Estimation of dynamic viscosities of vegetable oils using artificial neural networks

被引：0
|
作者：
Aksoy, Fatih [1 ]
Yabanova, Ismail [2 ]
Bayrakceken, Huseyin [1 ]
机构：
[1] Afyon Kocatepe Univ, Tech Educ Fac, Machine Educ Dept, Afyon, Turkey
[2] Afyon Kocatepe Univ, Elect Educ Dept, Machine Educ Dept, Afyon, Turkey
来源：
INDIAN JOURNAL OF CHEMICAL TECHNOLOGY | 2011年 / 18卷 / 03期
关键词：
Dynamic viscosity; Vegetable oils; Artificial neural networks; INJECTION DIESEL-ENGINE; METHYL-ESTER; TEMPERATURE; BLENDS; FUEL;
D O I：
暂无
中图分类号：
O69 [应用化学];
学科分类号：
081704 ;
摘要：
In this study, viscosities of raw sunflower and corn oils are measured at 1 degrees C intervals between 0-100 degrees C. Experimental results are fitted to six equations that are used in viscosity estimation and the correlation coefficients arc determined. The best correlation coefficient is obtained using In(mu)=a+b/(T+c) equation with 0.99972 and 0.99974 for sunflower and corn oil, respectively. In addition to this, viscosity values are obtained using artificial neural networks and the results are compared to the equation leading to the best correlation coefficient. Using artificial neural networks, the correlation coefficients are obtained as 0.999907 and 0.999925 for raw sunflower and corn oil respectively.
引用
收藏
页码：227 / 233
页数：7
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