LE QUY DON
Technical University
VietnameseClear Cookie - decide language by browser settings

Model Selection for Predicting the Evaporation Rate of Aviation Fuels

Pham Vu, T.N. and Pham Xuan, P. and Nguyen Trung, K. (2023) Model Selection for Predicting the Evaporation Rate of Aviation Fuels. In: Conference of SAE Automotive Technical Papers, WONLYAUTO 2023, 1 January 2023, Warrendale.

Full text not available from this repository. (Request a copy) (Upload)

Abstract

The prediction of accurate evaporation rates for aviation fuels, which are complex mixtures of hundreds of hydrocarbon components with varying evaporation characteristics, remains a challenge. Multi-component vaporization models, such as distillation curve (DC) and diffusion limit (DL), are capable of predicting evaporation rates well but require the construction of surrogate fuels, which is difficult. Mono-component models, on the other hand, can be used for rapid evaporation conditions similar to those in a heat engine combustion chamber, with acceptable uncertainties. However, the accuracy of these models under engine-relevant operating conditions is unclear. This study aims to address this research gap by experimentally measuring the evaporation rates of two aviation fuels (TS-1 and Jet-A1) at different temperature conditions and evaluating the feasibility of current theoretical models for predicting evaporation rates under engine-relevant conditions. The study found that current models cannot accurately describe special events such as micro-explosions or slow evaporation, which were observed in the case of TS-1 droplets at temperatures above 823 K. This study highlights the need for more accurate models for predicting the evaporation rates of aviation fuels under engine-relevant conditions. © 2023 SAE International. All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Vehicle and Energy Engineering
Identification Number: 10.4271/2023-01-5028
Uncontrolled Keywords: Distillation; Drops; Evaporation; Forecasting, Aviation fuel; Complex mixture; Condition; Droplet evaporation; Droplet evaporation model; Evaporation model; Evaporation rate; Fuel droplets; Hydrocarbon components; Model Selection, Engines
Additional Information: Conference of SAE Automotive Technical Papers, WONLYAUTO 2023; Conference Date: 1 January 2023; Conference Code:185956
URI: http://eprints.lqdtu.edu.vn/id/eprint/10863

Actions (login required)

View Item
View Item