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Advanced Turbulence Modeling for engine applications

Advanced Turbulence Modeling for engine applications. Chan Hee Son University of Wisconsin, Engine Research Center Advisor: Professor Christopher J. Rutland Sponsor: General Motors. Motivation. Linear k- e model widely used, but compromise between expense and accuracy

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Advanced Turbulence Modeling for engine applications

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  1. Advanced Turbulence Modeling for engine applications Chan Hee Son University of Wisconsin, Engine Research Center Advisor: Professor Christopher J. Rutland Sponsor: General Motors

  2. Motivation • Linear k-e model • widely used, but compromise between expense and accuracy • Inherently unable to account for secondary flows • Poor predictions for separated or curved streamline flows • Non-linear models • Able to predict secondary flow of the second kind • Numerical instability leads to excessive computational expense • Wallin-Johansson's explicit Algebraic Reynolds Stress Model as a representative case • v2-f model • Two turbulence scales are used • More accurate representation of the physics (eddy viscosity) close to the wall • Very good performance in flow separation regions

  3. Model formulation • Turbulence governing equations of v2 - f

  4. Sandia National Lab Optical engine • Specifications • Bore – 79.5mm, Stroke – 85.0 mm • CR = 18.7 • 1500 RPM • RS = 1.5 ~ 3.5 • Cold flow (no spray or combustion) • Measurement locations • 3 clusters of 5 points located in a vertical plane bisecting the exhaust valves • The 3 center points are at r= 13.6 mm with all neighboring measurement points being 1mm away.

  5. Radial and tangential velocities @ 5 ATDC with swirl ratio 3.5 v2-f W-J

  6. TKE history for case with swirl ratio = 3.5

  7. Conclusion • For the Sandia National lab optical engine simulation, W-J eARSM does not show any improvement for the mean flow. Even the k-e model is better. • Potential reason: the W-J ARSM is originally derived for 2D flow. 3D version is quartic order. Thus, too complex for practical use. • Increased levels of turbulence is predicted by the WJ model. • At swirl ratio 2.5 and 3.5, TKE prediction over time is very similar to k-e model in trend, but about 50% higher in turbulence level. • This is not due to the ability of this model to capture turbulence anisotropy, as the trend is almost exactly the same as k-e. At high swirl anisotropy increases. • The v2-f model consistently shows improved results. Still it fails to catch the trends of the experimental turbulent kinetic energy results.

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