A new predictive multi-zone model for HCCI engine combustion
Abstract
Here, this work introduces a new predictive multi-zone model for the description of combustion in Homogeneous Charge Compression Ignition (HCCI) engines. The model exploits the existing OpenSMOKE++ computational suite to handle detailed kinetic mechanisms, providing reliable predictions of the in-cylinder auto-ignition processes. All the elements with a significant impact on the combustion performances and emissions, like turbulence, heat and mass exchanges, crevices, residual burned gases, thermal and feed stratification are taken into account. Compared to other computational approaches, this model improves the description of mixture stratification phenomena by coupling a wall heat transfer model derived from CFD application with a proper turbulence model. Furthermore, the calibration of this multi-zone model requires only three parameters, which can be derived from a non-reactive CFD simulation: these adaptive variables depend only on the engine geometry and remain fixed across a wide range of operating conditions, allowing the prediction of auto-ignition, pressure traces and pollutants. This computational framework enables the use of detail kinetic mechanisms, as well as Rate of Production Analysis (RoPA) and Sensitivity Analysis (SA) to investigate the complex chemistry involved in the auto-ignition and the pollutants formation processes. In the final sections of the paper, these capabilities are demonstrated through themore »
- Authors:
-
- Politecnico di Milano, Milan (Italy)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1378539
- Report Number(s):
- LLNL-JRNL-696698
Journal ID: ISSN 0306-2619
- Grant/Contract Number:
- AC52-07NA27344
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 178; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 30 DIRECT ENERGY CONVERSION; 37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; 33 ADVANCED PROPULSION SYSTEMS; HCCI engine; Multi-zone model; Kinetic analyses
Citation Formats
Bissoli, Mattia, Frassoldati, Alessio, Cuoci, Alberto, Ranzi, Eliseo, Mehl, M., and Faravelli, Tiziano. A new predictive multi-zone model for HCCI engine combustion. United States: N. p., 2016.
Web. doi:10.1016/j.apenergy.2016.06.062.
Bissoli, Mattia, Frassoldati, Alessio, Cuoci, Alberto, Ranzi, Eliseo, Mehl, M., & Faravelli, Tiziano. A new predictive multi-zone model for HCCI engine combustion. United States. https://doi.org/10.1016/j.apenergy.2016.06.062
Bissoli, Mattia, Frassoldati, Alessio, Cuoci, Alberto, Ranzi, Eliseo, Mehl, M., and Faravelli, Tiziano. Thu .
"A new predictive multi-zone model for HCCI engine combustion". United States. https://doi.org/10.1016/j.apenergy.2016.06.062. https://www.osti.gov/servlets/purl/1378539.
@article{osti_1378539,
title = {A new predictive multi-zone model for HCCI engine combustion},
author = {Bissoli, Mattia and Frassoldati, Alessio and Cuoci, Alberto and Ranzi, Eliseo and Mehl, M. and Faravelli, Tiziano},
abstractNote = {Here, this work introduces a new predictive multi-zone model for the description of combustion in Homogeneous Charge Compression Ignition (HCCI) engines. The model exploits the existing OpenSMOKE++ computational suite to handle detailed kinetic mechanisms, providing reliable predictions of the in-cylinder auto-ignition processes. All the elements with a significant impact on the combustion performances and emissions, like turbulence, heat and mass exchanges, crevices, residual burned gases, thermal and feed stratification are taken into account. Compared to other computational approaches, this model improves the description of mixture stratification phenomena by coupling a wall heat transfer model derived from CFD application with a proper turbulence model. Furthermore, the calibration of this multi-zone model requires only three parameters, which can be derived from a non-reactive CFD simulation: these adaptive variables depend only on the engine geometry and remain fixed across a wide range of operating conditions, allowing the prediction of auto-ignition, pressure traces and pollutants. This computational framework enables the use of detail kinetic mechanisms, as well as Rate of Production Analysis (RoPA) and Sensitivity Analysis (SA) to investigate the complex chemistry involved in the auto-ignition and the pollutants formation processes. In the final sections of the paper, these capabilities are demonstrated through the comparison with experimental data.},
doi = {10.1016/j.apenergy.2016.06.062},
journal = {Applied Energy},
number = C,
volume = 178,
place = {United States},
year = {2016},
month = {6}
}
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