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SciNet Users Group Meeting
University of Toronto
Toronto, Ontario
February 9, 2011
Computational Combustion: Toward the use of
Sustainable and Alternative Fuels
Dr. Seth B. Dworkin
Mechanical and Industrial Engineering
University of Toronto
Toronto, Ontario
Collaborators and Acknowledgements
Prof. Murray Thomson
Dr. Qingan Zhang
Dr. Victor Chernov
Meghdad Saffaripour
Armin Veshkini
Parham Zabeti
Nick Eaves
SciNet
(Present Company)
The Demand for Energy
• 75% of power generation and transportation energy
comes from combustion
3
Global Climate Change
• CO2 and soot (black carbon particulate) are the #1 and #2
contributors to global climate change
• Addressing CO2
• Replace fossil fuels with biofuels that take in
CO2 as they grow
• Addressing Soot
• Fundamental soot studies
• Apply this knowledge to engine and power
plant technology
4
Research Streams
• Use fundamental thermofluid sciences and
computation
5
Research Methodology
• Modelling/experiment
understanding
1.
2.
fundamental
3.
4.
• Models help us understand properties and trends
that apply to practical combustion devices
6
Research Topics
1. Bio-Jet Fuel
2. Soot formation in
flames
3. Premixing fuel
studies
4. High pressure
combustion
7
Chemically-Reacting Flow Models
• Conservation equations for mass, momentum, energy, and species
conservation are simultaneously solved in a computational domain.
• A library of chemical reactions is used, which includes the prediction of
particle precursor molecules
• Conservation equations for a statistical representation of particle size
and shape are solved
• The particle equations are coupled to the gas phase:
• Inception rates from collision theory
• Oxidation via O2 and OH
• Growth via surface chemistry
• Enthalpy changes
8
1. Bio-Jet Fuel
Background
• Airplanes need liquid fuel
• Biomass To Liquid (BTL) has been proposed as an
alternative jet fuel
• Considerations:
–
–
–
–
Production & Distribution
Economic Viability
Airplane corrosion and degradation
Emissions
• Goal is to compare BTL combustion to standard jet fuel
via simulation
9
Computational Results
• After 3 months of compute time on 192 4.7-GHz CPUs (43 CPU-years!)
S1: n-decane
S2: n-propylbenzene
S3: n-propylcyclohexane
10
Validation (Species)
• Comparisons are made for major species along the centreline.
• Agreement between model and experiment is excellent.
11
Validation (Soot)
• Comparisons are made for soot volume fraction along the centreline and
along radial cuts at three axial heights.
• Data is well reproduced at the
lower axial locations.
• Soot is again underpredicted
along the centerline
• Current efforts are on computing
a BTL flame and on studying
soot formation
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2. Soot Formation in Flames
5.
There are ongoing processes of
coagulation, fragmentation,
oxidation, surface
condensation, and surface
reaction
4.
Spheres coagulate into soot
molecules
3.
Structures grow to spherules
via surface reactions
2.
Aromatics combine to form 3D
structures
1. Fuel gets decomposed into
small molecules which form
aromatics
13
Problem Statement
• Soot formation in flames remains poorly understood – most models
are semi-empirical
• Predicting soot inception is done empirically with approximations
Goals:
• Develop and validate a model for particle inception
• Build the new model into flame computations
• Model a well-understood flame
– Use a steady ethylene-fueled system
– Wealth of experimental data
• Perform engineering analysis on the results
14
Chemical Model Validation
• With collaborators at DLR – new mechanism
for PAH growth with over 700 reactions
15
Chemical Model Implementation
• The new chemical model is coupled to a full
CFD and soot model and computations are
performed in parallel.
16
Model Validation
17
Data Interpretation
• The data can be processed to track a fluid parcel
• This technique can relate its exposure to temperature, concentrations, etc.
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Data Interpretation
2000
Temperature (K)
1600
Appel et al.
7.0E-07
Pyrene Concentration
1800
8.0E-07
New Mech.
1400
1200
1000
800
600
400
New Mech.
5.0E-07
4.0E-07
3.0E-07
2.0E-07
1.0E-07
200
0
0.00
6.0E-07
Appel et al.
0.05
0.10
0.15
0.0E+00
0.00
time (s)
0.05
0.10
0.15
time (s)
• Lagrangian temperature historesis are similar
• Vast differences in aromatic exposure
S. B. Dworkin, Q. Zhang, M. J. Thomson, N. A. Slavinskaya, U. Reidel, Accepted to Combust.
Flame (2011) in press.
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Summary
• Using parallel computation we can study combustion
systems
• The models contains few assumptions
– Solve the full set of conservation equations for fluid
mechanics and thermodynamics
– Consider detailed chemical reaction libraries
– Contain a particle formation and dynamics model
• We can use experiment and computation to study and
compare proposed alternative fuels
• We can predict the formation tendencies of harmful
pollutants
• We can use data processing to increase our fundamental
understanding of flames and soot dynamics
20
Questions?