direct numerical simulations (dns) in simplified ice...
TRANSCRIPT
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LL
LES4ICE, Rueil-Malmaison, December 2018
Direct Numerical Simulations (DNS) in simplified ICE configurations
using immersed boundaries and detailed chemistry
Dominique Thévenin
Institute of Fluid Dynamics & Thermodynamics, Univ. of Magdeburg „Otto von Guericke“, Germany
[email protected] http://www.lss.ovgu.de
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Ø Turbulent flows with reactions are of fundamental interest and are found in uncountable practical applications, due to § Changing energy supplies, § Increased environmental pressure, § Need for a better control of process outcome, § More stringent safety regulations, § ...
Introduction
Ø In order to get an accurate representation of turbulent ignition and propagation, the present study relies exclusively on Direct Numerical Simulation (DNS)
Ø Taking into account real geometrical features becomes increasingly necessary
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Research relevant for ICE DNS study LES-based optimization of injection
[Hellmann et al., ICLASS, Chicago, 2018]
[Abdelsamie & Thévenin, Proc. Combust. Inst. 37, (2018) in press]
Spray ignition and combustion
[Theile et al., SAE Int. J. Engines 9(4), (2016) 1-17]
LES of cyclic variability
[Chittipotula et al., Chem. Eng. Sci. 70, (2012) 62-76]
Nanoparticle generation
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Needed building blocks?
• Taking into account detailed reaction networks, • and suitable schemes (from literature)
DNS in simplified ICE configurations using immersed boundaries and detailed chemistry
• Able to treat complex, possibly moving geometries
A (validated and efficient)
DNS code: DINO
Intr
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A (validated and efficient)
DNS code: DINO
Needed building blocks?
DNS in simplified ICE configurations using immersed boundaries and detailed chemistry
Intro
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DINO in a nutshell Ø 3rd-generation DNS tool in the group Ø High-order finite-difference solver Ø with Immersed Boundary Method (IBM) Ø Involving 3 co-developers (GIT), started 2012 Ø Core in Fortran 2003, external layer of C++ Ø Dimensional code Ø Currently: 7 users in 4 countries Ø Low Mach number or incompressible formulation Ø Semi-implicit time integration (Rosenbrock approach with direct Jacobian computation for reactions) Ø Up to 6th order in space, 4th order in time Ø Adapted but static tensor-product grid
[Abdelsamie et al., Comput. Fluids 131, (2016) 123-141] Intro
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Parallelization
Ø Parallelization: domain decomposition using MPI Ø Based on 2D x-pencil (2Decomp&FFT, open source)
Ø Including efficient 2D parallel FFT solver
Ø Taking further advantage of this to solve Poisson equation with FFT
Ø Even for non-periodic boundary conditions: then use in-house pre- & post-processing
Ø All simulations on SuperMUC (Leibniz Supercomputing Center in Munich) with nx1000 processors
yx
z
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Validation: turbulent flow Excellent agreement with experimental data
Excellent agreement with DNS of Moser et al., Vreman & Kuerten...
[Abdelsamie et al., Comput. Fluids 131, (2016) 123-141]
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Needed building blocks?
• Taking into account detailed reaction networks, • and suitable schemes (from literature)
DNS in simplified ICE configurations using immersed boundaries and detailed chemistry
Intro
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ion
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Detailed reaction networks
Oxidation mechanism involving many species and elementary reactions, providing accurate results also for complex fuels and configurations
∂ρ
∂t+
∂(ρuj)
∂xj= 0
∂(ρui)
∂t+
∂(ρuiuj)
∂xj= −
∂p
∂xi+
∂τij∂xj
(i = 1, 2, 3)
∂et∂t
+∂ (et + p)uj
∂xj=
∂ (ujτkj)
∂xk−
∂qj∂xj
∂ (ρYl)
∂t+
∂ (ρYluj)
∂xj= −
∂ (ρYlVDlj)
∂xj+Wlω̇l (l = 1 . . .Ns)
p = ρrTNs!
l=1
Yl = 1
τ = 2µd−2
3µ(∇.v) I or
τ = 2µd+ κ(∇.v) I
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Successfully tested up to 352 species and 13,264 elementary reactions in DINO (butanol)
from literature…
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Physicochemical models Ø Chemical kinetics described by:
§ CANTERA (default) § (CHEMKIN) § Tabulated chemistry
Ø Transport processes described by: § CANTERA (default) § EGlib § (TRANSPORT)
Ø Thermodynamics described by: § CANTERA (default) § (CHEMKIN)
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Kin
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12 sL =
ω k1
2
∫ dx + ρD∇Yk2 − ρD∇Yk
1
ρ1(Yk2 −Yk
1)
Luo et al., 2012: 32 species & 206 reactions UCSD, 2003: 39 species & 173 reactions UCSD, 2005: 46 species & 235 reactions
For example for ethylene (C2H4):
Validation: reacting flows
Flame speed Ignition delay
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Needed building blocks?
• Able to treat complex, possibly moving geometries
DNS in simplified ICE configurations using immersed boundaries and detailed chemistry
Intro
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Ghost-cell Immersed Boundary Ø Force term not computed directly, but enforced indirectly by the fictitious velocity at ghost points
Ø Conventional IBM: boundary-normal projection
[Chi et al., Int. J. Numer. Meth. Fluids 83, (2017) 132-148]
Φbp = 0.5(Φip +Φgp )+o(Δl2 )
Δl
Δl = o(Δx)
Poor assumption!
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New higher-order ghost-cell IBM
Flapping wing, Re=157
Ø Novelty 1: local directional extrapolation Accurate boundary representation, avoiding extra
iterations in the extrapolation scheme (better parallelization) Ø Novelty 2: always a single layer of ghost points
Sharp interface representation Ø Novelty 3: Δl = o(Δx) is not any more an assumption
Convergence rate ensured
[Chi et al., J. Comput. Phys., under review] Intro
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Resulting spatial order of IBM
2nd order
DINO/IBM
Test case: flow around cylinder Ref St = f D/U∞
Tseng et al. 0.164
Lai et al. 0.165
Kim et al. 0.165
Dias et al. 0.171
Williamson (Exp.) 0.166
Present IBM 0.166
IBM-Wall
IBM-Wall
flow
Test case: tilted Poiseuille flow Intro
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A (validated and efficient)
DNS code: DINO
Application examples
• Taking into account detailed reaction networks, • and suitable schemes (from literature)
• Able to treat complex, possibly moving geometries
DNS in simplified ICE configurations using immersed boundaries and detailed chemistry
Intro
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Simple ICE model
wall geometry/piston represented by IBM level-set function = 0
Compression ratio: 12Piston speed: 560 rpm (just enough to get turbulence, Remax=2990)
Ø Reference experiment of Morse et al. (1978) Ø Later investigated in a number of URANS and LES studies Ø First cold-flow DNS documented in Schmitt (2014), followed by numerous investigations, in particular by the same group (ETH Zürich) Ø Prescribed piston movement (sinus) Ø Prescribed inflow velocity Ø Isothermal no-slip walls Ø Mesh resolution down to 7,5 µm
moving piston
top dead center (TDC)
bottom dead center (BDC)
75 mm 60 mm
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Velocity of the piston reaches maximum. Jets impact side walls and separate. Rupture of symmetry.
90oCA45oCA
Gas is pushed in, and jets/vortex ring form.
Velocity magnitude
Cold-flow intake stroke
Flow dominated by flapping jets and small-scale structures.
135oCA
Piston reaches BDC. Large recirculating vortices still visible.
180oCA
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Mixing during intake stroke (2D) In
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Velocity magnitude Temperature Y(H2)
Inside cylinder: Y(O2) = 0.115, Y(N2) = 0.756, Y(H2O) = 0.129 Injection: homogeneous H2/air mixture at φ = 0.5
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Compression stroke (2D) In
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Temperature Y(H2)Zoom on self-ignition
Mechanism of Williams (9 species, 12 reversible reactions)
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Ø Progress in numerical techniques as well as computer power now allow DNS investigations of flows with reactions in complex, moving geometries
Ø DNS is a perfect tool to gain a deeper understanding, and investigate ignition and flame propagation,
Ø but many challenges remain, for instance: § Correct description of all transport and thermodynamic
properties for all relevant conditions; § Deriving from DNS simple but sufficiently accurate
models; § Efficient (on-the-fly) analysis of the results (no full
storage possible!) § …
Conclusions
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Next steps
[Eshghinejadfard et al., J. Fluid Mech. 849, (2018) 510-540]
[Hosseini et al., Physica A 499, (2018) 40-57]
Ø Fine-tune IBM implementation Ø 4th-generation DNS tool as hybrid with Lattice-Boltzmann? - Velocity/pressure (LB); Thermochemistry (Finite-Diff.)
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Dr. Abouelmagd Abdelsamie
Cheng Chi
Financing: DFG (Deutsche Forschungsgemeinschaft), Max Planck Society, German Ministry of Research, Volkswagen AG, Bosch GmbH Computing time: Leibniz Supercomputing Center, Munich
Dr. Martin Theile
Assoc. Prof. Gábor Janiga
Robin Hellmann Ali Hosseini