Response surface models for synthetic jet fuel properties

被引:9
作者
Coetzer, R. L. J. [1 ,4 ]
Joubert, T. S. [2 ,3 ]
Viljoen, C. L. [2 ]
Nel, R. J. J. [2 ]
Strydom, C. A. [3 ]
机构
[1] Sasol Grp Technol, 1 Klasie Havenga Rd, ZA-1947 Sasolburg, South Africa
[2] Sasol Energy Technol, 1 Klasie Havenga Rd, ZA-1947 Sasolburg, South Africa
[3] North West Univ, Chem Resource Beneficiat, Potchefstroom Campus,Private Bag X6001, ZA-2520 Potchefstroom, South Africa
[4] Univ Free State, Box 339, ZA-9300 Bloemfontein, South Africa
来源
APPLIED PETROCHEMICAL RESEARCH | 2018年 / 8卷 / 01期
关键词
Freeze point; Mixture experimental designs; Response surface models; Synthetic jet fuel; Viscosity;
D O I
10.1007/s13203-018-0196-7
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Jet fuel is a mixture of different hydrocarbon groups, and the mass contribution of each of these groups toward the overall chemical composition of the fuel dictates the bulk physical properties of the fuel after completion of the refining and blending processes. The fluidity properties of jet fuel mixtures at low temperatures are critical in understanding and mitigating the safety risks and performance attributes of aircraft engines, which may lead to the introduction of more stringent specification limits in the near future. Therefore, in this study the low-temperature viscosity and freeze point properties of jet fuels were investigated by variation of the linear to branched chain paraffin mass ratio, in conjunction with variation of the carbon number distribution according to a mixture by process variables experimental design. Furthermore, response surface models were developed and discussed for the two main fluidity properties of interest and inferences were made from the models for the potential generation of optimal jet fuel mixtures.
引用
收藏
页码:39 / 53
页数:15
相关论文
共 25 条
[1]   EFFECT OF COMPOSITION ON FREEZING POINTS OF MODEL HYDROCARBON FUELS [J].
AFFENS, WA ;
HALL, JM ;
HOLT, S ;
HAZLETT, RN .
FUEL, 1984, 63 (04) :543-547
[2]  
Agee MA, 1997, EC CONVERSION NATURA
[3]  
[Anonymous], 2015, D756615C ASTM
[4]  
*ASTM, 1991, 4B ASTM DS
[5]  
ASTM, 2016, D165516C ASTM
[6]  
Atkinson A., 2007, OPTIMUM EXPT DESIGNS, V34
[7]  
Brown T. E., 2018, CHEM CENTRAL SCI, P126
[8]  
Chuck CJ, 2016, BIOFUELS FOR AVIATION: FEEDSTOCKS, TECHNOLOGY AND IMPLEMENTATION, P1
[9]   Dual response surface optimization with hard-to-control variables for sustainable gasifier performance [J].
Coetzer, R. L. J. ;
Rossouw, R. F. ;
Lin, D. K. J. .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2008, 57 :567-587
[10]  
Coetzer RLJ, 2013, ADV MODEL ORIENTED D, P45