Dataset on statistical analysis of Jet A-1 fuel laboratory properties for on-spec into-plane operations

Adekitan, Aderibigbe I. and Shomefun, Tobi and John, Temitope M. and Adetokun, Bukola and Aligbe, Alex (2018) Dataset on statistical analysis of Jet A-1 fuel laboratory properties for on-spec into-plane operations. Data article.

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Abstract

Safety is of utmost essence in the aviation sector, both on-ground and in the air. Aviation Turbine kerosene (ATK) commonly referred to as Jet fuel is one of the major resources of the aviation sector, contributing significantly to the operating cost of an airline. Flight safety is a top-notch requirement in air transportation management. Jet fuel quality affects flight safety, and this makes it mandatory to ensure that, at all points in the jet A-1 aviation fuel supply chain, the jet fuel is contamination free and on-spec. Jet fuel quality is determined via various mandatory Joint Inspection Group (JIG) based quality analysis test procedures; both baseline and extensive lab tests by third party labs. Acceptable parameter range has been established for each jet fuel property, the electrical conductivity of jet A-1 fuel must be between 50 to 600 pS/m and the density at 15C must be between 0.775 to 0.840 g/cm3. Beyond this range, the fuel is deemed off-spec and unsafe for into-plane fuelling operations. This data article presents daily jet fuel test records for jet-A1 fuel. The dataset contains the date of the test, the conductivity, the specific gravity at ambient temperature, the converted specific gravity at 15C, and the temperature of the jet fuel sample under study. All the tests were performed at standard laboratory conditions using approved and certified equipment. The dataset provides an opportunity for developing a predictive model that can be used for jet fuel properties prediction on a given day, based on previous data trends and analysis using data pattern recognition, as an indication of the variation of jet fuel properties with daily weather variation.

Item Type:	Article
Uncontrolled Keywords:	air transportation, aviation turbine kerosene -ATK, data pattern recognition, Jet A-1 aviation fuel, jet fuel properties prediction, quality analysis
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Mrs Patricia Nwokealisi
Date Deposited:	24 May 2018 13:51
Last Modified:	24 May 2018 13:51
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/10832

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