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