This paper presents findings from a numerical study of intake valve jet flapping within a gasoline direct injection engine, using a large eddy simulation turbulence modelling approach. The experimental test case and computational setup, including choice of sub-grid scale turbulence model, are presented and discussed. An example cycle where intake valve jet flapping is seen to be prominent is discussed in detail. It was found to be initiated as a consequence of turbulent fluctuations in the intake valve curtains. Cycle-by-cycle variations in valve curtain flux and subsequent jet flapping events are investigated and significant cyclic variability is found. Finally, it was observed that due to the highly transient nature of this flow phenomenon, the typical ensemble-averaging procedure used in LES simulations causes most information related to this process to be lost

Nick Beavis (3688570)

Salah Ibrahim (1250199)

Weeratunge Malalasekera (1258755)

English

Loughborough University Institutional Repository

 1  3rd Biennial International Conference on Powertrain Modelling and Control 7-9th September 2016, Loughborough UK  A Numerical Study of Intake Valve Jet Flapping in a GDI Engine  N.J. Beavis1, S.S. Ibrahim1, and W. Malalasekera2  1 Department of Aeronautical and Automotive Engineering, Loughborough University, Leicestershire, UK 2 School of Mechanical and Manufacturing Engineering, Loughborough University, Leicestershire, UK  Abstract:  This paper presents findings from a numerical study of intake valve jet flapping within a gasoline direct injection engine, using a large eddy simulation turbulence modelling approach. The experimental test case and computational setup, including choice of sub-grid scale turbulence model, are presented and discussed. An example cycle where intake valve jet flapping is seen to be prominent is discussed in detail. It was found to be initiated as a consequence of turbulent fluctuations in the intake valve curtains. Cycle-by-cycle variations in valve curtain flux and subsequent jet flapping events are investigated and significant cyclic variability is found. Finally, it was observed that due to the highly transient nature of this flow phenomenon, the typical ensemble-averaging procedure used in LES simulations causes most information related to this process to be lost.  Keywords— CFD, flow, GDI, numerical, valve jet flapping 1-Introduction Investigations into the physical processes occurring within internal combustion engines (ICE) have been of research interest for a number of decades [1–4]. One area of continued interest, in particular due to its interaction with the fuel-air mixing and subsequent combustion processes, is the in-cylinder flow field. It can be characterised as: three-dimensional, compressible, spatially and temporally varying, fully turbulent, anisotropic, non-homogeneous, has high levels of interaction with solid boundaries and typically contains complex and highly transient flow phenomena that vary on a cycle-by-cycle basis.  2  Experimental techniques for characterising the in-cylinder flow structure are commonplace in research institutions. However, due to the ICE being a hostile and difficult to access environment, numerical methods remain an integral part of research and development activities.  Within three dimensional-computational fluids dynamics (3D-CFD) numerical modelling techniques, traditionally a Reynolds Averaged Navier-Stokes (RANS) approach to turbulence modelling has been used but this approach has inherent limitations. Time- or Favre-weighted averaging techniques, commonly used in this approach, cause information related to the fluctuating component of the flow field to be lost, losing the ability to investigate phenomenon occurring on a cycle-by-cycle basis. Recent advances in computer power have seen increased usage of more advanced turbulence modelling approaches, including Large Eddy Simulation (LES) [5] where the large scale eddies are solved directly and only the smaller eddies modelled using a sub-grid scale (SGS) model. This approach allows the investigation into highly transient flow phenomenon occurring on cycle-by-cycle basis. Intake valve jet flapping describes the sinusoidal flow motion generated between the two intake valves during the intake stroke which has been observed both experimentally and numerically in both detailed and simplified engine geometries [13–15]. Valve jet flapping has also been suggested as a potential source of cycle-to-cycle variability due to the instability of the flow structure, leading to significant differences in the resultant large scale tumbling motion[14,16]. In order to identify and investigate intake valve jet flapping, a 3D-CFD model and LES turbulence modelling approach have been applied to a detailed engine geometry realistic of a typical gasoline direct injection (GDI) engine. The paper first provides an outline of the experimental test case and details of the numerical model. Next, the results and discussion section presents an example of intake valve jet flapping and then discusses the findings in relation to causes, cycle-by-cycle variations, and limitations for predicting this phenomenon when using time-averaging techniques. The final section provides general conclusions drawn from this study. 2-Experimental Test Case The experimental test case was a single cylinder four stroke optical research engine based on the combustion chamber of a V8 engine with pent-roof cylinder head, centrally mounted injector and four valves per cylinder, representative of a typical commercial GDI engine design. The engine  3  featured a ‘Bowditch’ piston arrangement and fused silica piston crown, cylinder liner and pent-roof access window to allow significant optical access to the combustion chamber. The experimental engine is shown in Figure 1 and the configuration is summarised in Table 1. The engine geometry and experimental setup used to obtain the High Speed Digital Particle Image Velocimetry (HSDPIV) data used for model validation are described in detail in [6–8]. Table 1 – Experimental engine configuration [6] Bore  89 (mm) Stroke 90.3 (mm) Capacity 0.562 (l) Compression ratio 10.5 nominal Piston bowl shape Flat Combustion chamber shape Pent-roof Valves 2 Intake, 2 Exhaust Intake Valve Opening 24 °ATDC Intake Valve Closing 149 °ATDC Exhaust Valve Opening 274 °ATDC Exhaust Valve Closing 6 °ATDC   4   Figure 1 – Single cylinder optical research engine used for model validation  3-Numerical Model The numerical model was developed using CFD code STAR-CD (ver 4.20) and is a detailed representation of the experimental setup, as shown in Figure 1.  Figure 2 – Computational domain The computational domain was extended upstream and downstream to allow sufficient time for turbulence to develop prior to the cylinder and to prevent recirculating flow around the flow       z y x  5  outlet, respectively. The final mesh contained approximately 2.2million cells at Bottom Dead Centre (BDC) and had a typical cell size within the cylinder of approximately 0.8mm3. A LES approach was used for modelling turbulence whereby the large scale flow motions are solved directly via the Navier-Stokes (N-S) equations and only the small scale motions, defined by the cell size or filter width, are modelled at a SGS level. In a turbulent flow, the flow field is typically decomposed via the Reynolds Decomposition into a mean component 𝑢𝑢𝚤𝚤�  and a fluctuating component 𝑢𝑢𝑖𝑖′ (or in an LES context, the filtered and SGS components respectively), here shown for velocity as defined by equation (1).  𝑢𝑢𝑖𝑖 = 𝑢𝑢𝚤𝚤� + 𝑢𝑢𝑖𝑖′  (1) When this decomposition is introduced into the N-S equations, the following equation (2) is formed: 𝜕𝜕𝜌𝜌�𝑢𝑢�𝑖𝑖𝜕𝜕𝑡𝑡+ 𝜕𝜕𝜌𝜌�𝑢𝑢�𝑖𝑖𝑢𝑢�𝑗𝑗𝜕𝜕𝑥𝑥𝑗𝑗= − 𝜕𝜕𝜌𝜌�𝜕𝜕𝑥𝑥𝑖𝑖+ 𝜕𝜕Γ𝑖𝑖𝑗𝑗𝜕𝜕𝑥𝑥𝑗𝑗−𝜕𝜕𝜌𝜌�𝜏𝜏𝑖𝑖𝑗𝑗𝜕𝜕𝑥𝑥𝑗𝑗  (2) Where, in an LES context, 𝜏𝜏𝑖𝑖𝑖𝑖 represents the SGS stresses and drives the need for additional modelling to close the N-S equations. This study uses a turbulence viscosity closure approach as proposed by Smagorinsky [9], based on a local equilibrium assumption such that production and dissipation of SGS turbulence kinetic energy are assumed to be equal. The SGS turbulence viscosity (𝜐𝜐𝑇𝑇) is modelled as shown in equation (3) and closes the N-S equations. 𝜐𝜐𝑇𝑇 = (𝐶𝐶𝑆𝑆Δ)2|𝑆𝑆̅|  (3) Where CS is the Smagorinsky constant and set to 0.02 in this study [10], Δ is the filter width defined by equation (4), and 𝑆𝑆̅ is the Favre filtered strain rate tensor. ∆ =  √𝑉𝑉3   (4) Where V is the cell volume of the computational grid. The inflow at the intake plenum and outflow at the exhaust port outlet were specified as constant-pressure and constant-temperature environments. RANS predictions confirmed that the domain was extended sufficiently far upstream and downstream such that a steady pressure boundary was  6  adequate to correctly predict the intake and exhaust system wave dynamics [11]. A turbulence intensity of 10% and turbulence length scale of 10% of the hydraulic diameter were imposed at both the inflow and outflow. The numerical boundary conditions are summarised in Table 2. The simulation was initialised by first running a RANS cycle, then an LES initialisation cycle, and then the simulation was continued for a further 29 engine cycles. The time-step was set at 5.6x10-6s (equating to approximately 0.05ca/time-step) except around valve opening and closing periods where it was set to 1.1x10-6s (approximately 0.01ca/time-step). This provided adequate solution stability, an average Courant–Friedrichs–Lewy (CFL) number of less than one and a solver time of approximately 3 days per complete engine cycle. Table 2 – Numerical boundary conditions Engine Speed  1500 (rpm) Inflow Pressure 0.453 (bar) Inflow Temperature  301 (K) Inflow Turbulence  Intensity: 0.1 (none) Length scale: 0.0048 (m) Outflow Pressure  1.023 (bar) Outflow Temperature 784 (K) Outflow Turbulence Intensity: 0.1 (none) Length scale: 0.001 (m) Wall Temperatures Adiabatic  The mesh was generally found to provide upward of 80% turbulence resolution which is considered adequate for a LES simulation. The model was also validated against experimental PIV data at three separate crank angles within the intake stroke and at three different tumble cutting planes and showed reasonable agreement against mean and fluctuating velocity components [12].  4-Results and Discussion  7  In this study, individual cycles were investigated for evidence of intake valve jet flapping. Velocity magnitude contours at 5°CA intervals were used in the y-z cutting plane, intersecting through both intake valves. During early observations it became apparent that prior to an intake valve jet flapping event, a stronger velocity field was present in one of the intake valve curtains as a consequence of turbulent fluctuations. The difference in valve curtain flux between the two intake valves was compared to consecutive images of velocity magnitude contours and a relationship found between the temporal variation in valve curtain flux and valve jet flapping. Results from cycle 10 are shown in Figure 2 and Figure 3 to show these findings and discussed below in more detail. Early in the intake stroke, between 30-70°ATDC, variations in mass flux past the intake valve curtains are small and this is reflected in a fairly constant jet propagating down the centre of the combustion chamber (Figure 3(a)). At around 75°ATDC a significant variation valve curtain mass flux occurs between the two intake valves, with a visible weakening of the flow through the left valve curtain (Figure 3(b)). This imbalance in valve curtain flux causes a momentary strengthening of the valve jet from the right hand valve and a resultant instability in the combined vertical jet, causing it to propagate more diagonally under the left intake valve. 5°CA later at 80°ATDC, the difference in valve curtain flux has returned to similar values but this oscillation in the relative strength of each valve jet causes the resulting jet to begin to ‘flap’ in a sinusoidal motion (Figure 3(c)). A further 5°CA later at 85°ATDC, since the valve curtain flux had stabilised 5°CA earlier, any flapping has been dissipated but a weakening of the flow past the left valve prompts the initiation of further valve jet flapping, which is then visible at 90°ATDC (Figure 3(d) & Figure 3(e)). This process continues until approximately 140°ATDC where any difference in valve curtain flux between the two intake valves is minimal as a consequence of much lower valve jet velocities at large valve lifts.  8   Figure 3 – Difference in valve curtain flux between the intake valves for cycle 10 with red markers used to highlight crank angles for images in Fig.4     9   Figure 4 – Velocity magnitude contours with black circles highlighting valve curtain flow imbalance and black arrows highlighting valve jet flapping   (a) 70°ATDC (b) 75°ATDC   (c) 80°ATDC (d) 85°ATDC  (e) 90°ATDC  10  It has also been observed that all engine cycles show cycle-to-cycle variations in valve curtain flux through the intake stroke. As seen in Figure 4 where all engine cycles are overlaid, all cycles exhibit variation in the intake valve curtain flux with the magnitude and phasing of the variation changing on a cycle-by-cycle basis.  Figure 5 – Highlighting the variation in phase and magnitude of difference in intake valve curtain flux across all cycles As an example of the cyclic variations present, Figure 5 shows the difference in intake valve curtain flux and velocity magnitude contours at 100°ATDC for cycle 23. Here the flapping intake valve jet can be seen to have lower penetration into combustion chamber but oscillate at a higher frequency when compared to cycle 10. Figure 6 shows results at 75°ATDC for cycle 12 where the flapping valve jet oscillates at a lower frequency but penetrates all the way to the piston crown surface.  11    (a) (b) 100°ATDC Figure 6 – Cycle 23 (a) Difference in intake valve curtain flux, (b) Velocity magnitude contours at 100°ATDC   (a) (b) 75°ATDC Figure 7 – Cycle 12 (a) Difference in intake valve curtain flux, (b) Velocity magnitude contours at 75°ATDC Due to variation in the magnitude and phase of the intake valve jet flapping that occurs on a cycle-by-cycle basis, when an ensemble-averaging process is applied to the velocity field, most of the information associated with jet flapping is lost and the results largely show a steady valve jet penetrating directly down into the combustion chamber, as shown by Figure 7 (a). Interestingly, contrary to the findings of [14], when compared to a RANS solution of the same geometry as shown in Figure 7 (b), jet flapping is visible but due to the time-averaging of the N-S equations, does not capture any of the cyclic-variability present in the LES predictions.  12    (a) LES Ensemble-Average (b) RANS Figure 8 – Comparison of velocity magnitude contours at 100°ATDC for (a) LES 29 cycle ensemble-average, and (b) RANS predictions  5-Conclusions Intake valve jet flapping within a GDI engine has been investigated using a detailed 3D-CFD model and LES turbulence modelling approach in code STAR-CD. Details of the experimental test case and computational setup have been provided and reference made to the validation of the numerical model to experimental results. Intake valve jet flapping was seen to be the sinusoidal flow motion generated between the two intake valves during the intake stroke, as a consequence of turbulent fluctuations within the valve curtains. An example of prominent intake valve jet flapping was presented and discussed, indicating the presence of valve curtain flux imbalance that stimulates the subsequent jet flapping event. Significant cyclic variability has been observed in both the magnitude and phasing of valve curtain imbalance resulting in variations in frequency and penetration of the resultant flapping flow structure. It has also been observed that the valve jet flapping phenomenon is mostly lost during the ensemble-averaging procedure typically used in LES studies. In a comparative RANS simulation, whilst valve jet flapping was observed, it does not capture the cyclic variability present in the LES predictions.  13  Due to its significant cyclic variability and impact on large scale flow structures within cylinder, valve jet flapping influences the in-cylinder mixing processes and the final turbulence levels at the point of spark ignition in GDI engines. Fifteen additional engine cycles have recently been completed including an early injection event using a Lagrangian discrete droplet model to allow investigation into the impact of variations in intake valve jet flapping on the atomisation process and distribution of the fuel vapour cloud on a cycle-by-cycle basis.  Acknowledgements This work was supported by Jaguar Land Rover and the UK-EPSRC grant EP/K014102/1 as part of the jointly funded Programme for Simulation Innovation. References:   1. Lavoie, G.A., Heywood, J.B., and Keck, J.C., “Experimental and Theoretical Study of Nitric Oxide Formation in Internal Combustion Engines,” Combust. Sci. Technol. 1:313–326, 1970. 2. Gosman, A.D., Tsui, Y.Y., and Watkins, A.P., “Calculation of Three Dimensional Air Motion in Model Engines,” SAE Technical Paper 840229, 1984. 3. Poinsot, T., “Using Direct Numerical Simulations to Understand Premixed Turbulent Combustion,” Twenty-Sixth Symposium (International) on Combustion/The Combustion Institute, 219–232, 1996. 4. Genzale, C.L., Reitz, R.D., and Musculus, M.P.B., “Optical Diagnostics and Multi-Dimensional Modeling of Spray Targeting Effects in Late-Injection Low-Temperature Diesel Combustion,” SAE Int. J. Engines 2(2):150–172, 2009. 5. Rutland, C.J., “Large-eddy simulations for internal combustion engines - a review,” Int. J. Engine Res. 12(5):421–451, 2011. 6. Jarvis, S., Justham, T., Clarke, A., Garner, C.P., Hargrave, G.K., and Richardson, D., “Motored SI IC Engine In-Cylinder Flow Field Measurement Using Time Resolved Digital PIV for Characterisation of Cyclic Variation,” SAE Technical Paper 2006-01-1044, 2006. 7. 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A numerical study of intake valve jet flapping in a GDI engine

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A numerical study of intake valve jet flapping in a GDI engine

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