Forecasting Chemical Characteristics of Aircraft Fuel Using Artificial Neural Networks

• Main Authors: Felipe Valverde Rocha, Koshun Iha, Thiago Antonio Grandi de Tolosa
• Format: Article
• Language: English
• Published: Departamento de Ciência e Tecnologia Aeroespacial 2021-05-01
• Series: Journal of Aerospace Technology and Management
• Subjects: fuel; temperature; enthalpy; entropy; heat
• Online Access: https://www.scielo.br/pdf/jatm/v13/2175-9146-jatm-13-e2721.pdf

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.