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C4+ Surrogate Models for Thermophysical Properties of Aviation Kerosene RP‑3 at Supercritical Pressures

Due to the complexity of the chemical compositions in aviation kerosene, simplified surrogate models have gained significant attention to effectively reproduce the thermophysical properties of aviation kerosene. The available surrogate models usually adopt uniform representative compositions with a...

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Bibliographic Details
Published in:Energy & fuels 2021-05, Vol.35 (9), p.7858-7865
Main Authors: Shen, Yang, Liu, Yuan-Bin, Cao, Bing-Yang
Format: Article
Language:English
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Summary:Due to the complexity of the chemical compositions in aviation kerosene, simplified surrogate models have gained significant attention to effectively reproduce the thermophysical properties of aviation kerosene. The available surrogate models usually adopt uniform representative compositions with a fixed ratio. However, given that aviation kerosene is an extremely complex mixture and associated with physicochemical reactions in actual heating processes, such simple models generally cannot accurately reproduce the thermophysical properties of aviation kerosene in a wide range of temperatures and pressures. Therefore, this work aims to develop accurate and independent surrogate models named C4+ for various thermophysical properties of aviation kerosene RP-3 at supercritical pressures. The thermophysical properties include density, viscosity, constant-pressure heat capacity, and thermal conductivity. The C4+ surrogate models are determined by using a carefully designed genetic algorithm to minimize the relative deviations between the calculated and experimental data of the corresponding properties based on the previous C4 surrogate model. Especially, the effects of pyrolysis and autoxidation reactions have been equivalently introduced to the corrections of the surrogate models. Consequently, the prediction of our surrogate models shows overall good agreement with the experimental measurements and the highest accuracy among all simplified surrogate models so far.
ISSN:0887-0624
1520-5029
DOI:10.1021/acs.energyfuels.1c00326