Recent Progress and Challenges in Fundamental Combustion Research

࡯ᄺ䖯ሩ, 2014 ᑈ, ㄀ 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 combustion chemistry and dynamics from molecule scales to engine scales and to develop 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: 2014-04-01 † E-mail: [email protected] $i teas: Yiguang Ju. Recent progress and challenges in fundamental combustion research. "Evances in Mechanics,2014,44: c 2014Advances in Mechanics. 2 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

Reactivity Controlled Compression Ignition (RCCI), and pressure gain combustion 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 engine 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, alternative 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 properties 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 combustion 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 important. 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 computationally efficient sub-grid turbulent-chemistry model is available for advanced engine modeling (Chen 2011, Pope 2012). Moreover, previous turbulent combustion experiments and modeling 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 ࡯ᄺ䖯ሩ ㄀ 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) burners (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 combustion. In addition, due to the increase of ignition Damköhler number at elevated temperature, 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 Damköhler 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 approaches 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 combustion 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

Atom Molecular Microflow Flames Engine combustion Physical process Molecules collisions

Nanoparticles Molecular and turbulent transport scales

Thermo- Soot growth, Mixing, ignition, extinction, flame Physical, chemical chemistry aggregation structure, emissions models Kinetic rates of reactions Turbulent transport-chemistry interaction

Quantum Modeling approach Direct Numerical Simulation Chemistry Statistical Mechanics LES, PDF, RANS

Experiment/validation

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 contamination by H2OandNOx 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 capability 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 ࡯ᄺ䖯ሩ ㄀ 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, development and certification of alternative and renewable fuels from alternative resources and biomass (Chu et al. 2012, Hu et al. 2008, Höinghaus 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 lignocellulosic 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 combustion 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

Normal Branched Valeric Biodiesel, alkane alkane Aromatics biofuels Alcohols Ethers Esters

O O R R OH R 2 1 R2 R1 O

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 combustion properties can be used in model validation. In last several decades, counterflow flames, spherically propagating flames, flat flames, flow reactors, rapid compression machines, 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 8 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402 key combustion parameters such as the flame speeds and species profiles are not appropriately 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 radiation effects from H2OandCO2 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 improve 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 dependent. At high pressure, the branching ratio of pressure dependent unimolecular decomposition reactions will become increasingly important in affecting the fuel reactivity. At high pressure and low temperature combustion processes, HO2,H2O2,RO2, and ketohydroperoxide 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 temperature 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 autoignition 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

104 fuel/air mixture, ϕ=1.0, p=13.5 atm 103 toluene 102 iso-octane 101

100 n-heptane lgnition delay time/ms lgnition delay 10-1 0.8 1.0 1.2 1.4 1000/T[1/K] 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

Control of combustion duration by ration of fuels 200 Cool iso-octane PRF Burn Flame Burn Primarly n-heptane Primarly 150 n-heptane +entrained iso-octane iso-octane ] Ο

100 AHHR [J/ 50

0 -20 -10 0 10 20 Crank [ATDC] 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

Fig. 5

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

a b

QJ/m3/s)

8Τ1010 7Τ1010 6Τ1010 5Τ1010 4Τ1010 3Τ1010 2Τ1010 1Τ1010 0

HO2

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 Damköhler 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 Damköhler number, and high displacement speed ignition front, while the D-mode was characterized by high scalar dissipation rate and low displacement speeds in the order of the laminar flame speed with a small ignition Damköhler 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 Damköhler 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 chemistry 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), S u l n T =1+CLe−1 (1) SL SL δf 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 ࡯ᄺ䖯ሩ ㄀ 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 temperature (ignition Damköhler number) affect the turbulent flame regime. At low ignition Damköhler 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 turbulent 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 Damköhler 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

103 Distributed reaction zone Thin reaction 102 zone L 1 S

' 10 u Corrugated flamelet 100 Wrinkled Turbulent intensity Turbulent flamelet 10-1 10-1 100 101 102 103 104 103 Distributed 1dL Turbulent scale reaction zone Thin reaction 102 zone Da ig > L 1 1 S

' 10

u Corrugated flamelet 100 Wrinkled flamelet 10-1 10-1 100 101 102 103 104

1dL Progress of fuel oxidation Turbulence/chemistry interaction Fig. 7

The change of turbulent flame diagram with the increase of ignition Damköhler Ju Yiguang : Recent progress and challenges in fundamental combustion research 15 turbulent combustion. To demonstrate the effect of low temperature ignition on turbulent flame propagation, 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 induced 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 temperature. 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 Damköhler 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 600 K 650 K 700 K 700 K 700 K U=10 m/s 10 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 ignition Damköhler number and fuel reactivity, exhibiting distinctive four flame regimes; (a) chemically-frozen-flow regime, (b)–(d) low-temperature-ignition regime, (d) and (e) transitional regime between low- to high-temperature-ignition regimes, and (f) high-temperature- ignition regime (Won et al. 2014) 16 ࡯ᄺ䖯ሩ ㄀ 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 Damköhler 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 turbulent 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

n-heptane/air, 0.3<φ<1.1, a b 0.68 b 400 < <700 ) 6 K Treactor K ' L u S ' =3.0 Τ( at fixed u SL 60 mm T =650 K =1+1.53 reactor SL ST )0.87

L ' L 4 Τ(u S

S =1+0.52 a T L TS S S

400 500 2 K K 15 550 600 mm

K K O PLIF OH 650 K 700 K 2 550 600

K K CH CH O detected 2 650 K 700 K 0 0 2468

u'SL 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 =0.5and the reactor flow residence time of 100 ms (Won et al. 2014) Ju Yiguang : Recent progress and challenges in fundamental combustion research 17

Damköhler number for low temperature fuel oxidation. In summary, the above discussions revealed that turbulent combustion in advanced engines 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 ignition Damköhler 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 conditions

To achieve higher engine efficiency and lower emissions, new combustion technologies 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 concentration 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 ࡯ᄺ䖯ሩ ㄀ 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

1.0 Low temperature ignition (LTI)

0.8

0.6 Hot ignition

Cool flame dominated 0.4 double flame (decoupled)

Transition 0.2 Single high temperature High temperature flame flame front

Locations of flame and ignition fronts/cm dominated double flame (coupled) 0 0 0.005 0.010 0.015 Time/s 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 temperature 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 premixed and diffusion flames. On the other hand, for the toluene mixture, due to the lack of

dTdx(k.m-1 a 0 10000 20000 30000 40000 b 5 monotonic non-monotonic Onset of ignition T in kemel T in kemel driven oscillation -1 -2 nm II II 4 Premixed flame shock branch detonation /5 0 + no more supersonic flame x detonation for cool spot 3 Diffusion flame branch I II III ignition advance monotonic T in kemel 2 III-1 Onset of HT1 nm shock

detonation 1 /2 +

0 Onset of n-heptane/air supersonic flame x detonation LT1 I II III 0 0 10 20 30 40 50 60 70 Location heat release/cm of acimum 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 ζ Time/ms Fig. 11

(a) The effect of thermal stratification on autoignition modes at different temperature gradients 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 instability (Sun WQ et al. 2014) 20 ࡯ᄺ䖯ሩ ㄀ 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 combustion 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 effective 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 discharge, 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

50 a b No MW, Timing 1 MW, Timing 1 No MW, Timing 2 40 MW, Timing 2 MW, Timing 3 Stable Operating Limit 30 Lean limits /% imep 20 COV 10

0 12 16 20 24 28 A/F Ratio

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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

a b

ns pulser,40 kHz

ns pulser,1 kHz c

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,

However, the physical and chemical kinetic processes in plasma assisted combustion involve 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 diagnostic 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 at XF =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

Plasma discharge Flow mixing

Ionic wind Ions/electrons O2+

Fuel fragments Temperature increase Radicals O,NO,O3

H2 Excited species CH4 C2H2

N2*(ABC) C2H4 1 O2(a Dg)

Thermal enhancement Kinetic enhancement Transport enhancement

Fig. 14

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

a K 3 b 3 a.u. OH emission X =0.34 1.6 a.u. 1.6 10 O 10 XO =0.62 10 3 3

Temperature 10 / 10 10 8 1.4 8 1.4

6 Extinction 6 1.2 1.2 4 4 1.0 1.0 2 2

Ignition 0.8 OH emission 0 0 Temperature 0.8 0.1 0.2 0.3 0.4 0.1 0.2 0.3 0.4 Local temperature/ maximum OH* emission intensity/ OH* emission intensity/ Local temperature maximum Fuel mole fraction (XF) Fuel mole fraction (XF) 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 ࡯ᄺ䖯ሩ ㄀ 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 1 radicals and intermediate species such as O, N2(*), O3,O2(aΔg), and NOx on ignition and flame propagation. Uddi et al. (2009) and Sun et al. (2010) measured the atomic O concentration 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 consumption 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)andN2(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 discharge 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.

-5 Air - Φ

10 5 Air methane, /1 0

1 O atom mole fraction/ 0 0 1234 Time/10-3 s Fig. 16

Atomic O mole fraction vs. time after a single high-voltage pulse in air and in a methane-air mixture at P =60torrandΦ =1.0 (Uddi et al. 2009) Ju Yiguang : Recent progress and challenges in fundamental combustion research 25

1017

-3 N2(B) N2(C) 16 10 N2(A)

1015 Density/cm

-50 -25 0 25 50 75 100 discharge -3 1.2 pluse cm 1.0 18 0.8 10 0.6 TALIF 0.4 Calculated 0.2

Density/ 0 -50 -25 0 25 50 75 100 Time/ns Fig. 17

Measurements of number density of excited nitrogen and atomic oxygen in air plasma (Stancu et al. 2009)

1 The effects of O3,O2(aΔg), 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 1 1 + − 1 (O2(aΔg)) in a microwave generated plasma by using the (1,0) band of the b Σg aΔg 1 Noxon system. Several thousand ppm level of O2(aΔg) was reported and its effect on flame 1 propagation was then investigated. The effect of O3 and O2(aΔg) on flame propagation speed was studied in a lifted flame (Ombrello et al. 2010a, 2010b). The experiments demonstrated

1 thatbothO3 and O2(aΔg) 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 ࡯ᄺ䖯ሩ ㄀ 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.

104

103 /ppm 2 H 2

102

1 10 C2H2 C2H2

Mole fraction C CH4 CH4

H2O H2O Temperature Temperature 100 0 0.002 0.004 0.006 0.008 0.010 Time/s 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 experimental 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 fundamental 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

a b

Cool diffusion flame Hot diffusion flame

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 investigated 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,andCH4 indicated that the model over-predicted the QOOH thermal decomposition reactions to form olefins, resulting in substantial over-estimation of

C2H4,andCH4 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 research 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 fuels 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 important 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 properties 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 combustion, 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 ࡯ᄺ䖯ሩ ㄀ 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 surrogates. 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 components, 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

Temperature/K 1200 1000 800 600 a b 105 ST RCM 5 POSF 4658 s

m 1st Gen. POSF 4658 surrogate / ppm τ 4 2nd Gen. POSF 4658 surrogate 3 4 10 10 3 POSF 4658 O2 CO CO2 H2O 1st Gen. 3 2 surrogate 10 2nd Gen. surrogate 1 102 Lgnition delay time, Lgnition delay 40

Species concentration/ 500 600 700 800 900 1000 0.8 1.0 1.2 1.4 1.6 Temperature/K 1000K/T c 400 d 90

Tu=470 K -1

-1 80 s /s . E 300 a 70

200 60 Tu=400 K

50 Jet-A 100 1st Gen JETA POSF 4658 40 3 comp. surrogate 2nd Gen 4 comp. surrogate Extinction strain rate 0 Laminar flame speed/cm 30 0.2 0.3 0.4 0.5 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 φ Fuel mass fraction Yf Equivalence ratio, Fig. 20

(a) Flow reactor oxidation data for conditions of 12.5 atm, 0.3% carbon, ϕ =1.0andt = 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 =1.0inairat∼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 ࡯ᄺ䖯ሩ ㄀ 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” derived 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 composed 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 temperatures 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 chemical 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 × −1/2 (MWfuel/M Wnitrogen) . 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

104 s m

103

102 Trimethyi dodecane S-8 nC12/iC8 Surrogate Fuel Lgnition delay time/ Lgnition delay nC16/iC16 Model Fuel 101 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1000/T [1/K] 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) surrogate 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

500 n-decane n-nonane n-heptane iso-octane n-propylbenzene toluene

-1 1,2,4-trimethylbenzene 1,3,5-trimethylbenzene /s

E 400 -

a n alkanes aromatics

300

200

100

Extinction strain rate iso-alkane Tf/500 K and To/300 K 0 0.5 1.0 1.5 2.0 2.5 3.0

-1/2 3 [Fuel]ΤΔHc(MWfuel/MWnitrogen) [cal/cm ] 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)

500 - a b -1 n decane Fuel R n-nonane R2=0.97 i /s

E n-heptane a 400 - - iso octane n alkane 1 n-propylbenzene toluene 300 -trimethylbenzene iso-octane 1,2,4 0 70 1,3,5-trimethylbenzene

toluene 0 56 200

n-propylbenzene 0 67 100

Tf/500 K and To/300 K 1,2,4-trimethylbenzene 0 44 Extinction strain rate 0 0.5 1.0 1.5 2.0 -trimethylbenzene 1,3,5 0 36 -1/2 3 RiΤ[Fuel]ΤΔHcΤ(MWfuel/MWnitrogen) [cal/cm ] Fig. 23

Left: Derived radical index (Ri) for diﬀerent fuels; Right: Universal correlation of extinction −1/2 strain rates of all tested fuels in terms of Ri × [fuel] × ΔHc × (MWfuel/M Wnitrogen) ; 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 useful 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

a 450 Extinction of diffusion flame in b 500 counterflow configuration -1 Methy1

-1 Methy1 Tf/500 K and Tair/300 K @1 atm /s propanoate E /s Fuel Ri formate E a 400 a -alkane 350 JP8POSF 0 78 SHELL SPK 0 85 for n HRJ Camelina 0 82 =1 300 i R Tf/500 K, Tox/298 K 250 HRJ Tallow 0 8 SASOL IPK 0 76 200 Methy1 Formate JP8POSF 6169 Methy1 Ethanoate SHELL SPK POSF 5729 Methy1 Propanoate 150 -octane HRJ Camelina POSF 7720 Methy1 Butanoate HRJ Tallow POSF 6308 100 Methy1 Pentanoate for iso SASOL IPK POSF 7629 Methy1 Hexanoate n-alkane Methy1 Octanoate iso-octane Extinction strain rate Extinction strain rate =0.7 Methy1 Decanoate 50 R i 0 0.5 1.0 1.5 2.0 2.5 0.5 1.0 1.5 2.0 Transport-weighted enthalpy/[cal/cm3] Transport-weighted enthalpy/[cal/cm3] -1/2 [Fuel]ΤΔHcΤ(MWfuel/MWnitrogen) 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 reduced 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 ࡯ᄺ䖯ሩ ㄀ 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 reaction, 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 computation 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 methods 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

10-2 detail (121) DRG PFA

1 atm 10-3

10-3 Ignition delay time/s Ignition delay

20 atm 10-4 50 60 70 80 90 Number of species in reduced mechnism 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

2.8 Temperature 105 CO2 2.6 2.4 100 OH 2.2 1000 K / -5 10 2.0

1.8 10-10 VODE 1.6 Log10 mass fraction

MTS Temperature 10-15 HMTS 1.4 C10H22 10-20 1.2 0 12345 Time/0.1 ms Fig. 26

Time histories of temperature and species mass fractions during ignition predicted by different 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

PFA time Chemical solver's time 100 (HMTS/VODE) Other terms Real Fuel 2-Reduced-425 species P/1 0 atm Φ/1 0 50 T0/400 K CPU time/h

0 VODE VODE/DAC HMTS HMTS/DAC HMTS/CO-DAC 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 pressure 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 reaction 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 computation 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 pressure 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

1.20 H2/O2/Ar, f=2.5

Tf b 1600 K )

-1 1.00 s . -2 cm . 0.80

0.60 Present experiments Li et al. (2007) 0.40 Davis et al. (2005) Sun et al. (2007) Mass burning rate/(g 0.20 Konnov (2007) O'Connaire et al. (2004) Saxena & Williams (2006) 0 0 5 1015202530 Pressure/atm 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 comparison 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 hydrogen 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 revisit 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 temperature 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

0.15 H2/CH4/O2/He, ϕ/0 7 H2/CH4/1000

) Tf b 1600 K -1 s . 0.12 -2 cm . 0.09 H2/CH4/9010

0.06

0.03 - Mass burning rate/(g USC MECH II

Updated H2+USC-MECH II C1-C2 0 0 5 1015202530 Pressure/atm 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 elementary 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 mechanism (HP-Mech), which include H2OandCO2 for hydrogen, methane, ethylene, C2H2,and DME oxidation at high pressure is also under development (Shen et al., 2014). A collaborative 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 decreasing 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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

108 Present study Dames and Golden (2013) Li et al. (2007) 107 -1

106

105 Rate constant/s 1 atm 4 10 10 atm

103 0.50 0.60 0.70 0.80 0.90 1.00 1000/T[K-1] 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 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 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 uncertainty analyses

To develop quantitatively predictive kinetic mechanisms, the uncertainties in experimental 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

1.2

1266 K and 2.5 atm 1.0

0.8

0.6 1368 K and 2.4 atm

OH mole fraction 0.4 1458 K and 2.3 atm 3 CH 0.2 1610 K and 2.2 atm 0 0 500 1000 1500 Timems 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 focusing 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 propagating 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 ࡯ᄺ䖯ሩ ㄀ 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

0.25

air oxidizer 0.20

0.15

L/15 mm 0.10 L/9 mm L/25 mm O2 oxidizer

Acetone mole fraction 0.05

0 0 2 4 6 8 10 12 14 16 Distance from fuel nozzle/mm Fig. 32

Comparison of acetone distributions between PLIF measurements (closed symbols), sampling measurements (open symbols), and numerical results (lines) for different burner separation 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 microtube 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

abcd Air, oxidizer efgh

acetone , oxidizer

2 OH O 1.2 0.06 Acetone LIF probe at 0 mm 1.0 probe at 8 mm 0.05 probe at 12 mm 0.8 probe at 15 mm 0.04 0.6 Pichon et al. model 0.03 OH LIF 0.4 xf=0.05 0.02 -1 fraction 0.2 a=100 s 0.01 Acetone mole LIF singals/a.u. oxygen for oxidizer 0 0 8 9 10 11 12 13 14 15 Distance from the fuel nozzie/mm 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; −1 (a)–(d) at Xf =0.20, a = 100 s , 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 ࡯ᄺ䖯ሩ ㄀ 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 S0 ( L) 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 )

-1 0 6Rw 0 4Rw 0 3Rw 0 2Rw 0 1Rw s . 240 - φ /(cm Hydrogen air, 1 atm, =3.0 u

S 220

Q 200 Vb

180

Flow-corrected 160 uncorrected

Calculated flame speed, 0 1000 2000 3000 Stretch rate, κ/s-1 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.

ρb,ad Tb,ad SL = (Sb − ub)(2) ρu Tb The linear dependence of stretched ﬂame speed on stretch is a solution in the limit of weakly stretch ﬂames. S /S0 − M K L L =1 a a (3)

Where Ma and Ka are, respectively, the Markstein number and the Karlovitz number. 50 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

80 a b adiabatic and optically thin FSNB-CK Rch/10 cm adiabatic 60 t/0 07 s) 60 flame propagation

(in Rch/50 cm at t/0 02b0.08 s 50 cm 40 -1 40 with Dt/0 01 s) s -1 . s .

Rch/10 cm 20 20

0 Velocity/cm

Velocity/cm 0 optically Ub/3 7 cm/s -20 thin Ub/14 5 cm/s -20 0 246 8101214 16 0 246 81012 Radial coordinate, r/cm Radial coordinate, r/cm 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 nonlinear 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 intermediate 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 pressure 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

Equivalence ratio, φ 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 2.0

SbNESb,Premix

SbN3PSb,Premix

1.8 Sb,cNESb,Premix

H2/air Sb,cN3PSb,Premix

SExpNESb,Premix 1.6 SExpN3PSb,Premix

SExpNESbNE S N3PS N3P 1.4 Exp b SbNQSb,Premix n-heptane /air

SbNESb,Premix - 1.2 3 order trend line forSbNQSb,Premix Relative difference Relative

1.0

0.8 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Normalized equivalence ratio, φ/(1+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 ࡯ᄺ䖯ሩ ㄀ 44 ो : 201402

Fuel (RH)

+OH

+O2 Small RO C H 2 alkane 2 3

+O +O2 +O2 2

+O2+(M) HO OH 2 H/HCO +O +CH3/O 2 +fuel +H OH /O2 O+OH

H2O3 2OH 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 temperature; 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,andRO2 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 spectroscopy (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 atmospheric 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

Τ10-3

Mole fraction 1

0 600 700 800 900 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 interference 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 rotation 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 sensitivity 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 ࡯ᄺ䖯ሩ ㄀ 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 fundamental 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.

Modulated polarization Heated flow reactor

ωt) B0 cos(

Demodulate at ω Input polarization 0

-0.5 Signal/V -1.0

1396.80 1396.92 1397.04 Frequency/cm-1 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

a b 1200 HO2 25 Expt. H2O2 1000 Liu et al. 20 Zhao et al. 800 Τ5 15 600

10 400

5 200 Concentration/ppmv Concentration/ppmv

0 0 500 600 700 800 400 600800 1000 1200 Temperature/K Temperature/K 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 recently, 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 history. 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 ࡯ᄺ䖯ሩ ㄀ 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 Damköhler 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 reported. 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 stratifications can be one of major causes of engine knocking. Non-equilibrium plasma can significantly 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 discovered by using plasma activated ozone generation. However, there is still a large knowledge gap in low temperature chemistry and cool flames. Many fundamental combustion phenomena 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 combustion 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 developed 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 detailed 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, adaptive 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 chemistry 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 dependent 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 elementary 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 ࡯ᄺ䖯ሩ ㄀ 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 experimental 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 compression machines, and shock tubes all have large uncertainties in physical interpretation, boundary conditions, and probe perturbation, and need to be revisited the existing experimental 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 contamination by H2OandNOx on supersonic combustion have complicated the experimental studies for decades. Recently, as reported by Jiang and Yu (2014) the 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 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 experimental 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,andRO2 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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(䋷ӏ㓪ྨ: ྰᅫᵫ) Ju Yiguang : Recent progress and challenges in fundamental combustion research 71

➗⚻෎⸔ⷨおⱘ䖯ሩ੠ᣥ៬

⧮䆦ܝ †

Department of Mechanical and Aerospace Engineering, Princeton University, New Jersey, USA

ᨬ㽕䍙䖛 80% ⱘϪ⬠ⱘ㛑⑤䕀ᤶᰃ⬅➗⚻ᮍ⊩ᴹᅲ⦄ⱘ. থሩৃ߽⫼᳓ҷ➗᭭ⱘ ⏙⋕੠催ᬜⱘᮄൟথࡼᴎᰃ㾷އৃᣕ㓁㛑⑤থሩⱘ݇䬂Пϔ. ೼➗⚻ⷨお乚ඳ, ᅲ⦄ 䖭ϔⳂᷛⱘᣥ៬ᰃ㽕ᧁ⼎Ң➗᭭ߚᄤࠄথࡼᴎⱘ໮ሎᑺ➗⚻䖛⿟Ё࣪ᄺডᑨ੠☿✄ ࡼ࡯ᄺᴎ⧚, থሩ催ᬜ, ᅮ䞣ⱘ᭄ؐ῵ᢳᮍ⊩੠ᓔথᮄⱘ➗⚻ᡔᴃ. ᴀ᭛Ң 7 Ͼᮍ䴶㓐䗄᳔䖥޴ᑈ➗⚻乚ඳⱘ෎⸔➗⚻ⷨおⱘ䖯ሩ੠ᣥ៬. ᅗӀࣙᣀԢ⏽⏙⋕➗⚻ⱘথࡼᴎ ᡔᴃ, ᵕ䰤ᴵӊϟⱘ➗⚻ᴎ⧚੠⦄䈵, ᳓ҷ➗᭭੠⏋ড়➗᭭῵ൟ, ໮ሎᑺ࣪ᄺডᑨ῵ᢳ ᮍ⊩, 催य़➗⚻ডᑨࡼ࡯ᄺ, ෎⸔➗⚻ⱘᅲ偠ᮍ⊩, ੠ܜ䖯⌟䞣ᡔᴃ. ᴀ᭛佪ܜҟ㒡ഛ 䞣य़㓽⚍☿ (HCCI), ডᑨ᥻ࠊय़㓽⚍☿ (RCCI) ҹঞ๲य़➗⚻ㄝᮄൟথࡼᴎⱘὖܙؐ ᗉ, 䆘䗄➗᭭⡍ᗻ੠Ԣ⏽➗⚻ডᑨ䖛⿟ᇍ␡⌕➗⚻੠থࡼᴎⱘᕅડ, 䅼䆎থሩ෎⸔➗ ⚻ⷨおⱘᖙ㽕ᗻ. ㄀Ѡ, 㓐䗄➗᭭⌧ᑺߚሖ➗⚻, ⿔㭘➗⚻, ދ♢➗⚻, ҹঞㄝ⾏ᄤԧ ࡽ➗ㄝᵕ䰤➗⚻ᴵӊϟⱘᮄⱘ➗⚻⦄䈵੠☿✄ᴎࠊ. ㄀ϝ, ҹ㟾ぎ✸⊍੠⫳⠽᷈⊍Ў ՟ᴹ䅼䆎ᓎゟ῵ᢳⳳᅲ➗᭭੠᳓ҷ➗᭭ⱘ⏋ড়➗᭭῵ൟⱘᮍ⊩. ҟ㒡⌏ᗻ෎ᣛ᭄੠ 䕧䖤ࡴᴗⱘডᑨ⛧ⱘὖᗉᑊ⫼ᴹ↨䕗➗᭭ⱘ催⏽ডᑨ⡍ᗻ੠䆘Ӌ➗᭭ⱘߚᄤ㒧ᵘᇍ ➗⚻⡍ᗻⱘᕅડ. ㄀ಯ, 䆘䗄䆺㒚࣪ᄺডᑨᴎ⧚ㅔ࣪ⱘᮍ⊩. ҟ㒡໮ᯊ䯈ሎᑺ (MTS) ⱘ࣪ᄺডᑨⱘ῵ᢳ੠ࡼᗕ݇㘨ᗻ㞾䗖ᑨᴎ⧚ㅔ࣪ (CO-DAC) ⱘᮍ⊩ᴹᦤ催䆺㒚࣪ᄺ ডᑨᴎ⧚ⱘ䅵ㅫᬜ⥛. ㄀Ѩ, 䅼䆎催य़➗⚻ⱘ☿✄Ӵ᪁䗳ᑺⱘᅲ偠⌟䞣㒧ᵰҹঞ催य़ ➗⚻࣪ᄺডᑨᴎ⧚᠔ᄬ೼ⱘ䯂乬, ᑊߚᵤ催य़➗⚻ⱘ݇䬂㒘ߚ੠ডᑨ䏃ᕘ. ㄀݁, 䆘䗄⌟䞣☿✄䗳ᑺ੠㒘ߚㄝ෎⸔➗⚻ᅲ偠ᮍ⊩੠῵ൟЁⱘ䯂乬੠䇃Ꮒᴹ⑤. ҟ㒡ϔѯ

ᬊ〓᮹ᳳ:2014-01-29; ᖅ⭘᮹ᳳ:2014-03-16; ೼㒓ߎ⠜ᯊ䯈: 2014-04-01 † E-mail: [email protected] ᓩ⫼ᮍᓣ: Yiguang Ju. Recent progress and challenges in fundamental combustion research. ࡯ᄺ䖯ሩ, 2014, 44: 201402 c ǉ࡯ᄺ䖯ሩǊ⠜ᴗ᠔᳝ 72 ॏ༰ࠩႺ ㄀ 44 ो : 201402

ᬍ䖯⌟䞣ᮍ⊩੠ᦤ催⌟䞣㊒ᑺⱘᮍ⊩. ᳔ৢ, ҟ㒡⌟䞣Ԣ⏽➗⚻Ёⱘ݇䬂㒘ߚ੠㞾⬅ ෎ⱘ⌟䞣ᮍ⊩੠᳔ᮄ䖯ሩ.

Љ२ڛ䬂䆡 ඙ӝ௷ॸ, ௷౮ֱ࿫ݯस, տѤէ੦થ, ಬֺི֥, ݷ݇

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 propulsion, 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).