Prediction of recital characteristics of a CI diesel engine operated by bio-fuel extracts from cotton seed oil, linseed oil and mahua seed oil using ANN metho

IF 1.1 Q3 Engineering
Srinivasa REDDY KUNDURU, Hanumantha Rao YARRAPATHRUNI VENKATA, D. Vallapudi, Narmatha Deenadayalan, A. Kumaravel
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引用次数: 0

Abstract

In the wide survey, it is explored that the potential of artificial neural network is used to foretell the recital (performance) characteristics of a four stroke single cylinder diesel engine using the biofuel obtained from cottonseed, linseed and Mahua seed. The test engine was powered with diesel and biofuel with its blends from cotton seed, linseed and Mahua seed separately. Experimental results of the cotton seed oil, linseed oil and mahua oil as a substitute for diesel revealed that linseed oil provides the better engine performance nearly equal to diesel. The ANN is used to compute the performance characteristics such as Indicated power, Brake power, Friction power, Thermal efficiency, brake mean effective pressure, brake thermal efficiency, Brake specific fuel consumption, Indicated thermal efficiency, indicated mean effective pressure, Mechanical efficiency, Indicated specific fuel consumption, volumetric efficiency and combustion characteristics as compression ratio at different conditions of torque, speed, water flow , air rate and fuel rate. An ANN sculpt was developed with 80% of training data and 20% of testing data from experimental values. In this model, back propagation feed forward neural network with five inputs and eleven outputs has been used. The ANN model result accuracy was found to agree nearly with the experimental results with the regression coefficient value approximately equal to one and low mean square error value. Thus, the proposed ANN model was legitimate tool for predicting the combustion and performance of diesel engine.
应用人工神经网络方法预测棉籽油、亚麻籽油和马化油生物燃料提取物对CI柴油机性能的影响
在广泛的调查中,探索了利用人工神经网络的潜力来预测四冲程单缸柴油机的独奏(性能)特性,该柴油机使用了从棉籽、亚麻籽和麻花籽中获得的生物燃料。试验发动机由柴油和生物燃料提供动力,其混合物分别来自棉花籽、亚麻籽和麻花籽。用棉子油、亚麻籽油和马化油代替柴油的试验结果表明,亚麻籽油提供的发动机性能几乎和柴油相当。ANN用于计算性能特性,如指示功率、制动功率、摩擦功率、热效率、制动平均有效压力、制动热效率、制动器比油耗、指示热效率、指示平均有效压力和机械效率、指示比油耗,容积效率和燃烧特性,如在不同扭矩、速度、水流量、空气流量和燃料流量条件下的压缩比。利用80%的训练数据和20%的实验值测试数据开发了ANN造型。在该模型中,使用了具有五个输入和十一个输出的反向传播前馈神经网络。神经网络模型的精度与实验结果基本一致,回归系数值近似为1,均方误差较小。因此,所提出的神经网络模型是预测柴油机燃烧和性能的合理工具。
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来源期刊
CiteScore
2.40
自引率
18.20%
发文量
61
审稿时长
4 weeks
期刊介绍: Journal of Thermal Enginering is aimed at giving a recognized platform to students, researchers, research scholars, teachers, authors and other professionals in the field of research in Thermal Engineering subjects, to publish their original and current research work to a wide, international audience. In order to achieve this goal, we will have applied for SCI-Expanded Index in 2021 after having an Impact Factor in 2020. The aim of the journal, published on behalf of Yildiz Technical University in Istanbul-Turkey, is to not only include actual, original and applied studies prepared on the sciences of heat transfer and thermodynamics, and contribute to the literature of engineering sciences on the national and international areas but also help the development of Mechanical Engineering. Engineers and academicians from disciplines of Power Plant Engineering, Energy Engineering, Building Services Engineering, HVAC Engineering, Solar Engineering, Wind Engineering, Nanoengineering, surface engineering, thin film technologies, and Computer Aided Engineering will be expected to benefit from this journal’s outputs.
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