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Title: Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation

Abstract

3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user who may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations. This study used ANSYS® Forte, Version 17.2, and the built-in G-equation model, to investigate two tuning constants that influence flame propagation in 3D CFD SI engine simulations: the stretch factor coefficient, Cms and the flame development coefficient, Cm2. After identifying several Cm2-Cms pairs that matched experimental data at one operating conditions, simulation results showed that engine models that used different Cm2-Cms sets predicted similar combustion performance, when the spark timing, engine load, and engine speed weremore » changed from the operating condition used to validate the CFD simulation. A dramatic shift was observed when engine speed was doubled, which suggested that the flame stretch coefficient, Cms, had a much larger influence at higher engine speeds compared to the flame development coefficient, Cm2. Therefore, the Cm2-Cms sets that predicted a higher turbulent flame under higher in-cylinder pressure and temperature increased the peak pressure and efficiency. This suggest that the choice of the Cm2-Cms will affect the G-equation-based simulation accuracy when engine speed increases from the one used to validate the model. As a result, for the less-experienced CFD user and in the absence of enough experimental data that would help retune the tuning parameters at various operating conditions, the purpose of a good G-equation-based 3D engine simulation is to guide and/or complement experimental investigations, not the other way around. Only a truly-predictive simulation that fully couples the turbulence/chemistry equations can help reduce the amount of experimental work.« less

Authors:
 [1];  [2];  [1]
  1. West Virginia Univ., Morgantown, WV (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1435273
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Society of Automotive Engineers Technical Paper Series
Additional Journal Information:
Journal Volume: 1; Journal ID: ISSN 0148-7191
Publisher:
SAE International
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING

Citation Formats

Liu, Jinlong, Szybist, James, and Dumitrescu, Cosmin. Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation. United States: N. p., 2018. Web. doi:10.4271/2018-01-0183.
Liu, Jinlong, Szybist, James, & Dumitrescu, Cosmin. Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation. United States. https://doi.org/10.4271/2018-01-0183
Liu, Jinlong, Szybist, James, and Dumitrescu, Cosmin. Tue . "Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation". United States. https://doi.org/10.4271/2018-01-0183. https://www.osti.gov/servlets/purl/1435273.
@article{osti_1435273,
title = {Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation},
author = {Liu, Jinlong and Szybist, James and Dumitrescu, Cosmin},
abstractNote = {3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user who may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations. This study used ANSYS® Forte, Version 17.2, and the built-in G-equation model, to investigate two tuning constants that influence flame propagation in 3D CFD SI engine simulations: the stretch factor coefficient, Cms and the flame development coefficient, Cm2. After identifying several Cm2-Cms pairs that matched experimental data at one operating conditions, simulation results showed that engine models that used different Cm2-Cms sets predicted similar combustion performance, when the spark timing, engine load, and engine speed were changed from the operating condition used to validate the CFD simulation. A dramatic shift was observed when engine speed was doubled, which suggested that the flame stretch coefficient, Cms, had a much larger influence at higher engine speeds compared to the flame development coefficient, Cm2. Therefore, the Cm2-Cms sets that predicted a higher turbulent flame under higher in-cylinder pressure and temperature increased the peak pressure and efficiency. This suggest that the choice of the Cm2-Cms will affect the G-equation-based simulation accuracy when engine speed increases from the one used to validate the model. As a result, for the less-experienced CFD user and in the absence of enough experimental data that would help retune the tuning parameters at various operating conditions, the purpose of a good G-equation-based 3D engine simulation is to guide and/or complement experimental investigations, not the other way around. Only a truly-predictive simulation that fully couples the turbulence/chemistry equations can help reduce the amount of experimental work.},
doi = {10.4271/2018-01-0183},
journal = {Society of Automotive Engineers Technical Paper Series},
number = ,
volume = 1,
place = {United States},
year = {Tue Apr 03 00:00:00 EDT 2018},
month = {Tue Apr 03 00:00:00 EDT 2018}
}