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Articles

A hybrid multicomponent model for the vaporisation simulation of gasoline drop

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Pages 210-225 | Received 10 Nov 2017, Accepted 16 Jul 2018, Published online: 13 Aug 2018
 

Abstract

A Hybrid multicomponent drop vaporisation model inspired by both the continuous thermodynamics and discrete component approaches is developed to improve the simulation of drop vaporisation process of petroleum fuels. Using the hybrid model, the petroleum fuel is assumed to be the mixture of several hydrocarbon species groups, and the composition of each group is described by an individual gamma distribution about the molecular weight. Compared to a traditional continuous thermodynamics model based on a single gamma distribution, the hybrid model is first proved to be more adequate in the description of petroleum fuel composition. For each hydrocarbon species group, the normal boiling point is assumed to be linearly correlated with the molecular weight, and improved prediction of normal boiling point is obtained compared to a traditional model. On this basis, improved prediction of gasoline distillation curve is also achieved. The hybrid model is finally used to simulate the vaporisation of a single gasoline drop, and a more complex variation of liquid-phase composition is observed during the vaporisation process. The distribution of species composition in each group moves in the direction of increasing molecular weight, and a significant change in the overall molar proportion of the species groups in the liquid drop is also observed during the vaporisation.

Acknowledgments

Project supported by the National Natural Science Foundation of China (Grant No. 51306209) and the Science Foundation of China University of Petroleum, Beijing (No. YJRC-2013-43).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Project supported by the National Natural Science Foundation of China [grant number 51306209] and the Science Foundation of China University of Petroleum, Beijing [grant number YJRC-2013-43].

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