, 2014 , 44 : 201402

Recent progress and challenges in

fundamental combustion research

Yiguang Ju†

Department of Mechanical and Aerospace Engineering,

Princeton University, New Jersey, USA

Abstract More than 80% of world energy is converted by combustion. Develop-

ment of efficient next generation advanced engines by using alternative fuels and

operating at extreme conditions is one of the most important solutions to increase

energy sustainability. To realize the advanced engine design, the challenges in

combustion research are therefore to advance fundamental understanding of com-

bustion chemistry and dynamics from molecule scales to engine scales and to de-

velop quantitatively predictive tools and innovative combustion technologies. This

review will present the recent progresses and technical challenges in fundamental

combustion research in seven areas including advanced engine concepts using low

temperature fuel chemistry, new combustion phenomena in extreme conditions,

alternative and surrogate fuels, multi-scale modeling, high pressure combustion

kinetics, experimental methods and advanced combustion diagnostics Firstly, new

engine concepts such as the Homogeneous Charge Compression Ignition (HCCI),

†Received: 2014-01-29; accepted: 2014-03-27; online: 2014-04-01E-mail: yju@princeton.edu

i te as: Yiguang Ju. Recent progress and challenges in fundamental combustion research.

c©vances in Mechanics, 2014, 44:

2014 Advances in Mechanics.

2 44 : 201402

Reactivity Controlled Compression Ignition (RCCI), and pressure gain combus-

tion will be introduced. The impact of low temperature combustion chemistry of

fuels on combustion in advanced engines will be demonstrated. This is followed

by the discussions of the needs of fundamental combustion research for new en-

gine technologies. Secondly, combustion phenomena and flame regimes involving

new combustion concepts such as fuel and thermal stratifications, plasma assisted

combustion, and cool flames at extreme conditions will be analyzed. Thirdly, al-

ternative fuels and methodologies to formulate surrogate fuel mixtures to model

the target combustion properties of real fuels will be presented. A new concept of

radical index and transport weighted enthalpy will be introduced to rank the fuel

reactivity and to assess the impact of molecular structure on combustion prop-

erties The success and limitations of the current surrogate fuel models will be

discussed by using jet fuels and biodiesels as examples. Fourthly, the difficulty

of modeling large kinetic mechanism of real fuel will be discussed The multi-time

scale (MTS) method and the correlated dynamic adaptive chemistry (CO-DAC)

method for kinetic model reduction and computationally efficient modeling will

be compared and analyzed. Fifthly, the progress and challenges of high pressure

combustion kinetics for hydrogen and larger hydrocarbons will be discussed. The

important pressuredependent reaction pathways and key intermediate species at

high pressure will be analyzed. Fundamental experimental methods for combus-

tion and their uncertainties in acquiring combustion properties for the validation

of kinetic mechanism will be discussed. Finally, recent progress in diagnostics of

HO2, H2O2, RO2, ketohydroperoxide, and other key intermediate species for high

pressure kinetic mechanism development will be summarized. Conclusions and

opportunities of future combustion research will be made.

Keywords alternative fuels, flame chemistry multiscale modeling, experimental

methods and uncertainty, multi-species diagnostics

Classification code: O341 Document code: A DOI: 10.6052/1000-0992-14-011

Ju Yiguang : Recent progress and challenges in fundamental combustion research 3

1 Introduction

1.1 Advanced engine design and multi-scale turbulent combustion

modeling

Combustion converts more than 80% of world energy and has played a dominant role in

ground and air transportation. With the current difficulties in developing renewable energy,

for a foreseeable future, combustion will remain to be the major energy conversion process in

power generation and transportation. However, the energy conversion efficiency of existing

combustion engines is low and combustion of fossil fuels is the major source contributing

to climate change and air pollution (Chu et al. 2012). As such, there is an urgent need to

develop advanced engine technology and new combustion concepts to drastically increase

the engine efficiency and reduce emissions (DOE report, 2006). For ground transportation,

recently, various new combustion engine technologies such the Homogeneous Charge Com-

pression Ignition (HCCI) engines (Dec 2009, Lu et al. 2011, Reitz 2013) and the Reactivity

Controlled Compression Ignition (RCCI) engines (Reitz 2013) have been developed. These

engines take the advantage of high compression ratio of diesel engines and low emissions of

gasoline engines by using highly diluted, premixed and/or highly stratified fuel/air mixtures

with excessive exhaust gas recirculation (EGR). As such, to control engine knock, heat

release rate, and ignition timing at different engine loads, understanding the combustion

process at high pressure and low temperature conditions involving the negative temperature

coefficient (NTC) and cool flame chemistry (Curran et al. 1998) becomes extremely impor-

tant. Moreover, the low temperature and high pressure combustion processes coupled by

strong fuel and temperature non-uniformities in engines are controlled by both large-scale

turbulent mixing and sub-grid-scale turbulence-chemistry interactions. Therefore, detailed

understanding of combustion processes in HCCI and RCCI engines requires not only an

accurate turbulent combustion model which can appropriately predict sub-grid turbulent-

chemistry interaction but also a validated high pressure and low temperature chemistry for

real transportation fuels. Unfortunately, strictly speaking neither a validated high pressure

and low temperature kinetic mechanism for real fuels nor an accurate and computation-

ally efficient sub-grid turbulent-chemistry model is available for advanced engine modeling

(Chen 2011, Pope 2012). Moreover, previous turbulent combustion experiments and model-

ing are mainly focused on high temperature thin flame regimes and few studies are carried

to understand how low temperature combustion chemistry and autoignition affect turbulent

4 44 : 201402

flame regimes and propagation speeds (Won et al. 2014) Therefore, the first challenge in

combustion is how we can develop validated high pressure and low temperature combustion

models for advanced engine modeling.

In air transportation, to increase the fuel efficiency and meet the stringent CAEP-6 and

NASA (N+3) emission standards of the Committee on Aviation Environmental Protection

(CAEP) and NASA, new lean burn aircraft combustor concepts such as the twin annular

premixing swirled (TAPS) burner (Mongia 2010), lean-premixed pre-vaporized (LPP), lean

direct injection (LDI) burners (Tacina et al. 2003), trapped vortex combustion (TVC) burn-

ers (Hsu et al. 1998), and pressure gain combustors (Schwer and Kailasanath 2011) have

been developed. To achieve high speed propulsion, supersonic ramjet engines such as X-43

and X-51 have been developed and tested (Moorthy et al. 2012, Yu et al. 2013). Moreover,

new advanced gas turbine engines have higher compression ratios and thus have changed

the conventional rich-quench-lean diffusion combustion to fully and partially premixed com-

bustion. In addition, due to the increase of ignition Damkohler number at elevated tem-

perature, the thin flame front flame propagation process in conventional engines is replaced

substantially by volumetric ignition. Especially, at ultra-lean fuel conditions, local flame

extinction, re-ignition, and ignition to flame as well as ignition to detonation transitions will

occur. As such, premixed turbulent flame regimes at high ignition Damkohler may become

very different from that of the classical wrinkled and corrugated flamelet regimes (Bradley

1992, Driscoll 2008, Peters 2000) and the conventional incompressible flow, flamelet, and

pre-assumed probability density function (PDF) based turbulent combustion modeling ap-

proaches may not be appropriate (Peters 1988, Pitsch 2006, Pope 2013) for the new engine

modeling. As shown in Fig. 1 (Gou et al. 2010), combustion in engines involves many

orders of magnitudes of different time- and length-scales ranging from electronic excitation,

molecular diffusion, soot particle formation, sub-grid turbulent mixing, and engine scale flow

motion and instability. The main factors affecting the combustion phenomenon depend on

the combustion process. For example, for near limit combustion the time scales involving

elementary combustion chemistry is important. For engine instability, the timescales of sub-

grid turbulent mixing, heat release rate, and acoustic waves are more important. For flame

extinction, the molecular diffusion is important. Therefore, the second challenge of combus-

tion is how to develop a new turbulent combustion modeling approach which can address

the multi-time scale, multi-length scale, and multi-physics combustion processes accurately

with detailed kinetic mechanisms.

For high speed propulsion such as supersonic combustion and Scramjet engines, vitiated

Ju Yiguang : Recent progress and challenges in fundamental combustion research 5

Physical process

Modeling approach

Physical, chemical models

AtomMolecules

Molecular collisions

QuantumChemistry

Direct Numerical Simulation

Statistical Mechanics

Experiment/validation

LES, PDF, RANS

Thermo-chemistry

Soot growth,aggregation

Mixing, ignition, extinction, flamestructure, emissions

Microflow

Nanoparticles

Kinetic rates of reactions Turbulent transport-chemistry interaction

Molecular and turbulent transport scales

Flames Engine combustion

10-10 10-8 10-6 10-4 10-2 1 m

Fig. 1

Multi-scale processes and multi-scale prediction models in combustion (Gou et al. 2010)

air has been widely used in test facilities. As a result, the kinetic effects via air contamina-

tion by H2O and NOx on supersonic combustion have complicated the experimental studies

for decades. Recently, as reported by Jiang and Yu (2014) the world largest detonation-

driven hypervelocity shock tunnel was developed, tested, and calibrated at the Institute of

Mechanics in Beijing. This facility significantly extends the current hypersonic test capabil-

ity to mimic real flight conditions of Mach number 5∼9 at altitude of 25∼50 km for more

than 100 ms test duration, and reduce the kinetic uncertainties due to air contamination.

1.2 New combustion concepts under extreme and non-equilibrium

conditions

To enable the above new engine technologies and to achieve low emissions, fuel lean

and high speed combustion, various new combustion concepts such as partially premixed

and stratified combustion (Dec, 2009), plasma assisted combustion (Starikovskiy 2012, Uddi

et al. 2009, Sun et al. 2010), cool flames (Won et al. 2014), microscale combustion (Ju

et al. 2011, Fernandez-Pello 2002), and pulsed and spinning detonation engines (Schott

1965, Bykovskii et al. 2006), and nanopropellants (Ohkura et al. 2011, Sabourin 2009)

have been developed. These new combustion concepts involve in multi-physical interactions

of non-equilibrium chemical and transport processes, and lead to many new combustion

6 44 : 201402

regimes. For example, for high pressure stratified combustion, the flame regimes arising

from ignition to flame and ignition to detonation transitions at low temperature conditions

are very complicated and have not been well examined (Ju et al. 2011, Sun et al. 2014, Dai

et al. 2014) Understanding of cool flame chemistry is extremely important to control engine

knocking and to avoid stochastic engine failure. Although cool flames have been observed

for many decades (Barnard 1969, Griffiths 1992, Oshibe et al. 2010, Nayagam et al. 2012),

establishment of a stable cool flame in laboratories has not succeeded despite numerous

attempts. As such, the dynamics, chemical kinetics, and kinetics-transport coupling as well

as the cool flame regime diagram remain poorly understood. For example, to date we still

do not know how fast a cool flame can propagate and how lean it can burn. On the other

hand, for plasma assisted combustion, the highly non-equilibrium energy transfer between

electrons, electronically and vibrationally excited molecules, and neutral molecules are not

well known (Sun et al 2011, Stancu et al. 2009, Uddi et al. 2009). Moreover, the low

temperature fuel oxidation chemistry of large hydrocarbon transportation fuels activated

by plasma discharge is also poorly understood (Sun et al. 2014). For microscale energy

conversion, the strong thermal and kinetic coupling via flame-wall interaction significantly

modified the flame regimes (Ronney 2003, Ju et al. 2003, Maruta et al. 2005, Ju et al.

2005, Xu et al. 2009) In nano-propellant design, functional groups including hydrogen,

oxygen, and nitrogen bonds are added to nanosparticles and graphene sheets (Ohkura et

al. 2011, Sabourin 2009) to enhance ignition and combustion properties via non-equilibrium

photo-chemical and thermal chemical reaction processes. For spinning detonation, the wall

curvature and fuel/air mixing have significant impacts on the detonation initiation and

propagation modes (Sugiyama et al. 2013). Therefore, the third challenge in combustion is

the lack of fundamental understanding of combustion phenomena and flame regimes under

extreme and non-equilibrium conditions.

1.3 Alternative fuels

To address the issue of energy sustainability and CO2 emissions from fossil fuels, devel-

opment and certification of alternative and renewable fuels from alternative resources and

biomass (Chu et al. 2012, Hu et al. 2008, Hoinghaus et al. 2010, Dooley et al. 2010) have

attracted great attention. In the US, about 49 billion liters of corn ethanol (equivalent to

10% of the US annual gasoline consumption) and 4.1 billion liters of biodiesel were produced

in 2012. At the same time, unconventional shale gas production has reached one-third of

the total US natural gas production. Oil production from tar sand, high hydrogen syngas

Ju Yiguang : Recent progress and challenges in fundamental combustion research 7

production from coal and biomass, and synthetic aviation fuel production from natural gas,

coal, ethanol, and bio-oils have also increased (Bessee et al. 2011, Simon et al. 2011).

Furthermore, the second generation biofuels produced from non-food crops and lignocellu-

losic materials will further diversify the feedstock of transportation fuels (Dale et al. 2006,

Soetaert et al. 2009, Binder et al. 2009). As shown in Table 1, different fuels have different

molecular structures and functional groups, and thus different fuel reactivity and combus-

tion and emission properties (Westbrook 2013, Won et al. 2012, Dievart et al. 2012, Gail

et al. 2007). Practically, most of the alternative fuels are blended into existing petroleum

derived fuels and result in a real fuel with hundreds to thousands of species. On the other

hand, advanced engine design requires a generic method to evaluate the performance of

alternative fuels involving a large number of species with different functional groups. As

such, the fourth challenge in combustion is how we can construct a compact surrogate fuel

mixture and kinetic model to model the physical and combustion properties of a real fuel

appropriately. Since the resulting surrogate kinetic model will involve several hundreds of

species, naturally the fifth challenge is how we can use the large kinetic model of a surrogate

mixture to computationally efficiently model turbulent combustion for real fuels (Gou et al.

2010).

Table 1 Fuels with different molecular structures

Normalalkane

Branchedalkane

Biodiesel,Esters

Valericbiofuels Alcohols EthersAromatics

1.4 Experimental and diagnostic methods at high pressure

To develop validated surrogate fuel models, chemical kinetic models, and turbulent

combustion models for engine applications, it is important to develop experimental and

diagnostic methods with well defined experimental uncertainties so that the measured com-

bustion properties can be used in model validation. In last several decades, counterflow

flames, spherically propagating flames, flat flames, flow reactors, rapid compression ma-

chines, and shock tubes have been developed and used to acquire different experimental

targets. However, there are large discrepancies in these experimental data and some of the

OHO

R2

O

OR1R1R2R

8 44 : 201402

key combustion parameters such as the flame speeds and species profiles are not appropri-

ately extracted because of the perturbation of sampling nozzles as well as inappropriate

assumptions of physical processes and boundary conditions. In addition, with the use of

multi-component fuels and excessive exhaust gas recirculation (EGR), the chemical and ra-

diation effects from H2O and CO2 and the preferential transport effect of blended fuels will

significantly affect the flame dynamics and change the interpretation of experimental data

(Ju et al. 1997, 1998, Chen et al. 2007). Therefore, the sixth challenge is how to im-

prove and design fundamental combustion experiments with well defined physical processes

and boundary conditions so that the uncertainty of the experiments can be modeled and

quantified appropriately.

As the engine pressure increases and the reaction pathways are more pressure depen-

dent. At high pressure, the branching ratio of pressure dependent unimolecular decom-

position reactions will become increasingly important in affecting the fuel reactivity. At

high pressure and low temperature combustion processes, HO2, H2O2, RO2, and ketohy-

droperoxide related fuel oxidation chemistry starts to dominate. Therefore, it is critical to

measure the key radicals and intermediate species at elevated pressure to develop low tem-

perature chemistry models and to determine the branching ratio of radical decomposition

reactions. Unfortunately, due to the high radical reactivity and serious spectra overlaps

between HO2, H2O2, RO2, QOOH, and ketohydroperoxides in both infrared (IR) and ultra-

violet (UV) regions, the conventional gas sampling methods (Gail et al. 2007, Dooley et al.

2012, Lefkowitz et al. 2012, Tranter et al. 2002,) and molecular beam mass spectrometry

(Osswald et al. 2007, Guo et al. 2013, Qi 2013, Taatjes et al. 2008) as well as the laser

based diagnostic methods such as the laser induced fluorescence (Li et al. 2013, Ombrello

et al. 2006, Sun et al. 2012) and laser absorption methods (Hong et al. 2012, Bahrini et al.

2012) are difficult to be applied to detect HO2, H2O2, RO2, QOOH, ketohydroperoxides,

and other key intermediate species (Crowley et al. 1991). As such, the seventh challenge is

how to quantitatively measure key radicals and intermediate species at elevated pressure.

This review is to provide a summary of the recent progresses in above seven technical

challenges. Since the review topic is very broad, it is impossible for this review to include all

subject areas and important publications. As such, this review is intended to highlight the

major advances in the areas of fundamental research for applications in internal combustion

engines and gas turbine engines. Progresses in other specific areas such as oxyfuel combustion

(Buhre et al. 2005), supersonic combustion (Billig, 1993, Moorthy et al. 2012, Yu et al.

2013), and turbulent combustion modeling (Pope 2012) can be found in recent reviews

Ju Yiguang : Recent progress and challenges in fundamental combustion research 9

in journals such as Proceedings of International Symposiums on Combustion, Progress of

Energy of Combustion Science, and Journal of Propulsion and Power.

2 Progress and challenges in combustion research

2.1 The impact of combustion chemistry on turbulent combustion

in engines

Unlike the conventional gasoline and diesel engines (Fig. 2), which mainly rely on,

respectively, the propagation and transport of premixed and diffusion flames to produce

heat release, advanced HCCI and RCCI engines use partially or fully premixed combustion

processes with multi-pulse early fuel injection and EGR dilution. As such the combustion

process in HCCI and RCCI engines is more dominated by volumetric ignition than flame

front propagation. As a result, in advanced engines combustion processes involving auto-

ignition and ignition to flame transition play an important role.

Ignition process is highly governed by radical initiation and branching processes which

depend strongly on the size and structure of fuel molecules Therefore, the heat release rate of

advanced engines such as HCCI and RCCI is more affected by initial pressure, temperature,

and fuel reactivity than conventional engines. Figure 3 shows the computed ignition delay

time of three fuels, n-heptane (normal alkane), iso-octane (branched alkane), and toluene

(aromatics) with different molecular structures (Table 1) as a function of temperature at

13.5 atm by using the Real Fuel-2 mechanism (Dooley et al. 2013). It is seen that three fuels

have very different ignition delay times due to the difference in their molecular structures.

For n-heptane, at both high (larger than 1050 K) and low (less than 700 K) temperatures,

the ignition delay time increases exponentially with the decrease of temperature. However,

Gasoline engine Diesel engine HCCI RCCI

Fig. 2

Schematic of gasoline, diesel, HCCI, and early injection RCCI engines (Dec.2008, Reitz,

2013)

10 44 : 201402

0.8 1.0 1.2 1.4

104

103

102

101

100

10-1

1000/T[1/K]

fuel/air mixture, ϕ=1.0, p=13.5 atm

lgnitio

n d

ela

y t

ime/m

s

toluene

iso-octane

n-heptane

Fig. 3

Ignition delay times of n-heptane, iso-octane, and toluene as a function of temperature at

13.5 atm and stoichiometric condition

between 1050 K and 700 K, there is region that the ignition delay time decreases with the

decrease of temperature. This region is called the negative temperature coefficient (NTC)

region or the low temperature chemistry region (Curran et al. 1998). Note that in the

NTC region, the ignition delay time at 13.5 atm is as short as a few milliseconds which are

comparable with the combustion timescales in internal combustion engines and gas turbines.

Therefore, the NTC chemistry will have a significant impact on the combustion process as the

compression ratio of modern engines further increases. Figure 3 also shows that branched

alkanes (iso-octane) have longer ignition delay time and weaker NTC effect than normal

alkanes. On the other hand, for aromatic fuels, due to the ring stability, no low temperature

chemistry is observed and the ignition delay time is much longer than that of normal and

branched alkanes. Therefore, the high pressure combustion processes in an engine will be

a strong function of fuel molecular structures, particularly at the low temperature region.

Failure to control ignition at the NTC region may lead to engine knocking, instability, and

an increase of emissions.

To show how engine performance is sensitive to fuel molecular structure, Fig. 4 plots a

computed time history of the apparent heat release rate (AHRR) as a function of crank angle

after the dead center (ATDC) with an n-heptane and iso-octane mixture. It is seen that

at 15◦ before TDC, low temperature combustion of n-heptane (cool flame) occurs. As the

crank angle approaches to TDC, the in-cylinder temperature and pressure increase and the

n-heptane high temperature ignition occurs. As the crank angle passes the TDC, another

heat release peak is seen due to iso-octance combustion (longer ignition delay time than

Ju Yiguang : Recent progress and challenges in fundamental combustion research 11

-20 -10 0 10 20

Crank [ATDC]

AH

HR

[J/

Ο]

200

150

100

50

0

Control of combustion duration by ration

of fuels

Cool

Flame PRF Burn

Primarlyn-heptane

Primarlyiso-octane

iso-octane Burn

n-heptane+entrainediso-octane

Fig. 4

Time history of heat release rate in a RCCI engine with n-heptane and iso-octane mixture

(Reitz 2013)

n-heptane, Fig. 3). Figure 4 clearly shows that the combustion process in a RCCI engine

is sensitive to fuel molecular structure and that low temperature combustion in NTC region

affects the heat release rate.

Another example in turbulent combustion with elevated temperature and pressure in

air transportation is the staged combustion of in Twin Annular Premixed Swirler (TAPS)

burner used for the GEnx gas turbine engine (Fig. 5). In this engine, flames in the highly

diluted primary combustion zone are stabilized in the high temperature burned gas region

of a premixed pre-burner. Therefore, most of the jet fuel will be vaporized, ignited, and

burned at a high temperature and high pressure environment. When the auto-ignition time

becomes shorter than the mixing time at elevated temperature, the turbulent combustion

and flame instability will be affected by the low temperature ignition.

Recent direct numerical simulations (DNS) (El-Asrag et al. 2013, 2014, Zhang et al.

2013) of high pressure and temperature and concentration stratified HCCI combustion using

dimethyl-ether (DME) with and without exhaust gas recirculation (EGR) effects showed

that, due to the existence of low temperature chemistry of DME, two different ignition-

kernel propagation modes were observed (Fig. 6(a)): a wave-like, low-speed, deflagrative

mode (the D-mode) and a spontaneous, high-speed, kinetically driven ignition mode (the

S-mode). Three criteria were introduced to distinguish the two modes by different character-

12 44 : 201402

Fig. 5

Schematic of Twin Annular Premixed Swirler (TAPS) burner (Mongia 2010)

Q↼J/m3/s)

8Τ1010

7Τ1010

6Τ1010

5Τ1010

4Τ1010

3Τ1010

2Τ1010

1Τ1010

0

OH

HO2

a b

Fig. 6

(a) Heat release rate of different flame modes (AB and CD) due to fuel (dimethyl ether) and

temperature stratifications in a turbulent flow (EI- El-Asrag et al. 2013), (b) OH and HO2

distributions of an ethylene lifted jet flame with the co-flow temperature at 1550 k (Yoo et

al. 2011)

istic timescales and the ignition Damkohler number using a progress variable conditioned by

a proper ignition kernel indicator. The results showed that the spontaneous ignition S-mode

was characterized by low scalar dissipation rate, high mixing Damkohler number, and high

displacement speed ignition front, while the D-mode was characterized by high scalar dissi-

pation rate and low displacement speeds in the order of the laminar flame speed with a small

ignition Damkohler number. Another DNS of the near field of a three-dimensional spatially-

developing turbulent ethylene jet flame in highly-heated co-flow was performed by Yoo et

al. (2011) to determine the flame stabilization mechanism. The DNS was performed at a

jet Reynolds number of 10,000 with over 1.29 billion grid points. The results in Fig. 6(b)

of OH (heat release process) and HO2 (ignition and chain initiation process) distributions

Ju Yiguang : Recent progress and challenges in fundamental combustion research 13

show that, at an elevated co-flow temperature, auto-ignition in a fuel-lean mixture at the

flame base is the main source of stabilization of the lifted jet flame. The Damkohler number

and chemical explosive mode (CEM) analysis also verified that auto-ignition occurred at the

flame base. It was also observed that the lifted flame base exhibited a cyclic ‘saw-tooth’

shaped movement marked by rapid movement upstream and slower movement downstream.

This was a consequence of the lifted flame being stabilized by a balance between consecutive

auto-ignition events in hot fuel-lean mixtures and convection induced by the high speed jet

and co-flow velocities.

The above DNS results clearly show that auto-ignition involving low temperature chem-

istry for large hydrocarbon transportation fuels may play a very important role in turbulent

combustion of engines. Unfortunately, to date the major focus of turbulent combustion has

been placed on the measurements of high temperature flame burning velocities and flame

structures (Bradley 1992, Driscoll 2008, Peters, 2000, Yuen et al. 2009) and the effects of

pressure (Kobayashi et al. 1997, Soika et al. 2003), Lewis number (Bradley 1992, Rutland

et al. 1996, Chaudhuri et al. 2012), preferential diffusion (Dunn et al. 2013), and turbulent

flame geometry (Smallwood et al. 1995, Shepherd et al. 1992). The measured turbulent

burning velocity (ST ) normalized by the laminar flame speed (SL) is fitted as a function of

the normalized turbulent intensity (u′/SL), the Lewis number (Le), the turbulent integral

length scale (l), and the laminar flame thickness (δf ) (Bradley 1992, Driscoll 2008, Peters

2000, Chaudhuri et al. 2012),

ST

SL= 1 + CLe−1

(u′

SL

l

δf

)n

(1)

where C represents a constant and n is an adjustable exponent. A turbulent flame regime

diagram called the Borghi diagram was used to specify the turbulent flame regime based

on the turbulent time scale (l/u′) and the flame time scale (δf/SL) (Peters 2000, Borghi

1984, Li 1994). Although, this turbulent diagram provides very insightful information for

different flame regimes such as the wrinkled, corrugated, thin reaction zone, and distributed

reaction zone flames, it only includes one characteristic timescale of the flame speed. The

ignition timescale is not considered in the Borghi diagram. As a result, the Borghi diagram

and the turbulent flame speed relation in Eq. (1) may not be applicable directly to the

advanced engines in which ignition and low temperature fuel oxidation play an important

role. Therefore, a question naturally arises: how does the low temperature fuel chemistry

and auto-ignition at elevated temperature affect the turbulent flame propagation and the

Borghi diagram? Additionally, will the turbulent burning velocity still be a well-defined

14 44 : 201402

value when the low temperature reactivity changes the fuel composition and reactivity via

low temperature oxidation?

Figure 7 schematically shows how the increase of fuel reactivity at elevated tem-

perature (ignition Damkohler number) affect the turbulent flame regime. At low ignition

Damkohler number, turbulent flame regimes are governed by the length scale of turbulent

mixing (e.g. the Taylor microscale) and the thickness of the reaction zone. When the tur-

bulent mixing scale is smaller than the thickness of the thin reaction zone, the thin flame

regime becomes a distributed reaction zone. However, when the ignition Damkohler number

is increased at high temperature due to low temperature chemistry, the flame regime will

be affected by the turbulent mixing time, the auto-ignition time, and the flame propagation

time. If the auto-ignition time becomes shorter than the flame propagation time, a broad-

ened, distributed reaction zone due to auto-ignition will occur (Fig. 7). Unfortunately, few

previous studies have addressed the transition between ignition and flame propagation in

10-1 100 101 102 103 104

10-1 100 101 102 103 104

103

102

101

100

10-1

103

102

101

100

10-1

Turb

ule

nt

inte

nsi

ty

Distributedreaction zone

Distributedreaction zone

Thin reactionzone

Thin reactionzone

Corrugatedflamelet

Corrugatedflamelet

Wrinkledflamelet

Wrinkledflamelet

u'�

SL

1�dL Turbulent scale

Progress of fuel oxidationTurbulence/chemistry interaction

u'�

SL

1�dL

Da

ig>1

Fig. 7

The change of turbulent flame diagram with the increase of ignition Damkohler

Ju Yiguang : Recent progress and challenges in fundamental combustion research 15

turbulent combustion.

To demonstrate the effect of low temperature ignition on turbulent flame propaga-

tion, recently a new high temperature, high Reynolds number, Reactor Assisted Turbulent

Slot (RATS) burner has been developed to investigate turbulent flame regimes and burning

rates for large hydrocarbon transportation fuels (Won et al. 2014). The turbulent flow

characteristics were quantified using hot wire anemometry. The turbulent flame structures

and burning velocities of n-heptane/air mixtures were measured by using planar laser in-

duced fluorescence of OH and CH2O with reactant temperatures spanning from 400∼700 K.

Figure 8 shows the dependence of flame luminescence and shape on the reactor tempera-

ture. Figure 8(a) represents the conventional thin flame front chemically-frozen-flow flame

regime. In this case, the initial mixture temperature was so low (500 K) that there was no

fuel reactivity before the flame front. However, as the reactor temperature was increased

to 700 K with the same flow residence time, Figs. 8(b)∼8(d) show a new turbulent flame

regime, the low-temperature-ignition regime. In this flame regime, fuel is partially oxidized

due to the low temperature chemistry. Therefore, the conventional assumption of flamelet

fails. At Treactor = 700 K, by reducing the flow velocity (increasing the Damkohler number)

from 10 to 6 m/s, a transitional regime from low temperature ignition to hot ignition in

(a) (b) (c) (d) (e) (f)

Treactor=500 K

U=10 m/s

600 K 650 K 700 K 700 K 700 K10 m/s 10 m/s 10 m/s 10 m/s 6 m/s

Increasing the ignition Damkohler number & fuel reactivity

Fig. 8

Direct photos of n-heptane/air turbulent flames at ϕ = 0.6 with increasing of igni-

tion Damkohler number and fuel reactivity, exhibiting distinctive four flame regimes; (a)

chemically-frozen-flow regime, (b)–(d) low-temperature-ignition regime, (d) and (e) transi-

tional regime between low- to high-temperature-ignition regimes, and (f) high-temperature-

ignition regime (Won et al. 2014)

16 44 : 201402

the reactor is observed from Figs. 8(d) and 8(e). This result clearly shows that the flame

regime diagram in Fig. 8 needs to be dramatically changed when the ignition Damkohler

number is increased at practical engine conditions.

To further quantify the effect of low temperature chemistry on the turbulent flame

speed, Fig. 9 shows the dependence of normalized turbulent flame speeds and the OH/CH2O

planar laser induced fluorescence (PLIF) as a function of turbulent fluctuation velocity at

low and elevated temperatures. For the first time, Fig. 9 (left) shows that the turbu-

lent burning velocities have two different flame regimes, a chemically-frozen-flow regime

and a low-temperature-ignition flame regime, respectively, at low (a) and high (b) reactor

temperatures with different turbulent flame speeds. Moreover, the turbulent flame speed

at the low-temperature-ignition regime is higher than that of chemically-frozen-flow. The

OH/CH2O PLIF images (right) show clearly the difference of turbulent flame structures

of these two flame regimes and the CH2O formation of the low-temperature-ignition flame

regime. It is also interesting to note that, contrary to the previous studies, the results in

Fig. 9 suggest that the turbulent flame burning velocity for fuels with low temperature

chemistry may not be uniquely defined. Rather, it depends on the magnitude of ignition

0 2 4 6 8

6

4

2

0

u'�SL

ST�S

L

ST�SL =

1+1.53Τ(u'�SL)

0.68

ST�SL =1+0.52Τ(u'�

SL)0.87

n-heptane/air, 0.3<φ<1.1,

400 K<Treactor<700 K

at fixed u'�SL=3.0

Treactor=650 K

CH2O detected

400 K550 K650 K550 K650 K

500 K600 K700 K600 K700 K

60 mm

15 mm

CH

2O

PLIF

O

H P

LIF

a

ab

b

Fig. 9

Left: Measured turbulent burning velocity normalized by laminar burning velocity, ST /SL

as a function of turbulent intensity, u′/SL at low (a) and high reactor temperatures (b).

Solid color symbols represent the cases of CH2O detected at the nozzle exit. Black solid

symbols are from the measurements by fixing u′/SL constant.

Right: OH and CH2O PLIF images for turbulent premixed flames at thin flame reaction

regime at 500 K (a) and low temperature ignition regime at 650 K (b); both at ϕ = 0.5 and

the reactor flow residence time of 100 ms (Won et al. 2014)

Ju Yiguang : Recent progress and challenges in fundamental combustion research 17

Damkohler number for low temperature fuel oxidation.

In summary, the above discussions revealed that turbulent combustion in advanced en-

gines is highly governed by the low temperature chemistry and transitions between ignition

and flame propagation. The existence of low temperature chemistry and the increase of igni-

tion Damkohler number will significantly modify the turbulent flame regimes and the regime

diagram. However, few studies have been carried in this new combustion regime. Future

turbulent combustion and engine studies need to address how ignition and low temperature

chemistry affect the combustion regime, heat release rate, flame instability, flashback, and

engine knocking.

2.2 New flame regimes at low temperature and non-equilibrium con-

ditions

To achieve higher engine efficiency and lower emissions, new combustion technolo-

gies such as ultra lean, thermal and fuel stratifications, pressure gain combustion, micro-

combustion, flameless combustion, and plasma assisted combustion have attracted great

attention. These new combustion techniques often operate at near-limit conditions and the

combustion processes are more kinetically dominated by the chemistry with strong coupling

to flame dynamics. In this review, we limit our focus on the impact of how combustion

chemistry affects flame regimes at highly non-equilibrium conditions with thermal and con-

centration stratifications, plasma activation, and low temperature oxidation.

2.2.1 Flame regimes in NTC region with thermal and fuel stratifi-

cations

Thermal and fuel stratification is an important technique to control heat release rate in

HCCI and RCCI engines. However, how thermal and fuel stratifications affect combustion

dynamics and flame regimes is not well understood. Previously, a number of studies have

been conducted to understand ignition and flame propagation in HCCI and spark assisted

HCCI combustion (Persson et al. 2007, Hult et al. 2002) with small hydrocarbon fuels and

simplified models (Cox et al. 1985, Schreiber et al. 1994, Cowart et al. 1991, Martz et al.

2009, Gu et al. 2003, Zeldovich 1980, Sankaran et al. 2005, Chen et al. 2006, Hawkes et

al. 2006). The results showed that the initial temperature and species gradients played an

important role in affecting flame regimes. Unfortunately, few studies have been conducted

to understand the mechanism of flame transition involving large hydrocarbon fuels with low

temperature chemistry and the kinetic coupling between alkanes and aromatics.

18 44 : 201402

Recently, the flame regimes of ignition and flame propagation as well as transitions

between different flame regimes of n-heptane-air mixtures in a one-dimensional, cylindrical,

and spark assisted HCCI engine were numerically modeled with a comprehensively reduced

kinetic mechanism (Ju et al. 2010). It was found that the initial mixture temperature

and pressure had a dramatic impact on flame dynamics. As shown in Fig. 10, a spark

ignition at the center of a cylindrical chamber of lean (ϕ = 0.4) n-heptane-air mixture

at 700 K and 20 atm, led to different propagating ignition fronts and flame fronts. There

exist at least six different combustion regimes, an initial single high temperature flame

propagation regime, a coupled low temperature (cool flame) and high temperature double-

flame regime, a decoupled low temperature cool flame and high temperature double-flame

regime, a low temperature ignition regime, a single high temperature flame regime, and

a hot ignition regime. The results showed that the low temperature cool flame and high

temperature flames had distinct kinetic and transport properties as well as flame speeds,

and were strongly influenced by the low temperature chemistry. Furthermore, it was found

that due to the NTC effect, the critical temperature gradient for ignition and acoustic wave

coupling became singular in the NTC region. These results demonstrate that both the NTC

effect and the acoustic wave propagation in a closed reactor have a dramatic impact on the

0 0.005 0.010 0.015

1.0

0.8

0.6

0.4

0.2

0

Time/s

Low temperature ignition (LTI)

Cool flame dominateddouble flame (decoupled)

High temperature flamedominated double flame (coupled)L

ocations

of flam

e a

nd ignitio

n fro

nts

/cm

Transition

Hot ignition

Single high temperatureflame front

Fig. 10

The time history of propagating flame and ignition fronts after spark ignition in a cylindrical

chamber of lean (ϕ = 0.4) n-heptane-air mixture at 700 K and 20 atm (Ju et al. 2010)

Ju Yiguang : Recent progress and challenges in fundamental combustion research 19

ignition front and acoustic interaction. More recently, by introducing a cold spot (Dai et

al. 2014), different autoignition modes caused by the positive temperature gradient were

identified for n-heptane/air mixture. With the increase of the positive temperature gradient

of the cool spot, supersonic deflagration, detonation, shock-induced detonation, and shock-

induced supersonic deflagration were sequentially observed (Fig. 11). A regime map in

terms of the normalized temperature gradient and acoustic-to-excitation time scale ratio

was obtained for different autoignition modes.

To further understand the effect of fuel stratification on low temperature combustion

with different molecular structures, the transitions between ignition and flames in stratified

n-heptane and toluene mixtures were numerically modeled in a one-dimensional constant

volume chamber (Sun et al. 2014) (Fig. 11(b)). It is found that the low temperature

chemistry (LTC) and fuel stratification of n-heptane led to the formation of four different

combustion wave fronts: A low temperature ignition (LTI) front followed by a high temper-

ature ignition (HTI) front, a premixed flame front, and a diffusion flame front. Moreover,

it was shown that the propagation of the fast LTI and HTI wave fronts led to shock-like

pressure wave propagation and caused strong oscillation of the subsequently formed pre-

mixed and diffusion flames. On the other hand, for the toluene mixture, due to the lack of

0 10 20 30 40 50 60 70

0 10000 20000 30000 40000

x0/

2 n

mx

0/

5 n

m

dT�dx(k.m-1↽

ζ

supers

onic

fla

me

supers

onic

fla

me

no m

ore

ignitio

n a

dvance

for

cool sp

ot

I

deto

nation

II

II-1

III-1

II-2

deto

nation

III

monotonicT in kemel

monotonicT in kemel

non-monotonicT in kemel

shock+

detonation

III

shock+

detonation

III

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

Time/ms

Onset of ignitiondriven oscillation

Premixed flame branch

Diffusion flame branch

Onset of HT1

Onset of LT1

n-heptane/air

Location o

f acim

um

heat

rele

ase

/cm 5

4

3

2

1

0

ab

Fig. 11

(a) The effect of thermal stratification on autoignition modes at different temperature gra-

dients and cool spot sizes with T0 = 900 K in an n-heptane/air mixture (Dai et al. 2014),

(b) The effect of fuel stratification on different ignition and flame regimes and flame insta-

bility (Sun WQ et al. 2014)

20 44 : 201402

LTC, only a high temperature ignition front and a premixed flame front are observed. The

shockwave formation dynamics was analyzed by using the simplified Burgers equation. The

results revealed that the rich LTC reactivity of transportation fuels together with thermal

and fuel stratification is one of major causes of engine knocking. However, due to the limi-

tation of computation cost, multi-dimensional modeling of flame regimes involving LTC and

thermal and fuel stratifications remains still lacking.

2.2.2 Flame regimes of plasma assisted combustion

Non-equilibrium plasma is another method to enhance ultra-lean combustion and flame

stabilization. Plasma assisted combustion (PAC) has a great potential to enhance com-

bustion performance in pulsed detonation engines, gas turbine engines, scramjets, internal

combustion engines, and other lean burn combustion systems. Over the last decade, the

applications of plasma to improve the performance of combustion have drawn considerable

attention for its great potential to enhance combustion in internal combustion engines, gas

turbines, pulsed detonation engines, scramjet engines, and lean burn combustion systems

(Pilla et al. 2006, Ombrello et al. 2010a, 2010b, Sun et al. 2012, 2013, Starikovskaia 2006,

Starikovskiy 2013, Singleto et al. 2011, Matsubara et al. 2011, Leonov et al. 2010, Little et

al. 2010, Lacoste et al. 2013). Recently, through the collaboration between Princeton Uni-

versity and Imagineering Inc. in Japan, microwave plasma assisted ignition was investigated

to improve the ignition performance in single cylinder internal combustion engines (Ikeda

et al. 2009, Lefkowitz et al. 2012) (Fig. 12). Microwave was used to increase the electron

energy and ignition volume during the conventional spark ignition. It was found that the

plasma assisted spark plug produced a larger ignition kernel and led to an overall faster

ignition/flame with about 750 mJ energy addition. The experimental results showed that

the lean burn limit was extended by 20%∼30% in terms of the air/fuel (A/F) ratio by using

the microwave discharge, according to the coefficient of variation of the indicated mean effec-

tive pressure (COVimep) (Fig. 12(b)). More recently, ignition enhancement by nanosecond

pulsed surface dielectric barrier discharge was also demonstrated in a rapid compression

machine (Stepanyan et al. 2013). The results also showed that with the presence of dis-

charge, the ignition delays decreased significantly for methane and n-butane mixtures in the

pressure range of 7.5 to 15 atm. Knocking reduction was also reported in knocking-sensitive

regimes.

Towards the development of advanced gas turbines, plasma is also used as a new tech-

Ju Yiguang : Recent progress and challenges in fundamental combustion research 21

12 16 20 24 28

A/F Ratio

50

40

30

20

10

0

CO

Vim

ep/%

No MW, Timing 1MW, Timing 1No MW, Timing 2MW, Timing 2MW, Timing 3Stable Operating Limit

Lean limits

a b

Fig. 12

(a) direct photograph of plasma assisted 34 cc Fuji engine test setup, and (b) the comparison

of limits of stable engine operating conditions with and without microwave (MW) discharge

(Lefkowitz et al. 2012).

nology to increase energy efficiency, reduce emissions, and improve stability of flames in

the combustion chamber. Serbin et al. (2011) showed that a gas turbine combustor with

piloted flame stabilization by non-equilibrium plasma can provide better performance, wider

turndown ratios, and lower emissions of carbon and nitrogen oxides. Moeck et al. (2013)

studied the effect of nanosecond pulsed discharge on combustion instabilities. It was shown

that the discharge had a strong effect on the pressure pulsations associated with thermo-

acoustic dynamics. With the consumption of less than one percent of the total power of

the flame, the nanosecond discharge can significantly reduce the oscillation amplitude of the

acoustic pressure. Recently, Lefkowitz et al. (2013) extended the study of high-frequency

nanosecond pulsed discharge to pulsed detonation engines (PDEs). As shown in Fig. 13(a),

by comparing the ignition delay times and the ignition kernel growth with different igniters,

it was found a significant decrease of the ignition time in the PDE for a variety of fuels and

equivalence ratios. As shown in Fig. 13(b), with the same amount of total energy input,

higher frequency discharges showed dramatic benefits to initiate flame propagation. Fig-

ure 13(c) shows the difference between the nanosecond pulsed plasma igniter and multiple

spark discharge (MSD) igniter. With roughly the same amount of total energy consumption,

the MSD ignition kernel eventually extinguishes, while the plasma ignited kernel goes on

to become a self-propagating flame. In addition, both leaner and richer ignition could be

achieved with the help of the nanosecond pulsed igniter.

22 44 : 201402

a b

c

ns pulser,40 kHz

ns pulser,1 kHz

ns pulser,MSD energy

MSD

Fig. 13

(a) PDE engine facility at the Air Force Research Lab at Wright-Patterson Air Force Base,

(b) Schlieren imaging of nanosecond pulsed discharge igniter in CH4/air mixture, Φ = 1,

(c) Schlieren imaging of nanosecond pulsed discharge igniter in CH4/air mixture, Φ = 0.8

(Lefkowitz et al. 2013)

However, the physical and chemical kinetic processes in plasma assisted combustion in-

volve strong couplings (Fig. 14) between combustion kinetics and the active radicals, excited

species, ions/electrons, and other intermediate species produced specifically by the plasma.

In recent years, extensive efforts have been made to develop new combustion techniques

using non-equilibrium plasma, as well as new experimental platforms, advanced diagnos-

tic methods, kinetic models, and quantitative experimental databases to understand the

underlying interaction between the plasma and combustion mechanisms.

In order to fundamentally understand the physics of plasma enhanced ignition and flame

stability, a non-equilibrium in situ plasma discharge integrated with a counterflow flame

was developed (Sun et al. 2011, 2013). The relationship between OH emission intensity

as well as reaction zone peak temperature and XF is shown in Fig. 15 with oxygen mole

fraction at (a) XO = 0.34 and (b) 0.62, respectively. The temperatures of the reaction zone

were measured by the Rayleigh scattering method. The solid and open symbols represent

the results obtained, respectively, with increasing and decreasing of XF . Figure 15(a)

shows the typical ignition to extinction S-curve which is the fundamental phenomena of

combustion. It is interesting to note that if the oxygen concentration was increased to 0.62,

the ignition and extinction limits merged atXF = 0.09, resulting in a monotonic ignition and

extinction S-curve Fig. 15(b). The temperature measurements also demonstrated a similar

Ju Yiguang : Recent progress and challenges in fundamental combustion research 23

Temperature increase

Plasma discharge

Ions/electrons

Ionic wind

Flow mixing

Fuel fragments

Transport enhancementKinetic enhancementThermal enhancement

Radicals

Excited species

O2+

O,NO,O3

N2*(A↪B↪C)O2(a1Dg)

H2

CH4

C2H2

C2H4

Fig. 14

Possible enhancement pathways of plasma on combustion systems (Sun and Ju 2013)

0.1 0.2 0.3 0.4

10

8

6

4

2

0

1.6

1.4

1.2

1.0

0.8

Fuel mole fraction (XF)

Loca

l m

axim

um

tem

per

atu

re/10

3 K

1.6

1.4

1.2

1.0

0.8

Loca

l m

axim

um

tem

per

atu

re/10

3 K

OH

* e

mis

sion inte

nsi

ty/10

3 a

.u.

OH emissionTemperature

OH emissionTemperature

Extinction

Ignition

XO =0.34 XO =0.6210

8

6

4

2

0

OH

* e

mis

sion inte

nsi

ty/10

3 a

.u.

0.1 0.2 0.3 0.4

Fuel mole fraction (XF)

a b

Fig. 15

Effect of plasma discharge on ignition to extinction curve at different plasma repetition rate

represented by the dependence of OHemission intensity at different oxygen concentrations

(a) XO = 0.34, (b) XO = 0.62, (solid square symbols: increasing XF , open square symbols:

decreasing XF ) (Sun et al. 2013)

monotonic increase of the local maximum temperatures. The monotonic and fully stretched

ignition and extinction S-curve could be explained by the fact that the plasma generated

reactive species caused a transition of flame stabilization mode from the extinction-controlled

to the ignition-controlled modes. This means that the extinction limit did not exist by

the plasma/combustion chemistry interaction, thus the chemistry of plasma assisted flame

24 44 : 201402

stabilization was fully dictated by the enhancement of ignition limit via radicals production

by plasma. Similar experiments of ignition of large hydrocarbons were also conducted (Sun

et al. 2014). It was found that plasma can activate low temperature chemistry of dimethyl

ether even at low pressure.

In order to understand the elementary kinetic process of plasma-assisted combustion,

advanced species diagnostics have been carried to quantify the effect of plasma generated

radicals and intermediate species such as O, N2(*), O3, O2(1aΔg), and NOx on ignition and

flame propagation. Uddi et al. (2009) and Sun et al. (2010) measured the atomic O concen-

tration in nanosecond pulsed discharges using the Two Photon Laser Induced Fluorescence

(TALIF) technique, respectively, in a flow reactor and in a counterflow diffusion flame. It

was found that the discharge can generate significant amounts of atomic O and the consump-

tion of atomic O by fuel was very fast. As shown in Fig. 16, the rapid reaction between

fuel and atomic O initiated the low temperature combustion chemistry and produced heat

release. To further understand the formation pathways of atomic oxygen production by

excited N2(*) (known as N2(A), N2(B) and N2(C)), the absolute number density of N2(A)

was measured by Cavity Ring Down Spectroscopy (CRDS) and the densities of N2(B) and

N2(C) were measured by Optical Emission Spectroscopy (OES) in a nanosecond pulsed dis-

charge at atmospheric pressure in air (Stancu et al. 2009). The results show that in air

plasoxygen collisions with N2(B) and N2(C) are major reaction pathways to product atomic

oxygen in addition to direct electron impact oxygen dissociation.

0 1 2 3 4

6

5

4

3

2

1

0

Time/10-3 s

O a

tom

mole

fra

ction/10

-5 Air

Air-methane, Φ/10

Fig. 16

Atomic O mole fraction vs. time after a single high-voltage pulse in air and in a methane-air

mixture at P = 60 torr and Φ = 1.0 (Uddi et al. 2009)

Ju Yiguang : Recent progress and challenges in fundamental combustion research 25

-50 -25 0 25 50 75 100

-50 -25 0 25 50 75 100

Time/ns

1017

1016

1015

1.21.00.80.60.40.2

0

Densi

ty/cm

-3

Densi

ty/10

18 cm

-3

N2(B)N2(C)N2(A)

dischargepluse

TALIFCalculated

Fig. 17

Measurements of number density of excited nitrogen and atomic oxygen in air plasma

(Stancu et al. 2009)

The effects of O3, O2(1aΔg), and NOx on plasma assisted combustion was studied by

Ju and coworkers. By using Integrated Cavity Output Spectroscopy (ICOS) (Williams et

al. 2004, Ombrello et al. 2010b) measured the absolute concentrations of excited oxygen

(O2(1aΔg)) in a microwave generated plasma by using the (1,0) band of the 1

bΣ+g − 1

aΔg

Noxon system. Several thousand ppm level of O2(1aΔg) was reported and its effect on flame

propagation was then investigated. The effect of O3 and O2(1aΔg) on flame propagation speed

was studied in a lifted flame (Ombrello et al. 2010a, 2010b). The experiments demonstrated

that both O3 and O2(1aΔg) increased the flame propagation speed by a few percentage. The

effects of NOx production by plasma on ignition and flame extinction were also studied

by Ombrello et al. (2006, 2008). The results showed that NOx production by plasma

also reduced the ignition temperature and extended the extinction limits of hydrogen and

methane-air mixtures.

The above studies significantly advanced the understanding of the elementary processes

of plasma chemistry. However, the experimental diagnostics was limited to small species

and radicals at high temperature. In order to understand the kinetic processes of plasma

activated low temperature combustion, in situ diagnostics of intermediate species produced

by plasma assisted fuel oxidation is necessary. Recently, in situ measurements by mid-IR

laser absorption spectroscopy of C2H4/Ar pyrolysis and C2H4/O2/Ar oxidation activated

26 44 : 201402

by a nanosecond repetitively pulsed plasma have been conducted in a low temperature flow

reactor (below 500 K) for both continuous discharge mode and burst mode with 150 pulses

(Lefkowitz et al. 2014). As seen in the species time history in Fig. 18(a), it was found

plasma activated C2H4 oxidation has three fuel consumption pathways, a plasma activated

low temperature fuel oxidation pathway via RO2 chemistry; a direct fragmentation pathway

via collisional dissociation by electrons, ions, and electronically excited molecules; and a

high temperature oxidation pathway by plasma generated radicals. It was also shown that

the plasma activated low temperature oxidation pathway is dominant and leads to a large

amount of formaldehyde formation with less acetylene and negligible large hydrocarbon

molecules as compared to the pyrolysis experiment. However, simultaneous diagnostics of

multiple species at higher pressure and temperature become very challenging due the non-

uniformity of plasma as well as the pressure and temperature broadening of the absorption

lines. In addition, measurements of OH and RO2 related species at low temperature plasma

environment are still difficult. This information is necessary to understand the elementary

process of plasma assisted combustion and to develop validated kinetic mechanisms.

0 0.002 0.004 0.006 0.008 0.010

104

103

102

101

100

Time/s

Mole

fra

ction C

2H

2/ppm

C2H2

CH4

H2OTemperature

C2H2

CH4

H2OTemperature

Fig. 18

Measured (symbols) and modeled (lines) time history of C2H2, CH4, H2O, and temperature

after 150 pulses at 30 kHz repetition rate for a mixture of 6.25/18.75/93.75 C2H4/O2/Ar

(Lefkowitz et al. 2014)

2.2.3 Structure and Dynamics of Cool flames

Cool flame is a key process for engine knocking and has been a major subject of com-

Ju Yiguang : Recent progress and challenges in fundamental combustion research 27

bustion for more than a century (Perkin 1882, Curran et al. 1998, Mehl 2011). Several ex-

perimental approaches using a heated burner, heated flow reactor, and jet-stirred reactor for

the study of cool flames were developed (Lignola 1987, Dooley et al. 2010, 2012, Jahangirian

et al. 2010). Recently by using a heated microchannel, cool flames were also observed due

to the constrained reaction progress by the wall heat loss (Oshibe et al. 2010). However, all

the above cool flame experiments require external heating and wall heat losses, rendering

complicated thermal and chemistry coupling with the wall. As a result, detailed and funda-

mental understanding of cool flame behaviors has not been well established. Moreover, all

of the previous cool flame studies were focused on homogeneous fuel/air pre-mixtures. In-

terestingly, a recent experiment of droplet combustion in microgravity has shown that a cool

flame might be established in a diffusive system, hypothesizing the existence of cool diffusion

flame after radiation-controlled extinction (Nayagam et al. 2012) with the aid of numerical

simulation (Farouk et al. 2014). Although, the numerical simulation was able to capture the

global trend of droplet flame extinction and subsequent formation of cool diffusion flame,

detailed structure of cool diffusion flames has not been revealed yet. As such, cool flame

dynamics remain mysterious and the fidelity of cool flame chemistry remains unknown.

One of the main challenges to establish a self-sustaining cool flame is that at low

temperature the cool flame induction chemistry for the radical branching is too slow. On

the other hand, at higher temperature the radical branching becomes so fast that cool flame

will transit to a hot flame rapidly (Zhao et al. 2013). As a result, a cool flame is not

stable without introducing a heat loss to the wall. Therefore, the only way to create a

self-sustaining cool flame is to accelerate the chain-branching process at low temperature.

Recently, a novel method to establish self-sustaining cool diffusion flames with well-

defined boundary conditions has been experimentally demonstrated by using ozone into the

oxidizer stream in the counterflow configuration (Won et al. 2014) (Fig. 19). It was found

that the formation of atomic oxygen via the decomposition of ozone dramatically shortens

the induction timescale of low temperature chemistry, extending the flammable region of cool

flames, and enables the establishment of self-sustaining cool flames at pressure and timescales

at which normal cool flames may not be observable. This new method, for the first time,

provided an opportunity to study cool flame dynamics, structure, and chemistry simultane-

ously in a well-known flame geometry. Extinction limits of n-heptane/oyxgen cool diffusion

flames were measured. A cool diffusion flame diagram for four different flame regimes was

experimentally measured. Numerical simulations showed that the extinction limits of cool

diffusion flames were strongly governed by species transport and low temperature chemistry

28 44 : 201402

Cool diffusion flame Hot diffusion flame

a b

Fig. 19

Direct photos of n-heptane/oxygen cool diffusion flame (a) and hot diffusion flame (b) flames,

observed at the identical flow condition, fuel mole fraction of 0.07 and strain rate of 100 s−1

(Won et al. 2014).

activated by ozone decomposition. The structure of cool diffusion flame was further investi-

gated by measuring the temperature and species distributions with a micro-probe sampling

technique. It was found that the model over-predicts the rate of n-heptane oxidation, the

heat release rate, and the flame temperature. Measurements of intermediate species, such

as CH2O, acetaldehyde, C2H4, and CH4 indicated that the model over-predicted the QOOH

thermal decomposition reactions to form olefins, resulting in substantial over-estimation of

C2H4, and CH4 concentrations. The new experimental method of cool flame provides an

unprecedented platform to understand cool flame and low temperature chemistry.

In future research, if a self-sustaining premixed cool flame can also be established by

a similar method and appropriate diagnostic methods can be developed, this method will

bridge our knowledge gap of cool flames for more than one century. At high pressure, the

cool flame chemistry will be enhanced. Quantitative study of cool flames may provide a key

solution to solve engine knocking and develop new engine technologies.

2.3 Alternative fuels and surrogate fuel modeling

Due to the increasing concern of energy sustainability, another rapidly growing re-

search area in combustion is alternative fuels. Methodologies for alternative transportation

fuel production, using a range of fossil energy sources such as coal and natural gas and

renewable resources such as animal fats, plant oils, ligno-cellulosic biomass materials (Chu

et al. 2012, Huber et al. 2006, Khodakov et al. 2007) are increasing. As shown in Table

1, these alternative fuels have different molecular structures. Moreover, many synthetic fu-

els produced from the catalytic hydrogenation processes do not generally contain aromatic

components and are mainly composed of branched alkanes (Rye et al. 2012, Blakey et al.

Ju Yiguang : Recent progress and challenges in fundamental combustion research 29

2011, Balster et al. 2008) and often are blended together with conventional transportation

fuels. Recently, gas turbine fuel certification standards have been modified to encompass

blending of up to 50% bio-derived synthetic fuel components from hydroprocessed esters

and fatty acids (e.g. algae, camelina or jatropha, or from animal fats, i.e. tallow) or Fischer

Tropsch hydroprocessed synthetic paraffinic kerosine (F-T-SPK, from coal, natural gas or

biomass) (Blakey et al. 2011, Corporan et al. 2011). The introduction of alternative fuels

and the fuel blendings significantly increase the complexity of fuel screening and modeling.

Therefore, there is an urgent need to create a generic methodology to develop surrogate fuel

mixtures to screen alternative fuels and to evaluate the combustion and emission properties

of alternative and blended fuels.

Many previous studies have attempted to produce surrogate fuels to emulate real and

alternative fuel combustion kinetics and/or physical properties (Wohlwend et al. 2001).

These approaches emphasize the need to develop surrogates that describe both the impor-

tant physical and chemical kinetic related properties of a real fuel. For physical properties,

real fuel distillation curve and phase behavior were noted as key properties to describe the

vaporization/injection/mixing processes of multiphase combustion. Other physical proper-

ties such as viscosity are also commonly recognized to be important to spray atomization

phenomena. The early works of Wood et al. (1989) and Schultz (1992) proposed surrogates

formulated with the intention of emulating both chemical and physical properties of the real

fuels to reproduce distillation properties by using twelve or more individual components.

Violi et al. (2002) proposed a seven component surrogate mixture in order to emulate the

distillation curve, flash point, chemical class composition, sooting tendency, heat of combus-

tion, flammability limits, and pool burning regression rate of a generic JP-8 fuel. However,

as is frequently found, due to the large composition matrix no comprehensive experimental

verification of the surrogate fuel property to a target real fuel property was presented (Ranzi

et al. 2001, Cooke et al. 2005).

Recently, in order to develop compact and comprehensively validated surrogate fuel

mixtures, supported by the AFOSR multi-university research initiative (MURI) and led

by Princeton University, a generic method to construct surrogate component mixtures to

emulate real and alternative fuel combustion properties was proposed and validated (Dooley

et al. 2010, 2012) using jet fuels. The key point of this approach is to select surrogate

component fuels by emulating four “combustion property targets” of the alternative and

real fuels of interest: 1) Hydrogen to Carbon molar ratio (H/C ratio), 2) Derived Cetane

Number (DCN) from Ignition Quality Tester (IQT), 3) average molecular weight, and 4)

30 44 : 201402

Threshold Sooting Index (TSI). The first generation three-component surrogate mixture

of n-dodecane/iso-octane/toluene and the second generation four-component of surrogate

mixture of n-dodecane/iso-octane/1,3,5-trimethylbenzene/n-propylbenzene for Jet-A fuel

were formulated and tested. The first generation surrogate mimics the H/C ratio, DCN, and

TSI target but did not match the mean molecular weight. However, the second generation

surrogate matches all four surrogate targets. Detailed information of the surrogate mixtures

and their combustion property targets is listed in Table 2. Both surrogate mixtures were

examined by using a variable pressure flow reactor to quantify the fuel reactivity and species

profiles at 12.5 atm and 500∼1000 K, a shock tube for ignition delay time at 667∼1223 K

at 20 atm, a rapid compression machine at 645∼714 K at compressed pressures of 21.7 atm,

and a counterflow flame for flame speeds and extinction limit at atmospheric pressure.

Figures 20(a)–20(d) show the comparisons of the measured species profiles, ignition

delay time, diffusion flame extinction limits, and flame speeds for jet fuel POSF 4658 and its

1st generation and 2nd generation surrogates. It is seen that the low temperature oxidation

(near 600 K) of POSF 4658 is mimiced well by both the first and the second generation sur-

rogates. Although there is a small shift of the temperature window in the high temperature

oxiation zone (800 K), the overal CO, H2O, and CO2 concentrations are well reproduced.

It is interesting to note that both the 1st and the 2nd generation surrogates reproduce the

ignition delay very well. This implies that the difference in mean molecular weight does not

Table 2 Combustion property targets for the first and second generation surrogate compo-

nents, kerosene fuels, Jet-A POSF 4658 and proposed surrogates. 1st Generation POSF 4658

surrogate is n-decane/iso-octane/toluene 42.7/33.0/24.3 mole %, 2nd Generation POSF 4658

surrogate is n-dodecane/iso-octane/1,3,5 trimethylbenzene/n-propylbenzene 40.41/29.48/-

7.28/22.83 mole % (Dooley et al. 2013).

Fuel DCN H/C MW/g·mol−1 TSI‡

n-dodecane ∼78 2.16 170.3 7‡

iso-octane ∼17 2.25 114.2 6.8‡

1,3,5 trimethylbenzene 21.8∗ 1.33 120.2 62‡

n-propylbenzene 28.2∗ 1.33 120.2 53‡

Kerosene fuel range 30–60 1.84–2.07 N/A 15–26

Jet-A POSF 4658 47.1 1.96 142±20 21.4

1st Generation POSF 4658 surrogate 47.4 2.01 120.7 14.1

2nd Generation POSF 4658 surrogate 48.5 1.95 138.7 20.4

Ju Yiguang : Recent progress and challenges in fundamental combustion research 31

500 600 700 800 900 1000

5

4

3

2

1

Temperature/K

Fuel mass fraction Yf Equivalence ratio, φ

Lam

inar

flam

e sp

eed/cm

. s-

1

Extinct

ion s

train

rate

aE/s-

1

Temperature/K

1000K/T

Lgnitio

n d

elay t

ime,

τ/ms

Spec

ies

conce

ntr

ation/10

3 p

pm

POSF 4658

2nd Gen. surrogate

1st Gen. surrogate

O2 CO2 H2OCO

0.8

1200 1000 800 600

1.0 1.2 1.4 1.6

105

104

103

102

40

ST RCM

2nd Gen. POSF 4658 surrogate

1st Gen. POSF 4658 surrogate

POSF 4658

JETA POSF 4658 3 comp. surrogate4 comp. surrogate

0.2 0.3 0.4 0.5

400

300

200

100

00.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

90

80

70

60

50

40

30

Tu=470 K

Tu=400 K

Jet-A1st Gen2nd Gen

ba

dc

Fig. 20

(a) Flow reactor oxidation data for conditions of 12.5 atm, 0.3% carbon, ϕ = 1.0 and t =

1.8 s, for POSF 4658, 1st generation POSF 4658 and 2nd generation POSF 4658 surrogate.

(Dooly et al. 2012), (b) Ignition delay times, ϕ = 1.0 in air at ∼20 atm for POSF 4658,

1st generation POSF 4658 surrogate and 2nd generation POSF 4658 surrogate (Dooley et

al. 2012), (c) Comparison of diffusion flame extinction limits for POSF 4658, 1st generation

POSF 4658 surrogate and 2nd generation POSF 4658 surrogate, (d) Comparison of flame

speeds for POSF 4658, 1st generation POSF 4658 surrogate and 2nd generation POSF 4658

surrogate. (Dooley et al. 2012)

affect significantly the surrogate fuel reactivity. Similar observation is seen for the laminar

flame speed. Once again, the laminar flame speed is insenstive to the molecular size because

the reactivity of large alkanes is similar. However, the measured diffusion extinciton limits

show that the mean molecular weight has a consideral influence on diffusion flame extinction.

This is because the diffusion transport of fuel molecules affects the extinction limit of diffu-

32 44 : 201402

sion flames more than that of premixed flames. The above comprehensive validation shows

that the four metric physical and combustion property targets are successful to construct a

surrogate fuel mixture to mimic real fuel properties.

Recently, this method is further extended to a real F-T synthetic jet fuel “S-8” de-

rived from natural gas by Syntroleum Inc. and a single component alcohol derived jet fuel,

2,6,10-trimethyl dodecane (TMD) from Amyris Inc. These fuels contain no aromatic fraction

and large percentages of mono, di- and trimethylated, weakly branched alkanes. A simple

surrogate fuel mixture composed of only n-dodecane and iso-octane was formulated and

experimentally shown to closely emulate the combustion kinetic behavior of the synthetic

S-8 fuel. For the single molecule fuel TMD, the derived cetane number (DCN) (59.1) and

Hydrogen/Carbon ratio (2.133) are very close to those of S-8 and a surrogate mixture com-

posed of n-dodecane/iso-octane (DCN:58.9 and H/C:2.19) was constructed. Identical high

temperature global kinetic reactivities were observed in all experiments. However at tem-

peratures below ∼870 K, the S-8 surrogate mixture had ignition delay times approximately

a factor of two faster than that of TMD. A chemical functional group analysis identified

that the methylene (CH2) to methyl (CH3) ratio globally correlated the low temperature

alkylperoxy radical reactivity for these large paraffinic fuels. This result was further con-

firmed experimentally by comparing combustion targets using a surrogate fuel mixture of

n-hexadecane (n-cetane) and iso-cetane that shares the same methylene-to-methyl ratio as

TMD in addition to the same DCN and H/C. A kinetic modeling analysis on the model fuel

revealed that the formation of alkylhydroperoxy radicals (QOOH) to be strongly influenced

by the absence or presence of the methyl and methylene functional groups in the fuel chemi-

cal structure. These experimental observations and analyses suggest that for paraffinic based

fuels with high DCN values, in constructing a surrogate fuel mixture it is more appropriately

to include the CH2 to CH3 ratio as an additional property because DCN alone fails to fully

distinguish the relative reaction characteristics of low temperature kinetic phenomena.

To identify an alternative combustion properties for surrogate fuel modeling and to

understand the effect of fuel transport property on flame extinction, the diffusion flame

extinction limits of various fuels with different functional groups (Table 1) were measured

and compared in counterflow diffusion flames (Won et al. 2010, 2011, 2012). Figure 21

shows the comparison of the measured extinction strain rates for all tested hydrocarbon fuels

by introducing a new parameter, the transport weighted enthalpy (TWE), [fuel] ×ΔHc ×(MWfuel/MWnitrogen)

−1/2. TWE is a product of fuel mole fraction [fuel] and the enthalpy of

combustion ΔHc, normalized by the square root of the fuel molecular weight. The diffusive

Ju Yiguang : Recent progress and challenges in fundamental combustion research 33

0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6

104

103

102

101

1000/T [1/K]

Lgnitio

n d

ela

y t

ime/ms

Trimethyi dodecaneS-8 nC12/iC8 Surrogate FuelnC16/iC16 Model Fuel

Fig. 21

Comparison of measured shock tube ignition delay times of trimethyl dodecane, the n-

dodecane/iso-octane (51.9/48.1 S-8) surrogate and the n-cetane/iso-cetane (45.9/54.1) sur-

rogate mixtures at 20 atm (Won et al. 2013)

parameter is non-dimensionalized by employing the ratio of the molecular weight of the fuel

MWfuel to the molecular weight of nitrogen (dilution gas) MWnitrogen. Therefore, TWE is

the ratio of fuel enthalpy scaled by the fuel diffusivity. Using the TWE, the effect of transport

and enthalpy on the fuel extinction limits can be removed so that a direct comparison of high

temperature fuel reactivity can be achieved. It is seen that the extinction limits of all alkanes

fall into one line as a function of TWE. Therefore, they have the same high temperature

reactivity. This is why the fuel reactivity and flame speeds of n-alkanes are insensitive to

the mean molecular weight but the diffusion extinction limit is sensitive (Fig. 20). It is

also seen from Fig. 22 that compared to n-alkanes, iso-alkanes have lower reactivity due

to their reduced chemical kinetic potential. Moreover, the reactivities of aromatic fuels are

very different. Among those, n-propyl-benzene and 1,3,5-trimethyl benzene show the highest

and lowest reactivity due to the longest alkyl chain in n-propyl-benzene and the symmetry

of methyl side chains of 1,3,5-trimethyl benzene. Note that the large reactivity difference

between 1,3,5-trimethyl benzene and n-propyl-benzene while having the same molecular

weight and H/C ratio make them the best choice for surrogate fuel components because the

fuel reactivity can be adjusted independently from the molecular weight and the H/C in the

four surrogate mixture targets.

Figure 22 shows that an index for the fuel reactivity, the radical index (Ri), can be

derived by using the measured extinction limits and the TWE (Won et al. 2012). Figure 23

shows the derived radical index relative to n-alkanes and the universal correlation of extinc-

34 44 : 201402

0.5 1.0 1.5 2.0 2.5 3.0

500

400

300

200

100

0

[Fuel]ΤΔHc(MWfuel/MWnitrogen)-1/2[cal/cm3]

Extinction s

train

rate

aE/s-

1

n-decaneiso-octane1,2,4-trimethylbenzene

n-nonanen-propylbenzene1,3,5-trimethylbenzene

n-heptanetoluene

n-alkanes

iso-alkane

aromatics

Tf/500 K and To/300 K

Fig. 22

Extinction strain rates as a function of transport weighted enthalpy for all tested fuels; ΔHc,

enthalpy of formation, MW , molecular weight (Won et al. 2012)

Fuel

n-alkane

iso-octane

toluene

n-propylbenzene

n-decanen-nonanen-heptaneiso-octanen-propylbenzenetoluene1,2,4-trimethylbenzene1,3,5-trimethylbenzene

1,2,4-trimethylbenzene

1,3,5-trimethylbenzene

Ri

1

070

056

067

044

036 RiΤ[Fuel]ΤΔHcΤ(MWfuel/MWnitrogen)-1/2[cal/cm3]

0.5 1.0 1.5 2.0

500

400

300

200

100

0Extinct

ion s

train

rate

aE/s-

1

R2=0.97

Tf/500 K and To/300 K

a b

Fig. 23

Left: Derived radical index (Ri) for different fuels; Right: Universal correlation of extinction

strain rates of all tested fuels in terms of Ri × [fuel] × ΔHc × (MWfuel/MWnitrogen)−1/2;

line: linear fit of all experimental data (Won et al. 2012, 2013)

tion limits of all tested fuels in terms of Ri×TWE. The radical index shows that the fuel

reactivities (producing radicals) are very different from n-alkanes to aromatics due to the

change of molecular structure. Moreover, the alkyl chain position and length of aromatics

have a significant impact on the fuel reaction. The good correlation between the extinction

limits and the product of Ri×TWE demonstrates that radical index and the TWE are use-

ful parameters to rank the fuel reactivity by removing the effect of molecular size and the

difference in fuel heating value.

Ju Yiguang : Recent progress and challenges in fundamental combustion research 35

0.5 1.0 1.5 2.0 2.5

450

350

250

150

50

Extinct

ion s

train

rate

aE/s-

1

Transport-weighted enthalpy/[cal/cm3][Fuel]ΤΔHcΤ(MWfuel/MWnitrogen)-1/2

Transport-weighted enthalpy/[cal/cm3]

Extinction of diffusion flame in counterflow configurationTf/500 K and Tair/300 K @1 atm

Fuel Ri

JP8POSF

SHELL SPK

HRJ Camelina

HRJ Tallow

SASOL IPK

078

085

082

08

076

Ri=

1 for n-alka

ne

Ri=

0.7 fo

r iso-oc

tane

JP8POSF 6169

SHELL SPK POSF 5729

HRJ Camelina POSF 7720

HRJ Tallow POSF 6308

SASOL IPK POSF 7629

n-alkane

iso-octane

0.5 1.0 1.5 2.0

500

400

300

200

100

0

Extinct

ion s

train

rate

aE/s-

1

Methy1formate

Methy1propanoate

Tf/500 K, Tox/298 K

Methy1 FormateMethy1 EthanoateMethy1 PropanoateMethy1 ButanoateMethy1 PentanoateMethy1 HexanoateMethy1 OctanoateMethy1 Decanoate

a b

Fig. 24

(a) Reactivity ranking of synthetic jet fuels using transport weighted enthalpy (Won et al.

2013), (b) Reactivity ranking of methyl esters (biodiesel) using transport weighted enthalpy

(Dievart et al. 2013)

The TWE and the radical index were also used to screen alternative jet fuels and

biodiesels. As shown in Fig. 23(a), the reactivities of alternative jet fuels produced from

various sources are slightly different from that of JP-8. In addition, Shell SPK and Sasol IPK

have the highest and lowest radical index, respectively. Figure 24(b) shows the comparison

of fuel reactivity of all methyl esters in biodiesel surrogates. It is seen that small methyl

esters have unique fuel reactivity, that is, the fuel reactivity does not linearly depend on

the alkyl chain length. However, for large methyl esters the high temperature reactivity is

similar. Therefore, kinetic studies for methyl esters should be focused on small methyl esters

and the large esters are similar to n-alkanes. As such, Fig. 24 shows that radical index is

a successful parameter which is sensitive enough to rank fuel reactivity. Future research

should address: (1). How will the physical properties of alternative fuels be modeled? (2).

How does the turbulent flow affect the validation of surrogate fuel model? (3). How can we

find an affordable surrogate mixture which can allow large scale engine tests, and (4). How

to develop a compact and validated detailed kinetic model for surrogate fuel mixtures.

2.4 Multiscale and dynamic adaptive chemistry modeling using re-

duced and detailed mechanism

To capture the physics of turbulence-chemistry interaction involving low temperature

chemistry and different flame regimes for real fuels, a large kinetic mechanism involves

hundreds of species and thousands of reactions is needed. For example, a detailed n-heptane

36 44 : 201402

mechanism can have 1034 species and 4236 reactions (Curran et al. 2002) and a recent jet

fuel surrogate model has more than two thousand species and 8000 reactions (Won et al.

2013). The large number of species and the stiffness of the combustion kinetics results in a

great challenge to combustion modeling (DOE report 2005). For a typical implicit method,

the computation time is proportional to the cubic of the species number. Moreover, as shown

in Fig. 1, the timescales of the elementary reactions and physical processes have a disparity

of more than 10 orders of magnitude. Even with the availability of petascale computation

capability, direct numerical simulations with such large kinetic mechanisms remain to be

difficult.

In last 30 years, many kinetic model reduction methods have been developed to improve

the computation efficiency. These approaches can be summarized in five different categories.

The first category is the methods to generate a pre-reduced mechanism by removing unim-

portant species and reactions using reaction rate and sensitivity analysis. These methods

include the sensitivity analysis and quasi-steady state assumption method (Peters et al.

1987, Ju et al. 1994). These methods compare the reaction rates of each species and re-

action, and select quasi-steady state species by eliminating the corresponding fast reaction.

Therefore, the QSS species related to the fast time-scales can be analytical solved from al-

gebraic equations without direct numerical integration. However, this approach requires a

lot of human experience to determine the quasi-steady sate (QSS) species and the partial

equilibrium. In addition, the sensitivity analysis method, if used, is very computational

intensive.

To improve the model reduction efficiency, a second category of methods use the fluxes

of species connecting the reactants to the products to eliminate species and reactions with

negligible fluxes. These path flux based approaches include the visualization method (Bend-

sten et al. 2001), Direct Relation Graph (DRG) (Lu et al. 2005) method, DRG with Error

Propagation (DRGEP) (Pepiot-Desjardins et al. 2008), and the multi-generation Path Flux

Analysis (PFA) (Sun et al. 2010) method and other variations. The path flux based method

is much more efficient than the reaction rate and sensitivity based method. The computa-

tion efficiency is further improved by conducting the model reduction to generate a reduce

mechanism on the fly and with error control. For example, the dynamic adaptive chemistry

(DAC) (Liang et al. 2009) and error controlled dynamic adaptive chemistry (EC-DAC)

(Gou et al. 2013) belong to this category. However, the flux based methods do not provide

the time scales of species and thus the assumption of QSS still requires human experience.

To resolve this problem, the third category of reduction methods are the time-scale

Ju Yiguang : Recent progress and challenges in fundamental combustion research 37

based dimension reduction methods. The intrinsic low-dimensional manifold (ILDM) method

(Maas et al. 1992), computational singular perturbation method (CSP) (Lam et al. 1994,

Lu et al. 2005), and the multi-timescale (MTS)/hybrid multi-timescale (HMTS) method

(Gou et al. 2010, 2013) belong to this category. Among those, the IDLM and HMTS meth-

ods are much more computationally efficient than the others. In these methods, the reduced

chemistry involving slow species after reduction have to be integrated by using an implicit

ordinary differential equation (ODE) solver or the HMTS/MTS method.

To further improve the computation efficiency of the chemistry integration, the fourth

category of methods using solution mapping and tabulation have been developed. The

in situ adaptive tabulation ISAT (Pope 1997) and the piecewise reusable implementation

of solution mapping (PRISM) method (Tonse et al. 1999) and the multi-zone methods

(Aceves et al. 2000, Jangi et al. 2013) are belong to this category. The ISAT method

uses pre-calculated and/or built on the fly tables to interpolate the solutions of the reduced

chemistry without direct integration. On the other hand, the PRISM method uses high

dimensional polynomials to estimate the solution The multi-zone methods use a nonlinear

extrapolation method to project the grouped solutions back to individual cells. Although

these approaches significantly improve the solution of a large mechanism, the uncertainty of

the solution tabulation and mapping is difficult to estimate. Moreover, as the mechanism

size increases, the computation efficiency decreases significantly. For the multi-zone method,

if the kinetic mechanism involves low temperature chemistry the backward solution mapping

can be very difficult or inaccurate due to the existence of many isomers which play different

roles in fuel oxidation.

To achieve the best efficiency for large kinetic mechanisms, many new algorithms in

combination with the above methods have also been developed. This combined approach is

the fifth category of model reduction methods. For example, the DAC-ISAT (Contino et al.

2011), DAC-DRG (Shi et al. 2010), MTS-DAC (Gou et al. 2013), and HMTS-PFA (Gou

et al. 2010), and the most recent HMTS/CO-DAC method (Sun et al. 2014) belong to this

category.

In this review, we will use a few examples to show the recent progress of model reduction

involving DRG, PFA, MTS, DAC, and CO-DAC as well as their combinations. Figure 25

shows the comparison of the multi-generation path flux analysis (PFA) method with the

DRG method for model reduction of stoichiometric n-decane/air mixture at 1 atm and

20 atm. The detailed high temperature n-decane mechanism has 121 species (Chaos et

al. 2007). The purpose is to show how different the predicted ignition delay time from

38 44 : 201402

50 60 70 80 90

10-2

10-3

10-3

10-4

Number of species in reduced mechnism

Ignitio

n d

ela

y t

ime/s

detail (121)DRGPFA

1 atm

20 atm

Fig. 25

Ignition delay time comparisons of detailed and reduced mechanisms with different sizes of

reduced mechanisms of n-decane (Sun et al. 2010)

the reduced mechanisms generated by these two methods are at the same reduced species

number. Figure 25 shows the relations between the number of species in the reduced

mechanisms of n-decane and the discrepancies of ignition delay time predicted by DRG and

PFA methods at 1200 K. It is seen that PFA improved the prediction accuracy significantly

in a broad range of species numbers especially when the number of species in the reduced

mechanism is less than 73. Therefore, the improvement of PFA in generating reduced

mechanism is due to the high accuracy in the flux calculation by including two-generations

of fluxes to all species. Therefore, the higher the order of the fluxes is used in PFA, the

better the accuracy of reduced mechanism will be. However, the higher accuracy will come

with the penalty of computation time in model reduction.

Efficient integration of reduced chemistry is also very important in model reduction. For

the same n-decane/air mixture and reduced kinetic mechanism of with 121 species and 866

reactions, Figure 26 shows the comparison of the temperature, major species, and radical

concentrations calculated by multi-timescale (MTS), hybrid multi-timescale (HMTS) (Gou

et al. 2010), and the ODE solver for homogeneous ignition of stoichiometric n-decane-air

mixture at initial pressure of P = 1 atm and initial temperature of T = 1400 K. It is seen

that both MTS and HMTS agree well with the VODE method for all predictions. However,

unlike the VODE method whose computation time depends on the cubic of species number,

the computation time of the MTS and HMTS is only proportional linearly to the species

Ju Yiguang : Recent progress and challenges in fundamental combustion research 39

0 1 2 3 4 5

105

100

10-5

10-10

10-15

10-20

Time/0.1 ms

Log10 m

ass

fra

ction

Temperature

Tem

pera

ture

/1000 K

CO2

C10H22

OH

VODEMTSHMTS

2.8

2.6

2.4

2.2

2.0

1.8

1.6

1.4

1.2

Fig. 26

Time histories of temperature and species mass fractions during ignition predicted by dif-

ferent integration schemes (Gou et al. 2010)

number. Therefore, the computation time can be increased significantly by using MTS and

HMTS.

To further reduce the computation time in model reduction, a correlated dynamic

adaptive chemistry (CO-DAC) method is recently developed and integrated with the HMTS

method (Sun et al. 2014). The CO-DAC method is to generate reduced mechanism on

the fly by using correlation parameters in phase space. The same reduced model will be

used on both space and time ordinates unless the correlated phase parameters are larger

than the specified threshold. In this way, the PFA based model reduction time can be

significantly improved. The HMTS method is used to integrate the reduced mechanism by

CO-DAC so that efficient and accurate solutions of reduced mechanisms can be obtained.

The HMTS/CO-DAC method (Sun et al. 2014) was tested by the autoignition of the jet

fuel surrogate mixture (Won et al. 2013) at 1 atm, 400 K, and stoichiometric condition with

the Real Fuel-2 mechanism (425 species) (Dooley et al. 2013). The green and red sections

in Fig. 27 denote the computation time for chemistry integration and reduction. The black

section only represents the computation time for flow and transport calculation. It is seen

that the DAC method reduces the chemistry computation time by half and the HMTS

method reduces by more than factor of five. However, the combination of DAC with HMTS

fails to reduce the computation time due to the increase of time in the DAC model reduction.

By using CO-DAC method, the computation time can be further reduced it, rendering it

40 44 : 201402

VODE VODE/DAC HMTS HMTS/DAC HMTS/CO-DAC

100

50

0

CPU

tim

e/h

PFA time

Chemical solver's time

(HMTS/VODE)

Other terms

Real Fuel 2-Reduced-425 species

P/10 atmΦ/10

T0/400 K

Fig. 27

CPU time comparison between HMTS and VODE solver with and without DAC or CO-DAC

of stoichiometric reduced Real Fuel-2/air mixture at 1 atmosphere and 400 K

comparable with the transport and flow computation time. The above results show that

the HMTS/CO-DAC method is a promising method for the on the fly model reduction and

efficient chemistry integration. Future research in model reduction needs to focus on the

parallelization of this approach and the reduction of computation time for transport and

flow.

2.5 High pressure combustion kinetics

Combustion in practical engines is high pressures. Gasoline and diesel engines have

pressures up to 100 atm. Gas turbine engines are between 20 atm and 50 atm. Rocket

engines have pressures as high as 400 atm. Combustion kinetics is strongly affected by pres-

sure because many elementary reactions are pressure dependent. For example, as shown

in Table 3 reactions R1 and R2, R3 and R4, and R5 and R6 are competition pairs for

H radical production and consumption involving pressure dependent three-body recombi-

nation reactions. R1, R3, and R5 produce H radicals needed for chain-branching process.

However, reactions R2, R4, and R6 remove H radicals and produce either stable species or

less reactive radicals such as HO2. Therefore, with the increase of pressure, the reaction

rate of R2 increases faster than that of R1, leading to reduced H production and increased

HO2 formation. As a result, the combustion pathways at high pressure will be changed

Ju Yiguang : Recent progress and challenges in fundamental combustion research 41

Table 3 Elementary reactions

H+O2=O+OH (R1)

H+O2(+M)=HO2(+M) (R2)

H+HO2=2OH (R3)

H+HO2= O2+H2 (R4)

HCO (+M)=H+CO (+M) (R5)

HCO+O2=HO2+CO (R6)

CH2OH (+M)=H+CH2O (+M) (R7)

HCO (+M)=H+CO (+M) (R8)

significantly. Another type of reaction, which is also strong function of pressure, is the

unimolecular fuel and radical decomposition reaction like R7. Due to the collisional energy

transfer and the transition state dissociation, at low pressure the rate of unimolecular reac-

tion linearly depends on pressure via bimolecular collisions. However, at high pressure this

reaction rate becomes constant because the reaction process is limited by the energy redistri-

bution of the reaction complex to dissociate. Moreover, pressure also affects the equilibrium

and energy distributions between rotational and viborational energy modes, especially at

low temperature.

Recently, motivated by failure of conventional kinetic mechanisms in predicting high

pressure combustion properties, extensive research focusing on high pressure combustion

kinetics has been conducted. Figure 28 shows the comparison of measured and predicted

burning rate or laminar flame speeds of hydrogen as a function of pressure for equivalence

ratio of 2.5. It is seen that almost all the models failed in predicting the flame speeds at

high pressure. In addition, the experimental data shows a negative pressure dependence

of the burning rate, but none of the mechanisms predicted successfully. The failure of the

prediction of high pressure flame speeds of hydrogen demonstrates a big problem in existing

combustion kinetics and the needs of pressure dependent reactions.

To address this issue, the pressure dependent reactions of hydrogen combustion related

to HO2 formation was revisited by using both high level ab initio quantum chemistry com-

putation and recent measurements of elementary reaction rates (Burke et al. 2012). It was

found that the reaction pairs of R3 and R4 (Table 3) become very important at high pres-

sure and the uncertainties in rate constants of HO2 reactions with H, OH, O, and HO2 need

to be addressed. By updating the HO2 related elementary reactions and the third-body

42 44 : 201402

0 5 10 15 20 25 30

1.20

1.00

0.80

0.60

0.40

0.20

0

Pressure/atm

Mass

burn

ing r

ate

/(g

. cm

-2. s

-1)

H2/O2/Ar, f=2.5

Tf b 1600 K

Present experiments

Li et al. (2007)

Davis et al. (2005)

Sun et al. (2007)

Konnov (2007)

O'Connaire et al. (2004)

Saxena & Williams (2006)

Fig. 28

Comparison of measured and predicted burning rates of H2/O2/Ar mixture as a function

of pressure (Burke et al. 2010)

reaction of R2, a new high pressure hydrogen kinetic model was developed. This model was

further extended to high pressure hydrogen syngas mixture. Figure 28 shows the com-

parison of the measured and predicted burning rates of H2/CH4/O2 mixtures at elevated

pressures. It is seen that the high pressure flame speeds are well predicted. Since hydrogen

kinetics is the base of all hydrocarbon fuel, to address the problems of high pressure hydro-

gen kinetics, an independent kinetic study of high pressure hydrogen and syngas kinetics

was also conducted by a collaborative research group led by Curran (Burke et al. 2014).

The failure of hydrogen mechanism at high pressure attracts significant interest to re-

visit high pressure kinetics of larger hydrocarbon fuels such as methanol, CH2O, methyl

formate dimethyl ether. For example, reactions R7 and R8 are strongly pressure dependent

and very important for radical production at high temperature, but their pressure depen-

dences are not well represented in the existing kinetic mechanism. As shown in Fig. 29,

the reaction rate of R7 has strong pressure dependence. However, the rate constant used

in existing models (Li et al. 2004) differs by more than a factor of 5 at high tempera-

ture from the recent quantum chemistry calculation. Recently, at the Combustion EFRC

Center at Princeton University, several high pressure detailed chemical models for the high-

temperature combustion of butanol isomers (Harper et al. 2011), methanol and biodiesel

Ju Yiguang : Recent progress and challenges in fundamental combustion research 43

0 5 10 15 20 25 30

Pressure/atm

0.15

0.12

0.09

0.06

0.03

0

Mass

burn

ing r

ate

/(g

. cm

-2. s

-1)

H2/CH4/O2/He,ϕ/07

Tf b 1600 K

H2/CH4/100�0

H2/CH4/90�10

USC-MECH II

Updated H2+USC-MECH II C1-C2

Fig. 29

Comparison of measured and predicted burning rates of H2/CH4/O2 mixtures as a function

of pressure. (Burke et al. 2011)

surrogates (Dievart et al. 2012), and foundation fuels (H2, CO, C1–C4 hydrocarbons) were

also revisited. Figure 30 shows the comparison of measured and predicted methanol mole

fraction temporal profiles during the pyrolysis of 1% methanol in argon in a shock tube

experiment (Ren et al. 2013). It is seen that by considering the pressure dependence of ele-

mentary reactions in Table 1 and methanol fuel decomposition, the new model (Dievart et

al. 2014) predicts the methanol decomposition very well. New high pressure kinetic mecha-

nism (HP-Mech), which include H2O and CO2 for hydrogen, methane, ethylene, C2H2, and

DME oxidation at high pressure is also under development (Shen et al., 2014). A collabora-

tive work on the development of high pressure propene kinetic is also under the way (Burke

et al., 2014).

In high pressure kinetic theory, Truhlar and Green discovered a new pathway that plays

a role in the low-temperature oxidation chemistry of alkanes when the crucial, second O2

addition step takes place, and predicted its rate from first principles (Jalan et al. 2013).

This new pathway generates closed-shell, unreactive species instead of radicals, thus decreas-

ing the autoignition propensity of the system. New computational chemistry methods to

efficiently, yet rigorously handle the anharmonicities and vibration-rotation coupling arising

in molecules with coupled torsions and to consistently treat multiple-well systems, have also

44 44 : 201402

0.50 0.60 0.70 0.80 0.90 1.00

108

107

106

105

104

103

1000/T[K-1]

Rate

const

ant/

s-1

Present studyDames and Golden (2013)Li et al. (2007)

1 atm

10 atm

Fig. 30

Pressure dependence of CH2OH(+M)=H+CH2O(+M) reaction (Dievart et al. 2014)

been developed.

Future challenges are: 1) Experimental validation of kinetic mechanism and elementary

rate constant measurements at high pressure kinetics (1∼50 atm) and low temperature con-

ditions (500∼1100 K); 2) Large hydrocarbon and oxygenated fuel chemistry and pressure

dependent RO2 and QOOH reaction pathways; 3) Improvement of uncertainty in ab initio

quantum chemistry calculations; and 4) Development of automatic search of high pressure

reaction pathways and kinetic mechanism from the first principle.

2.6 Experimental methods of fundamental combustion and uncer-

tainty analyses

To develop quantitatively predictive kinetic mechanisms, the uncertainties in exper-

imental methods and data analysis have become a big problem to constrain the kinetic

mechanism in experimental mechanism. Recently, it has become increasingly important to

revisit the existing experimental methods such as jet stirred reactors (Gail et al. 2007), flow

reactors (Dooley et al. 2010, 2011, Li et al. 1996, Suzuki et al. 2013), rapid compression

machines (Vanhove et al. 2006, Healy et al. 2008, Kumar et al. 2010), and shock tubes

(Gauthier et al. 2004, Shen et al. 2010).

Rapid compression machines, counterflow flames, spherically propagating flames, and

low pressure flat flames all have their own uncertainties in extracting species, ignition, flame,

Ju Yiguang : Recent progress and challenges in fundamental combustion research 45

0 500 1000 1500

1.2

1.0

0.8

0.6

0.4

0.2

0

Time�ms

CH

3O

H m

ole

fra

ction

1266 K and 2.5 atm

1368 K and 2.4 atm

1458 K and 2.3 atm

1610 K and 2.2 atm

Fig. 31

Comparison of measured and predicted methanol mole fraction temporal profiles during the

pyrolysis of 1% methanol in Argon. (Dievart et al. 2014, Experimental data by Ren et al.

2013)

and kinetic information for the validation of kinetic mechanisms. Several review articles fo-

cusing on the uncertainties of different classes of experiments are under preparation (Egopo-

folous et al. 2014). In this review, we focus only on a few large uncertainties sources of

flame experiments and leave other topics to the other review articles.

In flame experiments, the counteflow diffusion and premixed flames, spherically prop-

agating flames, and the fat flames are extensively used in measuring species distribution

(Lefkowitz et al. 2012, 2013, O.βwald et al. 2011, Gail et al. 2007), flame speeds (Burke

et al. 2010, 2011, Qin et al. 2005, Kelly et al. 2011, Veloo et al. 2010, Huang et al. 2006,

Kumar et al. 2007) and extinction limits (Honnet et al. 2009, Won et al. 2010, 2011).

However, the species distribution, extinction limit, and flame speeds in flames are not only

affected by the chemical kinetics but also affected the flow field, molecular transport, thermal

radiation, compression waves, and probe perturbation. Unfortunately, few researchers have

systematically studied the uncertainties caused by the boundary conditions, flow field and

transport processes, and external perturbations. Below, we use counterflow diffusion flames

and the spherically propagating premixed flames to illustrate the sources of uncertainties

and the approaches to improve the experimental methods.

Counterflow flames have a quasi-steady one-dimensional flame geometry and their flame

properties are governed by the boundary conditions and the stretch rates. Counteflow flames

46 44 : 201402

have been developed for more than half a century (Saitoh et al. 1976, Wu et al. 1985). It has

been used extensively to measure species distributions, extinction limits and flame speeds.

The basic assumption of counterflow flames to measure flame properties are the plug flow

or potential flame assumption, and the linear stretch rate extrapolation method. However,

these assumptions are not always true. The first uncertainty source of counterflow flame is

the burner sepearation distance. Recent studies of counterflow diffusion flames (Sarnacki et

al. 2012, Lefkowitz et al. 2013) have shown that the plug flow assumption is not appropriate

if the ratio of the burner separation distance to the burner diameter is too small. When the

burner separation distance is very small the thermal expansion in the flames will modify the

pressure distribution between the burners and render the plug flow assumption invalid. As a

result, the experimental data of extinction limit and the species distribution in a counterflow

diffusion flame will be not be the only function of the stretch rate, leading to large uncertainty

in experimentally measured extinction limits and species distributions. Figure 32 shows

the comparison between the results of acetone PLIF, microtube sampling, and numerical

modeling of acetone diffusion flames (Lefkowitz et al. 2013). It is seen that when the burner

separation distance is smaller than 25 mm, there is a significant shift of acetone distribution

between the results of acetone PLIF, microtube sampling, and modeling.

The second major uncertainty source of counterflow flame is the linear extrapolation

method to obtain the unstretched flame speed at zero stretch rate. Since the stretched flame

0 2 4 6 8 10 12 14 16

0.25

0.20

0.15

0.10

0.05

0

Distance from fuel nozzle/mm

Aceto

ne m

ole

fra

ction

L/9 mmL/15 mm

L/25 mm

O2 oxidizer

air oxidizer

Fig. 32

Comparison of acetone distributions between PLIF measurements (closed symbols), sam-

pling measurements (open symbols), and numerical results (lines) for different burner sepa-

ration distances (L). (Lefkowitz et al. 2013)

Ju Yiguang : Recent progress and challenges in fundamental combustion research 47

speed is approximated by the minimum velocity caused by the thermal expansion in front of

the premixed counterflow flame, at low stretch rates the thermal expansion effect increases

so that the stretched flame speed and the stretch rate becomes highly nonlinear (Tien et al.

1991). Therefore, a nonlinear extrapolation method is required to obtain the stretch free

burning velocity from the counterflow flame experiments (Egopofolous et al. 2014).

The third uncertainty in counterflow flame experiment is the perturbation of micro-

tube sampling on the flame structure and location. Recently, simultaneous measurements

of acetone and OH PLIFs and microtube sampling were conducted in acetone diffusion

flames (Lefkowitz et al. 2013). The results in Fig. 33 show clearly that not only the

burner separation distance but also the flow perturbation induced by the micro-tube caused

a significant shift of the reaction zone and species distribution. In order to minimize the

a b c d

e f g h

acetoneOH

Distance from the fuel nozzie/mm

LIF

sin

gals

/a.u

.

8 9 10 11 12 13 14 15

1.2

1.0

0.8

0.6

0.4

0.2

0

0.06

0.05

0.04

0.03

0.02

0.01

0

Aceto

ne m

ole

fr

action

xf=0.05 a=100 s-1

oxygen for oxidizer

Acetone LIF

Air, oxid

izer

O2, oxid

izer

probe at 0 mmprobe at 8 mmprobe at 12 mmprobe at 15 mmPichon et al. model

OH LIF

Fig. 33

Direct images of simultaneous acetone and OH PLIF measurements to demonstrate the flow

perturbation by the existence of the sampling probe for the separation distance L = 25 mm;

(a)–(d) at Xf = 0.20, a = 100 s−1, and the oxidizer side is air, (e)–(h) at Xf = 0.05,

a = 100 s−1, and the oxidizer side is oxygen; (a) and (e) without probe, (b) and (f) probe at

0 mm from the fuel nozzle, (c) and (g) at 12 mm, and (d) and (h) at 15 mm (white dotted

line indicates the peak OH position for the case without the probe). Bottom plot (i) shows

acetone and OH profiles at the centerline as a function of distance for oxygen oxidizer cases,

for a number of probe positions, along with numerical results (Lefkowitz 2013)

48 44 : 201402

microtube perturbation effect, the reaction zone needs to be shifted to the fuel rich side

by increasing the oxygen concentration on the oxidizer side. In addition to the flow effect,

the effect of radical quenching and heat loss also modifies the local chemical kinetics and

the concentration of radicals. This problem may become more significant when a nozzle is

used in fat flame sampling (Guo et al. 2013, Qi, 2013) due to the fast diffusion and reduced

total enthalpy of the flames. Therefore, careful assessment of experimental uncertainties in

counerflow flame experiments is necessary to extract useful information to validate kinetic

mechanism. In addition, if a sampling nozzle is used, the effects of radical quenching and

heat loss on the species and temperature distributions need to be corrected.

Recently, due to the interest of high pressure kinetics, the spherically propagating flames

have been extensively used to measure flame speeds (Bradley et al. 1996, Tse et al. 2000,

Qin et al. 2005, Huang et al. 2006, Burke et al. 2010, 2011). In last five years, it has

been evident that there are many uncertainties in spherically expanding flame experiments

in terms of its physical hypothesis and boundary conditions. The unstretched flame speed

(S0L) measurement by spherical flames is based on the high speed imaging of the flame front.

This method requires several assumptions to obtain the unstretched flame speed: (1). zero

burned gas velocity (ub = 0), (2). adiabaticity of the flame (Tb = Tb,ad), (3). Constant

density ratio of burned to unburned gas (ρb/ρu = ρb,ad/ρu), and (4). linear/nonlinear

relationship between stretched flame speed and stretch rate.

Recent studies (Burke et al 2009, Chen et al. 2009) showed the first assumption of

zero burned gas velocity is not valid if a small cylindrical chamber or a large pressure rise is

used in experiments. Thermal expansion induced by flame outwardly flame propagation in

a small cylindrical chamber led to unsymmetrical flow motion and causes negative ub in the

burned gas (Fig. 34). As shown in Fig. 34, if the negative flow velocity is not corrected, the

unstretched flame speed will not be appropriately extrapolated. For a spherical chamber,

if the flame radius is larger than 30% of the chamber radius, due to flow compression an

inward flow (ub < 0) is also induced. The correction method of negative burned gas velocity

in flame speed measurements due to cylindrical chamber and flow compression was given in

by Chen et al. 2009.

The second and third assumptions become not valid when flame radiation is considered.

The radiative heat loss from the burned zone will cause a flow contraction and also induces

a radiation induced inward flow (ub < 0). In addition, the radiation heat loss will also result

in the change of peak flame temperature, thus, the change of density ratio. Figure 34

shows the effect of radiation heat loss (left) and the effect of radiation reabsorption on the

Ju Yiguang : Recent progress and challenges in fundamental combustion research 49

Q

Vb

0 1000 2000 3000

240

220

200

180

160

Stretch rate, κ/s-1

Calc

ula

ted fla

me s

peed,

Su/(c

m. s

-1)

06Rw 04Rw 03Rw 02Rw 01Rw

Hydrogen-air, 1 atm, φ=3.0

Flow-correcteduncorrected

Fig. 34

Left: Direct Schliren image of a spherically propagating flam and schematic of burned gas

velocity flow velocity. Right: Stretched flame speed as a function of stretch rate with and

without flow correction in a cylindrical chamber (Burke et al. 2009)

flow velocity in the burned gas region. It is seen that if an optically thin model is used

the radiation heat loss will induce a very large negative burned gas velocity. However, if

the radiation absorption is appropriately modeling by using a fitted statistical narrow band

correlated-k (FSNB-CK) model, the negative burned gas velocity will be much smaller than

that predicted by the optically thin model (Chen et al. 2007, Santer et al. 2014, Sun

et al. 2014). Numerical simulation also revealed that the density ratio at the end of the

reaction zone is also different from that of an adiabatic flame. Therefore, a correction of the

peak flame temperature (Tb,ad/Tb) to take into account of the change of the density ratio is

necessary. As such, in order to correct the effects of both negative burned gas velocity and

the change of density ratio due to radiation (Sun et al. 2014), an accurate radiation transfer

method including radiation absorption is needed. After the negative burned gas velocity

and the change of density ratio are appropriately estimated, the stretched flame speed can

be calculated using the equation below.

SL =ρb,adρu

Tb,ad

Tb(Sb − ub) (2)

The linear dependence of stretched flame speed on stretch is a solution in the limit of

weakly stretch flames.

SL/S0L = 1−MaKa (3)

Where Ma and Ka are, respectively, the Markstein number and the Karlovitz number.

50 44 : 201402

0 2 4 6 8 10 12 14 16

80

60

40

20

0

-20

Radial coordinate, r/cm

0 2 4 6 8 10 12

Radial coordinate, r/cm

Velo

city/cm

. s-

1

60

40

20

0

-20

Velo

city/cm

. s-

1

adiabatic and optically thin

adiabatic

optically

thin

Rch/10 cm

50 cm

FSNB-CK Rch/10 cm↼t/007 s)

flame propagation

(in Rch/50 cm

at t/002b0.08 s

with Dt/001 s)

Ub/↩37 cm/s

Ub/↩145 cm/s

a b

Fig. 35

Effect of radiation on the burned gas velocity of a spherically propagating flame in a chamber

with 10 and 50 cm radius, respectively. Left: adiabatic and optically thin modeling; Right

FSNB-CK modeling with radiation absorption (Sun et al. 2014)

Therefore, the fourth assumption of linear extrapolation of unstretched flame speed to zero

stretch becomes questionable when the mixture Lewis number (Ma) deviate significantly

from unity and the flame stretch rate (Ka) is very large. To resolve this problem, various non-

linear extrapolation methods by including large Lewis number and large flame curvature have

been proposed (Chen et al. 2007, 2009, Kelly et al. 2011, Wu et al. 2004). These methods

slightly improve the extrapolated flame speeds but significantly improve the extrapolated

Markstein length (Ma). However, the problem still remains when the mixture Lewis number

is significantly less than unity. A recent collaborative study (Wu et al. 2014) shows that

even a nonlinear extrapolation at very low stretch rate still led to about 20% over-prediction

of the unstretched flame speed of hydrogen. Similar observation can also be found, although

the uncertainty is smaller, for large mixtures with Lewis numbers.

Therefore, to appropriate extrapolate flame speeds from spherically expanding flames,

corrections of negative burning velocity, density ratio, and stretch need to be carefully made.

If an experimental system is very thermally radiative and has a Lewis number far different

from unity, rigorous radiation modeling including radiation absorbtion and direct numerical

simulation are needed to extract the unstretched flame speeds.

Similar uncertainties also exist in flow reactors and jet stirred reactors as well as flat

flames (Egolfopoulos et al. 2014). Future research needs to address this issue to improve

Ju Yiguang : Recent progress and challenges in fundamental combustion research 51

kinetic model validation.

2.7 Combustion diagnostics: key radicals and intermediate species

Diagnostics plays a critical role to validate computation and kinetic models. As the

engine pressure increases and temperature decreases, direct diagnotics of important inter-

mediate species and radicals become more important due to the fact that most kinetic

mechanisms at high pressure and low temperature regions were poorly validated. The pres-

sure dependence and the branching ratio of elementary reactions involving decomposition

RO2, QOOH, O2QOOH, and ketohydroperoxides are not well known. In addition, as shown

in Table 2, H2O2 and HO2 play key roles in the high pressure fuel oxidation chemistry and

the auto-ignition process. Figure 36 shows schematically the important reaction pathways

that describe the high pressure oxidation of hydrocarbon fuels (RH) at different temperature

ranges. At low (below 900 K) and intermediate temperatures (900∼1200 K), HO2 radicals

are formed from reactions of fuel (RH) with O2, and then form H2O2 after further reaction

0.90.2 0.3 0.4 0.5 0.6 0.7 0.8

2.0

1.8

1.6

1.4

1.2

1.0

0.8

Normalized equivalence ratio, φ/(1+φ)

Rela

tive d

iffe

rence

Sb↼NE↽�Sb,Premix

Sb↼N3P↽�Sb,Premix

Sb,c↼NE↽�Sb,Premix

Sb,c↼N3P↽�Sb,Premix

SExp↼NE↽�Sb,Premix

SExp↼N3P↽�Sb,Premix

SExp↼NE↽�Sb↼NE↽

SExp↼N3P↽�Sb↼N3P↽

Sb↼NQ↽�Sb,Premix

Sb↼NE↽�Sb,Premix

3-order trend line forSb↼NQ↽�Sb,Premix

H2/air

n-heptane /air

0.3 0.4 0.5 0.6 0.8 1.0 1.3 1.6 2.0 2.53.0 4.0 6.0

Equivalence ratio, φ

Fig. 36

Extrapolated flame speeds using different nonlinear models in relative to PREMIX results

for H2/air and n-heptane/air measurements (open symbols), and numerical results (lines)

for different burner separation distances (L) (Wu et al. 2014)

52 44 : 201402

Fuel (RH)

OH

OH

2OH

+OH

+CH3/O

HO2

H2O3

+O2

+O2

+fuel/O2

+O2

+O2+O2

+O2+(M)

RO2 C2H3

O+OH

+H

H/HCO

Smallalkane

Fig. 37

A schematic of the key reaction pathways for oxidation of hydrocarbon fuels at high pressure

(blue arrow: low temperature; yellow arrow: intermediate temperature; red: high tempera-

ture; dotted arrows: elementary steps) (Brumfield et al. 2013)

with another fuel molecule. The decomposition of H2O2 to OH via H2O2=2OH is the gov-

erning branching reaction that leads to “hot ignition”. As discussed in Table 2, at high

pressure, HO2+H=2OH is another important branching reaction. On the other hand, RO2

is formed from oxygen addition to fuel radicals (R). The subsequent isomerization RO2 and

second oxygen addition is another major pathway for OH production at low temperature.

Therefore, the formation and consumption of HO2, H2O2, and RO2 are extremely important

in high pressure combustion kinetics for all fuels from hydrogen to large hydrocarbons and

biofuels. However, direct measurements of these species in high pressure combustion are

extremely challenging, leading to large uncertainties in chemical kinetic models.

Recently, direct measurements of H2O2 were conducted by using cavity ring-down spec-

troscopy (cw-CRDS) at 0.01 atm using a jet stirred reactor of n-butane oxidation (Fig. 38)

(Bahrini et al. 2012) and using molecular beam mass spectrometry (MBMS) in an atmosph-

eric flow reactor (Guo et al. 2011), respectively. These data provided important validation

targets for ignition transition from low temperature ignition to hot ignition. However, both

methods required intrusive sampling which causes uncertainty due to wall quenching. A

UV photo-fragmentation LIF method was used to measure H2O2 at high pressure engines

by photo-dissociate H2O2 into OH and then measure OH using OH LIF (Li et al. 2013).

Ju Yiguang : Recent progress and challenges in fundamental combustion research 53

900600 700

Mole

fra

ction

800

4

3

2

1

0

Τ10-3

Temperature/K

Fig. 38

Evolution with temperature of the experimental (points) and computed (lines) mole fractions

of n-butane (white triangles and dotted line, mole fraction/5) and H2O2 (blue dots and full

line) (Bahrini et al. 2012)

However, this method suffers from the spectrum overlaps of HO2, H2O2, and side photo-

dissociation production of OH from other molecules.

Detection of HO2 is more challenging than H2O2 due to its high reactivity and low

concentration (∼10 ppm). The quenching problem becomes more serious for HO2 in MBMS

sampling, where it has recently been blamed for the failure in detection of HO2 in the same

study where H2O2 was quantified using cw-CRDS (Bahrini et al. 2012). Hong et al. (2012)

investigated the relative evolution of HO2 by using absorbance at 227 nm in a shock tube.

However, this method relies on the accuracy of a kinetic mechanism that may not be well

validated at high pressure, and the UV absorption is also complicated by spectral inter-

ference from H2O2, RO2, ketohydroperoxides, and large hydrocarbon molecules. Spectral

interference is also a problem that is encountered for near-IR optical detection of HO2,

particularly at high pressure.

More recently, the first direct in-situ measurements of hydroperoxyl radical (HO2) from

the exhaust of a laminar flow reactor have been carried out using mid-infrared Faraday ro-

tation spectroscopy (FRS) (Brumfield et al. 2013). Based on the results of non-linear fitting

of the experimental data to a theoretical signal model the technique offers an estimated sen-

sitivity less than 1 ppmv over an exhaust temperature range of 398.15 K to 673.15 K. FRS

is a dispersion-based magneto-optical technique that is selectively sensitive only to param-

agnetic (radical) species. Signals from diamagnetic molecules, such as H2O, are suppressed.

54 44 : 201402

Therefore, in theory FRS is a zero-background technique with a distinct advantage over

absorption spectroscopy as a combustion diagnostic method.

The FRS experimental setup to measure HO2 from the exhaust of an atmospheric

flow reactor is shown Fig. 39. An external cavity quantum cascade laser (EC-QCL, Day-

light Solutions, model 21074-MHF) operating in continuous wave (CW) mode was used to

provide tunable light for probing the HO2 Q-branch transitions in the ν2 bending funda-

mental around 1400 cm−1 (7.1 μm). A high extinction coefficient is crucial to achieving

good signal-to-noise ratio (SNR) in the FRS system. The laser beam is first transmitted

through a polarizer that cleans up the laser polarization state and then it is passed 2 mm

from the exit of the reactor. This spatial region at the reactor exit is overlapped with an AC

magnetic field (1.07× 10−2 T RMS, 610 Hz) from a Helmholtz coil arrangement. A second

polarizer transforms the polarization rotation into a modulated intensity which is measured

using a photodiode. The signal from the photodetector is then demodulated using a lock-in

amplifier. The HO2 concentration is calculated from the change of the polarization angle of

the laser beam by using experimental FRS spectra through a non-linear fitting (Fig. 39).

Figure 40 (left) shows the measured HO2 distribution in comparison with model prediction.

Heated flow reactor

Input polarization

Modulated polarization

Demodulate at ω

B0 cos(ωt)

1396.80 1396.92 1397.04

Frequency/cm-1

Sig

nal/

V

0

-0.5

-1.0

Fig. 39

Experimental layout of the FRS system for in situ detection of HO2 in flow reactor (Brumfield

et al. 2013)

Ju Yiguang : Recent progress and challenges in fundamental combustion research 55

500 600 700 800

25

20

15

10

5

0

1200

1000

800

600

400

200

0

Temperature/K

Concentr

ation/ppm

v

Concentr

ation/ppm

v

HO2 H2O2Expt.Liu et al.Zhao et al.

400 600 1000800 1200

Temperature/K

Τ5

a b

Fig. 40

Comparison of measured and predicted HO2 and H2O2 distributions in a flow reactor of

lean dimethyl-ether/O2/He mixtures (Naoki et al. 2014)

It is seen that the kinetic model of dimethyl ether (Naoki et al. 2014) significantly over-

prediction the HO2 formation at low temperature, leading to a faster oxidation of fuel. In

Fig. 40 (right), the H2O2 distribution measured by using MBMS at the same experimental

condition was also compared to kinetic modeling. The H2O2 distribution also suggests that

the current kinetic model over-predict the low temperature oxidation of fuel. Additional

measurements of CH2O and CO also support these results. Therefore, direct measurements

of HO2and H2O2 play a critical role in quantifying low temperature chemistry. More re-

cently, experimental confirmation of the low-temperature oxidation scheme of alkanes was

conducted by using photo-ionized MBMS (Battin-Leclerc et al. 2010). This work gave the

first experimental speciation of the low-temperature oxidation of organic compounds such

as ketohydroperoxides. Also, multi-species diagnostics in shock tubes using UV and infrared

absorption (Hong et al. 2012) also provide complementary information of species time his-

tory. The major challenge is quantitative measurements of HO2, RO2 ketohydroperoxides

and QOOH at high pressure.

2.8 Future research and conclusion

In last five years, there have been significant progresses in fundamental research of

combustion ranging from new combustion and engine technologies to elementary kinetics as

well as advanced diagnostics. Below are the summaries of advances and technical challenges

in the seven selected topic areas discussed in this review.

Modern engines are using more premixed and volumetric ignition modes than high

56 44 : 201402

temperature premixed and diffusion flame modes in conventional engines. The combustion

characteristics and engine performance of advanced engines are strongly affected by fuels and

fuel molecular structures. Low temperature and high pressure chemistry plays a critical role

in affecting the control of heat release rate and knocking of engines. Propagations of different

ignition and flame modes in HCCI and RCCI engines at NTC have been predicted by direct

numerical simulations. Recent turbulent flame studies of large hydrocarbon fuels revealed

that low temperature ignition can lead to different turbulent flame regimes and different

turbulent flame speeds. The existing Borghi turbulent flame diagram does not include the

flame regimes involving large ignition Damkohler number at elevated temperature. The

previous studies of turbulent flame regimes have been limited to high temperature thin

flame regime. Future studies in turbulence combustion in engines need to emphasize how

low temperature chemistry affects the turbulent flame regimes, propagation speeds, and

turbulence-chemistry interaction, especially at high pressure and high Reynolds number.

Many new ignition and flame regimes have been observed at non-equilibrium conditions

with fuel and thermal stratifications as well as plasma activation. Since low temperature

chemistry is very sensitive to fuel concentration and temperature, different coupled and

decoupled, low temperature and high temperature ignition and deflagration fronts were re-

ported. Moreover, temperature and fuel stratifications can induce strong flame oscillation as

well as propagation of supersonic ignition and detonation waves. The results revealed that

the rich low temperature fuel reactivity of transportation fuels with thermal and fuel strat-

ifications can be one of major causes of engine knocking. Non-equilibrium plasma can sig-

nificantly enhance low temperature ignition and combustion, and extend combustion limits.

A direct ignition to flame transition without ignition to extinction hysteresis was observed

with plasma activation of ultra-lean mixtures. The fundamental process of plasma assisted

combustion has been advanced by advanced laser diagnostics of plasma generated excited

molecules, intermediate species, and radicals. A new self-sustained cool flame was discov-

ered by using plasma activated ozone generation. However, there is still a large knowledge

gap in low temperature chemistry and cool flames. Many fundamental combustion phe-

nomena involving low temperature ignition and flames with fuel and thermal stratifications

are not well understood at high pressure. Moreover, there is a large uncertainty of kinetic

mechanisms in extreme conditions.

Alternative fuels provide great opportunities and challenges for combustion research.

Surrogate fuel models are necessary to model the kinetics of real and alternative fuels. A

generic surrogate fuel model with four combustion targets was proposed and systematically

Ju Yiguang : Recent progress and challenges in fundamental combustion research 57

tested for jet fuels and synthetic fuels. Derived centane number, H/C ratio, and molecular

transport were found to been critical to identify a surrogate fuel mixture. New concepts such

as radical index and transport weighted enthalpy were developed to decouple the extinction

limits from fuel transport properties and heating value, and to rank high temperature fuel

reactivity of fuels with different molecular structures and sizes. Although the four combus-

tion target surrogate fuel model was successful to reproduce jet fuel surrogates, mimicking

ignition properties precisely at low temperature for some bioderived and oxygenated fuels

remains a big challenge. The ratio of methylene (CH2) to methyl (CH3) was found to be an

important parameter to improve surrogate fuel modeling in addition to the four combustion

property targets. A detailed kinetic mechanism for real jet fuel surrogate mixtures was de-

veloped and tested. Future research should address: (1). How will the physical properties

of alternative fuels be modeled? (2). How does the turbulent flow affect the validation of

surrogate fuel model? (3). How can we find an affordable surrogate mixture which can

allow large scale engine tests, and (4). How can we develop a compact and validated de-

tailed kinetic model for surrogate fuel mixtures by using the lumping techniques for large

fuel molecules and a detailed C0-C4 kinetic mechanism for the oxidation of small molecule

fuels, respectively.

Multi-scale and multi-physics modeling using detailed kinetic mechanism remains to be

a challenging issue. Many methods using time splitting, path flux and graph analysis, adap-

tive chemistry, solution mapping, tabulation, and multi-timescales have been developed.

These methods significantly increased the computation efficiency. Future research in model

reduction needs address the large number of species needed to be carried in adaptive chem-

istry reduction, parallelization of model reduction method, and reduction of computation

time for transport and convection calculations

Elementary reactions and combustion strongly depends on pressure. HO2, RO2 and

QOOH chemistry play a critical role at high pressure. The recent results showed that HO2

chemistry led to the negative pressure dependence of hydrogen flame speeds on pressure.

Significant progress has been made in ab-initio quantum chemistry to predict pressure de-

pendent rate constant with 30% to 200% uncertainty for reactions involving small molecules.

Unfortunately, many existing kinetic mechanisms still use the rate constants at high pressure

limit. Future challenges are: 1) Experimental validation of kinetic mechanism and elemen-

tary rate constant measurements at high pressure kinetics (1∼50 atm) and low temperature

conditions (500∼1100 K); 2) Large hydrocarbon and oxygenated fuel chemistry and pressure

dependent RO2 and QOOH reaction pathways; 3) Improvement of uncertainty in ab initio

58 44 : 201402

quantum chemistry calculations; and 4) Development of automatic search of high pressure

reaction pathways and kinetic mechanism from the first principle.

To develop quantitatively predictive kinetic mechanisms, the uncertainties in experi-

mental methods and data analysis have become a big problem in constraining the kinetic

mechanism in experimental mechanism validation. Recently, it has become increasingly clear

that existing experimental methods such as jet stirred reactors, flow reactors, rapid com-

pression machines, and shock tubes all have large uncertainties in physical interpretation,

boundary conditions, and probe perturbation, and need to be revisited the existing exper-

imental methods. Uncertainties in flow compression, cylindrical chamber geometry, linear

extrapolation, radiation, and ignition energy to flame speed measurements in a spherically

propagating bomb have been addressed. The effects of potential flow assumption, burner

separation distance, probe perturbation, and linear stretch extrapolation in counter-flow

flames were also reported and examined. Future research needs to address these issues in

flat flames, flow reactors, and jet stirred reactors.

For high speed propulsion such as supersonic combustion and Scramjet engines, vitiated

air has been widely used in test facilities. As a result, the kinetic effects via air contamina-

tion by H2O and NOx on supersonic combustion have complicated the experimental studies

for decades. Recently, as reported by Jiang and Yu (2014) the largest detonation-driven hy-

pervelocity shock tunnel was developed, tested, and calibrated at the Institute of Mechanics

in Beijing. This facility significantly extends the current hypersonic test capability to mimic

real flight conditions of Mach number 5∼9 at altitude of 25∼50 km for more than 100ms

test duration. The initial test results are very encouraging that the uncertainties in exper-

imental methods for subsonic combustion can be reduced by this unique hypersonic shock

tunnel without air contamination. These advanced experimental facilities will produce more

reliable data that are important not only for fundamental combustion research but also for

aerospace engineering.

Diagnostics plays a critical role to validate computation and kinetic models. H2O2

and HO2, RO2, QOOH, and O2QOOH play key roles in the high pressure fuel oxidation

chemistry and the auto-ignition processes. However, diagnostics of these species remain

extremely difficult. Recently, progresses have been made in measuring H2O2, HO2, and RO2

related low temperature chemistry using Faraday rotational spectroscopy, cavity ring-down

spectroscopy, and photo-ionized molecular beam mass spectroscopy. The major challenge

in the future diagnostics is quantitative and time dependent measurements of HO2, RO2,

ketohydroperoxides, and QOOH at high pressure Moreover, quantitative species diagnostics

Ju Yiguang : Recent progress and challenges in fundamental combustion research 59

in high speed flow is much more challenging.

Acknowledgement: This work is was partially supported by the open research fund

of State Key Laboratory of High-temperature Gas Dynamics at Institute of Mechanics of

Chinese Academy of Science. The author would like to thank all the contributions from

his students, staff members, and many collaborators including S Klippenstein (ANL), M

Burke (ANL), Z Chen (PKU), XL Gou (CQU), and B Brumfield, P Dievart, FL Dryer, CK

Law, J Lefkowitz, N Kurimoto, J Santner, W Sun, WQ Sun, SH Won and G Wysocki at

Princeton University. This work is was partially supported by research grants including

the US DOE Energy Frontier Research Center on Combustion (DE-SC0001198), DOE-

NETL(DE-FE0011822), AFOSR (FA9550-13-1-0119, FA9550-07-1-0136), ARO (W911NF-

12-1-0167).

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Ju Yiguang : Recent progress and challenges in fundamental combustion research 71

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Department of Mechanical and Aerospace Engineering,

Princeton University, New Jersey, USA

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Yiguang Ju is the Robert Porter Patterson Professor at Princeton University.

His bachelor degree in Engineering Thermophyiscs from Tsinghua University

in 1986, and his PhD degree in Mechanical and Aerospace Engineering from

Tohoku University in 1994. He was appointed as an Assistant and Associate

Professor at Tohoku University in 1995 and 1998, and as a Changjiang Pro-

fessor and the Director of Thermophysics Institute at Tsinghua University in

2000. He joined Princeton University in 2001 and became a full professor in

2011. Prof. Ju’s research interests include combustion and propulsion in the

area of near limit combustion, microscale combustion, plasma assisted propul-

sion, alternative fuels, chemical kinetics, multiscale modeling, and functional nano-materials. He

has published more than 140 refereed journal articles. He is an ASME Fellow and a board member

of Combustion Institute of Eastern States. He received a number of awards including the Young

Investigators Award (1999) at the First Asia Pacific Conference on Combustion, the Best Paper

Award (1999) by the Japan Society for Aeronautical and Space Sciences, the Yangzi River Scholar

Award (2000) by the Chinese Education Ministry, the National Outstanding Young Scholar award

from NSFC (2001), the Distinguished Paper Award from the Thirty-third International Symposium

on Combustion (2010), the NASA Director’s Certificate of Appreciation award (2011), the Friedrich

Wilhelm Bessel Research Award by the Alexander von Humboldt Foundation (2011), and the Hsue-

Shen Tsien Professorship of Engineering Sciences of Institute of Mechanics at Chinese Academy of

Science (2013).