An Automatic Mechanism Reduction Process in Order to Model the Combustion in an HCCI Engine Fueled with Natural Gas and N-heptane

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Abstract

HCCI combustion engines due to their low fuel consumption and pollution have been studied by many researchers in recent years. Along with several experimental researches performed on these engines, mathematical modeling has also been utilized as a tool for prediction of their combustion, performance and pollution behaviours. Although use of detailed chemical kinetic mechanisms in the combustion models will result in a proper prediction of the above-mentioned behaviours, a significant increase in the computational time particularly for the more accurate combustion models will also occur. In order to overcome this challenge, mechanism reduction process in HCCI combustion engine conditions has been considered in the current study. In this direction, an optimized single-zone combustion model has been used as a necessary tool for simulation of combustion. Based on the studies performed in the current work, the Directed Relation Graph with Error Propagation (DRGEP) method, thanks to its low computational time while having high accuracy, has been selected as a proper method for the mechanism reduction process. Additionaly, instead of the traditional single-stage reduction approach, a novel approach based on gradual reduction with error propagation has been used. Therefore, the mechanism reduction process has been executed fully automatically in a wide interval of operating conditions of HCCI engine on GRI-Mech3.0 mechanism for simulation of combustion of natural gas, and on the Golovichevandrsquo;s mechanism for simulation of combustion of n-heptane. At the end of this process, the sizes of these two mechanisms were reduced from 53 species and 325 reactions, and 57 species and 290 reactions to 24 species and 95 reactions, and 42 species and 146 reactions, respectively. The errors caused by reduction, however, were remained less than 1 percent at all conditions

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  • Receive Date: 24 November 2013
  • Revise Date: 15 May 2024
  • Accept Date: 21 May 2017

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