Analysis of the Wind Effects on a Multi-field LNG Ground Flare

Paper from the AFRC 2013 conference titled Analysis of the Wind Effects on a Multi-field LNG Ground Flare by J. Smith

A Multi-Point Ground Flare (MPGF) was modeled at full flare gas flow conditions with an 8m/s corner wind. This MPGF consists of three flare fields with 469 flare tips in each field. The flare tips in the middle of the field are air-assisted tips. This entire MPGF system is capable of flaring in excess of 6x106 kg/hr of vented gas. The detailed computational fluid dynamics (CFD) model of this MPGF was developed using a proprietary flare modeling tool called C3d. Wind can have a detrimental effect on flows inside ground flares with vortices being particularly troublesome in some cases. The CFD simulation using C3d predicted that vortices did form, but these vortices were relatively weak due to sufficient influx of air through the porous fence. The MPGF generally had good performance for this wind condition at maximum flare gas flows. There was some concern as the air-assisted flare tips appeared to have insufficient blower air supply causing taller than desired flame heights. The air-assisted flare tips appeared to use up air causing the tips in the region downwind of these tips to also have taller than desired flame heights. This simulation aided in making modifications to ensure proper airflow to all tips.

American Flame Research Committees 2013 - INDUSTRIAL COMBUSTION SYMPOSIUM Safe and Responsible Development in the 21st Century Sheraton Kauai, Hawaii - September 22 -25, 2013 Analysis of Wind Effects on a Multi-field LNG Ground Flare Joseph D. Smith, Ph.D., Robert Jackson and Ahti Suo-Anttila, Ph.D., Systems Analyses and Solutions, Owasso, Oklahoma, USA Kerby Hefley, Doug Wade and Doug Allen and Scot Smith, Zeeco, Inc. Zeeco Inc. Broken Arrow, Oklahoma, USA ABSTRACT A Multi-Point Ground Flare (MPGF) was modeled at full flare gas flow conditions with an 8m/s corner wind. This MPGF consists of three flare fields with 469 flare tips in each field. The flare tips in the middle of the field are air-assisted tips. This entire MPGF system is capable of flaring in excess of 6x106 kg/hr of vented gas. The detailed computational fluid dynamics (CFD) model of this MPGF was developed using a proprietary flare modeling tool called C3d. Wind can have a detrimental effect on flows inside ground flares with vortices being particularly troublesome in some cases. The CFD simulation using C3d predicted that vortices did form, but these vortices were relatively weak due to sufficient influx of air through the porous fence. The MPGF generally had good performance for this wind condition at maximum flare gas flows. There was some concern as the air-assisted flare tips appeared to have insufficient blower air supply causing taller than desired flame heights. The air-assisted flare tips appeared to use up air causing the tips in the region downwind of these tips to also have taller than desired flame heights. This simulation aided in making modifications to ensure proper airflow to all tips. INTRODUCTION Low profile multipoint flares represent a special class of flares capable of safely processing significant quantities of flare gas in an environmentally responsible fashion. Systems Analyses and Solutions (SAS) engineers have developed a detailed computational fluid dynamics (CFD) model of a low-profile multi-point ground flare using SAS's proprietary flare modeling tool called C3d. This tool has been used to simulate many other flares including air and steam assisted flares, enclosed flares, and other multi-tip low profile ground flares. The present flare system supports a gas plant located in Southwest/central Queensland, Australia (see Figure 1) designed to process coal seam gas (CSG) from the Surat and Bowen Basins.1 The flare system includes three flare fields, each flare field containing 469 flare burner tips burner tips arranged in three flares. This flare system is designed to process approximately 2 million kg/hr smokeless (3 million kg/hr design) per flare field of flare gas from the process. Computational Fluid Dynamics simulations have been used to analyze the expected air flow through the surrounding wind fence and the resulting flame shape and height during maximum relief conditions. Flare tip spacing and row spacing have also been evaluated to ensure adequate air flow is provided to ensure smokeless operation at maximum relief conditions. 1 See http://www.aplng.com.au/ for more information.Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Figure 1 - Map showing proposed LNG processing facility in Queensland, Australia. The multi-point ground flare (MPGF) configuration consists of three flare fields designated "Field A", "Field B", and "Field C" firing mostly methane (see Figure 2). Each field is approximately 76m x 110m and consists of a total of 469 tips arranged in three separate flares: 1) Flare 1 with 3 runners firing over 350,000 kg/hr of methane and propane, 2) Flare 2 with 6 runners firing over 600,000 kg/hr of mostly methane, and 3) Flare 3 with a single runner with an air duct below each burner tip firing over 100,000 kg/hr of mostly methane. With two fields operating at maximum design capacity (3rd field serves as a spare) this facility provides over 6 million kg/hr of combined firing capacity. Wind fences surrounding the flare fields are approximately 18m (60 ft) tall with special configurations to block line of sight view of the flame while allowing sufficient wind (air) into the flare field for smokeless operation. Since the three flare fields are located next to each other (see Figure 3) they share a common wind fence between them so air flow to the flares located in the center field was also evaluated in this study. Given the size of the flare system and the number of tips involved in this analysis, the present study focused on evaluating two of the three fields with appropriate boundary condition to include the effect of the third field. Results from the maximum flow scenario are shown below and discussed in terms of air demand and radiation load to the fences. Both wind and no-wind conditions were analyzed with wind from two different approach directions to the flare considered. Previous work reported earlier has been done to validate the flare CFD model in general [1] and the combustion model used in this analysis [2]. The main focus of this paper is this CFD analysis was to assess the potential impact of operating multiple ground flares in adjacent flare fields at the maximum relief capacity. The information presented below describes this work and presents results and conclusions for large ground flare operation. Page 2 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Figure 2 - Ground flare system comprised of three flares in three adjacent flare fields Figure 3 - Multi-Point Ground flare THE FLARE MODEL The CFD tool used in this work simulates turbulent reaction chemistry coupled with radiative transport between buoyancy driven fires (i.e., pool fires, gas flares, etc.) and surrounding objects (i.e., wind fence, process equipment, etc.). The code provides "reasonably" accurate estimates of various risk scenarios including wind, % flame coverage, and thermal fatigue for a given geometry. Typical simulations generally require CPU times on the order of hours to a few days Wind fenceSeparate multi-tip Ground FlaresAdjacent Flare fields Field A Field B Field C Field A Field B Field C Wind Direction Page 3 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century on a "standard" windows (or LINUX) desktop workstation. Large Eddy Simulation (LES) is used to approximate turbulent mixing. The code used in this work is based on an earlier CFD tool called ISIS-3D [3-5]. ISIS-3D was previously validated for simulating pool fires to predict the thermal performance of nuclear transport packages [6-9]. ISIS-3D, originally developed at Sandia National Laboratory, has been commercialized into a new CFD tool called C3d which is specifically tailored to analyze large gas flare performance. C3d has previously been applied to large multipoint ground flares, air-assisted flares, and utility flares [1, 2] with new combustion models developed, implemented, and tested for various flare gas compositions including methane, ethane, ethylene, propane, propylene and xylene. C3d has been used to predict flare flame size and shape, estimate the smoking potential for a given flare design firing typical flare gas, and to estimate the radiation flux from the flare flame to surrounding objects. C3d simulations of flame height and flame-to-ground radiation have been validated by direct comparison to measured flame size, shape, and radiation measurements taken during single-burner and multi-burner tests conducted under no-wind and low-wind ambient conditions [10]. For the flare shown above, C3d predictions were made considering Fields B and C at maximum flare flow to each field with a portion of the fencing for Field A included (see Figure 4). The analysis was done with a wind speed of 8 m/s directed at the corner of Field C as shown in Figure 3. Wind fences can restrict wind flow to the flames and/or create unexpected flow profiles inside the flare field both of which could affect combustion performance of the MPGF. One goal of this analysis was to evaluate various fence configurations used on this MPGF to assess the potential adverse wind effects. Due to the size of the flare fields, modeling the exact fence geometry for the full simulation was not practical since it would require excessive computational cells and the associated CPU time to perform the analysis. To reduce the required analysis time, the flare model was restricted to two flare fields (as described above) and a detailed 3D model of the exact fence geometry was completed to determine the equivalent porous plate approximation for the fence. The flare models described below used the approximated fence model in the full simulation to allow practical grid resolution and reasonable analysis times for each simulation. Figure 4 - Full simulation included all of Fields B and C with a portion of Field A (fencing only on Field A) Page 4 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century TECHNICAL APPROACH The approach used in the present analysis was to analyze air flow through a 40 meter section of the wind fence to determine the pressure drop through the detailed fence (see Figure 5). The average pressure drop predicted for the full fence section modeled in the detailed fence model was 540 Pa. Based on this, the fence porosity was determined to be 0.489. The porous plate discharge coefficient was then modified using this porosity in a series of porous plate fence simulations; also 40 meters long, until the porous plate model provided the same flow and pressure drop characteristics as the detailed fence model. Once the porous plate fence model parameters were determined the full flare field simulation was set up using this porous plate model for the exterior fences as well as for the fencing between flare fields. Each of the flare tips was modeled as a jet with the appropriate exit area and velocity based on the actual flare tip geometry. Figure 5 - Fence configuration modeled with C3d showing streamlines through fence Page 5 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century The computational domain was set up with 40 meters between the external boundaries in the horizontal plane and extended 22 meters above the fence top. The grid used was a structured orthogonal hex mesh. During the analysis, the grid was refined several times to improve calculation results and to assure grid independent results. The final grid used had dimensions of 360 x 175 x 68 for a total of 4,284,000 cells. As shown in Figure 6 the cells were clustered around areas of high flow gradients which existed near the flare tips. Figure 6 - Final grid structure used in the flare analysis with fine grid in regions near flare tips to resolve ignition/combustion (Field B grid shown but similar grid structure used for Field C) COMBUSTION MODEL The combustion model in C3d is a variant of Said et.al. [12]. The relevant species included in the hybrid combustion model are Fuel vapor (F) from flare tip, oxygen (O2), products of combustion (PC) which include water vapor and carbon dioxide, radiating carbon soot (C), and non-radiating intermediate species (IS). The general combustion reactions involving these species include: 1kg F + (2.87-2.6S1) kg O2 → S1 kg C + (3.87-3.6S1) kg PC + (50-32S1) MJ Eq. 1 Page 6 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Eq. 1 describes incomplete fuel (F) combustion that produces soot (S) and products of combustion (PC) plus energy. The standard combustion soot stoichiometric parameter (S1) is set as 0.05 but can be adjusted based on fuel type. For natural gas a value of 0.005 was used. The endothermic fuel pyrolysis or cracking reaction (soot producing) consumes fuel (F) and energy and produces radiating carbon (C) plus the intermediate species (IS): 1kg F + 0.3 MJ → S2 kg C + (1-S2) kg IS Eq. 2 Eq. 2 includes the Cracking Parameter (S2) which is set as 0.15 but can also be adjusted based on fuel type. Soot combustion is described by: 1kg C + 2.6 kg O2 → 3.6 kg CO2 + 32 MJ Eq. 3 which consumes soot (C) and oxygen and produces carbon dioxide plus some energy. The Combustion of Intermediate Species (IS) is described by: MJS-1S3250 kgS-1S 6.387.3 kgS1S6.287.2 kg 12222222−+−→−−+PCOIS Eq. 4 where the coefficients are selected so that complete combustion of soot (C) and intermediate species (IS) produce the same species and thermal energy as direct combustion of the fuel. The coefficients in the formula are mass weights (not moles). The advantage of the three-step reaction is that the first reaction has a low activation energy, which allows the partial burning and heat release of the flare gas. This maintains combustion since the partial heat released allows the second reaction, which produces most of the heat and all of the soot, to occur. As in the previous combustion models developed for flare simulations [1, 2], the flare gas Arrhenius combustion time scale is combined with the turbulence time scale to yield an overall time scale for the reaction rate. The characteristic time from the kinetics equation was combined with the characteristic turbulence time scale as: tturb=C Δx2 / εdiff Eq. 5 where Δx is the characteristic cell size, C is a user input constant (0.2E-04), εdiff is the eddy diffusivity from the turbulence model, and tturb is the turbulence time scale, i.e. characteristic time required to mix the contents of a computational cell. The reaction rates are combined by simple addition of the time scales. This combustion model captures the eddy dissipation effects and local equivalence ratio effects. The reactions are all based on Arrhenius kinetics with: Page 7 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Eq. 6 where coefficients C and Activation Temperatures TA are supplied for all reactions. The Arrhenius kinetics and turbulent mixing are from the commonly used Eddy-Breakup (EBU) type combustion model. The kinetics and turbulence models are combined by summing the characteristic time scales. In addition to these dynamic models, sequences of irreversible chemical reactions that describe the combustion chemistry are required. To minimize computational load, a minimum number of chemical reactions are used that fulfill the requirements of total energy yield and species consumption and production. From the basis of heat transfer, flame size, and air demand the details of the chemical reactions are not critical as long as the oxygen consumption is correctly balanced for a given fuel type. To this end, a multi-step chemical reaction model for natural gas was used to approximate the global reaction mechanism as shown in the equation below: DX1/dt = Ak*Tb*X1c*X2d Exp(-Ea/T) Eq. 7 where Ak is the pre exponential coefficient, X1 is the mole fraction of natural gas, X2 is the mole fraction of oxygen, Ea is an activation temperature, T is the local gas temperature, and b, c and d are global exponents. Global reaction kinetics are often used to model combustion as a single step in CFD combustion simulations. The coefficients and powers are fit to existing experimental data. Although it is possible to use a global reaction mechanism with the same coefficients as those which have been published elsewhere, this could be misleading because the coefficients were originally fit to experimental data chosen by other authors for a specific combustion experiment being modeled and it is well known that simulation results are very sensitive to both the computational grid (cell structure and density) and the experimental data chosen by the original authors. A different computational grid or experiment would likely require a different set of reaction coefficients. In the present work, the global reaction mechanism described by Smith, et. al., 2010 [2] was used. This work relied on work by Duterque et. al. [14] and Kim [15] as starting points. However, since these authors adjusted their global reaction coefficients to match "laminar" flame speed data and since the combustion occurring in gas flares is governed by turbulent mixing, the original coefficients had limited applicability. The coefficients associated with the activation temperature and the exponents for mole fractions were based on the physics of the reaction mechanism thus were not expected to be affected by local grid structure. However, this is not the case for the pre-exponential coefficient. To match reaction rates to measured combustion rates, the pre-exponential coefficient was varied to develop the validated combustion model. Also, since the combustion model depended upon turbulent mixing of flare gas, the combustion was also governed by turbulent mixing with air. Since the C3d code uses an LES formulation to approximate turbulent mixing, and since that formulation uses two proportionality coefficients, these were also varied as parameters to determine the appropriate turbulent combustion model TTRNiRAiefCdtdf/1−−=Π Page 8 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century for natural gas. Using this approach, the required parameters shown in Eq. 7 were determined to establish the combustion model for the present work. MODELING ASSUMPTIONS The following assumptions were utilized in modeling the MPGF flare: 1. Combustion of the flare gas was approximated by the appropriate irreversible chemical reaction mechanism with specified kinetics (see above). 2. Thermal radiation was calculated using standard radiation models. 3. Ambient wind condition, flare gas inlet temperature and pressure, were set to match as closely as possible the conditions provided. Boundary Conditions The Boundary conditions used were hydrostatic pressure on all boundaries except the ground boundary (z-axis minimum) which was set as a zero mass-flux wall. A 8 m/s wind was set with appropriate velocity vectors imposed upon all flux boundaries. The thermal and species boundary conditions were set to 300 K (27˚C) and air composition respectively, with ambient air set to 23˚C. Physical and Numerical Sub-model Selection To simulate fluid flow, the momentum solver was the C3d LES turbulence model as described above. The energy equation was utilized to capture the temperature changes due to combustion and mixing. The energy equation also included radiation effects. The species equations were solved to keep track of the distribution and concentration of fuel, oxygen, intermediate species, soot, and products of combustion (CO2 and H2O). The combustion model was used to provide the species equations source and sink terms as a function of species concentrations, local gas temperature, and turbulent diffusivity. C3d includes a series of models to predict flame emissivity as a function of molecular gas composition, soot volume fraction, flame size, shape and temperature distribution. In turn these variables depend upon solutions to the mass, momentum, energy and species equations. The radiation transport model is used not only to predict radiation flux on external (and internal) surfaces, but it also provides source and sink terms to the energy equation so that flame temperature distribution can be predicted. Transient Calculation and Post-Processing Results To set up the steady wind profile, the transient simulation was run for 60 seconds before turning on the flare gas flow. Once the wind profile was established and the flare gas was turned on and ignited, it was allowed to burn for about 17 seconds to capture the fluctuations caused by interactions with the wind. The 17 second burn time provided essentially a "steady-state" burning condition of about 10 to 12 seconds. Page 9 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Since a transient solver was used, all field variables fluctuate in time due to turbulence and the other non-linearity's in the equation system. However when examining any field variable, no gradual slope was observed - just short term fluctuations as expected in turbulent flows. The convergence criteria chosen for the simulations were that the equation of state was always satisfied to within 0.1% or less at any location in the computational domain. Typically the convergence criteria was better than the maximum allowable since the time step constraint was limited by Courant conditions, which allows the flow field to be solved to a higher degree of accuracy. RESULTS The "wind-only" simulation appeared to reach nearly steady state conditions after approximately 15 seconds run time, but the solution was monitored for wind-only conditions for a total of 60 seconds to ensure a steady wind profile was established as would exist when a flaring event occurred in the field. Preliminary indications during the wind-only simulation suggested that the approximate fence model (described earlier) worked very well to allow the correct amount of wind to pass through the fence to prevent strong vortices from forming (see Figure 7). While some vortices did form they were relatively weak. Figure 7 - Streamlines during wind only simulation indicated limited and weak vortices During the 17 second burn time, simulation results fluctuated, as expected, due to turbulent combustion. However, examination of the results indicated that essentially steady conditions were achieved and maintained for between 10 and 12 seconds. As anticipated from the time of the wind-only simulation, vortices formed going over the fence corners around the field were generally not strong enough to force flames downward in the flare field as is shown in Figure 8. In this and subsequent figures, flames are represented using iso-surfaces of methane at a volume fraction of 0.02. These iso-surfaces are colored by temperature as indicated by the legend. Although the simulation confirmed that no flames would form below flare burner tips, there was some indication that the flame height might exceed the fence height as shown in Figure 9. Page 10 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Figure 8 - Flames represented by fuel iso-surface (volume fraction = 0.02) colored by temperature indicating wind vortices were not strong enough to push flames down below flare tip level While all flames fluctuated during the burn portion of the simulation, this area in both fields appeared to consistently experience low air flow which caused taller flames. The area of concern in both flare fields appeared to be in the region near where the air-assisted flare tips were operating in the middle of the fields and the area on the downwind side of theses air-assisted flares (see Figure 10). It appears that the air-assisted flare tips had insufficient blower air supply so that these tips used up the oxygen, leaving insufficient oxygen at lower levels (e.g., tip level) for the tips downwind of these tips, so that combustion wasn't completed until slightly higher. Both the air-assisted tips and some of the tips downwind of them were not able to complete burnout until they got up to levels close to the top of the fence. Based on these results additional attention was given to these regions by the design team to ensure that sufficient air flow was supplied to these flare tips. This was accomplished by spreading the tips and rows to allow more air to penetrate into these regions and by optimizing the air duct design that supplies air to these air-assisted flare tips. CONCLUSIONS The LES code, C3d was used to predict performance of a large Multi-Point Ground Flare (MPGF) at maximum flow conditions with a corner wind of 8 m/s. The simulation predicted that vortices did form, but these vortices were relatively weak due to sufficient influx of air through the porous fence. The MPGF generally had good performance for this wind condition at maximum flare gas flows. There was some concern as the air-assisted flare tips appeared to have insufficient blower air supply causing taller than desired flame heights. The air-assisted flare tips appeared to use up air causing the tips in the region downwind of these tips to also have taller than desired flame heights. This simulation aided in making modifications to ensure proper airflow to all tips. Page 11 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century Figure 9. Some long, tall flames were consistently present in an area of the flare field Figure 10 - Flames represented by fuel iso-surfaces with streamlines indicating areas in the field with low air flow resulting in longer flames Low air flow Low air flow Temp (K) Page 12 of 13 Design Optimization of Combustion Equipment September 22 - 25, 2013 Sheraton Kauai, Hawaii AFRC 2013: Safe and Responsible Development for the 21st Century REFERECNES 1. Smith, J.D., Suo-Anttila, A., Smith, S.K., and Modi, J., "Evaluation of the Air-Demand, Flame Height, and Radiation Load on the Wind Fence of a Low-Profile Flare Using ISIS-3D," AFRC-JFRC 2007 Joint International Combustion Symposium, Marriott Waikoloa Beach Resort, Hawaii, October 21-24, (2007). 2. 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"A Numerical Study on Propagation of Premix Flames in Small Tubes," Combustion and Flame, 146, 283-301 (2006). Page 13 of 13