MATEC Web Conf.
Volume 90, 2017The 2nd International Conference on Automotive Innovation and Green Vehicle (AiGEV 2016)
|Number of page(s)||11|
|Published online||20 December 2016|
Numerical investigation on soot particles emission in compression ignition diesel engine by using particulate mimic soot model
1 Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
2 Mechanical and Aerospace Technology Division, Science and Technology Research Institute for Defence (STRIDE), 43000 Kajang, Selangor, Malaysia
* Corresponding author: email@example.com
Research via computational method, specifically by detailed-kinetic soot model offers much more advantages than the simple model as more detailed formation/oxidation process is taken into consideration, thus providing better soot mass concentration, soot size, soot number density as well as information regarding other related species. In the present computational study, investigation of in-cylinder soot concentration as well as other emissions in a single cylinder diesel engine has been conducted, using a commercial multidimensional CFD software, CONVERGE CFD. The simulation was carried out for a close-cycle combustion environment from inlet valve closing (IVC) to exhaust valve opening (EVO). In this case, detailed-kinetic Particulate Mimic (PM) soot model was implemented as to take benefit of the method of moment, instead of commonly implemented simple soot model. Analyses of the results are successfully plotted to demonstrate that the soot size and soot mass concentration are strongly dependent on the detailed soot formation and oxidation process rates. The calculated of soot mass concentration and average soot size at EVO provide the end value of 29.2 mg/m3 and 2.04 × 10−8 m, respectively. Besides, post-processing using EnSight shows the qualitative results of soot concentration along simulation period in the combustion chamber.
© The Authors, published by EDP Sciences, 2017
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