AIChE 2011 - Multiphysics Model of Diesel Injector Deposit Formation
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Transcript of AIChE 2011 - Multiphysics Model of Diesel Injector Deposit Formation
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Multiphysics Model of Diesel Injector Deposit Formation.
Richard H. WestAmrit JalanWilliam H. GreenRiccardo Rausa
Massachusetts Institute of Technology
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Why do diesel engines lose power over time?!"#$%&'()'*+',-.-,/'$+0'&-/&'&1"-
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*+,-./0-1 2345.6-,7.!889.:4 !889.:4 '889.:4Caprotti et al. (Infineum UK) SAE 2006-01-3359
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Deposits form on diesel fuel injectors, blocking the nozzles
More efficient engines and less pollution → smaller nozzles
Smaller nozzles → deposit more problematic
Leedham et al. (Infineum UK) SAE 2004-01-2935
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Fuel additives is big busine$$!
Nobody understands the deposit-forming process.
Current development is based on expensive engine tests.
bp.combp.com
Dirty and clean injector nozzles, from BP Ultimate Diesel advertisement
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We want a predictive model of deposit formation.
Aim to gain insight into the effect of
•different conditions
•different fuels and fuel blends
•different detergents
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Model system of interest:a thin film of fuel, evaporating.
evaporating film
vapor diffusion
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Oxygen diffuses into the fuel from the air.
O2 diffusion
evaporating film
vapor diffusion
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Free-radical autoxidation reactions gradually oxidize the fuel.
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
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Over time the reaction continues; the diesel becomes more oxidized.
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
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Heavily oxidized reaction products are insoluble in non-polar diesel & phase separate.
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
insolubleoxygenates
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This polar oxygenate phase forms the deposit.
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
insolubleoxygenates
deposit
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Fuel injections wash the walls
speciesdiffusion
fresh diesel
insoluble oxygenates
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Model overview: React & evaporate, equilibrate, wash, replenish...
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
partially oxidizeddiesel
diesel
partially washeddiesel
insoluble oxygenates
phase equilibrationand separation
washing with clean dieseladd fresh diesel toreplace evaporated
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Chemistry depends on starting species
Diesel contains thousands of species.
Choose simple mixture to represent surrogate diesel.
chemical reaction
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Oxidation is driven by free-radical chain reactions
O OH
O OHO OO O
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Oxidation is driven by free-radical chain reactions
O OH
O OHO O
O OOO O
OOO
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Oxidation is driven by free-radical chain reactions
O OH
O OHO O
O OOO O
O
OO
OOH
HOO
HOO
O O
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Oxidation is driven by free-radical chain reactions
O O HO OH
O O
O OOO O
O
OO
OOH
HOO
HOOO O
OH
O
OO
OH
OOO
OH
OOO
O O
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Oxidation is driven by free-radical chain reactions
O O HO OH
O O
O OOO O
O
OO
OOH
HOO
O OHOO
OH
O
OO
OH
OOO
OH
OOO
OH
O
OO H
O
OHO
OHOH
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H
O O
Oxidation is driven by free-radical chain reactions
HO O
O OOO O
O
OO
OOH
HOO
O OHOO
OH
O
OO
OH
OOO
OH
OOO
OH
O
OO H
O
OHO
OH
OH OH H2O
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Detailed kinetic modeling is complex
Estimating all the reactions is tedious and error prone.
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Detailed kinetic modeling is complex
Estimating all the reactions is tedious and error prone.
Teach the chemistry to a computer!
⇌facebook.com/rmg.mitr m g . s o u rc e f o r g e . n e t
Reaction Mechanism Generator
•free and open source software
•version 3.3 released in February
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Reaction families propose all possible reactions with given chemical species
bond breaking and hydrogen abstraction
intramolecularH-abstraction
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Reaction families propose all possible reactions with given chemical species
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Octane autoxidation has many pathways
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Detailed kinetic modeling is complex
For each chemical reaction
we need:
•forward rate coefficient
•equilibrium constant
k f = A exp�−EaRT
�
∆G = ∆H − T∆S
k f
kr= Keq = exp
�−∆G
RT
�
A + B � C + D
r = k f [A][B]
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We can estimate thermochemistry of solvation from the molecular structure of the solute
Molecular structure
Platts’ group contributions
Solute parameters
Solvent parameters
Abraham’s method
Partition coefficient,K K=exp(-∆G/RT) ∆G
solvation
Mintz modelfor alkanes ∆H
solvation
∆G=∆H-T∆S∆S solvation
RMG group contributions
gas phase H(T), S(T)
See (551d) “Progress towards Capturing Solvent Effects In Automatic Mechanism Generation”Amrit Jalan, Richard H. West and William H. Green. Reaction Path Analysis II, Wednesday, 1:30pm
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RMG with solution-phase corrections was used to study autoxidation of surrogate diesel
facebook.com/rmg.mitr m g . s o u rc e f o r g e . n e t
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Current model contains 252 species and 5185 reactions.
•n-decylbenzene is most reactive componentand dominates kinetics
22/02/2009 5:23PM_rp_svg2.html
Page 1 of 1file:///Users/rwest/XCodeProjects/RMG/software/python/_rp_svg2.html
Scale = 9.8e-05
-
0.951
1 0.0480.00518
0.957 0.0494
chemical reaction
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Model overview: React & evaporate, equilibrate, wash, replenish...
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
partially oxidizeddiesel
diesel
partially washeddiesel
insoluble oxygenates
phase equilibrationand separation
washing with clean dieseladd fresh diesel toreplace evaporated
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Evaporation
•Abraham model gives gas/solvent concentration ratio
•Diffusivity estimated from molecular structure
O2 diffusion
evaporating film
vapor diffusion
Fuller, Schettler, Giddings. I&EC, 58, 1966.
HOO
HOO
HO
O
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Model overview: React & evaporate, equilibrate, wash, replenish...
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
partially oxidizeddiesel
diesel
partially washeddiesel
insoluble oxygenates
phase equilibrationand separation
washing with clean dieseladd fresh diesel toreplace evaporated
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Abraham’s Method predicts partition coefficients for different solutes and solvents
Solute parameters
Solvent parameters
Abraham’s method
Partition coefficient, K
log K= c + eE + sS + aA + bB +log K= c + eE + sS + aA + bB +
/solvent partitioning
lL
gas /solvent partitioning
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Abraham’s Method predicts partition coefficients for different solutes and solvents
Solute parameters
Solvent parameters
Abraham’s method
Partition coefficient, K
log K= c + eE + sS + aA + bB +
log K= c + eE + sS + aA + bB +
/solvent partitioning
vV
lL
gas
/solvent partitioningsolvent
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Model overview: React & evaporate, equilibrate, wash, replenish...
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
partially oxidizeddiesel
diesel
partially washeddiesel
insoluble oxygenates
phase equilibrationand separation
washing with clean dieseladd fresh diesel toreplace evaporated
![Page 36: AIChE 2011 - Multiphysics Model of Diesel Injector Deposit Formation](https://reader033.fdocuments.net/reader033/viewer/2022052507/55904fa81a28ab9f548b4582/html5/thumbnails/36.jpg)
Washing is mass transfer problem
Look up a correlation in Perry’s Handbook:
TABLE 5-19 Mass-Transfer Correlations for Flow in Pipes and Ducts—Transfer Is from Wall to Fluid. W: Tubes, turbulent, smooth tubes, constant surface concentration
NSh,avg =k�avgdt
DNSc =
µ
ρD NRe =ρubulk dt
µ
NSh,avg =0.0097N9/10
Re N1/2Sc
�1.10 + 0.44N−1/3
Sc − 0.70N−1/6Sc
�
1 + 0.064N1/2Sc
�1.10 + 0.44N−1/3
Sc − 0.70N−1/6Sc
�
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Current model overview:React, equilibrate, wash, replenish...
chemical reaction
O2 diffusion
evaporating film
vapor diffusion
partially oxidizeddiesel
diesel
partially washeddiesel
insoluble oxygenates
phase equilibrationand separation
washing with clean dieseladd fresh diesel toreplace evaporated
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Implementation
•Python: chosen for speed of development.
•PyDAS: Python interface to Fortran DAE solver DASSL.
•Cython: gives orders of magnitude reduction in CPU time.
•Parallel computing: simple use of array jobs.
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Python chosen for speed of development.
•General-purpose, high-level programming language.
•Free, open-source, extensible.
•Easy to learn.
•Fast (and fun) to develop in.
•Multi-paradigm programming language,but this project mostly object-oriented.
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PyDAS created to access specialized ODE solvers from Python code.
•Chemical reactions → very stiff systems of differential equations → require specialized ODE solvers.
•VODE (provided by SciPy) is not always robust enough.
•Fortran-based DASSL (Petzold, 1982) is a stiff DAE solver widely used in kinetic modeling.
•Python interface to DASSL developed and released:
https://github.com/jwallen/PyDAS
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Cython used to speed up the slow partsby orders of magnitude.
•Develop your code in Python
•Identify the slow parts by profiling (right hand side of ODE)
•Add some static type declarations (“cdef double x”)
•Compile to C using Cython
•50x speed up in overall computation time!
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Parameters:
•Reaction T
•Phase separation T
•Nozzle diameter
•Nozzle length
•Film thickness
•Injection velocity
•Injection duration
•Reaction time
Running simulations with different parameters gives a variety of results.
chemical reaction
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Parallel computing is easy and useful for parameter studies and sensitivity analysis.
Head Server
Compute nodes
submit jobs 1-1000 run job 3
run job 4...
•Use cluster’s queuing system for “array” jobs.
•Your code translates job number into set of parameters:
•Random (Uniform Distribution)
•Global Sensitivity Analysis (Modified Morris Method)
run job 1
run job 2
Simulate with parameter
set 1Simulate
with parameter set 2
Simulate with parameter
set 3
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Global Sensitivity Analysis identifies most significant model parameters.
•Identifies sub-models needing refinement.
•Guides laboratory experiments.
•Gives insight to underlying processes.
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Acknowledgements
•Project collaborators at MIT:
Amrit Jalan and Prof. William Green (ChE)Yinchun Wang and Prof. Wai Cheng (MechE)
•RMG developers:
•Industrial sponsors:
Eni S.p.A.
facebook.com/rmg.mitr m g . s o u rc e f o r g e . n e t
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Multiscale, multiphysics model gives insight into
•chemical reactions
•evaporation
•phase separation
•washing
Computational experiments reveal important parameters
•guide model development
•guide experiments
Contributions to industrial problem of deposit formation in diesel fuel injectors:
chemical reaction
OH
O
OO H
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Suggestions for multi-scale modeling ofother chemical engineering systems.
•Build detailed kinetic model to capture complicated T,P-dependence of real chemistry (RMG).
•Write software in Python: easy, fast, pleasant to write.
•Use specialized DAE solvers when necessary (PyDAS).
•Use Cython to speed up the slow parts.
•Use parallel computing environment for Global Sensitivity Analysis (eg. modified Morris method)
•Identify sensitive parameters, then refine models and experiments accordingly.
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Massachusetts Institute of Technology