A Multipurpose Reduced Mechanism for Ethanol Combustion

TL;DR

This paper develops simplified skeletal and reduced chemical mechanisms for ethanol combustion, significantly decreasing computational cost while maintaining accuracy in predicting combustion behavior, thus aiding computational studies of ethanol flames.

Contribution

The paper introduces new skeletal and reduced ethanol combustion mechanisms with fewer reactions and species, enabling faster computations without sacrificing accuracy.

Findings

Reduced mechanisms decrease computational cost by up to 80%.

Comparison with experimental data shows good agreement in ignition and flame properties.

Simplified mechanisms are useful for computational studies of ethanol combustion.

Abstract

New multipurpose skeletal and reduced chemical-kinetic mechanisms for ethanol combustion are developed, along the same philosophical lines followed in our previous work on methanol. The resulting skeletal mechanism contains 66 reactions, only 19 of which are reversible, among 31 species, and the associated reduced mechanism contains 14 overall reactions among 16 species, obtained from the skeletal mechanism by placing \ce{CH3CHOH}, \ce{CH2CH2OH}, \ce{CH3CO}, \ce{CH2CHO}, \ce{CH2CO}, \ce{C2H3}, \ce{C2H5}, \ce{C2H6}, \ce{S-CH2}, \ce{T-CH2}, \ce{CH4}, \ce{CH2OH}, \ce{CH3O}, \ce{HCO}, and \ce{O} in steady state. For the reduced mechanism, the steady-state relations and rate expressions are arranged so that computations can be made sequentially without iteration. Comparison with experimental results for autoignition, laminar burning velocities, and counterflow flame structure and extinction, including comparisons with the 257-step, 54-species detailed San Diego Mechanism and five other mechanisms in the literature, support the utility of the skeletal and reduced mechanisms, showing, for example, that, in comparison with the San Diego mechanism, they decrease the computational cost by 70\% and 80\%, respectively. Measures of computation times and of extents of departures from experimental values are defined and employed in evaluating results. Besides contributing to improvements in understanding of the mechanisms, the derived simplifications may prove useful in a variety of computational studies.