基于多目标优化的航空煤油生物替代燃料模型构建及验证

doi:10.11949/0438-1157.20250477

化工学报 ›› 2025, Vol. 76 ›› Issue (11): 5720-5729.DOI: 10.11949/0438-1157.20250477

• 专栏：能源利用过程中的多相流与传热 • 上一篇

基于多目标优化的航空煤油生物替代燃料模型构建及验证

顾林林¹^,²(), 刘重阳³, 杨仲卿¹^,²(), 姜东³, 齐东东³, 冉景煜¹^,²

^1.低品位能源利用技术及系统教育部重点实验室（重庆大学），重庆 400044
^2.重庆大学能源与动力工程学院，重庆 400044
^3.中国航发四川燃气涡轮研究院，四川绵阳 621000

收稿日期:2025-05-06 修回日期:2025-09-26 出版日期:2025-11-25 发布日期:2025-12-19
通讯作者: 杨仲卿
作者简介:顾林林（1998—），女，博士研究生，gulin199804@163.com
基金资助:
国家自然科学基金项目(52276099);国家财政稳定支持项目

Model construction and validation of aviation kerosene bio-alternative fuel based on multi-objective optimization

Linlin GU¹^,²(), Chongyang LIU³, Zhongqing YANG¹^,²(), Dong JIANG³, Dongdong QI³, Jingyu RAN¹^,²

^1.The Key Laboratory of Low-grade Energy Utilization Technology and System, Ministry of Education (Chongqing University), Chongqing 400044, China
^2.School of Energy and Power Engineering, Chongqing University, Chongqing 400044, China
^3.Sichuan Gas Turbine Research Institute of Aviation Gas Turbine Corporation of China, Mianyang 621000, Sichuan, China

Received:2025-05-06 Revised:2025-09-26 Online:2025-11-25 Published:2025-12-19
Contact: Zhongqing YANG

摘要/Abstract

摘要：

能源短缺与环境污染是航空业尤为突出的问题，而生物燃料作为一种新兴能源，具有直接替代传统石油燃料的潜力。基于遗传算法，以密度、运动黏度、低位热值、氢碳比及分子量等物性参数为遴选指标对RP-3替代燃料组分比例进行多目标优化，并在常压、临界压力条件下对模型的准确性进行验证。研究表明，最佳替代燃料由32.78%的正丁醚、14.64%的2-甲基呋喃以及52.58%的二代生物柴油组成，理化特性误差整体在3%以内，且在广泛的环境条件下，该模型具备较高的主要物理性质可靠性。另外，利用构建包含192个组分和1482个基元反应的生物替代燃料半详细反应机理验证了其化学性质替代性，结果表明该模型着火延迟时间与实验值良好吻合，对生物燃料优化设计具有指导意义。

关键词: 遗传算法, RP-3航空煤油, 生物燃料, 优化设计, 理化特性, 着火延迟时间

Abstract:

Energy shortage and environmental pollution are particularly prominent problems in the aviation industry. Biofuels, as an emerging energy source, have the potential to directly replace traditional petroleum fuels. Based on the genetic algorithm, a multi-objective optimization of the proportion of RP-3 alternative fuel components was carried out using physical parameters such as density, kinematic viscosity, low level calorific value, hydrogen to carbon ratio and molecular weight as the selection criteria. The accuracy of the model was verified under atmospheric and critical pressure conditions. It is shown that the optimal alternative fuel consists of 32.78% n-butyl ether, 14.64% 2-methylfuran, and 52.58% second-generation biodiesel. The overall error in physical and chemical properties is within 3%. The model demonstrates high reliability of key physical properties under a wide range of environmental conditions. In addition, the chemical substitutability was verified by constructing a semi-detailed reaction mechanism for bioalternative fuels containing 192 components and 1482 radical reactions. The results showed that the model's ignition delay time was in good agreement with the experimental values, which is of great significance for the optimal design of biofuels.

Key words: genetic algorithm, RP-3 aviation paraffin, biofuel, optimized design, physicochemical properties, ignition delay time

中图分类号:

V 312⁺.3

顾林林, 刘重阳, 杨仲卿, 姜东, 齐东东, 冉景煜. 基于多目标优化的航空煤油生物替代燃料模型构建及验证[J]. 化工学报, 2025, 76(11): 5720-5729.

Linlin GU, Chongyang LIU, Zhongqing YANG, Dong JIANG, Dongdong QI, Jingyu RAN. Model construction and validation of aviation kerosene bio-alternative fuel based on multi-objective optimization[J]. CIESC Journal, 2025, 76(11): 5720-5729.

图/表 8

表1 RP-3 航空煤油及其表征组分物性参数

Table 1 RP-3 physical properties of aviation kerosene and its characterisation components

种类	密度/（kg/m³）	运动黏度/（mm²/s）	氢碳比	低热值/（MJ/kg）	平均分子量
RP-3	799	1.55	2.03	43.75	148
正丁醚	763	0.834	2.25	37.9	130
2-甲基呋喃	917	0.546	1.2	30.4	82
二代生物柴油	792	3.29	2.12	46.2	240

图1 最佳个体的优化函数值

Fig.1 Optimisation function values for the best individual

表2 RP-3航空煤油与替代燃料物性参数比较及误差

Table 2 Comparison of physical parameters and errors between aviation kerosene and alternative fuels

种类	密度/（kg/m³）	运动黏度/（mm²/s）	氢碳比	低热值/（MJ/kg）	平均分子量
RP-3	799	1.55	2.03	43.75	148
替代燃料	800	1.549	2.015	40.60	151
误差/%	0.22	0.02	0.76	6.38	2.17

图2 常压工况下各燃料密度（a）和运动黏度（b）随温度的演变规律

Fig.2 Evolution of the density(a) and kinematic viscosity(b) of each fuel with temperature under atmospheric conditions

图3 超临界压力工况下各燃料密度随温度的演变规律

Fig.3 Evolution of the density of each fuel with temperature under supercritical pressure conditions

图4 超临界压力工况下各燃料运动黏度随温度的演变规律

Fig.4 Evolution of kinematic viscosity with temperature for each fuel under supercritical pressure conditions

图5 高压工况（P=1.0 MPa）下生物替代燃料着火延迟时间的数值模拟与实验验证

Fig.5 Numerical simulation and experimental validation of ignition delay time of bioalternative fuels under high pressure condition (P=1.0 MPa)

图6 常压工况P=0.1 MPa（a）和低压工况P=0.01 MPa（b）下生物替代燃料着火延迟时间的数值模拟与实验验证

Fig.6 Numerical simulation and experimental validation of ignition delay time of bio-alternative fuels under atmospheric pressure condition P=0.1 MPa(a) and low-pressure conditions P=0.01 MPa(b)

参考文献 30

[1]	赵贤. 革新研发理念缓解能源危机[J]. 节能与环保, 2017(3): 44-45.
	Zhao X. Innovative R&D concepts to alleviate the energy crisiss[J]. Energy Conservation & Environmental Protection, 2017 (3): 44-45.
[2]	王淑樱. 某型号发动机的生物燃料燃烧特性研究[D]. 天津: 中国民航大学, 2018.
	Wang S Y. Research on the combustion characteristics of biofuel for a certain type of engine[D]. Tianjin: Civil Aviation University of China, 2018.
[3]	杨飞. 某型生物航空煤油的基础特性研究[D]. 南京: 南京航空航天大学, 2019.
	Yang F. Research on the basic characteristics of a certain type of bio-aviation kerosene[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2019.
[4]	Yao M F, Wang H, Zheng Z Q, et al. Experimental study of n-butanol additive and multi-injection on HD diesel engine performance and emissions[J]. Fuel, 2010, 89(9): 2191-2201.
[5]	赵玉垒. 稀混合气浓度对正丁醇燃烧过程的影响[D]. 青岛: 青岛大学, 2011.
	Zhao Y L. The influence of lean mixture concentration on the combustion process of n-butanol[D]. Qingdao: Qingdao University, 2011.
[6]	Lupandin V, Thamburaj R, Nikolayev A. Test results of the OGT2500 gas turbine engine running on alternative fuels: BioOil, ethanol, BioDiesel and crude oil[C]//ASME Turbo Expo 2005: Power for Land, Sea, and Air. 2005:421-426.
[7]	Rehman A, Phalke D R, Pandey R. Alternative fuel for gas turbine: esterified jatropha oil-diesel blend[J]. Renewable Energy, 2011, 36(10): 2635-2640.
[8]	朱重阳, 甘志文. 生物质组分对航空煤油基础燃烧特性的影响研究[J]. 可再生能源, 2017, 35(12): 1751-1758.
	Zhu C Y, Gan Z W. Research on the influence of biomass components on the basic combustion characteristics of aviation kerosene[J]. Renewable Energy, 2017, 35(12): 1751-1758.
[9]	黄生洪, 徐胜利, 刘小勇. 煤油超燃冲压发动机两相流场数值研究煤油在超燃流场中的多步化学反应特征[J]. 推进技术, 2005, 26(2) :101-105.
	Huang S H, Xu S L, Liu X Y. Numerical study on two-phase flow field of kerosene supersonic ramjet engine and characteristics of multi-step chemical reactions of kerosene in supersonic flow field[J]. Propulsion Technology, 2005, 26(2): 101-105.
[10]	刘建文, 熊生伟, 马雪松. 正癸烷燃烧详细反应机理的构建及简化[J]. 推进技术, 2012, 33(1) :64-68.
	Liu J W, Xiong S W, Ma X S. Construction and simplification of the detailed reaction mechanism of n-decane combustion[J]. Journal of Propulsion Technology, 2012, 33(1): 64-68.
[11]	Wang T S. Thermophysics characterization of kerosene combustion[C]//34th Thermophysics Conference. Denver, CO, USA: AIAA, 2000: AIAA2000-2511.
[12]	Delfau J L, Bouhria M, Reuillon M, et al. Experimental and computational investigation of the structure of a sooting decane-O₂-Ar flame[J]. Symposium (International) on Combustion, 1991, 23(1): 1567-1572.
[13]	Dagaut P, Reuillon M, Cathonnet M, et al. High pressure oxidation of liquid fuels from low to high temperature (3): n-Decane[J]. Combustion Science and Technology, 1994, 103(1):349-359.
[14]	Dagaut P, Reuillon M, Boettner J C, et al. Kerosene combustion at pressures up to 40 atm: experimental study and detailed chemical kinetic modeling [J]. Symposium (International) on Combustion, 1994, 25(1): 919-926.
[15]	Vijay Kumar M, Veeresh Babu A, Ravi Kumar P. The impacts on combustion, performance and emissions of biodiesel by using additives in direct injection diesel engine[J]. Alexandria Engineering Journal, 2018, 57(1): 509-516.
[16]	Cai L M, vom Lehn F, Pitsch H. Higher alcohol and ether biofuels for compression-ignition engine application: a review with emphasis on combustion kinetics[J]. Energy & Fuels, 2021, 35(3): 1890-1917.
[17]	Pelucchi M, Namysl S, Ranzi E, et al. Combustion of n-C₃—C₆ linear alcohols: an experimental and kinetic modeling study (part II): Speciation measurements in a jet-stirred reactor, ignition delay time measurements in a rapid compression machine, model validation, and kinetic analysis[J]. Energy & Fuels, 2020, 34(11): 14708-14725.
[18]	Tran L S, Herbinet O, Li Y Y, et al. Low-temperature gas-phase oxidation of diethyl ether: fuel reactivity and fuel-specific products[J]. Proceedings of the Combustion Institute, 2019, 37(1): 511-519.
[19]	Tran L S, Wullenkord J, Li Y Y, et al. Probing the low-temperature chemistry of di-n-butyl ether: detection of previously unobserved intermediates[J]. Combustion and Flame, 2019, 210: 9-24.
[20]	Liu J, Hu E J, Zeng W, et al. A new surrogate fuel for emulating the physical and chemical properties of RP-3 kerosene[J]. Fuel, 2020, 259: 116210.
[21]	Li A, Zhang Z, Cheng X G, et al. Development and validation of surrogates for RP-3 jet fuel based on chemical deconstruction methodology[J]. Fuel, 2020, 267: 116975.
[22]	Wu Z Y, Mao Y B, Raza M, et al. Surrogate fuels for RP-3 kerosene formulated by emulating molecular structures, functional groups, physical and chemical properties[J]. Combustion and Flame, 2019, 208: 388-401.
[23]	Deng H W, Zhang C B, Xu G Q, et al. Density measurements of endothermic hydrocarbon fuel at sub- and supercritical conditions[J]. Journal of Chemical & Engineering Data, 2011, 56(6): 2980-2986.
[24]	Deng H W, Zhang C B, Xu G Q, et al. Viscosity measurements of endothermic hydrocarbon fuel from (298 to 788) K under supercritical pressure conditions[J]. Journal of Chemical & Engineering Data, 2012, 57(2): 358-365.
[25]	Herbinet O, Pitz W J, Westbrook C K. Detailed chemical kinetic mechanism for the oxidation of biodiesel fuels blend surrogate[J]. Combustion and Flame, 2010, 157(5): 893-908.
[26]	Fan X F, Liu Z K, Yang J Z, et al. Pyrolysis of lignocellulosic biofuel di-n-butyl ether (DBE): flow reactor experiments and kinetic modeling[J]. Energy & Fuels, 2021, 35(17): 14077-14086.
[27]	Cheng Z J, Niu Q, Wang Z D, et al. Experimental and kinetic modeling studies of low-pressure premixed laminar 2-methylfuran flames[J]. Proceedings of the Combustion Institute, 2017, 36(1): 1295-1302.
[28]	Mao Y B, Yu L, Wu Z Y, et al. Experimental and kinetic modeling study of ignition characteristics of RP-3 kerosene over low-to-high temperature ranges in a heated rapid compression machine and a heated shock tube[J]. Combustion and Flame, 2019, 203: 157-169.
[29]	Zhang C H, Li B, Rao F, et al. A shock tube study of the autoignition characteristics of RP-3 jet fuel[J]. Proceedings of the Combustion Institute, 2015, 35(3): 3151-3158.
[30]	姚峰. 激波管的研发与RP-3煤油点火延迟特性研究[D]. 杭州: 浙江大学,2019.
	Yao F. Research on the development of shock tube and the study on the delay characteristics of RP-3 kerosene ignition[D]. Hangzhou: Zhejiang University, 2019.

基于多目标优化的航空煤油生物替代燃料模型构建及验证

Model construction and validation of aviation kerosene bio-alternative fuel based on multi-objective optimization

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