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Modeling of Alternative Fuels
and Fuel Blends Using Surrogates
Anne Lown
Lars Peereboom
Carl T. Lira
5/14/2014
Department of Chemical Engineering and
Materials Science
UNCLASSIFIED: Distribution statement A. Approved for public release
Outline
• Introduction
• Fuels of Interest
• Fuel Composition
• Surrogate Development and Modeling
• Cloud point
• Distillation curve
• Cetane number
• Compressibility
• Conclusions
2
Introduction• Alternative fuels important research
• Projected 60 billion gal required by 2022[1]
• Mandated deadlines for renewable content in diesel
and jet fuels approaching[2]
• Second generation biofuels produce a wide
variety of molecules
• Ethanol from lignocellulosic sources
• Hydrocarbons from Fischer-Tropsch
• Butanol or mixed alcohols
3
1. Biofuels Digest. “Biofuels Mandates Around the World” http://www.biofuelsdigest.com/bdigest/2011/07/21/biofuels-mandates-
around-the-world/
2. St. Paul Pioneer Press (MN) - November 5, 2011 - A14 Business. “Officials urge delay in biodiesel boost”
Project Goals• Use of surrogates to predict mixture
properties
• Improve property prediction for fuels and
blends
• Minimize number of tests for a fuel/blend
• Minimize number of surrogate components
• Wide range of fuel specifications
4
Fuels of Interest
• JP-8 – Aviation fuel
• IPK – Fischer-Tropsch fuel
• Highly branched, gas-to-liquid (GTL) process
• HRJ-8 – Hydrotreated plant oil
• UOP process
• 4 additional alternative fuels in research
set
5
Petroleum Fuels
• Petroleum fuels have 5 classes of
components• Paraffins (n-alkanes)
• Isoparaffins
• Aromatics
• Naphthenes (cycloparaffins)
• Olefins
• Paraffins important for cold flow
• Ratio between alkanes, isoparaffins, and
aromatics important for cetane number
7
Composition Profile for JP-8
Experimental data provided by J. T. Edwards, AFRL, Wright Patterson AFB,
2014
UNCLASSIFIED
8
Composition Profile for IPK
9Experimental data provided by J. T. Edwards, AFRL, Wright Patterson AFB,
2014
UNCLASSIFIED
Composition Profile for HRJ-8
10Experimental data provided by J. T. Edwards, AFRL, Wright Patterson AFB,
2014
UNCLASSIFIED
Surrogate Development
• Most literature surrogates optimized to fit
one fuel property
• Need extension of surrogates to represent
multiple properties
• Surrogate composition guided by testing of
neat fuel batches
• Goals
• Identify key components to include in surrogate
• Develop code for predicting blend properties
12
MSU JP-8 Surrogate
Component StructureWeight % in
Surrogate
n-Octylbenzene 14.8
2,2,5,5-
Tetramethylhexane20
n-Butylcyclohexane 23
3-Methylundecane 2313
• 16 components total, only 4 adjusted
• 11 paraffins, total 17.8wt%
• 1-Methyl naphthalene for di-aromatic,
1.2wt%
Cloud Point Model• Solid Solution[3]
• Change T until ΣxiS = 1
• Can model selective precipitation by limiting
which components solidify
• UNIFAC model used for activity coefficients
in liquid phase
15
−
∆−==
im
fus
i
S
i
L
i
L
ii
TTR
H
x
xK
,
11exp
γ
3. Hansen et al. AIChE Journal. 1988, Vol. 34, pg 1937.
Jet Fuel Surrogates' Predicted Cloud Points
16
Fuel Cloud Point
MSU JP-8 Surrogate
4. Huber, M.L., E. W. Lemmon, and T. J. Bruno, Surrogate Mixture Models for the
Thermophysical Properties of Aviation Fuel Jet-A. Energy and Fuels, 2010. 24: p. 3565–3571
Distillation Curve Model• Single-stage batch distillation model
• Raoult’s law used to calculate bubble point
temperature
• Pre-set number of moles evaporated at
equilibrium concentration
• Change in liquid phase calculated
18
MSU Surrogate Distillation Curve
19
ASTM D-86Surrogate Model
80 90 1000 60 7040302010 50Volume Percent Distilled
Te
mp
era
ture
(˚C
)300
275
250
225
200
175
150
Cetane Number Model• Cetane number – measure of ignition delay
in a compression ignition engine
• Use the correlation of Ghosh and Jaffe (ExxonMobil)[5]
• β is an empirical parameter dependent on the molecular class
• Mixtures of fuels can also be calculated using surrogate β values
215. Ghosh P., Jaffe S.B., Detailed Composition-Based Model for Predicting the Cetane Number
of Diesel Fuels, Industrial & Engineering Chemistry Research, 45 (2006) 346-51.
Cetane Number for IPK and JP-8
Experimental data provided by N. Hubble TARDEC, Warren, MI, 2014
UNCLASSIFIED23
Compressibility Model• Compressibility of a fuel affects:• Injection timing
• Injected mass
• Emissions
• Prediction requires an EOS
25
ESD and SAFT-BACK
ESD (cubic)
0 2000 4000 60000
2
4
6
8
10
12
14
16
18
Density (mol/m3)
P (MPa)
298.15 K
410.93 K
510.93 K
675 K
SAFT-BACK
0 2000 4000 60000
2
4
6
8
10
12
14
16
18
Density (mol/m3)
P (MPa)
298.15 K
410.93 K
510.93 K
675 K
26
• Prediction for the density of n-decane using two
different models
Conclusions• Alternative fuel blend properties can be
modeled with appropriate surrogates
• PIAN distribution necessary for the representation of both distillation curve and cloud point
• Cetane model not dependent on detailed composition information
• Current surrogate results provide good estimates for CP, molecular weight, distillation curve, cetane number
27
Acknowledgements• B. Windom, M.L. Huber, and T.J. Bruno –
National Institute of Standards and Technology
• N. Hubble – TARDEC
• R. W. Morris and J. T. Edwards – AFRL, Wright Patterson AFB
• Defense Logistics Agency• Contract Number SP4701-09-C-0037
• Contract Number SP4701-11-C-0011
• Tank Automotive Research, Development, and Engineering Center• Contract Number W56HZV-13-C-0340
Questions?28
References1. Biofuels Digest. “Biofuels Mandates Around the World”
http://www.biofuelsdigest.com/bdigest/2011/07/21/biofuel
s-mandates-around-the-world/
2. St. Paul Pioneer Press (MN) - November 5, 2011 - A14
Business. “Officials urge delay in biodiesel boost”
3.Hansen et al. AIChE Journal. 1988, Vol. 34, pg 1937.
4. Huber, M.L., E. W. Lemmon, and T. J. Bruno,
Surrogate Mixture Models for the Thermophysical
Properties of Aviation Fuel Jet-A. Energy and Fuels,
2010. 24: p. 3565–3571.
5. Ghosh P., Jaffe S.B., Detailed Composition-Based
Model for Predicting the Cetane Number of Diesel Fuels,
Industrial & Engineering Chemistry Research, 45 (2006)
346-51.
29