A flame front is quenched when approaching a cold wall due to excessive heat loss. Accurate computation of combustion rate in such situations requires accounting for near wall flame quenching. Combustion models, developed without considering wall effects, cannot be used for wall bounded combustion modelling, as it leads to wall flame acceleration problem. In this work, a new model was developed to estimate the near wall combustion rate, accommodating quenching effects. The developed correlation was then applied to predict the combustion in two spark ignition engines in combination with the famous Bray–Moss–Libby (BML) combustion model. BML model normally fails when applied to wall bounded combustion due to flame wall acceleration. Results show that the proposed quenching correlation has significantly improved the performance of BML model in wall bounded combustion. As a second step, in order to further enhance the performance, the BML model was modified with the use of Kolmogorov–Petrovski–Piskunov analysis and fractal theory. In which, a new dynamic formulation is proposed to evaluate the mean flame wrinkling scale, there by accounting for spatial inhomogeneity of turbulence. Results indicate that the combination of the quenching correlation and the modified BML model has been successful in eliminating wall flame acceleration problem, while accurately predicting in-cylinder pressure rise, mass burn rates and heat release rates.
Funding
National Research Council of Sri Lanka under the grant number 15-097
History
School
Mechanical, Electrical and Manufacturing Engineering
This paper was accepted for publication in the journal International Journal of Engine Research and the definitive published version is available at https://doi.org/10.1177/1468087420972903. Users who receive access to an article through a repository are reminded that the article is protected by copyright and reuse is restricted to non-commercial and no derivative uses. Users may also download and save a local copy of an article accessed in an institutional repository for the user's personal reference.