Modeling reacting flows with detailed chemical kinetics in ... · ISAT Functioning cont… ISAT...
Transcript of Modeling reacting flows with detailed chemical kinetics in ... · ISAT Functioning cont… ISAT...
© 2011 ANSYS, Inc. November 4, 2015 1
Modeling reacting flows with detailed chemical kinetics in ANSYS CFD
Pravin Nakod Senior Technology Specialist
ANSYS Inc.
© 2011 ANSYS, Inc. November 4, 2015 2
• Introduction
• Detailed reaction mechanisms
• Detailed chemistry models – Laminar finite rate
– Eddy dissipation concept
– Composition PDF transport
• Chemistry acceleration tools – In-situ adaptive tabulation
– Chemistry agglomeration
– Dimension reduction
– Dynamic mechanism reduction
• Summary
Outline
© 2011 ANSYS, Inc. November 4, 2015 3
Detailed chemical kinetics • Tens of species and hundreds of
reactions • Each species participate in a
series of reaction steps – Produced in some steps and
destroyed in some other steps
• Example: H2-O2 reaction mechanism
• Suitable for modeling – Flame ignition and extinction – Pollutants (NOx, CO, UHCs) – Slow (non-equilibrium) chemistry – Intermediate species of interest
(OH…)
Introduction
© 2011 ANSYS, Inc. November 4, 2015 4
1000 2000 300010
-15
10-12
10-9
10-6
Sh
ort
est
Sp
eci
es
Tim
e S
cale
, S
ec
Temperature
Ethylene,
p = 1 atmT0 = 1000K
n-Heptane,
p = 50 atmT0 = 800K
Typical flow time
Chemical Stiffness
, K 101
102
103
104
102
103
104
before 2000
2000 to 2005
after 2005
iso-ocatane (LLNL)
iso-ocatane (ENSIC-CNRS)
n-butane (LLNL)
CH4 (Konnov)
neo-pentane (LLNL)
C2H4 (San Diego)
CH4 (Leeds)
Methyl
Decanoate
(LLNL)
C16 (LLNL)
C14 (LLNL)C12 (LLNL)
C10 (LLNL)
USC C1-C4
USC C2H4
PRF
n-heptane (LLNL)
skeletal iso-octane (Lu & Law)
skeletal n-heptane (Lu & Law)
1,3-Butadiene
DME (Curran)C1-C3 (Qin et al)
GRI3.0
Nu
mb
er
of re
actio
ns
Number of species
GRI1.2 pre-2000
2000 – 2005
post-2005
Number of Species
Num
ber
of
Reactions
nC7H16
C11H22O2Large Sizes
Characteristics of detailed reaction mechanisms • Large number of species • Wide range of chemical timescales (Stiffness)
– Small times scales, ~1e-8 (Reactions involving radical species) – Large times scales, ~ 1e-2 (CO oxidation, NOx formation)
Mechanisms for Practical Fuels
© 2011 ANSYS, Inc. November 4, 2015 5
• Three types – Detailed, Skeletal and Reduced mechanism
• Detailed mechanism – Large number of species
– Large number of elementary reactions
• Skeletal mechanisms – Shortened detailed mechanisms
– Unimportant species and reactions eliminated
• Reduced mechanisms – Further simplified detailed or skeletal mechanisms
– Quasi-Steady State Assumptions (QSSA)
Types of Detailed Reaction Mechanisms
Co
mp
uta
tio
nal
eco
no
my
Solu
tio
n a
ccu
racy
Low High
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Detailed reaction mechanisms available online • http://www.tfd.chalmers.se/~valeri/MECH.html
• http://www.detchem.com/mechanisms.html
• http://web.mit.edu/anish/www/MITcomb.html
• http://www.galcit.caltech.edu/EDL/mechanisms/library/library.html
• http://www.me.berkeley.edu/gri_mech/
• http://www.chem.leeds.ac.uk/Combustion/Combustion.html
• http://melchior.usc.edu/JetSurF/JetSurF2.0/Index.html
• http://www.erc.wisc.edu/chemicalreaction.php
• Reacting Design: Now part of ANSYS
Reaction mechanism is a user input
Acquiring Reaction Mechanisms
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CHEMKIN Format
Fluent can import CHEMKIN reaction mechanism files
• Symbolic description of an elementary reaction mechanism
– Information on elements, species and the reaction mechanism
• Appropriate unit conversion is done while importing the CHEMKIN file
• Separate thermodynamic database may be required
Sample file
Pre-exponential Factor Temp. Exponent Activation Energy
© 2011 ANSYS, Inc. November 4, 2015 8
Detailed Reactions Modeling in Fluent
• Detailed / skeleton reaction mechanisms – Species limit pre-R14.5: Up to 50 species
– R15: Up to 500 species
• Reduced mechanisms – Quasi Steady State Approximation (QSSA) reduced
mechanisms
– ARM-9 and ARM-19 mechanisms for methane combustion are inbuilt in Fluent
• Reaction rate – Arrhenius with reversible and third body efficiency
– Low and high pressure blend
• Lindemann, Troe, SRI
© 2011 ANSYS, Inc. November 4, 2015 9
Detailed Chemistry Models
• Laminar Finite Rate (LFR) model – Laminar flames
– Turbulent flames with weak turbulence-chemistry interaction
• Eddy Dissipation Concept (EDC) model – Assumes reaction occurs in small turbulence scales
– Turbulent flames with turbulence-chemistry interaction
• Composition PDF transport – Turbulent flames with rigorous turbulence-chemistry
interaction
– Computationally most expensive
© 2011 ANSYS, Inc. November 4, 2015 10
Laminar Finite Rate Model
• Laminar flows
– 𝝆 𝜕𝒀𝒊
𝜕𝒕+ 𝝆𝑼𝒊
𝜕𝒀𝒊
𝜕𝑿𝒊=𝜕
𝜕𝑿𝒊𝝆𝑫𝜕𝒀𝒊
𝜕𝑿𝒊+ 𝑺
– Diffusivity modeling affects the accuracy
• Turbulent flows
– 𝝆 𝜕𝒀𝒋
𝜕𝒕+ 𝝆 𝑼𝒋
𝜕𝒀𝒋
𝜕𝑿𝒋=𝜕
𝜕𝑿𝒋𝝆𝑫𝜕𝒀𝒋
𝜕𝑿𝒋−𝜕
𝜕𝑿𝒋𝝆 𝑼"𝒋𝒀"𝒋
+𝑺
– 𝑺 evaluated from mean temperature
– Can predict ignition characteristics correctly
– No corrections for temperature or species concentration fluctuations • Works fine for weak turbulence-chemistry interaction
– For larger turbulent fluctuations • Need to use smaller mesh size and/or time step size
© 2011 ANSYS, Inc. November 4, 2015 11
• Extension of LFR model to account for turbulence-chemistry interaction
• Suggested by Magnussen in 1981
• Assumptions – Reactants are mixed at molecular level
in the fine turbulent structures
• Of the order of Kolmogorov length scale
– Reactions take place within these structures
– Entire volume of fine scale structures is a fraction of total fluid volume
Eddy Dissipation Concept Model
Bjorn F Magnussen
Fine structures within a computational cell
B. F. Magnussen, 19th AIAA Sc. meeting, St. Louis, USA, 1981
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EDC Reaction Rate Evaluation
• Length fraction of the fine scales
• Volume fraction of the fine scales =
• Life-time of small scales
• Reactions proceed within the fine scales over the time, 𝝉∗ – Assuming constant pressure reactor
• Mean reaction rate in mean species equation
25.0
t
4/1
2
*Re
kC
Kolmogorov
2/1
*tC
)YY()1(
S i
*
i3**
2*
i
3*
Fine structures within a computational cell
* Quantities are fine scale quantities; = 2.1377 and = 0.4082 CC
© 2011 ANSYS, Inc. November 4, 2015 13
Composition PDF Transport Model
• RANS approach solves Favre averaged species and energy equations – Prone to errors for flows with strong turbulence-chemistry interaction
• A transport equation for joint probability density function (PDF) is obtained from species and energy equations
– Proposed by S.B. Pope (1976)
–𝜕
𝜕𝒕𝝆𝑷 +
𝜕
𝜕𝑿𝒊𝝆𝒖𝒊𝑷 +
𝜕
𝜕𝝋𝒌𝝆𝑺𝒌𝑷 =
𝜕
𝜕𝑿𝒊𝝆 𝒖"𝒊 𝝋 𝑷 +
𝜕
𝜕𝝋𝒌𝝆𝟏
𝝆
𝝏
𝜕𝑿𝒊𝑱𝒊,𝒌 𝝋 𝑷
• P is Favre joint composition PDF • 𝝋 is the composition space = 𝝋 (Y1, Y2, Y3 …… YN , T)
• 𝑨 𝑩 denotes the probability of event A, given the event B occurs
• Ji,k is molecular diffusion flux vector
S.B. Pope, Combustion and Flame, 27, 299-312 (1976)
S B Pope
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• Detailed chemistry calculations are computationally expensive
• Chemistry acceleration tools are available to speed – In-situ adaptive tabulation (ISAT)
– Chemistry Agglomeration (CA)
– Dimension Reduction
– Dynamic Mechanism Reduction (DMR)
Chemistry Acceleration Tools
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In-Situ Adaptive Tabulation (ISAT)
• Thermodynamic state of fluid characterized by – Mass fractions of species (Yi); Enthalpy (h) and Pressure (P)
• Broad class of flow P ~ P0 (Reference pressure)
• Species and temperature represented by a composition – (Y1, Y2, Y3 …… YN , T)
• Each as a point in D-dimensional composition space – D degree of freedom
• Evolution of
– M is rate of change due to transport
– S is rate of change due to chemical reaction • As t , the trajectory tends to chemical equilibrium
– Linear approximation • To calculate reaction mapping, R( ) for other points close by 0
Evolution of in a composition space
© 2011 ANSYS, Inc. November 4, 2015 16
ISAT Functioning
Initially, reacting flow code provides ISAT with
• Time step size, t
• Error Tolerance, tol
• Scaling matrix, B
– It is used to calculate errors
During calculation, reacting flow code gives a query to ISAT
ISAT returns, corresponding mapping within required accuracy
Reacting
Flow Code ISAT
t, B, tol
q
R( q)
© 2011 ANSYS, Inc. November 4, 2015 17
ISAT Functioning (cont…)
ISAT passes the composition ( 0) and time step size (t ) to Mapping module
Mapping module does direct integration and returns mapping R( 0) and mapping gradient matrix A( 0) to ISAT
ISAT stores this record in the form of binary tree
• At each leaf , there is a record – Fixed data: Point ( 0); Reaction Mapping R( 0); Mapping gradient A( 0)
– Changing data: EOA information
• At each node , there is a information about cutting plane
ISAT
Mapping
Module
ODE Solver
+ Chemistry
0
R( 0), A( 0)
© 2011 ANSYS, Inc. November 4, 2015 18
Direct integration
Algorithm
Initiate binary tree with single leaf
(Exact value of Mapping)
Reacting
Flow Code ISAT
Mapping
Module First Query ( 0)
0
R( 0), A( 0)
Reacting
Flow Code New Query ( q)
Look for
( 0 ) ( q ) & check
( q ) within EOA
ISAT
Traverse binary tree
Linear Approx. Get R( q) Yes No
R(
q)
Return R( q)
Calc. < tol
Yes No
Grow EOA Add new entry
R ( q)
Retrieve
Growth Addition
© 2011 ANSYS, Inc. November 4, 2015 19
ISAT: Best Practice Memory • The table size is user input (in Mb) • Set to a large fraction of your maximum available memory
Accuracy • Default ISAT tolerance is 0.001
– Relatively larger; Allows faster convergence • Large performance penalty for error tolerance smaller than it is needed to achieve acceptable
accuracy • For steady state problems:
– Obtain a converged solution with relative large ISAT tolerance (e.g., default value) – Then decrease it gradually and judiciously to obtain accurate thermo-chemical solutions
• For unsteady problems – For small calculations, perform an accuracy study by running the calculation with different
ISAT error tolerances – For large calculations, obtain the necessary ISAT error tolerance by performing an accuracy
study for the considered mechanism in a separate, similar but simple test case
Efficiency • Periodic cleaning of ISAT is more efficient
– For transient problems such as those in IC engines – For initial transition in steady-state problems
• Saving ISAT to reuse it in another calculation is not beneficial • Building the ISAT table from scratch in a calculation is in general preferred
© 2011 ANSYS, Inc. November 4, 2015 20
• Lots of cells or particles have similar composition
• Cells close in composition space – Similar in temperatures and mass
fractions of species – Clubbed for calculation of
reaction mapping
• Results in fewer calls to ISAT • Map reaction step back to
original cells
Chemistry Agglomeration
Mixture fraction (f)
T
© 2011 ANSYS, Inc. November 4, 2015 21
Chemistry Agglomeration Speed-Up
# of cells Agglomeration setting # of chemistry cal. Per iteration
CPU Time Speed-up
2352 No 2352 2970 1
2352 T + 3 species; 0.01 ~700 1080 2.75
2352 T + 3 species; 0.02 ~520 840 3.54
2352 T + 3 species; 0.03 ~395 610 4.87
2352 T + 3 species; 0.04 ~314 540 5.5
Goldin, Ren, Zahirovic, Combustion Theory and Modeling, 2009
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• Reduce the number of transported species – User to select number of the represented species
• Transport equations for the selected species only • Unrepresented species constrained to chemical
equilibrium – Ensure that the unrepresented species are near chemical
equilibrium for better accuracy
• Applications – Dimension reduction is principally to use for mechanisms
with more than 50 species
• Limitations – Equilibrium assumption for unrepresented species
• Not a good assumption for pollutant formation
Dimension Reduction
© 2011 ANSYS, Inc. November 4, 2015 23
Dynamic Mechanism Reduction (DMR)
Recall, at each flow iteration* or time-step
• Fluent calls ODE solver to solve chemistry IVP at each cell
• tODEsolver ~ c1Nspecies3 + c2Nspecies
2 + c3Nspecies + c4Nreactions
Dynamic Mechanism Reduction:
• Decrease tODEsolver by reducing Nspecies, Nreactions
– Evaluate kinetic rates before calling ODE solver
• Drop species and reactions with negligible contributions
– Solve smaller ODE set
• Compositions of dropped species are “frozen” throughout ODE solution
– Fewer reaction rates need to be evaluated during ODE solve
• Potentially different mechanism per cell, per flow iteration or time-step
• Mechanism reduction method in R15 : Directed Relation Graph (DRG)
– T.Lu and C.K. Law, 2005
*number of flow iterations per chemistry solve can be adjusted in UI; default = 1
© 2011 ANSYS, Inc. November 4, 2015 24
Sandia Flame D, Sydney bluff body flame, Yale flame
• Start from a converged equilibrium solution
• Run a certain number of iterations until convergence with Laminar Finite Rate model
• Compare results between Direct Integration and Dynamic Mechanism Reduction (including speedup factor and scalars accuracy)
Stationary Flames
© 2011 ANSYS, Inc. November 4, 2015 25
Sandia Flame D
Co-flow Outlet
Axis
Symmetry
Jet
Pilot
• Mesh 7112 Cells
• Mechanism Methane Flame
– 53 species, 325 Reactions
• DMR tolerance = 0.01 (default)
© 2011 ANSYS, Inc. November 4, 2015 26
Sandia Flame D Speedup factor (runtime full mechanism / runtime DMR) = 1.97
Temperature profile (axis)
© 2011 ANSYS, Inc. November 4, 2015 28
Sandia Flame D DMR post processing related quantities
Large concentration of chemically active cells in a small region of the domain which gives a high potential for reduction techniques
Speedup factor = 1.97
© 2011 ANSYS, Inc. November 4, 2015 29
Initial conditions and set up • Poor initial condition can cause stiff chemistry solver to fail
• Obtain initial solution with any of the fast chemistry model
– Provides a good initial guess for temperature and species
ISAT tolerance • In final solution, decrease the ISAT tolerance to make sure
that the solution is independent of any table interpolation error
With stiff chemistry solver • For slow converging cases, increase the aggressiveness factor
• Aggressiveness factor – Between 0 (most robust but slowest convergence) and 1
– The default aggressiveness factor is 0.5
Solution Strategies
© 2011 ANSYS, Inc. November 4, 2015 30
• New chemistry ODE solver CVODE
• Improvements to chemistry solver – More speedup expected for large
mechanism
• Improvements to ISAT efficiency
• Improvements to Dynamic Mechanism Reduction efficiency
Stiff Chemistry Solver R16 New Features
© 2011 ANSYS, Inc. November 4, 2015 31
Initial conditions
Pressure (bar) 1.1
Temperature (K) 330
Equivalence ratio 0.4
Turbulent kinetic energy (m2/s2) 0.01
Turbulent dissipation rate (m2/s3) 0.01
Swirl velocity (m/s) 0.01
Boundary conditions
Cylinder temp. (K) 400
Head temp. (K) 450
Piston temp. (K) 550
Test Case
Generic HCCI engine
Setup:
• Compressible flow
• Laminar Finite Rate
• Dynamic mesh : Crank Angle step of 0.5, reduced to 0.1 around ignition
• 20 iterations per time step, 866 time steps
head
piston
cylinder
Mesh : 650 up to 11550 cells
Engine properties : Compression ratio : 13.5 Speed : 1500 RPM Simulation from IVC -143 CA aTDC to EVO 130 CA aTDC
axis
Mechanism : 160 species / 1540 reactions (n-heptane flame)
© 2011 ANSYS, Inc. November 4, 2015 32
Test Matrix
Run the case with Direct Integration (no chemistry acceleration tool)
Run the case with ISAT (storage 500 MB, tol = 1e-04, cleaning up the table every 50 time-steps)
Run the case with Dynamic Mechanism Reduction (default tolerance = 0.01)
Run the case using both ISAT and DMR
Compare R15 and R16 in terms of
• Accuracy (averaged temperature time evolution in the cylinder)
• Speedup on the ODE solver runtime
© 2011 ANSYS, Inc. November 4, 2015 33
Comparison in Runtimes (R15 and R16)
93%
60%
72%
31%
92%
40%
28%
69%
Percentage represents the ODE solver runtime over the total runtime
In R16 the chemistry ODE solver runtime becomes comparable or sometimes less
than the transient flow solver
Speedup Factors = ODE solver runtime case R15 / ODE solver runtime case R16
© 2011 ANSYS, Inc. November 4, 2015 34
Comparison in Accuracy (R15 and R16)
Direct Integration case (no chemistry acceleration tool)
Similar accuracy between R15 and R16
© 2011 ANSYS, Inc. November 4, 2015 35
Chemistry Acceleration Tools in R16
Speedup Factors = ODE solver runtime case DI / ODE solver runtime
© 2011 ANSYS, Inc. November 4, 2015 36
Chemistry Acceleration Tools in R16
Accuracy Comparison
© 2011 ANSYS, Inc. November 4, 2015 37
Test Case: RCM-3
Presented at: 13th International Conference on Numerical Combustion April-2011, Corfu, Greece
© 2011 ANSYS, Inc. November 4, 2015 38
MASCOTTE Combustor: RCM-3 Details
Combustor features: • Cylindrical injectors • Square combustion chamber
Thermodynamic conditions
• GH2 Supercritical (Both Pressure and Temperature are supercritical)
• LOx Transcritical (Pressure is supercritical and Temperature is subcritical)
Hydrogen Tc = 32.98 K
Pc = 1.29 MPa
Oxygen Tc = 154.58 K Pc = 5.04 MPa
© 2011 ANSYS, Inc. November 4, 2015 39
Geometry
Actual MASCOTTE combustor has a circular injection section and square combustion chamber
However, whole model is considered to be cylindrical for the modeling purpose
• Increased diameter is used to reproduce the volume of the combustor
Injector geometry
© 2011 ANSYS, Inc. November 4, 2015 40
2D Axi-symmetric
Inbuilt real gas models
SST k-w turbulence model
Combustion models • Laminar finite rate: 8-species, 21-
reactions – Li, Zhao, Kazakov, and Dryer, Princeton
University, 2003
• Non-premixed model: Equilibrium approach
Transport properties: • NIST data for LOx
• Kinetic theory for other species
Models Set-Up
© 2011 ANSYS, Inc. November 4, 2015 41
Cheng & Farmer
Fluent - SRK
Tmax ~3700
Fluent - ARK
Fluent - RK
Fluent - PR
Tmax = 3714
Tmax = 3720
Tmax = 3716
Tmax = 3722
Temp (K)
Tmax ~3700
Tmax = 3626
Tmax = 3622
Tmax = 3623
Tmax = 3626
Temp (K)
Laminar finite rate model Non-premixed equilibrium model
Laminar finite rate model
Temperature Contours
© 2011 ANSYS, Inc. November 4, 2015 42
Comparison of Axial Temperature
0
475
950
1425
1900
2375
2850
3325
3800
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40
Tem
p (
K)
Axial distance from injector exit (m)
Cheng & Farmer
SRKARK
RKPR
0
475
950
1425
1900
2375
2850
3325
3800
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40
Tem
p (
K)
Axial distance from injector exit (m)
Cheng & FarmerSRKARKRKPR
Laminar finite rate model Non-premixed equilibrium model
© 2011 ANSYS, Inc. November 4, 2015 43
Test Case: FIRE-II
© 2011 ANSYS, Inc. November 4, 2015 44
Reentry Vehicle Geometry
FIRE-II: Flight Investigation of Reentry
Environment; Flight-II
• A high-velocity flight experiment
• Velocity of 11.35 km/s representative of Apollo
lunar return velocities
Two sections • Fore body
• After body
Only fore body section is considered
2D axi-symmetric model
Two meshes used • Initial solution with coarser mesh
• Final solution with finer mesh
Reentry vehicle geometry
Fore body After body
© 2011 ANSYS, Inc. November 4, 2015 45
Mesh
Initial Adapted
Cells 10640 22151
Initial Adapted Initial
Adapted
Dynamic adaption (velocity gradient) Boundary adaption
© 2011 ANSYS, Inc. November 4, 2015 46
Test Conditions and Models
FIRE II : Flight Condition
Models
• Solver: DBNS, Implicit
• Flow: Laminar
• Reactions: Laminar finite rate
– 11 species, 20 reactions
– Stiff chemistry solver
Boundary Conditions
• Pressure far field
– Mach No. 37.3
– Pressure 10.5 Pa; Temperature 210 K
– Mass fractions: O2 23.3%; N2 76.7%
• Reentry vehicle wall
– Isothermal: 810 K Axis
Pressure far field
Wall
Pressure outlet
Altitude (km)
Velocity (km/s)
Density (kg/m3)
T
(K) Tw
(K)
71.04 11.31 8.57e-5 210 810
© 2011 ANSYS, Inc. November 4, 2015 47
Reaction Model
11 species, 20 reaction Gupta et. al. model
© 2011 ANSYS, Inc. November 4, 2015 48
Temperature
DPLR LAURA DPLR-LAURA Present work
Shock stand off distance (m)
0.04598 0.04624 0.04446 0.04573
Temperature (K) contours Axial temperature profile
0
5000
10000
15000
20000
25000
30000
35000
0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05 0.055 0.06Te
mp
era
ture
(K
) Axial distance from stagnation point (m)
DPLR
LAURA
DPLR-LAURA
Present work
© 2011 ANSYS, Inc. November 4, 2015 49
Results
Sharp perpendicular shock near axis
Mach No Velocity (m/s) Static Pressure (Pa)
© 2011 ANSYS, Inc. November 4, 2015 50
Electrons Distribution
Electron mole fraction
Y-co
ord
inat
e (m
)
© 2011 ANSYS, Inc. November 4, 2015 51
Self-ignition and flame propagation of high-pressure hydrogen jet during sudden discharge from a pipe
© 2011 ANSYS, Inc. November 4, 2015 52
Experimental Observations: Ignition is a Possibility
• Not every case results in ignition
• Sometimes, auto-ignition is followed immediately by quenching
• auto-ignition and flame propagation has been observed only for a certain combination of – Pipe diameter – Length of the pipe – Burst Pressure
© 2011 ANSYS, Inc. November 4, 2015 53
Test Case
© 2011 ANSYS, Inc. November 4, 2015 54
Reaction Mechanism: 8 Species and 21 Reactions
© 2011 ANSYS, Inc. November 4, 2015 55
Comparison Along the Axis
Mach Number
Pressure (bar)
© 2011 ANSYS, Inc. November 4, 2015 56
Comparison Along the Axis
Axial velocity
Temperature (K)
© 2011 ANSYS, Inc. November 4, 2015 57
Temperature Contours at 35s
Xu et. al. Present work
Overall flame capture is reasonable Need to refine mesh and other modeling set up to improve the accuracy
© 2011 ANSYS, Inc. November 4, 2015 58
R16 Detailed Chemistry Improvements
© 2011 ANSYS, Inc. November 4, 2015 59
New chemistry ODE solver CVODE
Improvements to chemistry solver
• More speedup expected for large mechanism
Improvements to ISAT efficiency
Improvements to Dynamic Mechanism Reduction efficiency
Stiff Chemistry Solver New Features
© 2011 ANSYS, Inc. November 4, 2015 60
Initial conditions
Pressure (bar) 1.1
Temperature (K) 330
Equivalence ratio 0.4
Turbulent kinetic energy (m2/s2) 0.01
Turbulent dissipation rate (m2/s3) 0.01
Swirl velocity (m/s) 0.01
Boundary conditions
Cylinder temp. (K) 400
Head temp. (K) 450
Piston temp. (K) 550
Test case
Generic HCCI engine
Setup :
• Compressible flow
• Laminar Finite Rate
• Dynamic mesh : Crank Angle step of 0.5, reduced to 0.1 around ignition
• 20 iterations per time step, 866 time steps
head
piston
cylinder
Mesh : 650 up to 11550 cells
Engine properties : Compression ratio : 13.5 Speed : 1500 RPM Simulation from IVC -143 CA aTDC to EVO 130 CA aTDC
axis
Mechanism : 160 species / 1540 reactions (n-heptane flame)
© 2011 ANSYS, Inc. November 4, 2015 61
Test matrix
Run the case with Direct Integration (no chemistry acceleration tool)
Run the case with ISAT (storage 500 MB, tol = 1e-04, cleaning up the table every 50 time-steps)
Run the case with Dynamic Mechanism Reduction (default tolerance = 0.01)
Run the case using both ISAT and DMR
Compare R15 and R16 in terms of
• Accuracy (averaged temperature time evolution in the cylinder)
• Speedup on the ODE solver runtime
© 2011 ANSYS, Inc. November 4, 2015 62
Comparison in runtimes between R15 and R16 Speedup Factors = ODE solver runtime case R15 / ODE solver runtime case R16
93%
60%
72%
31%
92%
40%
28%
69%
Percentage represents the ODE solver runtime over the total runtime
In R16 the chemistry ODE solver runtime becomes comparable or sometimes less
than the transient flow solver
© 2011 ANSYS, Inc. November 4, 2015 63
Comparison in accuracy between R15 and R16 Direct Integration case (no chemistry acceleration tool)
Similar accuracy between R15 and R16
© 2011 ANSYS, Inc. November 4, 2015 64
Chemistry acceleration tools in R16 Speedup Factors = ODE solver runtime case DI / ODE solver runtime
© 2011 ANSYS, Inc. November 4, 2015 65
Chemistry acceleration tools in R16 Accuracy comparison
© 2011 ANSYS, Inc. November 4, 2015 66
• Different modes are available in ANSYS CFD to model detailed reactions mechanisms
• A variety of chemistry acceleration tools are also available to speed up the chemistry calculation
– Depending on the size of reaction mechanism they can be combined to achieve calculation speed-up
• Variety of problems are modeled using detailed reactions in FLUENT
– Flames
– Compressible
– Cryogenic conditions
– IC Engine
– Self ignition…….
Summary