A zonal hybridization of the RNG - URANS model is proposed for the simulation of turbulent flows in internal combustion engines. The hybrid formulation is able to act as URANS, DES or LES in different zones of the computational domain, which are explicitly set by the user. The resulting model has been implemented in a commercial computational fluid dynamics code and the LES branch of the modified RNG - closure has been initially calibrated on a standard homogeneous turbulence box case. Subsequently, the full zonal formulation has been tested on a fixed intake valve geometry, including comparisons with third-party experimental data. The core of the work is represented by a multi-cycle analysis of the TCC-III experimental engine configuration, which has been compared with the experiments and with prior full-LES computational studies. The applicability of the hybrid turbulence model to internal combustion engine flows is demonstrated, and PIV-like flow statistics quantitatively validate the model performance. This study shows a pioneering application of zonal hybrid models in engine-relevant simulation campaigns, emphasizing the relevance of hybrid models for turbulent engine flows.
SpalartPRJouWHStreletsMKAllmarasSR. Comments on the feasibility of LES for wings, and on a hybrid RANS/LES approach. In: LiuCLiuZ (eds) Advances in DNS/LES. Columbus, OH: Greyden Press, 1997, pp.137–147.
2.
TuckerPG. Computation of unsteady turbomachinery flows: part 2—LES and hybrids. Prog Aerosp Sci2011; 47: 546–569.
3.
TuckerPGDeBonisJR. Aerodynamics, computers and the environment. Philos T R Soc A2014; 372: 20130331.
4.
HasseCSohmVDurstB. Detached eddy simulation of cyclic large scale fluctuations in a simplified engine setup. Int J Heat Fluid Fl2009; 30: 32–43.
5.
KrastevVKDi IlioGFalcucciGBellaG. Notes on the hybrid URANS/LES turbulence modeling for internal combustion engines simulation. Enrgy Proced2018; 148: 1098–1104.
6.
BuhlSHartmannFHasseC. Identification of large-scale structure fluctuations in IC engines using POD-based conditional averaging. Oil Gas Sci Technol2016; 71(1): 1–16.
7.
BuhlSGleissFKöhlerMHartmannFMessigDBrückerCHasseC. A combined numerical and experimental study of the 3D tumble structure and piston boundary layer development during the intake stroke of a gasoline engine. Flow Turbul Combust2017; 98(2): 579–600.
8.
BuhlSDietzschFBuhlCHasseC. Comparative study of turbulence models for scale-resolving simulations of internal combustion engine flows. Comput Fluids2017; 156: 66–80.
9.
BuhlSHainDHartmannFHasseC. A comparative study of intake and exhaust port modeling strategies for scale-resolving engine simulations. Int J Engine Res2018; 19(3): 282–292.
10.
PiscagliaFMontorfanoAOnoratiA. A scale adaptive filtering technique for turbulence modeling of unsteady flows in IC engines. SAE Int J Engine2015; 8(2): 426–436.
11.
WuYMontorfanoAPiscagliaFOnoratiA. A study of the organized in-cylinder motion by a dynamic adaptive scale-resolving turbulence model. Flow Turbul Combust2018; 100(3): 797–827.
12.
HasseCSohmVDurstB. Numerical investigation of cyclic variations in gasoline engines using a hybrid URANS/LES modeling approach. Comput Fluids2010; 39: 25–48.
13.
HasseC. Scale-resolving simulations in engine combustion process design based on a systematic approach for model development. Int J Engine Res2016; 17(1): 44–62.
14.
KrastevVKBellaGCampitelliG. Some developments in DES modeling for engine flow simulation. SAE technical paper 2015-24-2414, 2015.
15.
KrastevVKBellaG. A zonal turbulence modeling approach for ICE flow simulation. SAE Int J Engine2016; 9(3): 1425–1436.
16.
KrastevVKSilvestriLFalcucciGBellaG. A zonal-LES study of steady and reciprocating engine-like flows using a modified two-equation DES turbulence model. SAE technical paper 2017-24-0030, 2017.
17.
KrastevVKSilvestriLFalcucciG. A modified version of the RNG k–ε turbulence model for the scale-resolving simulation of internal combustion engines. Energies2017; 10: 2116.
18.
KrastevVKSilvestriLBellaG. Effects of turbulence modeling and grid quality on the zonal URANS/LES simulation of static and reciprocating engine-like geometries. SAE Int J Engine2018; 11(6): 669–686.
19.
Di IlioGKrastevVKPiscagliaFBellaG. Hybrid URANS/LES turbulence modeling for spray simulation: a computational study. SAE technical paper 2019-01-0270, 2019.
20.
RutlandCJ. Large-eddy simulations for internal combustion engines—a review. Int J Engine Res2011; 12(5): 421–451.
21.
BaumannMDi MareFJanickaJ. On the validation of large eddy simulation applied to internal combustion engine flows part II: numerical analysis. Flow Turbul Combust2014; 92: 299–317.
22.
TruffinKAngelbergerCRichardSPeraC. Using large-eddy simulation and multivariate analysis to understand the sources of combustion cyclic variability in a spark-ignition engine. Combust Flame2015; 162: 4371–4390.
23.
ZhaoLMoizAASomSFoglaNBybeeMWahiduzzamanS, et al. Examining the role of flame topologies and in-cylinder flow fields on cyclic variability in spark-ignited engines using large-eddy simulation. Int J Engine Res2018; 19(8): 886–904.
24.
SofianopoulosABoldajiMRLawlerBMamalisSDecJE. Effect of engine size, speed, and dilution method on thermal stratification of premixed homogeneous charge compression–ignition engines: a large eddy simulation study. Int J Engine Res. Epub ahead of print 15 January 2019. DOI: 10.1177/1468087418820735.
25.
KoId’AdamoAFontanesiSMinK. Study of LES quality criteria in a motored internal combustion engine. SAE technical paper 2017-01-0549, 2017.
26.
KoIMinKRulliFd’AdamoABerniFStefanoF. Investigation of sub-grid model effect on the accuracy of in-cylinder LES of the TCC engine under motored conditions. SAE technical paper 2017-24-0040, 2017.
27.
HanZReitzRD. Turbulence modeling of internal combustion engines using RNG k–ε models. Combust Sci Technol1995; 106: 267–295.
28.
El TahrySH. K–ε equation for compressible reciprocating engine flows. J Energy1983; 7(4): 345–353.
29.
TravinAKShurMLStreletsMKSpalartPR. Physical and numerical upgrades in the detached-eddy simulation of complex turbulent flows. In: FriedrichRRodiW (eds) Advances in LES of complex flows. Dordrecht: Kluwer Academic Publishers, 2002, pp.239–254.
30.
SpalartPR. Detached-eddy simulation. Annu Rev Fluid Mech2009; 41: 181–202.
31.
BreuerMJovičićNMazaevK. Comparison of DES, RANS and LES for the separated flow around a flat plate at high incidence. Int J Numer Meth Fl2003; 41: 357–388.
32.
DeckS. Zonal-detached-eddy simulation of the flow around a high-lift configuration. AIAA J2005; 43(11): 2372–2384.
33.
DeckS. Recent improvements in the Zonal Detached Eddy Simulation (ZDES) formulation. Theor Comp Fluid Dyn2012; 26(6): 523–550.
34.
DeckSGandFBrunetVBen KhelilS. High-fidelity simulations of unsteady civil aircraft aerodynamics: stakes and perspectives. Application of zonal detached eddy simulation. Philos T R Soc A2014; 372: 20130325.
35.
SagautPDeckSTerracolM. Multiscale and multiresolution approaches in turbulence: LES, DES and hybrid RANS/LES methods: applications and guidelines. London: Imperial College Press, 2013.
36.
SpalartPRDeckSShurMLSquiresKDStreletsMKTravinAK. A new version of detached-eddy simulation, resistant to ambiguous grid densities. Theor Comp Fluid Dyn2006; 20: 181–195.
37.
ShurMLSpalartPRStreletsMKTravinAK. A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities. Int J Heat Fluid Fl2008; 29: 1638–1649.
38.
ShurMLSpalartPRStreletsMKTravinAK. An enhanced version of DES with rapid transition from RANS to LES in separated flows. Flow Turbul Combust2015; 95(4): 709–737.
39.
KeskinenKNuutinenMKaarioOVuorinenVKochJWrightYM, et al. Hybrid LES/RANS with wall treatment in tangential and impinging flow configurations. Int J Heat Fluid Fl2017; 65: 141–158.
40.
KubackiSDickE. Hybrid RANS/LES of flow and heat transfer in round impinging jets. Int J Heat Fluid Fl2011; 32(3): 631–651.
41.
FröhlichJVon TerziD. Hybrid LES/RANS methods for the simulation of turbulent flows. Prog Aerosp Sci2008; 44: 349–377.
42.
JakirliSKniesnerBKadavelilG. On interface issues in LES/RANS coupling strategies: a method for turbulence forcing. J Fluid Sci Tech2011; 6(1): 56–72.
43.
STAR-CD CFD/CCM user guide, version 4.28. Plano, TX: Siemens Product Lifecycle Management Software, Inc., 2017.
44.
LiuKHaworthDCYangXGopalakrishnanV. Large-eddy simulation of motored flow in a two-valve piston engine: POD analysis and cycle-to-cycle variations. Flow Turbul Combust2013; 91(2): 373–403.
45.
Di MareFKnappsteinRBaumannM. Application of LES-quality criteria to internal combustion engine flows. Comput Fluids2014; 89: 200–213.
46.
FontanesiSPaltrinieriSd’AdamoACantoreGRutlandCJ. Knock tendency prediction in a high performance engine using LES and tabulated chemistry. SAE Int J Fuel Lubr2013; 6(1): 98–118.
47.
FontanesiSPaltrinieriSd’AdamoADurantiS. Investigation of boundary condition and field distribution effects on the cycle-to-cycle variability of a turbocharged GDI engine using LES. Oil Gas Sci Technol2014; 69(1): 107–128.
48.
FontanesiSd’AdamoARutlandCJ. Large-eddy simulation analysis of spark configuration effect on cycle-to-cycle variability of combustion and knock. Int J Engine Res2015; 16(3): 403–418.
49.
d’AdamoABredaSBerniFFontanesiS. Understanding the origin of cycle-to-cycle variation using large-eddy simulation: similarities and differences between a homogeneous low-revving speed research engine and a production DI turbocharged engine. SAE Int J Engine2019; 12(1): 22.
50.
ShekhawatYHaworthDCd’AdamoABerniFFontanesiSSchiffmannP, et al. An experimental and simulation study of early flame development in a homogeneous-charge spark-ignition engine. Oil Gas Sci Technol2018; 72(5): 160164.
51.
d’AdamoABredaSCantoreG. Large-eddy simulation of cycle-resolved knock in a turbocharged SI engine. Enrgy Proced2015; 82: 45–50.
52.
Comte-BellotGCorrsinS. Simple Eulerian time correlation of full-and narrow-band velocity signals in grid-generated, isotropic turbulence. J Fluid Mech1971; 48(2): 273–337.
53.
KnaepenBDebliquyOCaratiD. DNS and LES of a shear-free mixing layer. In: MoinPMansourN (eds) Annual research briefs—2003. Stanford, CA: Center for Turbulence Research, Stanford University, 2003, pp.307–318.
54.
BungeUMockettCThieleF. Guidelines for implementing detached-eddy simulation using different models. Aerosp Sci Technol2007; 11: 376–385.
55.
SmagorinskyJ. General circulation experiments with the primitive equations: I. The basic experiment. Mon Weather Rev1963; 91(3): 99–164.
56.
DeardorffJW. A numerical study of three-dimensional turbulent channel flow at large Reynolds numbers. J Fluid Mech1970; 41(2): 453–480.
57.
YoshizawaAHoriutiK. A statistically-derived subgrid-scale kinetic energy model for the large-eddy simulation of turbulent flows. J Phys Soc Jpn1985; 54(8): 2834–2839.
58.
STAR-CD methodology, version 4.28. Plano, TX: Siemens Product Lifecycle Management Software, Inc., 2017.
59.
ThoboisLRymerGSoulèresTPoinsotT. Large-eddy simulation in IC engine geometries. SAE technical paper 2004-01-1854, 2004.
60.
PopeSB. Turbulent flows. Cambridge: Cambridge University Press, 2000.
61.
PopeSB. Ten questions concerning the large-eddy simulation of turbulent flows. New J Phys2004; 6(1): 35.
62.
DavidsonL. Large eddy simulations: how to evaluate resolution. Int J Heat Fluid Fl2009; 30: 1016–1025.
63.
ThoboisLRymerGSoulèresTPoinsotTVan Den HeuvelB. Large-eddy simulation for the prediction of aerodynamics in IC engines. Int J Vehicle Des2005; 39: 368–382.
64.
SchiffmannPGuptaSReussDSickVYangXKuoT-W. TCC-III engine benchmark for large-eddy simulation of IC engine flows. Oil Gas Sci Technol2016; 71(1): 3.
65.
AmeenMMYangXKuoTWSomS. Using LES to simulate cycle-to-cycle variability during the gas exchange process. In: Proceedings of the ASME internal combustion engine division fall technical conference, vol. 2: emissions control systems; instrumentation, controls, and hybrids; numerical simulation; engine design and mechanical development, Seattle, WA, 15–18 October 2017. New York: ASME.
66.
CicaleseGBerniFFontanesiSd’AdamoAAndreoliE. A comprehensive CFD-CHT methodology for the characterization of a diesel engine: from the heat transfer prediction to the thermal field evaluation. SAE technical paper 2017-01-2196, 2017.
67.
BerniFFontanesiSCicaleseGd’AdamoA. Critical aspects on the use of thermal wall functions in CFD in-cylinder simulations of spark-ignition engines. SAE Int J Commer Veh2017; 10: 547–561.
