文献类型：期刊文献

英文题名：Liaw-UNIFAC flash point model for alcohols-kerosene/diesel fuel blends using average fuel structure

作者：Huo, Xin[1];Lu, Qiang[2];Wang, Jian[1]

机构：[1]Univ Sci & Technol China, State Key Lab Fire Sci, Hefei 230026, Anhui, Peoples R China;[2]East China Univ Sci & Technol, Sch Resource & Environm Engn, Shanghai 200237, Peoples R China

年份：2022

卷号：160

起止页码：400

外文期刊名：PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

收录：;EI(收录号：20221111787586);WOS:【SCI-EXPANDED(收录号:WOS:000834857000003)】；

基金：This work was supported by the National Science and Technology Major Project (J2019-VIII-0010-0171) ; and the Fundamental Research Funds for the Central Universities (WK2320000052) .

语种：英文

外文关键词：Flash point; Kerosene; Alcohol; UNIFAC model; Group structure

摘要：Alcohol has already been widely used as an alternative fuel to blend with petroleum-based fuels. Accurate knowledge of flash points and their reliable prediction methods is essential in hazard identification, fire hazard reduction, process inherently safer design, and the risk management of alcohol-based fuels. This work presents a model to predict the flash point for alcohol + petroleum-based fuel blends based on the Liaw model incorporated with the original UNIFAC model. The flash point prediction model was modified by two steps: 1. applying a single vapor-temperature relationship for the petroleum-based fuel; 2. obtaining the activity coefficients by UNIFAC model using an average fuel structure for the petroleum-based fuel. The proposed model was verified experimentally for five fuel blends of alcohol + kerosene (alcohol being n-butanol, n-hexanol, and n-octanol) and alcohol + diesel (alcohol being n-butanol and n-hexanol). The flash point prediction procedure for alcohol + petroleum-based fuel blends was reduced to that of a binary mixture. The deviations between the predicted values and experimental data were mostly within 2 degrees C for the five fuel blends. (C) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.