Title of article :
OPTIMIZATION OF GRI-MECH 3.0 MECHANISM USING HCCI COMBUSTION MODELS AND GENETIC ALGORITHM
Author/Authors :
Yousefzadi Nobakht, A. sahand university of technology - Department of Mechanical Engineering, تبريز, ايران , Khoshbakhi Saray, R. sahand university of technology - Department of Mechanical Engineering, تبريز, ايران , Soleimani Astiar, G. sahand university of technology - Department of Mechanical Engineering, تبريز, ايران
From page :
155
To page :
168
Abstract :
This paper presents a modeling study of a CNG Homogenous Charge Compression Ignition (HCCI) engine using a single-zone and a multi-zone combustion model. Authors developed code is able to predict engine combustion and performance parameters in closed part of the engine cycle. As detailed chemical kinetics is necessary to investigate combustion process in HCCI engines, therefore, GRI-mech3.0 mechanism was used which includes 53 chemical species and 325 reactions for natural gas combustion. Although, single-zone model is useful to parametric study on variation of some engine combustion parameters such as start of combustion (SOC); But, it could neither be able to accurately predict other engine combustion related parameters nor engine performance and emission parameters. Hence, a multi- zone combustion model was developed to predict those parameters accurately. GRI-mech 3.0 combustion mechanism was developed for natural gas combustion without considering Exhaust Gas Recirculation (EGR). To consider the effect of EGR on HCCI combustion, the mechanism s rate coefficients should be optimized. These coefficients were optimized using a developed genetic algorithm code. Predicted values show good agreement with corresponding experimental values for whole ranges of engine operating conditions.
Keywords :
HCCI Combustion , Chemical Kinetics , Single , Zone Model , Multi , Zone Model , Genetic Algorithm
Journal title :
International Journal of Engineering
Journal title :
International Journal of Engineering
Record number :
2563686
Link To Document :
بازگشت