cfd study of important flare operating parameters study of important flare operating parameters for...
TRANSCRIPT
CFD Study of Important Flare Operating
Parameters
for
2014 TARC Meeting/SETRPC Air Quality Symposium
By
Raj Alphones, Kader Rasel, Vijaya Damodara, Daniel Chen, Helen Lou, & Peyton
Richmond
Dan. F. Smith Dept. of Chemical Engineering
Ajit Patki, Xianchang Li
Mechanical Engineering Department
Lamar University
August 8, 2014
Contents
I. Needs
II. Objectives
III. Methodology
IV. Yr 1 Results
V. Proposed Yr 2 Work
Introduction/Needs
Issues with Industrial Flares
– Operators have a tendency to over-steam or over-air to suppress smoke at the expense of combustion efficiency (CE) or carbon conversion Efficiency (CCE)
– Incipient smoke point (ISP), while widely recognized as a convenient indicator for good combustion, is neither well understood nor scientifically defined.
– Many factors affect soot emission and unburned/ produced VOC emissions. This leads to a question of how to operate the flares in order to achieve the optimal environmental performance (min. smoke + min. VOCs)? (EPA/OAQPS, 2012;
http://www11.tceq.state.tx.us/oce/eer/index.cfm)
Needs for Computational Fluid Dynamics (CFD) and Response
Surface Flare Modeling
• Flare field tests are expensive
• Validated, rigorous CFD flare models are useful for parametric
studies & flare optimization
• Response surface models are even more convenient for parametric
studies, performance analysis, and flare optimization
Objectives • Understand the relationship between flare performance and the
operating parameters at or near the Incipient Smoke Point
(ISP).
• Develop validated rigorous or empirical modeling tools to study
the above-mentioned relationship.
Methodology
Approach • Develop reaction mechanism with soot precursor species or
utilize built-in soot models in Fluent in order to strike a balance
in soot and VOC modeling
• Develop validated CFD tools that can be used to study important
flare operating parameters and to fill the data gap
– By simulating various flare test cases for which both soot and VOC
data are available
• Develop easy-to–use response surface models based on
available experimental data
Data Sources for Validation of CFD Modeling
Controlled Flares
UT/John Zink/ARI (TCEQ 2010 Flare Study)
Marathon Data & 2006/2011-12 HRVOC Flares Survey Data
Carleton U. (Soot Formation, 2012-2014)
J.H. Pohl, Evaluation of the Efficiency of Industrial Flares, 1984/1985, EPA600-2-85-95 and 106
Propylene/Propane flare with Continuous Monitors/GC (EPA, 1983)
Laboratory Flames CH4 Sandia/ TU Darmstadt Flame (2006) Methane/Air Flame (Raman-Rayleigh-LIF, UC Berkeley 2005) Ethylene flames (MBMS, Zhang 2006) Methane/Ethane/H2/CO flames [TNF, 2012]
http://www.sandia.gov/TNF/DataArch/delft3.html
Image Source: 2010 TCEQ Flare Study Project, Final Report
9
• Reduced mechanisms can save computing time and, in many instances, are required (e.g., using FLUENT EDC chemistry-turbulence interaction model)
• Lamar research group has developed a series of 50-species reduced mechanisms for the combustion of C1-C3 light hydrocarbons (LU1.0, 1.1, and 2.0 based on GRI-3.0 and USC-I mechanisms )
• New mechanism LU 3.0.1 that contains soot precursor species and is suitable for the combustion of C1-C4 light hydrocarbons has been developed in the current project period based on the USC-II mechanism.
• All mechanisms were validated with experimental results like laminar flame speeds, adiabatic flame temperature, ignition delay, and burner stabilized flame.
Combustion Mechanisms
"A reduced reaction mechanism for the simulation in ethylene flare combustion,“ Clean Technologies and
Environmental Policy, June 16, 2011;
,"Validation of a Reduced Combustion Mechanism for Light Hydrocarbons," Clean Technologies and
Environmental Policy, “ Clean Technologies and Environmental Policy, 14(1) 1-12, 2012.
"Optimal Reduction of the C1-C3 Combustion Mechanism for the Simulation of Flaring, " Industrial &
Engineering Chemistry Research, February 13, 2012.
Table 3: Comparison of EDC and PDF models
EDC (Eddy Dissipation Concept) PDF (Probability Density Function)
Reactions taking place in the flame are governed by the Arrhenius
rates Reactions are governed by a conserved scalar quantity known
as mixture fraction
Incorporates detailed chemical mechanisms
(More accurate for VOC species)
Fast reactions are assumed (Valid for
>1600 K).
Molar concentrations are derived from Reaction rates, which are
calculated using ISAT algorithm
Molar concentrations are derived from the predicted mixture
fraction fields
Any number of inlet streams can be defined Only two inlet streams are allowed i.e. Fuel and Oxidizer
Computationally very expensive; requires 5-6 days for convergence Requires less time for convergence; only 2-3 days 11
• Realizable k- viscous (or turbulence) model
• Turbulence intensity = 15%
• Turbulence viscosity ratio = 10
• Turbulence-chemistry interaction model
• Probability Density Function (PDF) Model
• Eddy dissipation concept model (EDC, Reduced 50-species mechanism required)
Fluent Model Selection
Validation of the CFD Simulations
• The CFD methodology has been validated with the lab scale flames
(Sandia Lab CH4/Air flame & McKenna C2H4/O2/Ar flat flame), the EDC
model accurately predicts the profiles of temperature and concentrations of
major species (CH4, C2H4 , CO2, CO).
12
UC Berkley: Sandia Lab (Raman-
Rayleigh-LIF measurements)
CH4 (33.33%) / Air (66.67%)
NOx chemistry present (including
premixed N2 from air)
McKenna Flat flame
National Synchrotron Radiation Lab, China
(MBMS, Molecular-Beam Mass Spectrometry)
C2H4/O2/30% Ar
NOx data absent
Validation with John Zink Flare Tests (September 2010, Tulsa, OK) Data
Modeling Air-assisted flares (Concentrated, localized fuel leads to a
sustained flame)
Outlet
Stack
Fuel + Pilot
Air-assist
13
• The EDC model with a new geometry (as shown) improves DRE of air-assisted
low LHV/low jet velocity propylene flares with an average of 4.6% compared to
13.3% in the 2011 AQRP 10-022 report (for A/F mass ratio<28)
• It also improves CE prediction with an average of 2.6% compared to 29.8% in the
2011 AQRP 10-022 report (for A/F mass ratio<28).
Crosswind
CFD VOC/Soot Modeling
• Developed a new, reduced 50-species mechanism (LU 3.0.1 includes soot
precursors required in Fluent soot models) based on the USC-II mechanism (111
species and 784 reactions, Wang, 2007) and applicable to oxidation of H2/CO/C1-C4.
• Utilize Fluent Built-in Soot Models
– Khan and Greeves model
– Tesner model
– Moss-Brookes model
– Moss-Brookes-Hall model
• Created different 2D and 3D geometries and meshed in GAMBIT/ ANSYS-
Workbench.
• Pressure-based solver with double precision; realizable k- model; non-
premixed combustion (PDF) model
• Model laboratory-scale/controlled industrial flare test data for which both DRE/CE
and soot data are available (1983/1984 EPA data; 2010 TCEQ data; Carleton
University Data, Matt Johnson, J. Air Waste Manage. Assoc., 62(3):307-321).
15
Polynomial Equations
Exponential Equations
Response Surface Models
2
5
2
43210 ****** YaXaYXaYaXaaZ
cb YXaZ **
CE = (a+b*U+c*V+d*U^2+e*V^2+f*U*V+g/V+h/U+i/V^2+j/U^2+k*U/V+p*(U/V)^2)*(x*CZHV^m)
17
18
A 3-D contour map can show 4-D Information:
For instance, F (color code) as a function of X and Y at constant Z
Year 1 Results
19
Combustion Mechanism LU3.0.1 • New reduced combustion mechanism with 50 species and 310
reactions was developed from the USC-II mechanism
• Contains important soot precursor species and can handle combustion of C1-C4 hydrocarbons (n-butane, 1-butene and 1,3-butadiene included) – Predicts both volatile organic compounds (VOCs) and soot
emissions
• New mechanism has been compared to the full USC II mechanism and validated against experimental data in CHEMKIN-PRO
• LU3.0.1 is capable of predicting soot in CFD simulations of TCEQ air-assisted flare cases
Validation with experimental data
35
40
45
50
55
60
65
70
0.7 0.9 1.1 1.3
Fla
me
spee
d,
cm/s
Equivalenceratio
Flame speed for ethylene
LU 3.0.1
Experiment
Ignition delay
10
100
1000
10000
62 64 66 68 70 72 74 76 78
Ign
itio
n d
ela
y(1
0^
-6 s
ec)
10^4/T(K)
Ignition delay for Propene
Exp.
LU3.0.1
Adiabatic Flame temperature
PDF Results- Combustion Efficiency
Case no.
CE Experiment
(%)
CE Simulation
(%) % error
A1.1 96.9 96.93 0.03
A2.1 95.9 95.09 0.84
A3.1 98.3 98.88 0.59
A4.1 97.1 99.23 2.19
A5.1 95.9 99.37 3.62
A6.1 99.4 92.9 6.54
Avg. 2.3
PDF Results-Soot
Case no.
BC Experiment
(lb/MMBTU)
log BC Experiment
(lb/MMBTU)
BC simulation
(lb/MMBTU)
log BC Simulation
(lb/MMBTU) Error, a
factor of
A1.1 3.05 0.48 4.22 0.63 1.38
A2.1 4.6 0.66 6.19 0.79 1.35
A3.1 3.95 0.60 1.86 0.27 2.12
A4.1 2.68 0.43 1.22 0.09 2.2
A5.1 3.45 0.54 1.55 0.19 2.23
A6.1 8.05 0.91 11.46 1.06 1.42
Avg. 1.78
Non-Assisted Lab-Scale Flare Experiments at Carleton
University, Ottawa, Canada
Photo showing sampling hood and flare at the Energy &
Emissions Research Lab. Flare Facility at Carleton University
Photo showing close-up of the flare
Fuel: C1-C4 Alkane Mixtures
Jet Velocity
m/s
CO2 yield experimental
kg/kg
CO2 yield simulation
kg/kg
0.28 2.83 2.85
0.56 2.83 2.84
1 2.84 2.84
1.67 2.84 2.84
Jet Velocity (m/s)
CE % Experimental
CE % Simulation
0.28 99.67 (+/-0.31) 99.96 0.56 99.70 (+/-0.06) 99.95
1 99.75 (+/-0.05) 99.93 1.67 99.75 (+/-0.04) 99.87
Soot Yield
Simulated (PDF) and experimental
combustion efficiency of C1-C4 alkane mixture
CO2 yield
•CE are within the experimental uncertainties;
•Soot yields are in the same order of magnitude even though the trend is a little off.
Soot
yield
kg/kg
Jet velocity m/s
Jet Velocity (m/s)
Soot yield simulation
kg/kg
Soot yield experimental
kg/kg
0.28 0.00103 0.00154
0.56 0.00138 0.00161
1 0.00187 0.00153
1.67 0.00225 0.00158
Response Surface Models for Soot, CCE, and DRE Steam assisted flare tests:
a. logBC versus DB, LHV, S, and VG
log BC = -2.567 + 0.002904 LHV - 0.4747 S - 0.1679 VG + 4.321 DB -
0.000001 LHV*LHV+ 0.000078 LHV*VG - 0.001005 LHV*DB
+ 0.4575 S*DB
b. CCE versus D, LHV, S, V, and VG
CCE = 98.78 + 0.1088 S - 0.001152 LHV - 0.00771 V + 0.0862 VG
- 0.023 D - 0.000741 S*S - 0.00620 D*D - 0.001299 S*VG
+ 0.000169 LHV*D
c. DRE versus D, LHV, S, and VG
DRE = 99.561 - 0.000708 LHV + 0.0363 S + 0.0287 VG - 0.0860 D
- 0.000448 S*S + 0.000129 LHV*D- 0.000740 S*VG
Response No. of
data
points
Soot (BC) Exit
Velocity
(V)
Steam
assist (S)
Vent gas
heat flow
(VG)
Double
bond
(DB)
Lower
Heating Value
(LHV)
Flare tip
diameter
(D)
R2 R2
(Adj)
lb/MMBTU ft/s lb/MMBTU MMTBU/hr BTU/scf inch % %
Log BC 101 0 – 3.41 0.2 – 1509 0 – 202 0.1 – 48.6 0/1 290 – 2350 3 – 36 87.8 86.7
CCE 104 0 – 3.41 0.2 – 1509 0 – 202 0.2 – 48.6 0/1 290 – 2350 3 – 36 78.2 76.1
DRE 103 0 – 3.41 0.2 – 1509 0 – 202 0.1 – 48.6 0/1 290 – 2350 3 – 36 78.9 77.5
LHV…. Lower Heating value (BTU/scf)
D……… Flare tip Dia (inch)
S…….. Steam assist (lb/MMBTU)
DB…… Double bond (0/1)
V…….. Exit velocity (ft/s)
BC…… Soot (lb/MMBTU)
VG….. Vent gas (MMBTU/hr)
CCE …. Carbon Conversion Efficiency (%)
DRE ….. Destruction and Removal Efficiency (%)
Response Surface Models for Soot, CCE and DRE
Air assisted flare tests:
a. logBC versus A, D, DB, LHV, and V
log BC = -2.350 - 0.000001 LHV*LHV + 0.0501 A*A + 0.000115 LHV*D
+ 0.000187 LHV*A - 0.01579 D*A - 0.01203 D*V
+ 0.07571 D*DB - 0.1208 A*V
b. CCE versus A, D, LHV, and VG
CCE = 107.24 - 0.04917 LHV - 3.18 A + 1.773 VG - 6.79 DB
+ 0.000021 LHV*LHV - 1.396 A*A - 0.000980 LHV*VG
- 0.649 A*VG + 5.66 A*DB
c. DRE versus A, DB, LHV and VG
DRE = 92.835 + 0.002843 LHV - 5.192 A - 0.1971 VG + 0.000983 LHV*A
Response No. of
data
points
Soot (BC) Exit
Velocity
(V)
Air assist
(A)
Vent gas
heat flow
(VG)
Double
bond
(DB)
Lower
Heating
Value (LHV)
Flare tip
diameter
(D)
R2 R2
Adj
lb/MMBTU ft/s lb/MMBTU MMTBU/hr BTU/scf inch % %
Log BC 51 0.002 – 9.8 0.5 – 72 0 – 26200 1.5 – 21 0/1 330 – 2180 18 – 24 97.1 96.5
CCE 48 0.002 – 9.8 0.5 – 72 0 – 26200 1.5 – 21 0/1 330 – 2180 18 – 24 82.8 78.8
DRE 47 0.002 – 9.8 0.5 – 72 0 – 26200 1.5 – 21 0/1 330 – 2180 18 – 24 92.3 91.7
LHV…. Lower Heating value (BTU/scf)
D……… Flare tip Dia (inch)
A…….. Air assist (lb/MMBTU)
DB…… Double bond (0/1)
V…….. Exit velocity (ft/s)
BC…… Soot (lb/MMBTU)
VG….. Vent gas (MMBTU/hr)
CCE …. Carbon Conversion Efficiency (%)
DRE …. Destruction and Removal Efficiency (%)
Inverse Response Surface Models to Identify
Regions of Interest
S, A, LHV, or VG = f (CE and Log BC)
Regions of low soot and high CE (logBC < -1 & CE > 96.5%) are identified
Assist Variables Unit Optimal range
Steam Steam assist (S) lb/MMBTU 20 – 70
LHV BTU/scf 700 – 1300
Vent gas flow (VG) MMBTU/hr 11 – 20
Air Air assist (A) lb/MMBTU 4000 – 10000
LHV BTU/scf 400 – 600
Vent gas flow (VG) MMBTU/hr 1.5 – 4
CCE (%)
logBC
1009896949290888684
0
-1
-2
-3
-4
>
–
–
–
–
< 20.0
20.0 40.0
40.0 80.0
80.0 120.0
120.0 160.0
160.0
S
15000
20000
20
40
80
120
160 S = -2718 - 28.3 logBC + 69.8 CCE - 5.80 logBC*logBC -
0.427 CCE*CCE R^2=0.53
CCE(%)
logBC
100969288848076
0.5
0.0
-0.5
-1.0
-1.5
-2.0
-2.5
>
–
–
–
< 5000.0
5000.0 10000.0
10000.0 15000.0
15000.0 20000.0
20000.0
A
15000
10000
5000
20000
A = -252570 - 6968 logBC + 6806 CCE - 2166 logBC*logBC
- 43.0 CCE*CCE R^2=0.55
Is there a potential for increasing
CCE while maintaining low soot
emissions?
Analysis of Incipient Smoke Point Data:
Absorbance, Transmittance, Absorptance, and the Beer-Lambert Law
According to the Beer-Lambert law,
Transmittance , T = I/IO
=> T = e (-A)
Absorbance is defined as
A = - ln (I/IO);
A = ε *L*W
Absorptance = 1 – Transmittance = Soot visibility
ln (I/IO) = 0.06103 * W*L
where
I …….. Intensity of transmitted radiation (cd/ft2)
Io …… Intensity of incident radiation (cd/ft2)
ε ……. Molar absorptivity (104ft2/lb)
W…… BC concentration (lb/MMft3) in Combustion Zone
L …….. Path length (102ft) estimated from Plume Volume
Ref: 1. Hawksley, Badzioch, and Blackett. (1961). Measurement of solids in flue gases. 206 – 209. British Coal Utiliz.
Research Assn. Leatherhead. England.
Absorptance vs. Soot emission
Steam assisted flares Air assisted flares
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 0.5 1 1.5
Ab
sorp
tan
ce
Soot (lb/MMBTU)
Propylene (80%)
%TNG (20%) -
2010
Propane &
Nitrogen - 1984
Propylene
(100%) - 2010
0
0.2
0.4
0.6
0.8
1
1.2
0 2 4 6 8 10 12
Ab
sorp
tan
ce
Soot (lb/MMBTU)
Propylene
(80%) % TNG
(20%) -2010
Propane (80%)
&TNG (20%)
-2010
Propylene
(100%) - 2010
Absorptance vs Soot emission
Precision
17 Data Points
R^2 = 0.9775
R^2adj = 0.9775
Rmsd = 0.0157
Variance = 0.0044
Precision 18 Data Points
R^2 = 0.9999
R^2adj = 0.9999
Rmsd = 1.625E-04
Variance = 5.031E-07
Steam assisted flares Air assisted flares
1.21.00.80.60.40.20.0
1.0
0.8
0.6
0.4
0.2
0.0
Soot(lb/MMBTU)
Absorp
tance
Absorptance = 1 - exp(-5.35586 *BC )
0.198
Absorptance at 0.1981lb/MMBTU = 0.654 Absorptance at 0.422 lb/MMBTU = 0.708
1086420
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Soot (lb/MMBTU)
Absorp
tance
Absorptance = 1 - exp(-2.92011 * BC)
0.422
0.654
0.708
Absorbance vs Soot emission
Steam assisted flares Air assisted flares
Absorbance = 4.5983*BC +0.2149
R2 = 0.914
Absorbance = 4.02 *BC +0.272
R2 = 0.8632
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 0.5 1 1.5
Ab
sorb
an
ce
Soot (lb/MMBTU)
Propylene(80%)&
TNG(20%)-2010
Propane &
Nitrogen - 1984
Propylene(100%)
- 2010
0
5
10
15
20
25
30
35
40
45
0 5 10 15
Ab
sorb
an
ce
Soot (lb/MMBTU)
Propylene(80%)
&TNG(20%) -
2010
Propane(80%) &
TNG(20%) -
2010
Propylene
(100%) - 2010
ISP?
Absorptance = 0.681 = 1 – exp (-Absorbance)
Absorbance = 1.14
36
Summary
• New mechanism LU3.0.1 was developed to handle both
soot and VOC emissions for flaring C1 to C4 light
hydrocarbons.
• LU3.0.1 in conjunction with Fluent Moss-Brookes soot
model was successfully applied in PDF modeling of 2010
flare study air flares and Carleton U’s Lab-scale flares.
• Response surface models were developed for Log BC, CE,
and DRE.
• The most favorable operating ranges are determined via
inverse response surface models of steam/air-assists as a
function of Log BC and CE.
• ISPs are estimated in terms of absorbance/absorptance
Planned Year 2 Tasks
Future Work
• Work on Geometry/Meshing for steam/air assisted flares.
• Continue to simulate 2010 JZ data (Propylene/Propane) and 1983/1984 EPA data (with Propane) with PDF & EDC models.
• Include CU’s data (Air-Assist = 0) in statistical analysis
• Use Dimensionless Variables in Response Surface Models
• Work on CU’s data with Olefins and H2 (if funded).
• Study the effect of fuel composition on soot particle size and absorbance (if funded)
Future Work (II)
• Optimally define CZHV for steam and air
flares.
• Better define ISP in terms of absorbance/
absorptance
• Better understand the relationship between ISP
and soot particle size/ fuel species/plume
temperature/steam chemistry, among others.
• Analyze operating regions in terms of
absorbance/absorptance to achieve overall
environmental performance (Soot & CE)
Expanded Definition of CZHV
for Steam and Air-assisted Flares
• fi: Volume flow rate of ith component in vent gas
• m: Volume flow rate of makeup gas
• a: Volume flow rate of assisted air
• s: Volume flow rate of assisted steam
• Hi: Heating Value of the ith component in fuel gas (BTU/scf)
• Hm: Heating Value of the makeup gas (BTU/scf)
• CZHV: Combustion Zone Heating Value (BTU/scf)
• xeff : Effective fraction (effective fraction of air-assist that causes the dilution),
2% is proposed for 2010 JZ Tulsa tests
K. Singh et al, " Parametric Study of Ethylene Flare Operations and Validation of a
Reduced Combustion Mechanism," Engineering Applications of Computational
Fluid Mechanics, Vol. 8, No. 2, pp. 211–228 (2014).
40
effi
mii
xasmf
HmHfCZHV
*
**
Response Surface Models Using Dimensionless Variables
• Consider Reynolds number with Diameter, U or V, air or
flame viscosity
• Consider Grashof number for flame buoyancy, heat release
• Richardson number or momentum ratio
42
Milestone Chart
2nd year
Activity Q1 Q2 Q3 Q4
1. CFD Modeling of Flare Tests ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
2. Response Surface Models ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
3. Model Analysis ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
4. Annual/Final Reports ▒▒ ▒▒
Lamar University CFD Lab • Graduate Students
– Kader Rasel, Vijaya Damodara, Lan Liu (PhD), Ajit Pataki, Raj Alphones,
(DE), Hashim Mrayani, Anan Wang (MES)
• Cutting Edge High Performance Computing (HPC) Cluster
– 3 X 12 core servers; Intel Xeon X5670 @2.93GHz
– More than 50 high speed processors
– Up to 10GBs/second of data transfer speed for faster parallel computing
Acknowledgements
• Financial support from Texas Air Research
Center (TARC) is gratefully acknowledged.
• Special thanks are due to Ed Fortner and
Scott Herndon of Aerodyne Research, Inc.
(ARI) for providing numeric soot data for 2010
JZ flare campaign.
09/18/2008 Chen, Yuan, Lou, Lin, Li
46
46
Comparison reduced mechanisms for mole fraction of major
species at residence time of 1 sec for C3H6 fuel
Species USC II LU 3.0.1 Abs. error % LU 1.0 Abs. error % LU 2.0 Abs. error %
C2H2 1.46E-06 1.32E-06 9.72 1.19E-06 18.53 1.21E-06 17.23
CH4 3.01E-07 3.02E-07 0.23 3.30E-07 9.68 3.91E-07 30.07
CO 5.59E-03 5.70E-03 1.97 6.24E-03 11.68 5.98E-03 7.06
CO2 1.21E-01 1.21E-01 0.2 1.20E-01 0.64 1.21E-01 0.35
H2 1.35E-03 1.37E-03 2.1 1.51E-03 12.31 1.45E-03 7.41
Average abs. error % 2.84 10.57 12.42
Species USC II New Error, a
factor of LU 1.0 Error, a
factor of LU 2.0 Error, a
factor of
C3H6 4.35E-08 4.67E-08 1.07 4.59E-08 1.05 1.48E-07 3.41
HO2 1.19E-07 1.16E-07 1.02 2.06E-07 1.73 2.51E-07 2.1
OH 1.27E-03 1.33E-03 1.05 1.26E-03 1 1.22E-03 1.04
CH3CHO 3.16E-12 4.22E-12 1.34 3.58E-11 11.34 4.44E-13 7.11
CH2O 2.11E-07 1.68E-07 1.25 1.75E-07 1.21 2.02E-07 1.04
C2H4 1.81E-08 3.16E-08 1.74 3.84E-08 2.12 2.47E-08 1.36
CH2CHO 8.80E-12 1.10E-11 1.25 1.07E-11 1.21 1.70E-11 1.93
Average error 1.25 2.81
2.57
Comparison of prediction errors for mole fraction of trace species
at residence time of 1 sec for C3H6 fuel
• Process Type (Vent Gas Species/Heating
Value/Flammability)
– Refinery, Olefin, Polymer, Landfill,
and Exploration fields (H2-C4;
Alkanes vs. Alkenes)
• Operation Mode (Exit velocity)
– Startup, Shutdown, Upset,
Maintenance, and Standby (
Turndown Ratio up to 15000:1)
• Flare Design/Control
– Air assisted, Steam assisted, Non-
assisted, Pressure-assisted
– Elevated, Enclosed
– Steaming, Aeration
– Tip Diameter
• Meteorological condition
– Cross wind
Complexity in Flare Emissions
What species are emitted?
DRE/CE?
ethylene
Methodology
Result Methodology Base
mechanism
USC-II
Reaction path Analyzer
LU3.0.1
Reaction Rate analysis
Key performance indicators of a
flame • Laminar flame speed
-Speed at which a laminar flame propagates through a pre-mixture of fuel and air.
-Fundamental property of a fuel-air mixture
-Strongly influences design parameters of combustion equipment.
• The ignition delay time -Period between the creation of a combustible mixture when the fuel is
injected in an oxidizing environment, and the sustained, on onset of the rapid reaction phase leads to the rise of temperature and pressure.
• Adiabatic flame temperature -Measure of the maximum temperature that could be reached by combusting
a particular gas mixture under a specific set of conditions.
TCEQ Air assist geometry &
mesh
Eddy Dissipation Concept
• For turbulent flows – Detailed Arrhenius chemical kinetics can be incorporated in turbulent flames.
• It assumes that reaction occurs in small turbulent structures, called finite scales.
• Combustion occurs as a constant pressure reactor with initial conditions taken as current species and temperature in the cell.
• Reactions, governed by Arrhenius rates proceeding over time are numerically integrated using ISAT algorithm(In-Situ Adaptive Tabulation)
Non-Premixed Combustion (PDF)
• Probability Density Function (PDF) model used.
• 30 steady flamelets are generated with 100 grid points in
each flamelet
• Viscous model k-ε turbulent model (Realizable) with
standard wall functions
• Moss-Brookes soot model for soot
Soot precursors- C2H2 and C6H6
Surface growth species – C2H2, C2H5 & C6H6
• The mass fraction of the soot as well as the mean mass of individual
soot particle can be obtained
EDC Results-Case A1.1
Experiment:
DRE = 96.9%
CE = 98 %
Experiment_soot = 3.05 lb/MM
BTU
Simulation_soot = 2.6 lb/MM
BTU
EDC Results-Case A2.1
Experiment:
DRE = 96.8%
CE = 97.8 %
Experiment_soot = 4.6 lb/MM
BTU
Simulation_soot = 3.02 lb/MM
BTU
Major bottlenecks
• Very dilute fuels with low LHVs are difficult to simulate with EDC model
• Sufficient mixing is not observed in the EDC cases for dilute fuels.
• Simulations for non-premixed combustions are computationally easy but
1. assumes very fast reactions
2. 100% burning of fuel is observed
3. turbulent diffusion at inlet is observed leading to higher errors in C and H balance.
Jet Velocity
m/s
CO2 yield experimental
kg/kg
CO2 yield simulation
kg/kg
0.28 2.83 2.85
0.56 2.83 2.84
1 2.84 2.84
1.67 2.84 2.84
Jet Velocity (m/s)
CE % Experimental
CE % Simulation
0.28 99.67 (+/-0.31) 99.96 0.56 99.70 (+/-0.06) 99.95
1 99.75 (+/-0.05) 99.93 1.67 99.75 (+/-0.04) 99.87
Test no.
Jet velocity
(m/s)
Maximum Flame
Temperature (K)
12 0.28 1766.2
13 0.56 1783.4
14 1.00 1797.4
15 1.67 1802.1
Maximum flame temperature
attained by flare
Simulated and experimental
combustion efficiency of C1-C4 alkane mixture
CO2 yield
•CE are within the experimental uncertainties;
•Soot yields are in the same order of magnitude even though the trend is a little off.
Soot
yield
kg/kg
Jet velocity m/s
New steam geometry
New Air assist geometry
Air
assist
Vent
gas
inlet
Pilot
gas
CCE versus CE
Steam assisted flare Air assisted flare
8% decrease in CCE 17 – 22%
decrease in CCE
80
85
90
95
100
80 85 90 95 100
CC
E(%
)
CE (%)
CCE vs CE
Propylene (80%) & Propane (20%) - 1983
Propylene (80%)& TNG (20%) - 2010
Propylene (100%) - 2010
75
80
85
90
95
100
75 80 85 90 95 100
CC
E (
%)
CE (%)
CCE vs CE
Propylene (80%) & Propane (20%) - 1983
Propylene (80%) & TNG (20%) -2010
Propane (80%)& TNG (20%) - 2010
Propylene (100%) - 2010
Mass fraction of Soot at ISP
• Steam assist flare test: Max soot emission – 1.17lb/MMBTU (S8.3.1)
Mass of soot/Mass of C in Propylene = 7.469 lb of soot/ 251.14 lb of C = 0.0297lb of soot/lb of C in Propylene
• Air assist flare test: Max soot emission – 9.84 lb/MMBTU (A6.1.1)
Mass of soot/Mass of C in Propylene(feed) = 25.22 lb of soot/ 101.14 lb of C = 0.249 lb of soot/ lb of C in Propylene
Flare Operating Parameters
• Combustion zone heating value (or lower flammability
limit)
• Jet velocity/Crosswind
• Diameter
• Composition
• Sensitivity tests for H2 and C1-C4 alkanes by keeping CZHV (or
LFL) constant
• Sensitivity tests for C2-C4 alkenes by keeping CZHV (or LFL)
constant
• Sensitivity tests for H2-Etylene, Ethylene-Ethane, Propylene-
Propane 50%-50% mixture
64
Lower flammability limit (LFL) (I)
• Lower flammability limit (LFL, vol.%), an important
chemical property, is the lower end of the concentration
range (standard value is given at 25 °C and atmospheric
pressure) for which air/vapor mixtures can ignite.
– The flammability range is confined by the upper and lower
flammability limits (UFL & LFL), which are functions of
temperature and pressure.
– Flammability limits of a combustion zone mixture can be calculated
using Le Chatelier's mixing rule for combustible volume %i
– All inerts, including nitrogen, are assumed to have an infinite lower
flammability limit (e.g., LFLN2 = ∞).
– However, adjustments are made for water and carbon dioxide for
nitrogen equivalency
Lower flammability limit (LFL) (II)
• 1/LFLmix= (%i/LFLi)-(Ne, H2O-1)xH2O -(Ne,CO2-1)xCO2
• %i = Percentage of combustible component i in mixture,
volume percent
• xH2O & xCO2= volume fraction for H2O and CO2
• Ne, H2O & Ne,CO2= nitrogen equivalency for H2O and CO2
• 1/LFLi can be viewed as the contribution to flammability
for component i
• H2O and CO2 can be viewed as contribute negatively to
flammability (fire retardants)
Lower flammability limit (LFL)
Time Sequence of Flare Vent Gas Moving Through Flammability Region (Between B & C)
[EPA Office of Air Quality Planning and Standards (OAQPS), April 2012.] 67
Publications • K. Singh, T. Dabade, H. Vaid, P. Gangadharan, D. Chen, H. Lou, X. Li, K. Li, C.Martin, "Computational
Fluid Dynamics Modeling of Industrial Flares Operated in Stand-By Mode," Industrial & Engineering
Chemistry Research, 51 (39), 12611-12620, October, 2012.
• H. Lou, D. Chen, C. Martin, X. Li, K. Li, H. Vaid, K. Singh, P. Gangadharan, "Optimal Reduction of the
C1-C3 Combustion Mechanism for the Simulation of Flaring, "Industrial & Engineering Chemistry
Research, 51 (39), 12697-12705, October, 2012.
• H. Lou, C. Martin, D. Chen, X. Li, K. Li, H. Vaid, A. Tula, K. Singh,"Validation of a Reduced
Combustion Mechanism for Light Hydrocarbons," Clean Technologies and Environmental Policy, 14
(4), pp 737-748, August 2012.
• H. Lou, C. Martin, D. Chen, X. Li, K. Li, H. Vaid, A. Kumar, K. Singh, & D. Bean, "A reduced reaction
mechanism for the simulation in ethylene flare combustion," Clean Technologies and Environmental
Policy, 14 (2), pp 229-239, April 2012.
• Hitesh S. Vaid, Kanwar Devesh Singh, Helen H. Lou, Daniel Chen, Peyton Richmond, "A Run Time
Combustion Zoning Technique towards the EDC Approach in Large-Scale CFD Simulations,"
International Journal of Numerical Methods for Heat and Fluid Flow, Vol. 24 No. 1, 2014, pp. 21-35.
• Kanwar Devesh Singh, Preeti Gangadharan, Daniel Chen, Helen H. Lou, Xianchang Li, P. Richmond, "
Parametric Study of Ethylene Flare Operations and Validation of a Reduced Combustion Mechanism,"
Engineering Applications of Computational Fluid Mechanics, Vol. 8, No. 2, pp. 211–228 (2014).
• Kanwar Devesh Singh, Preeti Gangadharan, Daniel Chen, Helen H. Lou, Xianchang Li, P. Richmond,
“CFD Modeling of Laboratory Flames and an Industrial Flare,” Journal of the Air & Waste
Management Association (in Press, 2014).
68
Incipient Smoke Points of Flare Tests
Steam assisted flare tests:
Air assisted flare tests:
Test case 46 91 94 102 105 S1.5 S4.1 S5.1 S6.1 S8.3
Report year 1984 1984 1984 1984 1984 2010 2010 2010 2010 2010
Steam flow
(lb/MMBTU)
0 21.43 2.96 3.89 2.38 94 101 111 84 84.85
BC
(lb/MMBTU)
0.071 3.97E-05 0.004 3.96E-05 0.004 0.011 0.015 0.683 0.431 1.171
Test case A1.1 A2.1 A3.1 A4.1 A5.1 A6.1 A7.1
Report Year 2010 2010 2010 2010 2010 2010 2010
Air Flow
(lb/MMBTU)
8247 12000 4950 7600 5250 4440 4679
BC
(lb/MMBTU)
3.237 4.442 3.949 2.401 3.901 9.569 0.068
Absorbance vs Soot emission
0
5
10
15
20
25
30
35
40
45
0 5 10 15
Ab
sorb
an
ce
Soot (lb/MMBTU)
Propylene(100%)
-2010
Propylene(80%)
&TNG(20%) -
2010
Propane(80%)&
TNG(20%) -
2010
Steam assisted flare Air assisted flare
Absorbance = 4.5983*BC +0.2149
R2 = 0.914
Absorbance = 4.02 *BC +0.272
R2 = 0.8632
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 0.5 1 1.5
Ab
sorb
an
ce
Soot (lb/MMBTU)
Propane &
Nitrogen - 1984
Propylene(100
%) -2010
Propylene(80%
)&TNG(20%)-
2010