Assessment of LES- CMC simula4ons for Spray A combus4on

Transcription

1 Assessment of LES- CMC simula4ons for Spray A combus4on IEA Work Shop Detroit, 7 th April 2014 D. Farrace*, R. Schindler, Y. M. Wright and K. Boulouchos Aerothermochemistry and Combustion Systems Laboratory ETH Zurich, Switzerland * dfarrace@lav.mavt.ethz.ch

2 Motivation Outline Experimental setup Sandia constant-volume combustion chamber, test cases Methodology Numerical setup CMC combustion model Averaging procedure Results Non-reactive Averaging procedure and mesh sensitivity Two-phase flow validation Reactive Ignition delay, Lift-off length Integrated OH comparison Conclusions and Outlook 2

3 Motivation Investigation of cycle-to-cycle ignition fluctuations for diesel spray combustion Spray ignition is key process for dual fuel engines Strong influence on flame growth and combustion stability Investigation of soot mechanisms in transient sprays Numerical investigations with LES can support experiments More flexible Better insight (all data available for post-processing) Physical phenomena can be investigated in detail Good spray as a first step for further investigations 3

4 Experimental setup Sandia constant-volume chamber with optical access Non-reactive cases Orifice pressure drop 500, 1000, 1500 bar Oxygen content («EGR») 0 % V 1.25 l z Air pressure 49.6, 60.5 bar Air temperature 900, 1100 K Temperature variation Inj. pressure variation Reactive cases Orifice pressure drop 1500 bar Oxygen content («EGR») 13, 15, 21 % Air pressure 52.5, 60.5, 66.2 bar Air temperature 800, 900, 1100 K Temperature variation EGR variation 4 different cases 6 different cases Measurement techniques: Mixing (Rayleigh scattering) Penetration length (Schlieren / Mie-scattering) Ignition delay (pressure trace) Lift-off length (OH* chem.) Source: L.M. Pickett and D.L. Siebers, Int. Journal of Eng. Res (2006) 4

5 3D CFD code STAR-CD v4.20 Mesh: 3D-Cartesian Coarse grid: 0.52 Mio. cells Standard grid: 1.87 Mio. Cells Fine grid: 2.75 Mio. cells Initial conditions: quiescent, homogeneous mixed flow field Turbulence model (LES): k-l / Dynamic structure (DSM) Spray model: Lagrangian Atomisation: Reitz-Diwakar Break-up: Reitz-Diwakar / KHRT Combustion model: Conditional Moment Closure with Numerical setup Reduced C 7 H 16 mechanism: Liu* 22/44 species Reduced C 12 H 26 mechanism: Luo** 106 species (first attempts) *) Mechanism: Liu et al., Comb. Flame 137 (2004) **) Mechanism: Luo, Doctoral Dissertations (2013) 5

6 Species Q α t CMC combustion model ( ) + u i η Q α = N η 2 Q α u Y i α η ρ P(η) η 2 ρ P(η) Le =1 + w α η Qα = Yα ξ = η Q T t Conditional velocity + u i η Q T = N η 2 Q T η 2 ( ) u T η ρ P(η) i ρ P(η) Molecular mixing + c p 1 η + N η 1 P ρ t Conditional turbulent flux c p η + 1 η c p η η Chemistry Temperature N + c p,α η Q α α =1 η w H η ρ η c p η + w η RAD Q T η ρ η c p η + w η WALL ρ η c p η Time-varying pressure Chemistry Radiation Wall heat transfer Source: De Paola, Mastorakos, Wright & Boulouchos, Combustion Science and Technology 180 (2008) 6

7 Averaging procedure Spatial averaging: Uniform half sections in polar coordinates ( points per half section) Interpolate and average over all considered sections Distance between sections should be larger than resolved turbulent length scales Time averaging: No multiple simulations attempted Averaging over 1ms after establishment of quasi steady-state (lift-off length stabilisation) Θ 7

8 Results: Non-reactive Averaging procedure sensitivity Mixture fraction 10 half planes 50 half planes half planes 50 half planes 21 time steps Number of timesteps 8

9 Results: Non-reactive Grid sensitivity Coarse grid cells Smallest cell: mm Standard grid cells Smallest cell: mm Fine grid cells Smallest cell: 0.1 mm Mixture fraction Mixture fraction Mixture fraction Experiment Experiment Experiment Simulation Simulation Simulation Exp. Sim

10 Liquid length: Liquid length highly sensitive to threshold More robust definition is required (99% of liquid mass?) Vapour penetration: Underestimated with all turbulence models à spray momentum issue Results: Non-reactive Vapor and liquid length CMT* injection profile Virtual ROI generator (~10% more mass flow) * CMT-Motores Termicos (Valencia) 10

11 Exper. Simul. Mixture fraction Results: Non-reactive DSM / KHRT (900K, 15% O 2, 150MPa) Experimental uncertainty: 95% confidence interval* Calculated mean MF within exp. uncertainty Calculated MF std. deviation reflects well the experimental std. deviation trend Exp. Sim. * Engine Combustion Network 11

12 Exper. Mixture fraction Results: Non-reactive DSM / KHRT (900K, 15% O 2, 100MPa) Injection pressure influence: Δp inj =1000 bar Simul. Relative good agreement Mixture fraction slightly underestimated downstream Exp. Sim. 12

13 Results: Reactive Ignition delay Temperature variation Oxygen variation heptane 0.89 (105%) Exp-heptane* / Luo Exp-heptane* 0.26 (108 %) 0.29 (55%) dodecane 0.05 ms (~12%) 0.28 (88 %) Trend over temperature and EGR sweeps well captured n-heptane chemical mechanism used for n-dodecane combustion à strongly reduced computational costs (~15 times less expensive) *) Pastor et al., 14. Tagung Graz,

14 Results: Reactive Lift-off length Temperature variation Oxygen variation 7 (36%) 4.9 (31%) 3 (33%) 1.5 (13%) Lift-off length highly dependent on Scalar Dissipation Rate (flow field)* à likely explaining the lift-off underestimation à confident for improving by considering effect of evaporation on MFV *) Bolla et al., CTM, 2014 (in press) 14

15 Conclusions & Outlook First attemps of LES-CMC simulations Setup optimization for non-reactive cases, two-phase validation Mixing of spray well predicted in the visible range of 18 to 50 mm in axial distance Ignition delay: trend well predicted with n-heptane chemistry, excellent agreement for n-dodecane chemistry Lift-off length underpredicted for all cases, but trend captured à underestimation attributed to flow field Further investigations Influence of numerical schemes and CMC grid Assess the accuracy of the time averaging procedure (multiple sim.) Modeling of the evaporation contribution in the MFV equation 15

16 Thank you! Questions, comments, suggestions? IEA Work Shop Detroit, 7 th April 2014 Funding: Competence Center for Energy and Mobility Swiss Federal Office for Energy