Topic 1 – Internal flow Presenter: Marco Arienti, Sandia National Laboratories Support by Sandia National Laboratories’ LDRD (Laboratory Directed Research and Development) is gratefully acknowledged. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

Spray C/D (4 contributors) Politecnico di Milano - OpenFoam:     Ehsanallah Tahmasebi,  Tommaso Lucchini and Gianluca D'Errico ANSYS-FLUENT: Saeed Jahangirian, Aleksandra Egelja-Maruszewski, and Huiying Li Università di Perugia - Converge: Michele Battistoni CMT - CavitatingFoam (OpenFoam) Pedro Martí

Spray C Spray D Common rail fuel injector Bosch 3-22 Fuel injector nominal diameter 0.20 mm Nozzle K factor K=0 Nozzle shaping 5% hydroerosion Flow with 10 MPa pressure drop 200 cc/min Number of holes 1 (single hole) Common rail fuel injector Bosch 3-22 Fuel injector nominal diameter 0.186 mm Nozzle K factor K=1.5 Nozzle shaping Hydroerosion to Cd=0.86 Flow with 10 MPa pressure drop 228 cc/min Number of holes 1 (single hole) Wireframe of the tangentially-averaged interior wall of the sac Radius Axial coordinate

Zwart-Gerber-Belamri Institution/Code Uni-PG Converge ANSYS-FLUENT Polimi OpenFOAM - cavitatingFoam CMT Cavitation Model Homogenous Relaxation Zwart-Gerber-Belamri Homogenous Equilibrium Inclusion of turbulent viscous energy generation Y Turbulence LES Dynamic sgs RANS: SST k-ω with compress. SST k-ω - k-epsilon - SST k-ω Spatial discretization 2nd order - QUICK for void fraction - 2nd order Solver PISO Steady-State Coupled PIMPLE Yl = 1.46e-6 s2/m2 Yv= 3.43e-5 s2/m2 Instead of the classical PISO algorithm, a PIMPLE approach is used to support partial convergence of intermediate iteractions, it can be turned into a PISO or SIMPLE algorithms by selecting the right number of inner and outer loops. PIMPLE algorithm combines the loop structures of PISO and SIMPLE, including @=@t terms in equations but not limited by Courant number [OpenFOAM]. POLIMI Details about the solver and its validity presented by (Salvador et al 2010) For solving N-S equations , PIMPLE (Piso-Simple) algorithm with 3 correctors and 4 non-orthogonal correctors is used. Adjustable time steps according to the maximum Courant number =0.5 and maximum Acoustic Courant number = 20 is applied. Euler algorithm for time derivatives, and Gauss algorithms are used for divergence schemes. Results are presented at time = 0.002

EOS models Uni-PG Converge ANSYS-FLUENT Polimi OpenFOAM - cavitatingFoam CMT K liquid bulk modulus. Schmidt et al., Int. J. of Multiphase Flow (2010) [1] Caudwell et al., Int. J. of Thermophysics 25(5) 2004 [2] To match Khasanshin, et al. Int. J. of Thermoph. 24(5) 2003 [3] Zwart et al. ICMF 2004 [1] Salvador et al., Mathematical and Computer Modelling 52 2010 [1] Desantes et al., SAE l Paper 2014-01-1418 [2] Khasanshin, et al. Int. J. of Thermophysics 24(5) 2003

Fixed fully open needle configuration Institution Code Uni-PG Converge ANSYS-FLUENT Polimi OpenFOAM CMT Inlet boundary P = 150 MPa T = 343 K Outlet boundary P = 20 MPa T = 303 K Fixed fully open needle configuration CMT: Time varying static pressure? Low of the wall? Slip vs. no slip?

3D, full axis-symmetric model Institution Code Uni-PG Converge ANSYS-FLUENT Polimi OpenFOAM - cavitatingFoam CMT OpenFOAM -cavitatingFoam Dimensionality 3D, full axis-symmetric model 2D axis-symmetric 3D 5o wedge Cell Type - Cartesian cut cells - Wall functions, y+ = 30 Hex mesh with 10 boundary layers (from 1 μm) Hex & tets quads Cell count (total interior and exterior) 2.5 mm 20k (79k in adapted mesh) 51k (Spray C) 54k (Spray D) Submerged N Y

Internal flow: sharp (spray C) vs. smooth (spray D) pressure decrease

Without cavitation, Spray D produces a slightly longer liquid core length and a narrower cone angle Spray C Spray D

This effect is recognized in new measurements of the spray width and length From spray boundary contrast (threshold 0.37 KL) using the diffuse backlit illumination (DBI) technique:* Diffuse backlit illumination is a technique for measuring soot volume fraction and liquid length. KL is what we call the optical thickness and has no dimension. It is the natural logarithm of the transmission of light through the line of sight. The diffused nature of the light counteracts beam steering effects caused by gradients in the refractive index through the media and leaves only light attenuation from absorption and scattering. The dense spray region near the nozzle scatter the light and we use this physical interaction to identify the spatial location of the liquid phase of the spray. *from Fredrik Westlye’s presentation

Comparison against measured mass flow rate [g/s] CONVERGE and FLUENT-ANSYS simulations are the only that capture the increase between spray C and D In the aggregate, there is more variation amongst models for the same spray type than between the sprays for the same model

Comparison against measured momentum CONVERGE and FLUENT-ANSYS simulations are the only to capture the increase between spray C and D (by a rather small margin)

Mass flow rate and momentum values SPRAY C Experiment(*) Uni-PG Converge ANSYS-FLUENT Polimi OpenFOAM k-ω SST CMT OpenFOAM k-ε Mass flow rate (g/s) 10.07±0.11 10.3 10.8 12.8 10.4 Momentum (N) 5.83±0.06 6.29 6.49 7.69 6.30 6.79 SPRAY D Experiment Uni-PG Converge ANSYS-FLUENT Polimi OpenFOAM k-ω SST CMT OpenFOAM k-ε Mass flow rate (g/s) 11.72±0.15 10.9 11.3 11.6 10.2 10.5 Momentum (N) 7.03±0.11 6.41 6.62 6.27 6.24 6.69 (*) std. dev. from the CMT measurements on 5 different specimens

Spray C: noticeable differences in boundary thickness between simulations

Spray D vs. spray C at the exit orifice Similar velocity/density profiles are obtained for spray D Cavitation displaces mass flow toward the orifice axis in spray C Spray C Spray D

The effect of cavitation for spray C Note the different models’ effectiveness in generating cavitation at the orifice’s wall liquid core boundary

Conclusions Relatively small variations in the amount of cavitation at the wall result in differences of mass flow rate and momentum for spray C simulations Even when the variation is correctly predicted, its magnitude is underestimated The trend in spray penetration/width from spray C to spray D is correctly captured by the only non-submerged simulation (UniPG with Converge) Cannot quantify agreement for lack of averaged data Passing pockets of vapor in the liquid core are shown in the only LES simulation (UniPG with Converge) A frequency analysis of this feature is recommended

Topic 1.2 – Spray A needle transient opening Presenter: Marco Arienti, Sandia National Laboratories Support by Sandia National Laboratories’ LDRD (Laboratory Directed Research and Development) is gratefully acknowledged. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

Two of the remaining questions for Spray A from ECN3: What is the exit temperature of the fuel? Is the injection transient modeled realistically?

Spray A (3 contributors) CMT - OpenFOAM w/ Eulerian Spray Atomization Pedro Martí Bosch - Cascade Technologies Edward Knudsen, Eric Doran (Bosch Research & Technology Center) SNL - CLSVOF Marco Arienti Initial transient was not the priority for Bosch

Institution: Code: Bosch Cascade Technologies CMT OpenFOAM ESA SNL CLSVOF Equation of State for the liquid phase Peng-Robinson Non-linear r(P,T)(Payri et al., Fuel 2011) Tait eqn. calibrated for n-dodecane; new e(P,T) Moving mesh N N/Y (axial only) Y Inlet Static pressure increases from 0.5Pinj to Pinj at t = 0 Time-varying static pressure Constant pressure Turbulence LES Dynamic sgs model RANS SST k-ω No turbulence model Inclusion of turbulent viscous energy generation? Spatial Discretization 2nd order 1srorder 1st / 2nd order 􏱡􏰳􏰵CMT inlet boundary condition: constant temperature time-varying velocity condition at injection pressure and temperature. ‪I use the standard mesh solver included in OpenFOAM. The input is the wall velocity and direction, and I set up the solver for cells deforming equally in all directions.

Spray A reference and actual laboratory conditions At SNL and ANL, ambient density is matched at cooler, non-vaporizing conditions. From Lyle et al. SAE 2014-01-1412 Spray A ANL SNL Liquid T [K] 363 333 343 Gas 0% O2 N2 Gas T [K] 900 303 440 Back-pressure [MPa] 6 2 3 Density kg/m3 22.8 Bosch*, CMT+ SNL+ Injection into a low-temperature environment is necessary at Argonne in order to prevent damage to x-ray transparent polymer windows. A slightly elevated ambient temperature (440 K) at Sandia is required because of seal design for the high-temperature chamber. The ambient temperature in either facility is lower than the boiling point temperature for n- dodecane (489 K at 1 bar) such that minimal vaporization occurs. Line-of-sight radiography measurements were made at different axial and radial positions. *Tfuel,intern.< 363 K +Tfuel,intern. = 343 K

Exit temperature predictions from ECN3 ANL Converge Sandia CLSVOF UMass HRMFoam CMT ESA IFP C3D Incompressible Non-linear function of p,T Const. compressibility Stiffened gas EOS turbulent viscous energy generation Specific heat constant for CMT DT = 0 DT ≅ 0 DT << 0 DT << 0 DT < 0 T [K]

Contributions to DT = Texit-Tinlet Expansion through the orifice  Viscous energy dissipation  Heat transfer through injector’s wall DT 

Liquid phase compression Peng-Robinson Calibrated Tait 100% C12H26 Tc = 658 K rc =226 kg/m3 p = 2000 bar r = r0(T ), p0 = 1 bar Liquid phase compression CMT - Density and speed of sound as function of pressure and temperature were calculated by Khasanshin et al. [22]. [Caudwell et al., Int. J. of Thermophysics, 2004]

Isentropic expansion upper bound: Dp = -1440 bar DT = -22 K from calibrated Tait EOS DT = 0 K from isobaric EOS DT = -217 K from adiabatic p.g. EOS (g =1.4) 787 kg/m3 363 K 1500 bar 646 kg/m3 341 K 60 bar adiabatic p.g.: g = 1.4 Density[ kg/m3] Temperature [K] Crosses r = 600 at 102.5 Mpa Gets to 145 K

SNL results show limited temperature increase with adiabatic walls Temperature [K] Density [kg/m3] Adiabatic w. Constant TW = 383 K Adiabatic w. Constant TW = 383 K 343 351 359 367 375 383 720 736 752 768 784 800 DTL,exit = +3 K DTL,exit = +18 K rL,exit = 716 kg/m3 rL,exit = 720 kg/m3

CMT results also show small DT except near the wall Temperature [K] Density [kg/m3] Adiabatic 343 K Constant TW = 363 K Adiabatic 343 K Constant TW = 363 K

The viscous dissipation of turbulent energy is the main source of temperature increase Orifice cross-sections: 273 K 303 K 323 K Adiabatic 343 K 363 K

However, the opening transient displays a bulk temperature increase Simulation with moving needle Tw = 383 K Interpretation: the fuel heats up while passing through the narrow gap between needle and injector This effect disappears once the passage is fully open

Independent study: transient and non-isothermal modeling of cavitation with GFS* Steady-state temperature field Variation of the outlet temperature in one injection cycle 350 K 500 K Minimum gap: 5 mm (with standard wall function) Minimum cell size Dx = 0.5-0.83 mm City University in London *By Salemi, McDavid, Koukouvinis, Gavaises, and Marengo, in ILASS 2015

Conclusions on DT = Texit-Tinlet Expansion through the orifice: Moderate but constant during injection Potentially under-estimated depending on EOS Viscous energy dissipation: Potentially large but transient Puts under scrutiny the choice of standard wall function in micron-size gap

The measured Rate of Injection (ROI) and Rate of Momentum (ROM) of Spray A The experiments were intended to be "cold", but in fact we have a different ambient gas T distribution and the duty cycle on the injector is different. In addition, Argonne's data are an ensemble average as collected, rather than a collection of instantaneous data that is later averaged. There may be some jitter problems that make it harder to define the true start of injection. In the lab, vibrations may transmit pressure waves in the hydraulic tube that are falsely associated as ROI The virtual ROI has been tuned based on some the experimental data that are considered real—for example we have measured momentum that coincides with measured fuel pressure fluctuations (measurement is 7 cm from the injector inlet). We believe those. Please also see the latest in SAE 2013-24-0001 Diagram from SAE 2013-24-0001

Initial conditions: injection delay as a function of partially filled sac/orifice Vgas = 0.065 mm3 (1/3of the sac) Tdelay = (339-330) ms = 9 ms Fully open fuel passage Time of apparent injection Tdelay = 3 ms (instantaneous opening) Vgas = 4 mm3 (half orifice) At t < 0 the pressure in the sac is ~Pinj/2

Mass flow rate during opening transient* Steady mass flow: 2.56 g/s *After removing all injection delays

Momentum flow rate during opening transient

Jet penetration during opening transient I think it is worth mentioning explicitly in the caption that bosch has a fixed needle.  As I mentioned to Sibendu, we looked a lot more at downstream penetration than at initial transients and we therefore didn’t tune the initialization to match experiments.  The transient profile that you plot is fine to show, but it would be helpful to make clear that its shape a strong function of our arbitrary initialization and the lack of needle movement.

A request: establish a common set of properties and reliable EOS correlations T = 353 K Pressure [MPa] Speed of sound [m/s] Example: speed of sound calculation for liquid n-dodecane Khasanshin et al., Int. J. of Thermophysics, 24(5) 2003 Padilla-Victoria, Fluid Phase Eq. 2013 Note that D coefficient in Arient’s paper should be corrected as: D = 0.16+(0.778- 0.7155)/12+2.5e-3*T-5.85e-6*T*P;

Backup

Note 3: Dependence of internal energy on pressure P = 0.1 MPa P = 20 MPa P = 140 MPa New fit: NIST data: P = 0.1 MPa P = 20 MPa P = 140 MPa Supercritical Equation of state for n-dodecane compiled from data; Khasanshin, et al., Int. J. of Thermophysics, 2003. Padilla-Victoria et al., Fluid Phase Equilibria 2013. [JSAE 20159137 SAE 2015-01-1853]

Experiment set-up and reference parameters Fuel n-dodecane Inlet pressure 150 MPa Ambient pressure 6 MPa Fuel Temperature 363 K Thermodynamic properties from NIST web-book (for dodecane): Vapor sound speed (m/s) 134.59 Liquid sound speed (m/s) 1037.8 Liquid saturation density (kg/m3) 697.13 Vapor density (kg/m3) 0.071548 Saturation pressure (Pa) 12622 Liquid viscosity (Pa.s) 5.6 e-4 Vapor viscosity (Pa.s) 5.44 e-6 (6-12622*1e-6)/(150-6)=0.0415 mu = 2.5e-3 kg/m/s Re C = 4*10.26/PI()/0.02^2*0.02/0.025=26k Re D = 4*11.67/PI()/0.0186^2*0.0186/0.025=32k Cav 0.042 Re 26k/32k 41 41

Details of mesh preparation

Meshing Institution Bosch New meshing tool by Bosch-Cascade Flow Domain Chamber: 45 mm Long New meshing tool by Bosch-Cascade Start from CAD surfaces Seed domain with points Build Voronoi diagram, connectivity No sliver cells at boundaries Face normals point to cell centers Minimal cell skew More ‘sampling’ than hexes Institution Bosch Dimensionality 3 Cell Type 14-faced polyhedra Cell count (total) 3x106 Voronoi Mesh

Institution CMT Institution SNL Dimensionality 2 Cell Type Quad Cell count (total) 67.4K Geometry 12x6 mm Institution SNL Dimensionality 3 Cell Type Cube Cell count (total) 7x107 to 21x107 Geometry 1.7x1.7x15.3 mm CMT: is it immersed flow?