Prediction of jatropha-algae biodiesel blend oil yield with the application of artificial neural networks technique

被引：25

作者：

Kumar, Sunil ^{[1
]}

Jain, Siddharth ^{[2
]}

Kumar, Harmesh ^{[3
]}

机构：

[1] Gurukula Kangri Vishwavidyalaya, Fac Engn & Technol, Dept Mech Engn, Haridwar 249404, India

[2] Coll Engn Roorkee, Dept Mech Engn, Roorkee, Uttar Pradesh, India

[3] Panjab Univ, Univ Inst Engn & Technol, Dept Mech Engn, Chandigarh, India

来源：

ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS | 2019年 / 41卷 / 11期

关键词：

Biodiesel; prediction; biodiesel yield; ANN; transesterification; OPTIMIZATION; MODEL; FLOW;

D O I：

10.1080/15567036.2018.1548507

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this work, the experiments of the transesterification process were carried out on jatropha-algae oil blend and the prediction of the synthesized biodiesel was investigated. The study was divided into two parts. In the first part, a series of experiments were employed practically and in the second part, the prediction is made with the artificial neural network (ANN). The ANN with Levenberg-Marquardt (LM) algorithm was trained with topology 4-10-1. The estimated results were compared with the experimental results. An ANN model was developed based on a back-propagation learning algorithm. An R-square value of the model from ANN was 0.9976. The results confirmed that the use of an ANN technique is quite suitable. The artificial neural network gave acceptable results.

引用

页码：1285 / 1295

页数：11

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