniform, velocity cannot be measured
Very noisy data!
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12
Evaluation of measurement quality
Fraction of successful measurements
at three fluidization velocities.
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Examples of the velocity distributions:
Measured (gray)
Corrected by interpolation (black).
13
Effects of uncertainties on measurements
Solids volume fraction measured with
the optical probe:
Full data (solid lines).
Points with valid velocity data
(dashed)
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Reynolds averaged solids measured
with the optical probe
Original data (solid lines)
Corrected velocity distributions
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Measured velocities and fluxes
Favre averaged solids vertical
velocity.
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Local solids flux measured with the
optical probe
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Measured solids velocity correlations
Solids velocity correlation
(<
>) measured with the
optical probe.
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Solids velocity correlation
obtained by weighing with volume
fraction.
=
,
,
16
Qualitative effect of solids concentration
detection threshold on the results
The analysis is based on simulated data
Velocity and voidage are strongly correlated
Significant effects on time-averaged properties
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PIV measurements at Chalmers
Center line of the bed was horizontally illuminated with a laser
probe
Dense falling clusters on the front wall complicate the analysis
Complex pre- and postprocessing is required to obtain reliable
results
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PIV measurements at Chalmers
Experiments with fluidization velocities 2.0, 2.5 and 3.0 m/s @
3.8 m height
Velocity distributions were again corrected by linear interpolation
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PIV measurements at Chalmers
Experiments with fluidization velocities 2.0, 2.5 and
3.0 m/s @ 3.8 m height
3.0 m/s was found too dense for credible PIV results
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Conclusions
Measurement methods are associated with limitations and
inaccuracies
a combination of several measurement methods is
necessary
Optical probes (with dual sensors):
Simultaneous measurements of solids volume fraction and the vertical
velocity
Usable at solids volume fractions above 0.01
Very noisy data
Fluctuation measurement result are qualitative at best
PIV measurements:
Much more reliable lateral and vertical velocities over a region-of-interest
Usable at solids volume fractions below 0.005
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Acknowledgements
The authors gratefully acknowledge the financial support of
Tekes, VTT Technical Research Centre of Finland, Etelä-Savon
Energia Oy, Fortum, Metso Power Oy and Numerola Oy, and the
support from Saarijärven Kaukolämpö Oy.
The invaluable contribution of Filip Johnsson, David Pallarés and
Ulf Stenman at Chalmers University of Technology and of Alf
Hermanson, Debanga Mondal and Henrik Saxém at Åbo Akademi
University are gratefully acknowledged.
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