用人工神经网络预测飞机燃料的化学特性

IF 0.9 Q3 ENGINEERING, AEROSPACE
F. Rocha, K. Iha, T. A. G. Tolosa
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引用次数: 0

摘要

被称为喷气推进的飞机燃料被用于航空领域的几个活动领域。有以煤油为基础的喷气燃料,也就是商业上获得的燃料,还有实验室生产的合成燃料。所有这些燃料都包含在所谓的推进剂中。本文以喷气推进-8(JP 8)燃料为数据分析基础,对两个温度范围进行了分析。第一个范围,从300到2500 K,分析了比热、焓和熵。基于理论和实验数据,开发了人工神经网络(Ann)来识别其他工作条件下的这些特性,即在其他温度下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Chemical Characteristics of Aircraft Fuel Using Artificial Neural Networks
Aircraft fuels, called jet propulsion, are used in several areas of activity within aeronautics. There are jet fuels based on kerosene, that is, those obtained commercially, and there are synthetics produced in the laboratory. All of these fuels are included within the so-called propellants. In this article, Jet propulsion-8 (JP 8) fuel was used as the basis for data analysis, and thus two temperature ranges were analyzed. The first range, from 300 to 2500 K, was analyzed for specific heat, enthalpy and entropy. Based on theoretical and experimental data, artificial neural networks (ANNs) were developed to identify these properties in other working conditions, that is, at other temperatures.
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CiteScore
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