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Multi-dimensional Conditional Moment Closure Modelling Applied to a Heavy-duty Common-rail Diesel Engine

Journal Article
2009-01-0717
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 20, 2009 by SAE International in United States
Multi-dimensional Conditional Moment Closure Modelling Applied to a Heavy-duty Common-rail Diesel Engine
Sector:
Citation: Wright, Y., Boulouchos, K., De Paola, G., and Mastorakos, E., "Multi-dimensional Conditional Moment Closure Modelling Applied to a Heavy-duty Common-rail Diesel Engine," SAE Int. J. Engines 2(1):714-726, 2009, https://doi.org/10.4271/2009-01-0717.
Language: English

Abstract:

A multi-dimensional combustion code implementing the Conditional Moment Closure turbulent combustion model interfaced with a well-established RANS two-phase flow field solver has been employed to study a broad range of operating conditions for a heavy duty direct-injection common-rail Diesel engine. These conditions include different loads (25%, 50%, 75% and full load) and engine speeds (1250 and 1830 RPM) and, with respect to the fuel path, different injection timings and rail pressures. A total of nine cases have been simulated.
Excellent agreement with experimental data has been found for the pressure traces and the heat release rates, without adjusting any model constants.
The chemical mechanism used contains a detailed NOx sub-mechanism. The predicted emissions agree reasonably well with the experimental data considering the range of operating points and given no adjustments of any rate constants have been employed. In an effort to identify CPU cost reduction potential, various dimensionality reduction strategies have been assessed. Furthermore, the sensitivity of the predictions with respect to resolution in particular relating to the CMC grid has been investigated.
Overall, the results suggest that the presented modelling strategy has considerable predictive capability concerning Diesel engine combustion without requiring model constant calibration based on experimental data. This is true particularly for the heat release rates predictions and, to a lesser extent, for NOx emissions where further progress is still necessary.