Conference Paper

NREL/CP-540-46738

May 2010

Modeling the Fuel Spray and 

Combustion Process of the Ignition 

Quality Tester with KIVA-3V

G.E. Bogin, Jr., and A.M. Dean

Colorado School of Mines

A. DeFilippo, J.Y. Chen, and G. Chin

University of California, Berkeley

J. Luecke, M.A. Ratcliff, and B.T. Zigler

National Renewable Energy Laboratory

Presented at the Fall Meeting of the Western States Section of the 

Combustion Institute 

Irvine, California

October 26−27, 2009
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Modeling the Fuel Spray and Combustion Process of the Ignition Quality 

Tester with KIVA-3V

Gregory E. Bogin Jr.1, Anthony DeFilippo 2, J.Y. Chen 2, Gregory Chin 2, Jon Luecke 3

Matthew A. Ratcliff 

, 3

, Bradley T. Zigler 3, Anthony M. Dean 1

1

Golden, Colorado 80401, USA

Colorado School of Mines,

2

Berkeley, California 94720, USA

University of California, Berkeley,

3

Golden, Colorado 80401, USA

National Renewable Energy Laboratory,

Presented at the 2009 Fall Meeting of the Western States Section of the Combustion Institute

Hosted by the University of California, Irvine, Irvine, CA

Oct. 26-27, 2009

Development of advanced compression ignition and low-temperature combustion engines is increasingly dependent 

on chemical kinetic ignition models. However, rigorous experimental validation of kinetic models has been limited 

as a result of several factors. For example, shock tubes and rapid compression machines are often limited to 

premixed gas-phase studies, precluding the use of more realistic, low-volatility diesel or biodiesel surrogates. The 

Ignition Quality Tester (IQT) constant-volume spray combustion system measures ignition delay of low-volatility 

fuels; therefore, the IQT has the potential to validate ignition models experimentally. However, a better 

understanding of the IQT’s fuel spray and combustion processes is necessary to facilitate chemical kinetic studies. 

KIVA-3V is utilized in developing a three-dimensional computational fluid dynamics (CFD) model that accurately 

and efficiently reproduces ignition behavior and temporally resolves temperature and equivalence ratio regions 

inside the IQT. The model’s fuel spray characteristics (e.g., velocity, cone-angle, oscillations) are experimentally 

validated; n-heptane is initially studied because of the simplicity of its chemical kinetics and use as IQT calibration 

fuel. Reduced/skeletal n-heptane chemical mechanisms (60, 42, and 33 species) and one-step chemistry are 

employed. The CFD results indicate combustion is governed by autoignition kinetics, and perturbations/oscillations 

in the fuel spray have significant effects on the combustion process, as verified experimentally. The CFD model 

provides insight into the complex interaction between the fuel spray and combustion processes, which is vital to 

expanding the fuel research capabilities of the IQT.

1. Introduction

Enhanced understanding of kinetic pathways to combustion autoignition has become 

increasingly important to the development of advanced combustion engines and fuels. 

Homogeneous charge compression ignition (HCCI) and other forms of low-temperature 

combustion (LTC) strategies rely on fuel autoignition kinetics to control combustion timing [1].

Additionally, the autoignition characteristics of new generation biofuels are of current great 

interest [2,3]. Development of accurate chemical kinetic models for the ignition of diesel and 

biodiesel model compounds relies on well-characterized experiments [4]. However, rigorous 

experimental validation of these kinetic models has been limited for a variety of reasons. Shock 

tubes and rapid compression machines are typically limited to premixed gas-phase studies, for 

example [5,6]. Although some progress in studying lower vapor pressure fuels has been made 

with these devices [7,8], other research platforms may complement this work and extend ignition 

kinetics studies.
2

The Ignition Quality Tester (IQT) is a constant-volume combustion chamber experimental 

apparatus developed to measure ignition qualities of diesel type fuels [9,10,11,12,13]. The 

American Society for Testing and Materials (ASTM) method D6890-08 was developed around 

the IQT device to allow rapid determination of derived cetane number (DCN) [14]. The D6890 

method calculates DCN for a fuel based on correlation of averaged ignition delay times from a 

series of IQT injection events, to reference tests using the ASTM D613 engine test method [15]. 

Since the IQT is a constant-volume spray combustion system that allows ignition and 

combustion studies of low-volatility fuels, the IQT has potential to generate experimental data 

relevant to validating kinetic ignition models by virtue of its well-controlled temperature, 

pressure, and spray fuel injection. IQT-based DCN measurements have been shown to be reliable 

over a range of cetane numbers for middle distillate and some nonconventional diesel fuels

[16,17,18]. 

The IQT, which burns fuel injected into a high-pressure chamber, conveniently quantifies 

ignition processes for traditional hydrocarbon fuels through a semi-empirical correlation between 

measured ignition delay and engine-based cetane number [13]. This correlation will not likely 

hold for anticipated new fuels derived from biomass, which will have properties that are different 

from those of traditional fuels. A better understanding of the IQT combustion process may lead 

to its use as a development and validation platform for kinetic models of novel fuels, as the 

device provides a well-controlled environment for such tests in comparison to a traditional 

engine. Experimental parameters such as charge pressure, chamber wall temperature, air 

temperature, oxygen concentration, and mass of fuel injected are easily quantifiable for model 

implementation. The IQT offers the additional benefit of a low fuel quantity requirement 

(capable of testing with approximately 50 mL), increasing its desirability for testing 

experimental biofuels produced in small amounts. 

In this analysis, measurements of IQT spray events at ambient and pressurized conditions are 

used in retrieving the physical spray characteristics necessary for development of a threedimensional KIVA-3V numerical model. Values for spray velocity, mass flow rate, droplet size, 

and other fuel nozzle effects are selected such that the spray model matched measurements from 

high-speed imaging of ambient spray events. With a valid physical model in place, chemical 

kinetics are applied to the simulation, and the results of the combustion simulation are compared 

with pressure rise data from high-pressure IQT events. Simulations uncover the importance of 

autoignition chemistry on IQT combustion events. Additionally, study of model results allow for 

comparison of the relative effects of droplet breakup, droplet evaporation, and chemical kinetic 

delay in contributing to overall ignition delay within the IQT. Such a parametric understanding 

allows for developing the potential of using the IQT as a chemical mechanism validation tool, 

filling an experimental void and complementing other research platforms.
3

2. Experimental Setup and Computational Model

2.1 IQT overview

The ignition quality tester (IQT) is a bench-scale, constant-volume combustion device (Figure 1) 

with a spray injection system designed for the direct measurement of the ignition delay of liquid 

fuels. Ignition delay is then used to calculate a derived cetane number (DCN) using the ASTM 

D6890-08 method with high repeatability (±0.85 DCN, 34-61 DCN range) [14], providing high 

sensitivity for middle distillate fuels. A piezo-electric pressure transducer installed in the 

combustion chamber measures the pressure rise during the combustion event; the time delay 

between the start of injection (SOI) and the rise in combustion pressure to the combustion 

pressure recovery point of injected fuel determines the ignition delay for various fuels [9,10] 

(Figure 2). The ignition delay comprises both physical processes (e.g., spray breakup, 

vaporization, air entrainment) and the chemical kinetics of ignition [9]. A pneumatically driven 

mechanical fuel pump is used for the injection of the fuel along with a single-hole S-type delayed 

(inward opening) pintle nozzle. The injection pressure, as experimentally determined, is 

approximately 225 bar during the main injection period; n-heptane (≥99.5%, Fluka) is used for 

all experiments in this study and is chosen because of its use as a calibration fuel for the IQT, 

with a reference ignition delay time of 3.78 ms [14].

 

Figure 1. The Ignition Quality Tester (IQT)

(Note: All photos were taken by the authors.)
4

Figure 2. Typical combustion pressure and needle-lift traces used to determine ignition 

delay; n-heptane, m ≈ 73 mg/inj., ignition delay = 3.78 ms

Several electric rod heaters are inserted into the outer wall of the stainless steel combustion 

chamber [11]; they maintain a constant charge temperature of approximately 550°C (in the 

vicinity of the nozzle tip). There is approximately a 40°C temperature gradient (increase) to the 

second thermocouple (7 cm down range) along the axial direction of the combustion chamber. 

The lower injection end temperature is due to the heat transfer to the coolant around the injection 

nozzle body and surface exposure to ambient air (Figure 3). The chamber (volume ≈ 0.21 L) is 

pressurized to approximately 21 bar prior to injection of the fuel [10,14].

Figure 3. Schematic of the IQT combustion chamber
5

2.2 Spray characterization of the IQT fuel injection system 

The goal of validating ignition kinetic models using the IQT requires a thorough understanding 

of the combustion and injection processes within the IQT, as the measured ignition delay is a 

combination of the physical dynamics of the spray and combustion chemistry. A threedimensional model was developed and utilized to gain a better understanding of the injection and 

combustion processes. Compared with a reciprocating engine, the well-controlled experimental 

parameters of the IQT—such as charge pressure, chamber wall temperature, air temperature, 

oxygen concentration, and mass of fuel injected—facilitate accurate implementation of these 

parameters into the model. This improves the model’s ability to predict realistic and 

representative combustion events. To ensure the accuracy of the modeled spray, experimental 

tests capture IQT injection system spray events at ambient conditions using high-speed chargecoupled device (CCD) imaging.

2.2.1 High-speed imaging. The IQT injection system is placed in a fume hood and controlled 

using the system’s software to study fuel spray under ambient conditions (Ta = 22°-25°C, Pa = 

0.87 bar). The injection pressures (~225 bar at 0.027-in. needle-lift) are the same ones used 

during normal operation of the IQT. The needle-lift sensor is attached to the injector body during 

imaging to correlate the position of the injector needle with the fuel spray. The fuel spray images 

are captured using a Photron SA3 (120k-M2) high-speed digital camera capable of capturing 

images at 250,000 frames per second (fps). For this study, images are captured at 10,000 fps, 

resulting in a 0.1 ms time-step and 512x256 resolution for a main injection period of 

approximately 2 ms. However, high-speed imaging continued over a period of 4–6 ms to capture 

secondary fuel spray injections (see the needle-lift traces in Figure 2). High-speed imaging of the 

fuel spray provides injection velocity, cone angle, and penetration depth as a function of the 

injection period (Figure 4). 

Figure 4. Spray imaging (0.4 ms after SOI) (cone angle: ~35°, penetration depth: 48.38 mm, 

spray tip velocity: 142.5 m/s); n-heptane
6

Photron FASTCAM Viewer software is used to determine the penetration depth of the fuel spray 

by using the diameter of the nozzle tip as a scale (see Figure 4). The spray tip velocity is 

calculated based on the penetration depth for each time step of 0.1 ms along with the cone angle. 

The CCD imaging also provides insight into the nonuniformity of the fuel spray and captures the 

highly complex spray patterns that develop during the injection process (Figure 5). The 

nonuniformity of the spray pattern is due to the use of an inward opening pintle nozzle. The 

geometry of the injector needle and pintle tip allows a small fraction of the fuel to exit during the 

beginning of the injection process before allowing the bulk of the fuel to exit the nozzle at a 

higher velocity and wider angle. The nonuniformity of the spray patterns can have a significant 

effect on the outcome of the predicted combustion event; therefore, it is currently under 

investigation and will be implemented in the numerical model.

 a) 0.1 ms after SOI b) 0.2 ms after SOI c) 0.3 ms after SOI d) 0.4 ms after SOI

 e) 0.5 ms after SOI f) 0.6 ms after SOI g) 0.7 ms after SOI h) 0.8 ms after SOI

 i) 0.9 ms after SOI j) 1.0 ms after SOI k) 1.2 ms after SOI l) 1.3 ms after SOI

Figure 5. High-speed images of the fuel spray during typical injection process; n-heptane, 

Pf ≈225 bar
7

2.2.2 Fuel injection parameters. The discharge coefficient is defined as the ratio of the 

experimentally determined mass injection rate to the theoretical mass injection rate [19]. As a 

result of the complex geometry of the S-type pintle nozzle and injector needle movement, the 

mass injection rate changes as functions of needle displacement (injection pressure) and nozzle 

orifice. Because the bulk of the fuel is injected from 2.5 to 3.5 ms (Figure 2), the injection 

process is simplified here by considering only the steady-state fuel flow during the main 

injection period, in which the injection pressure and nozzle orifice are constant. Thus, the 

discharge coefficient calculated from the mass flow rate during this period is considered the 

input parameter for the numerical model. Further work is required to determine the discharge 

coefficient during the entire injection process, which will lead to a detailed look-up table that 

accounts for the change in needle-lift position (injection pressure) and orifice area. The measured 

fuel spray tip velocities, along with needle-lift position as a function of the injection period, are 

in the current look-up table. The fuel spray parameters from both experiments and imaging 

(Table 1) are utilized in the numerical model. Initial droplet size is not measured; thus, maximum 

droplet size is estimated based on the spacing of the orifice of the injector nozzle as a function of 

time; details are presented later in this paper. The mass of fuel injected is an average of three test 

collections of the fuel (each composing 10 injections) as directed by the IQT manual [20].

Table 1. Fuel spray parameters for numerical model

Fuel n-heptane

Fuel temperature (°C) ~56

Air temperature (°C) ~590

Mass of fuel injected 

(mg/inj.)

73–76

Injection duration (ms) 1.8–2

Discharge coefficient (CD) ~0.8 (steady-state)

Cone angle 7°–35° (over range of injection period)

Initial droplet size estimated based on nozzle orifice

Injection velocity (m/s) 0–182 (over range of injection period)

2.3 Numerical model

Reacting fuel spray is simulated using a modified version of KIVA-3V software [21]. The code 

couples Lagrangian particle tracking of liquid spray droplets with Eulerian simulation of threedimensional fluid flow as governed by the Navier-Stokes equations. These equations are solved 

on a structured grid domain of 59,868 cells generated using ANSYS ICEM computational fluid 

dynamics (CFD) commercial software (Figure 6). The Reitz Kelvin-Helmholtz Raleigh-Taylor 

(KHRT) spray breakup model [22] governs droplet breakup, as implemented in KIVA-3V by 

Professor Tsai [23]. A custom look-up table coded for this analysis specifies the time-varying 
8

liquid injection velocity, mass flow rate, initial droplet size, and spray cone angle. Single step 

and reduced/skeletal chemical mechanisms simulate n-heptane combustion. Mechanisms include 

a 33-species mechanism from Nissan [24], a 42-species mechanism created by adding NOx

reactions and removing iso-octane reactions from a 41-species mechanism developed at the 

University of Wisconsin [25], and a 60-species mechanism developed at the University of 

California-Berkeley [26].

Figure 6. Isometric view shows the block structure of the ~60,000 cell IQT grid

3. Results

To create a functional numerical model of the IQT, the modeled spray physics and combustion 

chemistry are tuned to match experimental conditions. This is accomplished by first developing a 

valid model for the flow physics of a nonreacting spray and then adding chemical reactions. 

Once the model accurately reproduces experimental IQT behavior, the relative effects of 

physical and chemical phenomena are compared.

3.1 Tuning the spray parameters

The spray model is tuned at ambient conditions, in which high-speed imaging provides a visible 

time history of flow structure without the confounding effects of chemical reactions. Defining 

the spray requires setting the initial droplet diameter, injected velocity, instantaneous mass flow 

rate, spray cone angle and thickness, and fuel temperature. The characteristic Kelvin-Helmholtz 

breakup time directly scales with the input coefficient, B1, which accounts for the internal effects 

of the injector [22]; thus, B1 must be empirically specified, though it is expected to fall within 

the range of 1.73 to 60.

Instantaneous injected mass flow rate is assumed to be proportional to measured instantaneous 

injector valve needle lift, with the flow rate normalized such that the integral of the mass flow 

rate gives a total injected mass of 73 mg. The time history of injector valve needle lift also leads 
9

to a specification of initial droplet diameter, with the initial Sauter Mean Diameter set equal to 

the nozzle opening (~120 μm).

With all other injection parameters specified, B1 can be tuned in KIVA until the time history of 

spray penetration depth matches the spray penetration depth measurements at ambient conditions 

(Figure 7). A visual comparison of the time history of the spray penetration depth comparing the 

high-speed imaging and KIVA is in Figure 8.

Figure 7. Spray penetration depth comparisons of experiments and model

a) 0.1 ms after SOI

b) 0.2 ms after SOI

0

50

100

150

200

250

0 0.5 1.0 1.5 2.0

Model

data

Time (ms)

P

e

n

etratio

n

D

e

pth (m

m)
10

c) 0.3 ms after SOI

d) 0.4 ms after SOI

e) 0.5 ms after SOI

f) 0.6 ms after SOI

Figure 8. Visual comparison of the spray penetration depth; n-heptane, Pf = 225 bar, Pa = 

0.87 bar, Tf ≈ 30°C, Ta ≈ 25°-30°C

Transitioning from ambient conditions to the IQT combustion chamber environment (Pa = 21 bar 

and Ta = 550°C−590°C) requires an adjustment of spray velocity in the model, as the pressure 

drop across the injector will be smaller and produce a slower initial injection velocity in 

comparison to ambient conditions. Bernoulli’s equation accomplishes this scaling by relating 

fuel injection pressure, air pressure within the chamber, and the density of the fuel injected 
11

(Equation 1). The cone angle of the spray at ambient conditions is assumed to be relatively 

unchanged with higher back pressures in the combustion chamber [27].

D

f

f a C

P P

v m s ⋅ ⋅ − = ρ

2 [ ] ( / ) , Equation (1)

where Pf = fuel pressure, Pa = pressure of air in the chamber, ρf = density of the fuel, and CD = 

the discharge coefficient.

3.2 Chemical mechanism comparison for high-pressure IQT system

With valid spray physics implemented, reacting behavior is modeled through the inclusion of an 

n-heptane chemical mechanism in the three-dimensional KIVA model. Single-step, 33-species, 

42-species, and 60-species mechanisms vary in their simulated overall ignition delay behavior, as 

shown by the pressure histories of Figure 9. 

The 42-species n-heptane mechanism predicts the ignition delay times closest to the 

experimental ignition delay times, which is explained by the conditions under which the 

mechanism was validated when developed. Designed for internal engine applications, the 42-

species n-heptane mechanism was validated under direct injection diesel conditions and was 

specifically tuned to capture the rich onset of autoignition in regions where fuel evaporation has 

locally cooled the mixture [25]. This contrasts with the 33-species mechanism, which was tuned 

primarily for lean homogeneous charge compression ignition (HCCI) combustion. Using the 33-

species mechanism under the predicted fuel-rich IQT combustion conditions results in an overall 

ignition delay of ~1.7 ms longer than the experimental value. The 33 species mechanism’s 

overprediction of ignition delay at this rich equivalence ratio, Φ ≈ 2.0, possibly stems from 

model’s exclusion of H, H2, CH3, and CH4 reactions [24]. 

The 60-species mechanism, which was validated for lean HCCI combustion environments [26], 

predicts ignition delays ~0.9 ms shorter than those in the experimental data. The variation in 

performance of these validated chemical mechanisms in the IQT environment indicates the 

IQT’s suitability as a validation tool for direct-injection autoignition engines, because of the 

IQT’s similarities to such an environment.

Differences in modeled ignition delay time between the chemical mechanisms likely result from 

the variance in chemical reactions and reaction rates related to autoignition chemistry. Chemical 

autoignition delay times for each mechanism, calculated using a Senkin zero-dimensional wellmixed reactor (WMR) model [28] initially at 590°C and 21 bar, are in Figure 10. In addition to 

the reduced mechanisms, the full detailed n-heptane mechanism from Lawrence Livermore 

National Laboratory was employed as a reference [29]. These simulations show that the 
12

differences in chemical autoignition delay times within the range of equivalence ratios at which 

autoignition initiates (1 < Φ < 3) are comparable to the differences in overall delay in the 3-D 

models. For example, the 60-species mechanism has a zero-dimensional chemical delay time 1.3 

ms shorter than that of the 42-species mechanism, while the KIVA modeled ignition delay time, 

using the 60-species mechanism, is about 1.5 ms shorter when flow physics are included. The 

42-species n-heptane mechanism predicts ignition delay times closest to the experimental 

ignition delay times; thus, the 42-species n-heptane mechanism is utilized for further 

investigation of the combustion event inside the chamber.

Figure 9. Varying chemical mechanism affects the predicted ignition delay

Figure 10. Chemical mechanism ignition delay time dependence on Φ explains differences 

in behavior; autoignition occurs where Φ is slightly rich, as seen with the 33-species 

mechanism, with the longest delay time, and with the 1-step mechanism, with the shortest 

delay time

10

30

50

70

0 2 4 6 8

60 sp

42 sp

33 sp

data average

1step

Time AfterInjection (ms)

Pre

s

s

ure (b

ar) 0.0001

0.001

0.01

0.1

0 2 4 6 8 10

LLNL Detailed

60sp (Based on LLNL)

33sp

42sp

1-step

Equivalence Ratio (-)

Ignition Delay (s)
13

Further evidence of the governing effects of autoignition on the predicted combustion event can 

be seen in an evolution of the KIVA model at the onset of ignition. Dispersed locations within 

the chamber ignite as favorable conditions for autoignition are met, and no single propagating 

diffusion flame front dominates the process (Figure 11). The observed rich onset of autoignition 

near Φ = 2 for n-heptane mixtures that have been cooled by evaporative cooling is well 

documented in the literature [30,25].

t = 1.41 ms

t = 3.69 ms 

t = 4.29 ms
14

t = 4.42 ms

t = 4.77 ms

Figure 11. The role of autoignition is shown by the time evolution of the temperature 

contour plots (left) and the corresponding plots of temperature vs. equivalence ratio (right), 

which demonstrate that the onset of combustion occurs primarily in the rich regions 

around Φ = 2

3.3 Comparing the relative effects of physics, chemistry, and thermodynamics on ignition delay

For the IQT to become a useful tool for chemical mechanism validation, the relative influence of 

chemical interactions must be higher than the uncertainties in spray fluid mechanics. A series of 

physical processes precede chemical autoignition; the overall ignition delay time from start of 

injection is thus roughly approximated by a combination of breakup time, evaporation time, and 

chemical reaction time (Figure 12). The following analysis examines the characteristic times of 

these processes for comparison purposes. These processes operate continuously on the spray; 

therefore, initial sites of chemical autoignition may influence remaining unburned fuel spray.

Figure 12. Droplet breakup and evaporation processes precede chemical autoignition
15

3.3.1 Droplet breakup time. Droplets leaving the injector nozzle that are on the order of the 

pintle opening in size would take a long time to evaporate and combust if not for the 

aerodynamic forces that lead to their breakup into smaller droplets. In this model, the droplet 

breakup is modeled considering both Kelvin-Helmholtz and Raleigh-Taylor instabilities [22]. 

The KHRT breakup algorithm [31] was coded into MATLAB® and applied to a single droplet 

120 μm in diameter traveling at an initial velocity of 120 m/s, which is typical of a droplet 

injected into the KIVA-3V model. Correct quantification of momentum transfer from the droplet 

to the surrounding air complicates the analysis, as the relative droplet velocity in the surrounding 

air governs breakup events. For this reason, two analyses were run: one in which the surrounding 

air stays stagnant and one in which the air gains velocity as the droplet loses velocity, 

implemented by doubling the rate at which drag forces decrease the relative velocity. Breakup 

rates in both cases slow after 0.2 ms (Figure 13), so 0.2 ms is chosen as the characteristic 

breakup time. Though the breakup times are coincidentally similar, the stagnant air model ends 

with a 21 μm droplet traveling at 43.4 m/s and the drag-doubled model ends with a 38 μm 

droplet traveling at 32.7 m/s. The effects of these differences in final droplet velocity and 

diameter are described in the following section, in the discussion of the evaporation time 

calculation.

Figure 13. Drag model treatment affects the KHRT breakup model predictions

3.3.2 Droplet evaporation time. Droplet vaporization is a critical step in spray combustion, as it 

generates the vapor necessary for gas-phase combustion. Droplet diameter decreases as heat 

transfer from the surrounding gases evaporate the liquid fuel. The lifetime of a droplet is 

governed by the rate of heat transfer to the droplet and its initial size. Convective effects increase 
16

the heat transfer rate such that droplets moving faster have shorter lifetimes. In Figure 14, results 

are charted of numerical simulations of droplet lifetimes at varying initial diameters and 

velocities, demonstrating these important relations. In the previous section, a 21 μm diameter 

droplet traveling at 43 m/s and a 38 μm diameter droplet traveling at 32.7 m/s were presented as 

the results of 0.2 ms of breakup processes under varying momentum transfer rates. Supposing 

now that this droplet evaporates, the numerical model suggests that it will turn completely into 

vapor in 0.5 ms, given the initial conditions resulting from the stagnant air case, or in 1 ms, given 

the initial conditions resulting from the double-drag case. At this point, the fuel is in gas phase, 

and assuming well-mixed conditions, combustion chemistry begins. 

Figure 14. Projected lifetime for a single droplet decreases as droplet velocity increases and 

as droplet initial diameter decreases

3.3.3 Chemical reaction time. Chemical oxidation mechanisms have associated induction 

periods (i.e., chemical ignition delay) during which initial hydrogen abstraction by oxygen 

produces alkyl, hydroperoxyl, and hydroxyl radicals, leading to the chain reactions that consume 

the hydrocarbon and release heat. The KIVA model results described showed that the 42-species 

mechanism most accurately reproduces IQT behavior. For this mechanism, the zero-dimensional, 

well-mixed reactor simulation (see Figure 10) demonstrates that the chemical ignition delay 

times in the relevant equivalence ratio range vary from 1.8 ms at Φ = 1 to 1.0 ms at Φ = 3. 

3.3.4 Discussion. A compilation of the ranges of characteristic times from the preceding 

analyses is presented in Table 2. Uncertainties in these values come from treatment of 

momentum transfer to the surrounding fluid. Additional discrepancy from actual behavior comes 

from the serial nature of the calculations, the lack of calculation of a characteristic mixing time 

for the turbulent flow, and the assumption of constant temperature in the ambient air.

0

0.002

0.004

0.006

0.008

0 20 40 60

50m/s

25m/s

10m/s

1m/s

Droplet size (μm)

Life tim

e (s)
17 

Table 2. Delay time breakdown comparison 

Phenomenon

ZeroDimensional 

Parametric 

Study

Three-Dimensional 

KIVA-3V Model

IQT Experiment

Breakup time (KHRT 

model) 

0.2 ms

Processes modeled 

simultaneously 

Processes occur 

simultaneously 

Evaporation time (single 

droplet model) 

0.5 ms–1 ms

Chemical ignition delay 

(zero-dimensional WMR, 

42 species mechanism)

1.0 ms–1.8 ms

Total Delay Time 1.7 ms–3 ms 4.2 ms 3.78 ms

4. Conclusions

In this study, a KIVA-3V model is developed for the IQT spray combustion system and tested 

with n-heptane. The model predicts that the combustion event is governed by autoignition, and 

that dispersed ignition events occur throughout the combustion chamber. KIVA predicts an 

ignition delay time of approximately 4.2 ms in comparison to the experimental ignition delay 

time of 3.78 ms; further investigation into the overprediction of ignition delay time is required. 

Modeled differences show that overall ignition delay changes significantly when chemical 

mechanisms vary in their chemical ignition delay time; thus, performing a sensitivity analysis of 

the various chemical reactions and reaction rates in each mechanism may provide insight into the 

cause of the varying prediction of chemical ignition delay times. 

 

The efficacy of validating fuel combustion kinetic mechanisms during spray combustion using 

the IQT depends on the relative importance of the chemical reaction time to the overall ignition 

delay. An accurate understanding of the physics of the fuel spray is thus vital for capturing and 

isolating physical effects on the overall ignition delay time. The physics of the fuel spray 

implemented in the model are based on a detailed experimental characterization of the fuel spray 

and an analytical estimation when necessary. The KIVA-3V model of the IQT combustion 

chamber allows a comparison of the overall ignition delay times through sensitivity analyses of 

various experimental parameters and the use of different reduced chemical mechanisms. 
18

Simplified models of droplet breakup, evaporation, and chemical ignition solved serially provide 

insight into the relative impact of chemical mechanism, initial droplet size, and initial droplet 

velocity on the overall ignition delay time. This leads to a better understanding of the predicted 

overall ignition delay times from the KIVA model, in which physics and chemistry are coupled. 

The chemical ignition delay time (42 species) accounts for approximately half (at Φ = 1) of the 

overall ignition delay time using a zero-dimensional, well-mixed reactor model. The physical 

ignition delay time (droplet breakup and evaporation) accounts for the other half of the overall 

ignition delay time, and the time necessary for droplet evaporation is dominant. Thus, reducing 

the initial droplet size and increasing its initial velocity will reduce the overall impact of the 

spray physics on the overall ignition delay time, permitting a more direct study of the chemical 

ignition delay times between various fuels. Future analyses will show if the relative impact of 

chemical ignition delay can be improved by using a higher temperature spray with smaller and/or 

faster droplets to improve breakup and evaporation.

The KIVA-3V model provides detailed insight into the coupling of the fuel spray and 

combustion chemistry, providing valuable information about the processes governing 

combustion within the IQT chamber. Zero-dimensional modeling, in contrast, allows the physics 

of the fuel spray and combustion chemistry to be decoupled, so that parametric effects can be 

compared. The greater understanding of spray physics and combustion chemistry gained from 

these models will ultimately permit optimization of the experimental system, leading to a robust 

system with engine-like conditions in which chemical kinetics studies can be performed. The 

model most accurately predicts ignition delay using a 42-species chemical mechanism for nheptane, which was originally validated under spray combustion conditions in a diesel engine. 

Thus, for direct-injection, autoignition applications, the well-controlled conditions of the IQT 

make it a potentially attractive chemical mechanism validation platform.

Acknowledgements

The authors wish to thank the U.S. Department of Energy Vehicle Technologies Program and 

Program Manager Kevin Stork for their support of this fuels research.
19

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F1147-E(10/2008) 

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4. TITLE AND SUBTITLE

Modeling the Fuel Spray and Combustion Process of the Ignition 

Quality Tester with KIVA-3V

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DE-AC36-08-GO28308

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6. AUTHOR(S)

G.E. Bogin, Jr., and A.M. Dean: Colorado School of Mines; 

A. DeFilippo, J.Y. Chen, and G. Chin: University of California, 

Berkeley; J. Luecke, M.A. Ratcliff, and B.T. Zigler; National 

Renewable Energy Laboratory

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Developing advanced compression ignition and low-temperature combustion engines depends increasingly on 

chemical kinetic ignition models, but rigorous experimental validation of the models has been limited. Shock tubes 

and rapid compression machines are often limited to premixed gas-phase studies, precluding the use of realistic, lowvolatility diesel or biodiesel surrogates. The Ignition Quality Tester (IQT) constant-volume spray combustion system 

measures ignition delay of low-volatility fuels and could validate ignition models experimentally, but a better 

understanding of the IQT’s processes is needed. KIVA-3V was used to develop a 3D CFD model that accurately 

reproduces ignition behavior and resolves temperature and equivalence ratio regions inside the IQT. The model’s 

fuel spray characteristics (e.g., velocity) are experimentally validated, and it provides insight, vital to expanding the 

fuel research capabilities of the IQT, into the complex interaction between fuel spray and combustion processes.

15. SUBJECT TERMS

advanced compression ignition engines ; chemical kinetic ignition models ; Ignition Quality Tester ; KIVA-3V 

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