ANALYZING US NAVY F/A-18 FUEL CONSUMPTION FOR PURPOSES OF ENERGY CONSERVATION
| dc.contributor.advisor | Buttrey, Samuel E. | |
| dc.contributor.author | Barnhill, David | |
| dc.contributor.department | Operations Research (OR) | |
| dc.contributor.secondreader | Whitaker, Lyn R. | |
| dc.date.accessioned | 2021-05-14T03:50:33Z | |
| dc.date.available | 2021-05-14T03:50:33Z | |
| dc.date.issued | 2021-03 | |
| dc.description.abstract | Energy usage and conservation are perennial challenges facing the Naval Aviation Enterprise (NAE) and the U.S. Navy (USN) writ large. In order to promote USN energy conservation, the Naval Air Systems Command (NAVAIR) established the Air Energy Conservation (Air ENCON) program to further analytics-driven energy consumption assessment, and assist the USN to meet broader conservation goals. This study used a flight sortie data set built by Deloitte Consulting, constructed from three separate data sources, to assess F/A-18 fuel consumption, aiding Air ENCON analysis goals. The data set, which was derived from aircraft memory unit (MU) recordings, Naval Aviation Flight Records (NAVFLIR), and the Sierra-Hotel Aviation Readiness Program (SHARP) records, consisted of more than 466,000 USN F/A-18 sorties spanning a four-year time frame. This research evaluated the veracity of sortie data fuel output metrics and identified broad fuel consumption trends despite a significant proportion of missing or unused information. Furthermore, this thesis documents the effectiveness of the data to predict fuel consumption by use of original and generated predictors in combination with various imputation methods. Results suggest that while statistical inference is difficult due to the amount of missing data, broad trends related to sortie location are identifiable, and models using imputation coupled with original and generated predictors exhibit the best results for predictive effectiveness. | en_US |
| dc.description.distributionstatement | Approved for public release. distribution is unlimited | en_US |
| dc.description.recognition | Outstanding Thesis | en_US |
| dc.description.service | Commander, United States Navy | en_US |
| dc.description.uri | http://archive.org/details/analyzingusnavyf1094567103 | |
| dc.identifier.curriculumcode | 360, Operations Analysis | |
| dc.identifier.thesisid | 34847 | |
| dc.identifier.uri | https://hdl.handle.net/10945/67103 | |
| dc.publisher | Monterey, CA; Naval Postgraduate School | en_US |
| dc.relation.ispartofseries | NPS Outstanding Theses and Dissertations | |
| dc.rights | This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. | en_US |
| dc.subject.author | fuel | en_US |
| dc.subject.author | fuel conservation | en_US |
| dc.subject.author | F/A-18 | en_US |
| dc.subject.author | E-2D | en_US |
| dc.subject.author | E/A-18 | en_US |
| dc.subject.author | naval aviation | en_US |
| dc.subject.author | machine learning | en_US |
| dc.subject.author | predict | en_US |
| dc.title | ANALYZING US NAVY F/A-18 FUEL CONSUMPTION FOR PURPOSES OF ENERGY CONSERVATION | en_US |
| dc.type | Thesis | en_US |
| dspace.entity.type | Publication | |
| etd.thesisdegree.discipline | Operations Research | en_US |
| etd.thesisdegree.grantor | Naval Postgraduate School | en_US |
| etd.thesisdegree.level | Masters | en_US |
| etd.thesisdegree.name | Master of Science in Operations Research | en_US |
| relation.isSeriesOfPublication | c5e66392-520c-4aaf-9b4f-370ce82b601f | |
| relation.isSeriesOfPublication.latestForDiscovery | c5e66392-520c-4aaf-9b4f-370ce82b601f |
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