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A comparison of literature models for the oxidation of normal heptane

Published

Author(s)

David A. Sheen, Wing Tsang

Abstract

The development of detailed chemical kinetic models has proceeded unabated since the pioneering work of Dixon-Lewis and coworkers forty-five years ago. In that time, computational power has increased ten million-fold, and yet, we do not have a consensus on a complete description for the pyrolysis and oxidation of fuels as simple as hydrogen. This paper presents a comparison of three detailed models and one lumped, semi-empirical model, all from literature, for the oxidation of normal heptane, a fuel of practical interest because of its use in gasoline surrogates. We find that most of the models give predictions that agree with each other within the propagated uncertainty from the rate constant estimates, and also show “satisfactory agreement” with experimental measurements. Differences among the models can be attributed to peculiarities in how the models treat the initial decomposition of the fuel. The rate constants for these reactions do not agree within the uncertainty assigned for them, however, which means that the models are fundamentally, quantitatively different. Because their predictions agree with each other and with experiment, it can be concluded that the models have gotten the right answer for wrong reasons, through luck. Given the predictive capability of the semi-empirical model, we suggest that future combustion research should concentrate on developing a model that treats only the key, rate-limiting processes in a rigorous manner, rather than continuing the current trend of attempting to describe all possible elementary reactions exactly, but poorly.
Citation
Combustion and Flame
Volume
161

Keywords

Reaction mechanisms , Uncertainty Analysis , n-Heptane

Citation

Sheen, D. and Tsang, W. (2014), A comparison of literature models for the oxidation of normal heptane, Combustion and Flame, [online], https://doi.org/10.1016/j.combustflame.2014.01.014 (Accessed February 25, 2024)
Created February 1, 2014, Updated November 10, 2018