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Scale Similarity Analysis of Internal Combustion Engine Flows—Particle Image Velocimetry and Large-Eddy Simulations
Technical Paper
2018-01-0172
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This presentation is an assessment of the turbulence-stress scale-similarity in an IC engine, which is used for modeling subgrid dissipation in LES. Residual stresses and Leonard stresses were computed after applying progressively smaller spatial filters to measured and simulated velocity distributions. The velocity was measured in the TCC-II engine using planar and stereo PIV taken in three different planes and with three different spatial resolutions, thus yielding two and three velocity components, respectively. Comparisons are made between the stresses computed from the measured velocity and stress computed from the LES resolved-scale velocity from an LES simulation. The results present the degree of similarity between the residual stresses and the Leonard stresses at adjacent scales. The specified filters are systematically reduced in size to the resolution limits of the measurements and simulation. The analysis is limited to data planes cutting through the intake jet at mid intake stroke, at 800 rpm, 95 kPa motored operation.
The most important result is the demonstration of a method to assess the residual-to-Leonard-stress similarity with wavenumber (spatial scale), and to quantify their relationship. Taken at face value, the results demonstrate the viability of a linear relationship for the prediction of the residual stress from the modified Leonard stress, at the scales resolved by the measurements and simulations here. However, acceptance of these results need be tempered by the need for a comprehensive error analysis of the measurements and simulations, which was not considered here.
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Chang, Y., Wu, A., Reuss, D., and Sick, V., "Scale Similarity Analysis of Internal Combustion Engine Flows—Particle Image Velocimetry and Large-Eddy Simulations," SAE Technical Paper 2018-01-0172, 2018, https://doi.org/10.4271/2018-01-0172.Data Sets - Support Documents
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