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Combustion Science and Technology

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Exploring Computational Methods for PredictingPollutant Emissions and Stability Performanceof Premixed Reactions Stabilized by a Low SwirlInjector

Andres Colorado & Vincent McDonell

To cite this article: Andres Colorado & Vincent McDonell (2017) Exploring ComputationalMethods for Predicting Pollutant Emissions and Stability Performance of Premixed ReactionsStabilized by a Low Swirl Injector, Combustion Science and Technology, 189:12, 2115-2134, DOI:10.1080/00102202.2017.1363193

To link to this article: https://doi.org/10.1080/00102202.2017.1363193

Accepted author version posted online: 10Aug 2017.Published online: 05 Sep 2017.

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Exploring Computational Methods for Predicting PollutantEmissions and Stability Performance of Premixed ReactionsStabilized by a Low Swirl InjectorAndres Colorado a and Vincent McDonellb

aGrupo GASURE–Facultad de Ingeniería, Departamento de Ingeniería Mecánica, Universidad de Antioquia,Medellin, Colombia; bUCICL, Henry Samueli School of Engineering, Department of Mechanical and AerospaceEngineering, University of California Irvine, Irvine, CA, USA

ABSTRACTThis article addresses the numerical modeling of NOx emissionsand lean blowoff (LBO) limits of confined and pressurized turbu-lent premixed flames stabilized with a low swirl burner. The studyalso evaluates existing numerical methods that can be used topredict exhaust pollutant emissions and reaction instability closeto the LBO limit. One of the strategies presented in the articleconsists of establishing a chemical reactor network (CRN), whichis a simplified model of the fluid dynamics and energy balance ofthe system coupled with a detailed reaction mechanism. Sincethe computing turnaround time for a CRN model is several ordersof magnitude less than the simplest computational fluid dynamics(CFD) case, the parameters controlling the pollutant formationand stability of the system can be quickly assessed over thecomplete flammable range. The results show the value of asimple reactor network as a design tool that can be used tooptimize emissions and LBO limits of combustion systems. Theparametric analysis examines the most important variables thatcontrol the formation of pollutant species (pressure, recirculationof gases, heat losses, geometry variables, air to fuel ratio, and fuelcomposition). Experiments were carried out at a pressure of 304kPa using two fuel compositions: natural gas and natural gasenriched with up to 90% hydrogen (by volume). The resultsobtained with the CRN for NOx and LBO are in good agreementwith those observed experimentally and show that, for ultra-lowNOx burners, the lowest NOx emissions are concomitant to theonset of instabilities associated with LBO. In sharp contrast, theCFD-based simulations of NOx fail to accurately predict the effectof the fuel composition on the LBO limit. Further analysis of theCRN results show that, at lean conditions and pressures abovethree atmospheres, NOx is formed primarily through the N2Opathway, regardless of the fuel composition. The CRN modelindicates that adding hydrogen to natural gas promotes theproduction of NOx through the Zeldovich, NNH, and N2O routeswhile reducing formation via the prompt route. Understandingthe relative contributions of each route provides a starting pointfrom which to propose modifications to the system to reduceNOx emissions.

ARTICLE HISTORYReceived 11 April 2016Revised 4 May 2017Accepted 31 July 2017

KEYWORDSFuel flexibility; Hydrogen;Lean blowoff; NOx; Pollutantsimulation

CONTACT Andres Colorado felipe.colorado@udea.edu.co Grupo GASURE–Facultad de Ingeniería, Departamentode Ingeniería Mecánica, Universidad de Antioquia, Medellin, Colombia.Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/gcst.

COMBUSTION SCIENCE AND TECHNOLOGY2017, VOL. 189, NO. 12, 2115–2134https://doi.org/10.1080/00102202.2017.1363193

© 2017 Taylor & Francis

Introduction

Motivation

For land-based gas turbines, lean premixed combustion is a proven method to control NOx

below 10 parts per million (ppmdv) and CO below 15 ppmdv (both corrected to 15% O2)without requiring exhaust gas cleanup (Cheng et al., 2009; Leonard and Stegmaier, 1994;Richards et al., 2001). Since more stringent regulations for the NOx control are being imple-mented worldwide, combustion systems have been pushed to operate at conditions near theirstability limits, where lean blowoff (LBO) and acoustic instabilities can seriously affect the engineperformance (Davis et al., 2013; Emadi et al., 2012; Lieuwen et al., 2008; Pourramezan et al.,2015).

In the present study, a flame stabilized with a low swirl burner (LSB) serves as a fuel flexibleplatform for the experimental and numerical analysis of NOx formation and the onset of LBO ina combustor operated on natural gas (NG) and hydrogen enriched NG. Hydrogen enrichmentdecarbonizes the fuel and can reduce the production of greenhouse gases and carbon-basedpollutant emissions, such as CO2, CO, unburned hydrocarbons, soot particles, and volatileorganic compounds. Furthermore, the addition of hydrogen to the fuel can stabilize ultra-leanhydrocarbon flames with fuel concentrations well below the corresponding LBO limit of thepure hydrocarbon (Beerer, 2013; Davis et al., 2013; Littlejohn and Cheng, 2007; Schefer et al.,2002). Regarding the effect of the fuel composition on the emission of NOx, many researchershave observed an increase in NOx emissions with the addition of hydrogen to natural gas foreither fixed air to fuel ratio or even at a fixed bulk flame temperature (Akbari et al., 2013; Beerer,2013; Beerer and Mcdonell, 2011; Beerer et al., 2012; Bell et al., 2013; Cheng et al., 2009; Daviset al., 2013;Day et al., 2015;Dinkelacker et al., 2011; Emadi et al., 2012; Francisco Jr. et al., 2013; Jiand Wang, 2009; Karalus et al., 2012; Kim et al., 2009; Lee et al., 2010; Littlejohn and Cheng,2007; Rørtveit et al., 2002; Therkelsen et al., 2013). Such results suggest that hydrogen kineticshave a dominant effect and thus contribute to increased NOx emissions levels. However, otherstudies have shown that, under specific conditions, enriching the fuel with hydrogen can reducethe NOx emission levels compared to pure hydrocarbon mixtures. For example, Rørtveit et al.(2002) reported a comparison of low-NOx burners for combustion of methane and hydrogenmixtures for four different burners. Their results indicated that the addition of hydrogen tonatural gas or methane increased NOx for most burners, but decreased NOx for one burner(metal fiber-surface stabilized combustion burner). Similarly, Fackler et al. (2015) demonstratedthat when hydrogen is added tomethane, the NOx levels may increase or decrease depending onthe combustor wall heat loss. Their results indicate that, for combustors that lose significantamounts of heat through the walls, the addition of hydrogen can decrease NOx levels (Fackleret al., 2015). In light of the inconsistent observations regarding the effect of hydrogen addition onNOx emissions, further studies are required to understand why the NOx trends are technology-dependent and how hydrogen enrichment affects the extinction limits and NOx productionrates. It is not possible to understand what mechanisms are controlling the formation of NOx byanalyzing only the exhaust emissions; therefore, the use of numerical models and reactionmechanisms with a detailed description of the chemical kinetics is necessary to realize theinteractions’ turbulence/chemistry that control the formation of NOx and the reaction stability.

Several numerical strategies to model NOx formation in combustion reactions have beenpresented in the literature. Themost accuratemodels spatially resolve, in three dimensions (3D),

2116 A. COLORADO AND V. MCDONELL

the emissions formation by coupling a detailed kinetics set (including the nitrogen chemistry)and fully resolving the turbulent flow (Bakker et al., 2000; Bell et al., 2013; Bouvet et al., 2013;Dayet al., 2015;Nogenmyr et al., 2007;Oefelein et al., 2006; Taamallah et al., 2015; Zheng et al., 2013).These strategies include large eddy simulations (LES), direct numerical simulation (DNS), anduse of Reynolds averaged Navier–Stokes equations (RANS) or some turbulence model inconjunction with a combustion model, i.e., the eddy dissipation concept (EDC) model byMagnussen and Hjertager (1977). However, the requirement of ultra-fine meshes to capturethe finest turbulent scales raises the computational cost and makes these strategies prohibitivelyexpensive for most industrial users. Furthermore, these types of simulations consider a singleoperating condition per simulation, i.e., the burner running on pure methane, fixed air to fuelratio (φ), fixed thermal input, fixed geometry, etc. Using any of those strategies, a singleemissions point can be predicted per converged simulation. LES only resolves the large scalesof the flow field while modeling the finest scales; a solution with this approach is attainable usingmodern supercomputers, yet still requires order of days per solution. DNS techniques resolveeven the finest scales of the turbulence in the computational mesh, which makes it prohibitivelyexpensive for nearly all systems. RANS models are more efficient than DNS or LES; however,coupling the turbulence model with a detailed reaction mechanism to resolve species behaviorrenders this approach highly time intensive as well.

In many Computational fluid dynamics (CFD) approaches, the NOx behavior is basedon a given flow field and combustion solution with simplified (e.g., 2–10 step) kinetics. Insuch approaches, NOx is post-processed (decoupled) from the combustion simulation. It isthus evident that an accurate combustion solution (temperature and species profile)becomes a prerequisite for precise NOx prediction based on post-processed results. Withthe last strategy, NOx variation trends can be predicted, but the NOx quantity itself issubject to considerable uncertainty.

To accurately predict the formation of pollutant species and the impact of the fuelcomposition, it is necessary to couple the effect of the fluid dynamics with a detaileddescription of the chemical kinetics. This can be achieved, especially for premixed systems,by using a chemical reactor network (CRN), which couples a complete reaction mechanismwith a simplified description of the fluid dynamics. The concept of modeling the flow fieldusing a network of ideal reactors was first introduced by Bragg in 1953. Bragg successfullymodeled the combustion products of a premixed flame using a perfectly stirred reactor (PSR),followed by a plug flow reactor (PFR; (1953). The PSR is a zero-dimensional (0D) model thatassumes perfect mixing and homogeneous composition; the PFR assumes frictionless, 1Dflow, and uniform properties in the direction perpendicular to the flow. With a simple CRN,the most important parameters controlling the species formation and stability can be variedwithin the complete flammable range and results can be generated very quickly, since thecomputing turnaround time is several orders of magnitude less than even the simplest CFDsimulation. This methodology has been successfully implemented to the analysis of emissionfrom simple burners represented by two or three reactors in series (Novosselov, 2006; Rutarand Malte, 2002; Rutar et al., 2000; Sahraei et al., 2015). Other researchers have incorporatedalgorithms to automatically generate a CRN that fills the complete volume of the combustorwith PSRs or a combination of PSRs and PFRs (Benedetto et al., 2000; Cuoci et al., 2013;Falcitelli et al., 2002; Fichet et al., 2010; Kang et al., 2015; Kanniche, 2010; Lee et al., 2011; Lyraand Cant, 2013; Park et al., 2013; Stagni et al., 2014; Vourliotakis et al., 2011; Wang et al.,2016). However, even automatically generating the CRN still requires one CFD simulation per

COMBUSTION SCIENCE AND TECHNOLOGY 2117

every operating condition, which again increases the computational cost of the analysis. Forthis strategy it is necessary to guarantee the quality of the CFD solution, i.e., the predictedflame structure must be similar to the actual reaction and the energy balance must accuratelyrepresent the conditions of the actual reactions.

In the present work, the objective is to provide an efficient computational strategy tomodel the formation of NOx and LBO stability limits of combustion reactions stabilizedwith a low swirl burner. The study presents the value of a simple CRN as a design toolthat can be used to optimize pollutant emissions and their relation to the LBO limits.The target technology is the LSB that has been previously investigated for its use inboiler and furnace applications (Cheng et al., 2000; Littlejohn et al., 2002), and forelectricity generation in gas turbines (Cheng et al., 2009; Davis et al., 2013; Emadi et al.,2012; Khalil et al., 2016; Littlejohn and Cheng, 2007; Therkelsen et al., 2013). Theparametric study presented here is focused on gas turbine combustor design. A CRNmodel built with four reactors includes the most important variables governing thestability and emissions, such as the effect of the exhaust recirculation (EGR), geometryof the combustor, heat losses from the burner, radiation from the premixed flame,operation pressure, and the impact of the fuel composition on the formation of pollutantspecies and the NOx pathways. This approach is also useful in exploring how combus-tion systems might be modified to better address a known change in gas composition,operating pressure or during the design process to minimize pollutant emissions andstability issues.

Background

The numerical analysis presented in this article is applied to experimental work previouslyconducted by Beerer and colleagues (Beerer, 2013; Beerer and Mcdonell, 2011; Beerer et al.,2012). Beerer and colleagues characterized the performance of a reaction stabilized in a low-swirlflow inside an optically accessible high-pressure vessel. Emissions levels and LBO limits weremeasured for NG and blends of NG with hydrogen (up to 90% H2). The measured NOx resultsfollowed the general trend of the correlation developed by Leonard and Stegmaier (1994) for wellmixed combustors. Following the experimental work by Beerer et al., Neumayer (2013)modeledthe low swirl reactions using a 2D, axisymmetric, steady state model coupled with the RANSequations for modeling the turbulent effects. Neumayer used two combustion models, the EDCand the turbulent flame speed closuremodel (TFC; Zimont et al., 1998). Neumayer’s goal was tomodel the reaction structure and divergence of flow field without focusing on the pollutantemissions. The numerical results showed that EDC was unable to predict the measured flameshape or position correctly (see Figure 1).

In the current work, the finite rate eddy dissipation model by Spalding (1971) was alsoconsidered for species transport and reactions; however, this model did not successfully predictthe reaction structure nor the velocity profiles. Conversely, the TFC combustionmodel provideda reasonable estimate of the flow field and flame shape. Since the flame structure obtained withthe TFC was in reasonable agreement with the experimental data, new simulations using thismodel were carried out to analyze the fluid dynamics and extent of EGR occurring in thecombustion chamber. These simulations also helped guide the building of the CRN. It is notedthat the TFCmodel is not expected to predict the effect of the fuel composition on the pollutantformation, since the TFC model cannot be coupled with a reaction mechanism.

2118 A. COLORADO AND V. MCDONELL

Approach

To elucidate the mechanisms that control NOx emissions and the stability limits of the reactionsstabilized in a confined low-swirl flow, two simulation approaches were taken. First, a “standard”CFD approach deriving NOx from a post processing step is used. This approach requires aconvergedCFD solution to estimate the emission levels using equilibrium and quasi-equilibriumassumptions. This serves as a baseline. In the second approach, a CRNmodel of four zones basedon CFD results and experimental results is used. For both approaches, a simplified CFD strategywas used with a global CH4 combustion mechanism to approximate the flow-field, temperaturevariation, and flame structure within the combustor. With the CRN approach, the relative NOx

contribution of four NOx production pathways is assessed using the methodology of Fackleret al. (2011).

The study also seeks to analyze the sensitivity of the reactor network to some widely usedreaction mechanisms. To address this, the sensitivity of the results to the use of four reactionmechanisms were considered: GRI 3.0 (Smith et al., n.d.); Galway III (Petersen et al., 2007);USCmech II (Wang et al., 2007); and Konnov 0.4 (Konnov, 1998). Further analysis of the CRNresults is used to investigate the NOx pathways that dominate the NOx formation (Zeldovich,Prompt, N2O, and NNH) and how the fuel composition (hydrogen addition) affects the NOx

formation through the different routes.

Experiments

The two fuel compositions used are natural gas (assumed as 100% CH4 in the study) andhydrogen-enriched methane (90% H2–10% CH4 by volume); in order to stabilize thereactions of both fuels with a single technology a fuel-flexible burner is required. The LSBmeets this requirement. For the experiments and numerical simulations, the thermalpower was held constant at 362 kW, the operating pressure was set at 304 kPa (3 atm),

Figure 1. Contours of reaction progress modeled with three combustion models. Turbulent Flame SpeedClosure-TFC next to a picture of the actual flame (Left); Eddy Dissipation Concept-EDC (Center); FiniteRate-Eddy Dissipation-FRED (Right)-EDC and FRED legends (Right).

COMBUSTION SCIENCE AND TECHNOLOGY 2119

and the gas inlet temperature was ~294 K. For NG, the equivalence ratio (φ) was variedfrom 0.55 to 0.98 and for the H2 mix from 0.25 to 0.98. The equivalence ratio (φ) ismathematically defined as follows:

ϕ ¼ fuel to oxidizer ratiofuel to oxidizer ratioð Þstoich

¼ m fuel=m ox

m fuel=mox� �

stoich

(1)

A low-swirl injector (LSI) was placed in the premixer section between the fuel injectorsand the nozzle exit. The premixing chamber consists of a 32-mm-diameter stainless steelpipe, 30 cm in length with three 3.1-mm fuel spokes positioned perpendicular to the flownear the inlet of the tube. Each spoke contains seven holes evenly spaced, each 1 mm indiameter. The holes are pointed in the direction perpendicular to the axis of the premixer.The premixing length is roughly 18 cm long. Given a nominal bulk velocity of 40 m/s, thepremixing time is roughly 5 ms. The LSI consists of an inner channel with a perforatedplate and an annulus containing multiple swirl vanes. The premixed reactants that passthrough the annulus form the swirling outer region, while the reactants passing throughthe inner channel form the non-swirling inner region. The perforated plate imparts acertain degree of turbulence on the inner flow and also sets the flow splits between the tworegions. As illustrated in Figure 2 (center), upon exiting the low swirl injector, the swirlingregion expands radially outward due to centrifugal action. This induces the inner non-swirling region to similarly diverge. Through the principle of conservation of mass, thisdivergence leads to a linearly decreasing mean axial velocity within the inner flow field.For direct comparison, Figure 2 also includes the schematics of jets (left) and a high swirlflow (right). Notice the low swirl flow is a combination of the jet and high-swirlconfigurations.

Figure 2. Schematic representation of the aerodynamics of a confined jet reaction (Left), low-swirlstabilized reaction (Center) and high-swirl stabilized reaction.

2120 A. COLORADO AND V. MCDONELL

Reactor network analysis: Methodology

Information regarding the flow, thermal, and concentration fields are obtained from acombination of experimental results and CFD simulations. The first step to build theCRN consists of splitting the combustor volume according to the local profiles ofvelocity and temperature. The PSR is ideal for representing a flow field with highlyvaried directions and magnitudes, whereas the PFR describes a flow field with uniformvelocity magnitudes or unidirectional flow. A PSR is also required to start the reactionprocess, unless a PFR with either recycle of hot products or high inlet temperature isused.

For the PSRmodel, three variables govern the chemical kinetics: (1) reactor volume (V); (2)pressure (P); and (3) heat losses (HL). Reactor volume can be related to the average residencetime (Rt), the species spent in the reactor through the following relation: Rt ¼ ρV= _m. Othervariables like the mass flow, temperature (T) at the end point, and species concentration arepassed sequentially from reactor to reactor, i.e., the solution for species and temperature at theexit of the first reactor are inputs for the next reactor.

Figure 3 shows the zone distribution using the CFD results for temperature andstreamlines. PSR0 represents the pre-flame zone. This reactor is at blowoff since theinitial P, T, and Rt do not ignite the mixture. PSR0 is set as a fixed volume reactor at theconditions of the incoming fresh reactants (294 K and 304 kPa). This reactor has volumecorresponding to the cylinder upstream of the main flame zone (VPSR0 � 70cm3) andoccupies the space near the premixed gas inlet. The other reactors (PSR1, PSR2, andPFR) are initialized at a temperature above the auto-ignition value. The location of the

Figure 3. Zone distribution using the CFD results for temperature and streamlines (Left). CRN repre-senting the reacting flow in a simplified flow (Right).

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main flame or core of the reactions is represented by PSR1. In this analysis, the flamevolume is assumed to be constant.

Figure 4 shows pictures of OH* using chemiluminescence. The results show that thevolume of the NG reactions is around twice the volume of the hydrogen-enriched flame ata constant firing rate and same operating conditions. As a result, for NG, the volume ofthe PSR1 is approximately 200 cm3, whereas for the hydrogen blend, the volume of thisreactor is 100 cm3. This volume is calculated as a truncated cone.

As shown in Figure 4, the variation of the flame volume within the studied range of airto fuel ratio is small and is therefore neglected. Hence, all of the reactor volumes are fixed,which yields an analysis that varies the residence time in each reactor and the temperatureconditions reached by the extension of the reactions. Following this analysis, a single CRNrepresenting the combustor volume can be used to represent multiple operating condi-tions, which results in a highly time efficient parametric study.

A recirculation loop is modeled with another fixed volume PSR that loses heatthrough its walls (PSR2). The volume enclosing the truncated cone section is used tomodel the EGR region. This volume is 790 cm3 for the hydrogen mix and 1580 cm3 forNG. Even though the heat losses through the walls were not measured during theexperiments, the CRN allows this parameter to be varied over a complete range ofheat losses and used to tune the energy balance of the network. Finally, the post flameregion is represented with a PFR since the exhaust gases in that zone flow mainly in onedirection. The length and diameter of the PFR are 50 cm and 11 cm, respectively. Thislength corresponds to the distance the gases travel before reaching the gas analyzerprobe. In this manner, the complete volume of the combustor is filled with three PSRsand one PFR.

Heat losses

At least for atmospheric conditions, thermal radiation from turbulent premixed flames hasreceived little attention perhaps because of relatively low radiative heat loss compared tothe non-premixed counterpart. Nevertheless, the high-temperature sensitivity of NOx

Figure 4. OH* chemiluminiscence of NG (Top) and 90% H2/NG (Bottom).

2122 A. COLORADO AND V. MCDONELL

kinetics warrants consideration of the radiation heat loss. Assuming these flames areoptically thin, the RADCAL radiation model by Grosshandler (1993) is utilized. Theradiative heat loss rate per unit volume QðT; speciesÞ [W/m3] may be calculated usingEq. (2):

QðT; speciesÞ ¼ 4σXn

i

piapi � T4 � Tb4

� �� �(2)

where σ is the Stefan–Boltzmann constant,Pn

irepresents a summation of species in the

gaseous mix, pi is the partial pressure of species “i” in atmospheres (mole fraction timeslocal pressure), api is the Planck mean absorption coefficient, T is the local flametemperature, and Tb is the background temperature. It is noted that the mean absorptioncoefficient of CO2 is ~5 times the coefficient of H2O. Therefore, water molecules emit andabsorb less radiation, which is one reason that hydrogen flames radiate less heat than NGflames.

The radiation heat loss for each fuel estimated with the RADCAL model is presented inFigure 5. For NG, the radiation heat loss remains under 1% at pressures below 5 atm andreaches a maximum of ~7% at upper pressure considered in this study of 40 atm.Conversely, hydrogen-enriched NG flames radiate very little heat in general, reaching amaximum of ~2.5% at 40 atm. Below 20 atm, the radiation heat loss remains under 1%.The trends indicate that radiative heat loss increases with temperature and pressure, anddecreases with the addition of hydrogen to the fuel.

EGR

The local EGR is defined as the ratio of the mass flow of gases recirculated into thereaction zone to the total mass of fresh reactants entering the chamber (Eq. (3)):

EGR½%� ¼ _mr

_ma þ _mf(3)

Figure 5. Radiation heat loss at variable operating pressure; estimated with the RADCAL model a) NG.b) Hydrogen blend (90% H2/10% NG).

COMBUSTION SCIENCE AND TECHNOLOGY 2123

where _mr is the mass flow rate of gases flowing upstream and _ma þ _mf are the mass flowof air and fuel at the burner inlet. In order to estimate the amount of EGR, the approachproposed by Lezcano et al. (2013) is followed. By post-processing the flow-field resultsfrom the CFD simulations, it is possible to obtain the mass flow of recirculated gases _mr.This strategy is based on the fact that mass flux is constant in the axial direction, whichimplies that the mass of recirculated gases through each transverse plane can be calculatedusing Eq. (4):

_mr ¼ �AρvxdA (4)

where ρ is the density, vx is axial component of the velocity in the negative direction, anddA is the differential of the transverse area linked to the local values of density andvelocity. Using this approach, the maximum EGR was 15% for NG and 13% for thehydrogen blend. The EGR variation is insignificant within the range of equivalence ratiosanalyzed and, hence, is fixed in the subsequent CRN analysis.

Parametric analysis

A summary of parameters used in the parametric analysis is provided in Table 1. A fixedinput represents a parameter that is constant for the model. Those parameters can bedetermined from CFD results, experimental tests, the actual geometry of the combustor,or through other models like RADCAL. For example, the volume of the main flame can beestimated from OH* images or from CFD results. Pressure and geometry of the PFR(diameter and length) are known variables from the experimental rig and local conditions.Other variables, such as the heat losses from radiation, are considered “known indepen-dent variable inputs” as they are function of the flame temperature and the composition ofthe combustion products, which are also dependent on ϕ and fuel type. Additionally, thehighlighted cells indicate other parameters that were varied to check the sensitivity of theprediction of NOx and LBO to these inputs. The equivalence ratio is varied from the leanblowoff limit up to the stoichiometric condition ϕ ¼ 1. The thermal power is heldconstant and used to establish the mass flow rate of fresh reactants as it depends on thefuel composition and ϕ. The dependent variables outputs are those variables of interest forthe study, in this case the species concentrations in each reactor zone and at the exhaust.The empty cells are non-required inputs for the type of reactor. The tuning parameter

Table 1. List of parameters used in the CRN. The highlighted variables were varied to test the effect ofthese parameters on the prediction of NOx and LBO.Parameters Symbol Inlet PSR0 PSR1 PSR2 PFR

Volume V — FI FI FI —Pressure P FI FI FI FI FIHeat losses HL None None KIVI (RADCAL) Tuning parameter NoneTemperature T FI FI DVO DVO DVOLength L — — — — FIDiameter D — — — — FIExhaust gas recirculation EGR — — FI (EGR estimation) — —Species concentration [] KIVI (ø) DVO DVO DVO DVOMass flow rate ṁ KIVI f(ø) DVO DVO DVO DVO

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(i.e., heat losses through the EGR loop) is used to find the conditions that better matchsimultaneously the experimental results for NOx and LBO. The simultaneous prediction ofNOx and LBO is based on the following principle: ultra-low NOx burners such as the lowswirl burner operate at conditions that are close to the theoretical flammability limit. Closeto that limit, the heat generated by the reactions is insufficient to ignite the incomingmixture of fresh reactants. In low-NOx combustor design, this limit is often bound by theonset of combustion instability in the form of LBO. As the flame temperature is decreasedto reduce NOx, the chemical reactions slow to the point where temperature becomes therate limiting factor and the onset of LBO is triggered. These low temperature conditionsalso match the conditions that hinder the formation of NOx. Therefore, it is possible touse the CRN methodology to predict LBO and NOx. The LBO is found when the NOx

emissions approach minimum values. This is consistent with the design goal of leansystems to operate as close to the stability limit as possible to minimize NOx.

For example, the heat losses through the recirculation loop are varied to match the experi-mental LBO and NOx trends. When the conditions that match these two variables simulta-neously are found, the CRN is said to be “tuned” and can be applied and analyzed to understandthe underlyingmechanisms that control the stability and emissions. Figure 6 depicts the effect ofheat loss though the recirculation loop on the emission of NOx, at fixed conditions varying onlythe percent of heat losses through the recirculation loop.

Numerical simulations

To solve the reactor network, Chemkin Pro 15131 was used. The solver was set as steadystate; the problem type solves the energy equation. The CFD simulations were run onANSYS Fluent 15.0. The simulations are pressure based, 2D, and axisymmetric with swirl.

Figure 6. Effect of the heat losses through the EGR loop and their effect on the prediction of NOx andLBO limit.

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The gas density is calculated with the incompressible ideal gas model. The Reynolds–Stressturbulence model, which considers the anisotropy of the turbulence, with linear pressurestrain is used. As the mesh is not fine enough to resolve the boundary layers on the walls,an enhanced wall treatment is used. As indicated in the background, to solve thecombustion chemistry, the TFC model or partially premixed model (in Fluent) is selected.For the pressure velocity coupling the SIMPLE solver is selected. The spatial discretizationis second-order upwind for the turbulence and species variables. For strongly swirlingflows, the PRESTO pressure solver is the preferred method.

Finally, the sensitivity of the NOx prediction to four reaction mechanisms is carriedout. It is important to highlight that the CRN was tuned using GRI 3.0; hence, it would beunfair to say that GRI is the most accurate mechanism to predict the trends since the sametuning process can be applied with any other mechanisms. Still, in order to test the trendvariation, other mechanisms purposefully designed to model the chemistry of NG andhydrogen-enriched fuels were tested without modifying the tuned CRN. USC II andGalway III mechanisms do not include nitrogen reactions; therefore, the rates of forma-tion through the Zeldovich, Prompt, N2O, and NNH mechanisms from the GRI 3.0mechanism were added to these two mechanisms. The Konnov mechanism includes itsown NOx rates and hence it was not modified. The thermal and transport properties aretaken from GRI-Mech 3.0 database.

Results and discussion

Numerical prediction: CFD and CRN versus experimental data

The experimental and predicted NOx emissions (corrected to 15% O2) of NG and 90%hydrogen mixed with NG are plotted as a function of the adiabatic flame temperature(AFT) in Figure 7. Diamonds identify the NG-NOx results at steady state, and redtriangles are used for the hydrogen blend. Figure 7 also includes the experimental resultsobtained by Cheng et al. (2009), at the National Energy Technology Laboratory (NETL).Even though their experiments were carried out at different pressure and temperatureconditions (4 atm and 500 K preheating premixed blend), the experimental trend overlapsthe result obtained at UCI, which indicates that NOx emissions and LBO limit are mainlya function of the flame temperature and fuel composition while pressure and preheatingtemperature apparently play an almost negligible role. Similarly, the results show that theaddition of hydrogen up to 90% to NG leads a significant shift on the concentration ofNOx emissions at a constant flame temperature. Previous emissions results by Cheng et al.(2009) with the LSI at NETL have also shown that high hydrogen fuels tend to generatemore NOx than NG or methane. Since the CRN was optimized to match LBO and NOx

trends, it can be used to add insight into the role of the fundamental parameters governingthe emission formation close to the LBO limit.

For instance, a consequence of the high reactivity of hydrogen is a shorter flamelength. High reactivity or fast chemistry counteracts the effect of mixing with thecombustion products, which contain diluents and slow the reaction intensity. Thefresh H2-air mixes with EGR, ignites and burns with high reactivity, generating highfree radical concentrations, which produce more NOx than do methane flames at equalcombustion temperature.

2126 A. COLORADO AND V. MCDONELL

Also shown in Figure 7 are post-processed NOx values based on the CFD solution. FLUENTuses a decoupled analysis that post-processes a given flow field and combustion solution andcalculates the NOx rates. Even though the simulated flow field and temperature profiles were ingood agreement with the experimental results, the CFD-based result is not able to predict thesignificant shift of the NOx emissions when enriching the fuel with hydrogen. As observed inFigure 7, the CFDmodel predicts an increasing trend with the flame temperature; however, theimpact of the fuel composition is almost undetectable with this strategy. Furthermore, it isapparent that the CFD post-processed results are unable to predict the LBO limits. This resultindicates the importance of using a complete chemistry set (as used in the CRN) to predict theeffect the fuel composition on the emissions and LBO stability limit.

Lean blowoff and sensitivity to reaction mechanism

Figure 7 shows that the addition of hydrogen to natural gas widens the flame temperaturesover which stable operation occurs. While for pure NG the LBO limit occurs atϕCH4

¼ 0:55, for a hydrogen enriched NG up to 90% H2, this limit is ϕ90H2¼ 0:25. As

mentioned in the background, several studies have focused on H2/CH4 flames and shownthat small additions of H2 substantially enhance the mixture resistance to extinction orblowout.

After tuning the CRN model with the GRI mechanism and considering the same boundaryconditions, the differences in the results are related only to the sensitivity of the method to thereaction mechanism. The four mechanisms predict the same trends. The Galway II mechanismpredicts similar results without further modifying the CRN, while the USC II and Konnov 0.4mechanism tend to predict a slightly higher level of NOx emissions. The sensitivity check for thehydrogen case indicates similar results (not shown for brevity).

Figure 7. NOx emissions and LBO limit as predicted with a CFD (non-kinetic) model, CRN with completechemistry and experimental results collected in UCI and elsewhere.

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Sensitivity of the CRN to the geometric variables, EGR, and heat losses

The sensitivity of the LBO and NOx to the geometry and heat losses of the reactors ispresented in Figures 8a and 8b, respectively.

In order to test the results’ sensitivity to these variables, the volume of the PSRs was doubled(2V) and divided by 2 (V=2) and the length of the PFR was doubled to 2L. The geometricvariables were varied one by one, while the heat losses and % of EGR were fixed at the initialestimated values. Increasing the length of the PFR increases the total production of NOx atequivalence ratios close to 1, without affecting the prediction of the LBO limit, which coincideswith the predictedNOx levels below 0.6 ppmdv@15%O2. TheNOx levels atϕ< 0:8.Varying thevolumes of the PSR0 and PSR2 has a negligible effect on the results as the trends overlap thebaseline case. Conversely, doubling the volume of the PSR1 shifts the NOx production upwards.Halving the volume shifts the trenddownwards. Still, the variation of the geometric parameters is

Figure 8. a) Sensitivity of the CRN zones to the geometric variables for NG using GRI 3.0. b) Effect ofheat losses through the reactors walls.

2128 A. COLORADO AND V. MCDONELL

not the principal variable responsible for an accurate prediction of NOx and LBO. Figure 8bshows the effect of the heat losses and EGR on the prediction of NOx levels and LBO. Increasingthe heat losses in the PFR reduces theNOx levels formixtureswithϕ from0.8 to 1; the predictionof the LBO limit is not impacted by this variable. In contrast, the NOx levels and LBO are highlysensitive to the heat losses from the core of the reactions (PSR1), which are initially estimated asradiation heat losses using the RADCALmodel. For a 10%heat loss compared to 1%used for thebaseline case, the results are shifted downwards, significantly reducing the NOx emissions andincreasing the LBO limit from 0.63 < ϕ < 0.72. The results indicate the NOx reduction is moreeasily achieved by increasing the heat losses through the walls than by increasing the EGR level.

Chemical kinetics discussion

The molar NOx production rate in the different reactors indicates that NOx formation occursalmost exclusively in the flame zone (PSR1) or core of the reactions, where radical concentra-tions are significantly above the equilibrium values. The production rate of NOx in the flameregion is around three and five orders of magnitude higher in the flame region compared to postflame and the EGR zones, respectively. For NG and for ϕ between 0.64 and 0.98, in the flameregion the molar production of NOx (mole/cm3 s) varies between 10–8 to 10–5. In the post flameregion the production rate varies from 10–11 to 10–8 and in the recirculation loop this rate variesbetween 10–12 and 10–10. The participation of the four elementary NOx pathways on the totalemissions is presented as a function of AFT for NG and the hydrogen blend in Figures 9a and9b, respectively. In order to gain better insight on these trends, each of the four NOx productionpathways is isolated and the model is rerun per the methodology of Fackler et al. (2011). It isobserved that all of the pathways increase the production of NOx at higher temperatures. Therelative participation of the NNH remains almost constant within the range of temperaturesanalyzed, although the addition of hydrogen to the fuel enhances the concentration of H radicalsthat take part in the NNH reactions, and consequently the production of NOx through thatpathway increases four- to five-fold compared to NG. At constant AFT, the addition ofhydrogen reduces the prompt NO due to the decrease in hydrocarbon radicals in a flame. Forthe NG flames, the participation of the prompt route goes from 11% to 30% at 1700 < AFT <1900 K, while for the hydrogen blend it goes from 3% to 9% within the same range oftemperatures. Since the combustion temperatures are purposefully maintained at relativelylow values (e.g., below 1900 K) and given the low ϕCH4

0.62–0.74 and ϕ90H2¼ 0:55� 0:67,

the Zeldovich NOx pathway is not expected to dominate the NOx emitted. Still, in the combus-tion environment, the high reactivity of the hydrogen may cause a rise in the local flametemperature, which would result in an increase of NOx through the Zeldovich route. Still, thereactions in a PSR1 happen at a uniform temperature; therefore, the increase of NO producedthrough the Zeldovich route is only a function of the kinetics of the reaction, i.e., the addition ofH2 increases the concentration of H-atoms and OH radicals and the leaner mixtures guaranteeexcess O2, which can produce O-atoms. The increased concentration of these radicals accel-erates the production of Zeldovich NO. Although the fraction of Zeldovich NO is around thesame for both fuels, the addition of H2 leads an increase of around 2.5 times the NOx generatedby the flame of NG.

At 1700 K the NOx formed via the nitrous oxide (N2O) pathway is responsible for 80% of thetotal NOx produced and this ratio reduces to 50% at 1900 K with either fuel. The N2O

COMBUSTION SCIENCE AND TECHNOLOGY 2129

mechanism is dominant for temperatures below 1900 K. Above 1900 K, the Zeldovich andprompt mechanisms become more important as expected. Zeldovich NOx follows the expectedexponential trend with the temperature, while the N2O follows a more linear trend, whichexplains the lower participation of the N2O route at higher temperature. In addition, the NOx

formation via theN2Omechanism is pressure dependent and the pressure influence is evidencedin the reaction: Oþ N2 þM $ N2OþM, whereM represents a chemically unchanged third-body species. As the CRN models the LSB operating at elevated pressure (3 atm), perLe’Chatelier’s principle, increasing pressure drives the equilibrium to the right side of theequation, thus enabling NOx formation through the subsequent N2O reactions.

Conclusions

An optimized CRN model, including the effect of the EGR and heat losses, is able toaccurately predict the changes in the emissions and lean blowoff limits when changing thefuel composition.

Figure 9. Participation of the NOx pathways modeled with GRI 3.0. a) 100% CH4. b) 90% H2/10% CH4.

2130 A. COLORADO AND V. MCDONELL

The study illustrates how the CRN approach can be used as a valuable tool for thedesign of combustion systems. The CRN is able to correlate the geometry of a system withthe variables that govern the formation of pollutants (operating pressure, heat transfer,residence time, temperature, mixing strategy), governing the formation of pollutants andits relation to the geometric variables. Therefore, it can be used as a design tool tominimize emissions and control stability issues.

The effect of the pressure up to 40 atm on the radiation heat from hydrogen and NGlean premixed flames was assessed numerically with the RADCAL model. The trendsindicate that increasing the pressure increases the direct radiation from the flame; how-ever, as the fuel mixture is enriched with hydrogen, the higher concentration of water inthe gases reduces the radiative heat losses compared to natural gas flames.

The operating conditions of the low swirl burner in the current study, including elevatedpressure and ultra-lean equivalence ratios, lead to formation of NOx mainly through theN2O intermediate species mechanism and the Zeldovich routes. At temperatures below 1900K, the N2O pathway is dominant. The CRN indicated that, for an AFT = 1700 K, about 80%of the total NOx emissions is produced through the N2O pathway. At temperatures above1900 K the thermal and prompt NOx become more significant.

The reactor network analysis indicated that the addition of hydrogen to the fuel underlean conditions increases the production of NOx through the Zeldovich, N2O, and NNHroutes, whereas the prompt NOx is hindered since the hydrocarbon radicals that promotethis route are reduced.

Acknowledgments

The experimental results provided by David Beerer and the CFD analysis conducted by MathiasNeumayer are highly appreciated. Discussions with Phil Malte, John Kramlich, Megan Karalus, andIgor Nossolev regarding the application of the CRN were very helpful.

Funding

The authors gratefully acknowledge Colciencias for the financial support of Andres Coloradothrough the scholarship Francisco Jose de Caldas. Also, the support of the California EnergyCommission (Contract 500-13-004) is gratefully appreciated.

ORCID

Andres Colorado http://orcid.org/0000-0003-0268-8841

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