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, 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
†
Department of Mechanical and Aerospace Engineering,
Princeton University, New Jersey, USA
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: 2014-01-29; : 2014-03-16; : 2014-04-01† E-mail: yju@princeton.edu
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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).
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