A Computer Generated Reduced Iso-Octane Chemical Kinetic Mechanism Applied to Simulation of HCCI Combustion 2002-01-2870
This paper shows how a computer can systematically remove non-essential chemical reactions from a large chemical kinetic mechanism. The computer removes the reactions based upon a single solution using a detailed mechanism. The resulting reduced chemical mechanism produces similar numerical predictions significantly faster than predictions that use the detailed mechanism.
Specifically, a reduced chemical kinetics mechanism for iso-octane has been derived from a detailed mechanism by eliminating unimportant reaction steps and species. The reduced mechanism has been developed for the specific purpose of fast and accurate prediction of ignition timing in an HCCI engine. The reduced mechanism contains 199 species and 383 reactions, while the detailed mechanism contains 859 species and 3606 reactions. Both mechanisms have been used in numerical simulation of HCCI combustion. The simulations show that the reduced mechanism predicts pressure traces and heat release with good accuracy, similar to the accuracy obtained with the detailed mechanism.
As may be expected, emissions of hydrocarbon and carbon monoxide are not as well predicted with the reduced mechanism as with the detailed mechanism, since the reduced mechanism was targeted for predicting HCCI ignition and not HC and CO emissions. Considering that the reduced mechanism requires about 25 times less computational time than the detailed mechanism (2 hours vs. 2 days), the ability to automatically generate a problem specific reduced mechanism is an important new tool for combustion research in general.
Citation: Aceves, S., Martinez-Frias, J., Flowers, D., Smith, J. et al., "A Computer Generated Reduced Iso-Octane Chemical Kinetic Mechanism Applied to Simulation of HCCI Combustion," SAE Technical Paper 2002-01-2870, 2002, https://doi.org/10.4271/2002-01-2870. Download Citation
Salvador M. Aceves, Joel Martinez-Frias, Daniel Flowers, J. Ray Smith, Robert Dibble, J. Y. Chen
Lawrence Livermore National Laboratory, University of California Berkeley
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