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Journal of Aviation Technology and Engineering

Journal

2024

Weather

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Deficiencies In Safe Practices By Pilots Operating General Aviation Aircraft In Weather Conducive For Icing, Douglas Boyd Phd, Thomas Guinn Phd Apr 2024

Deficiencies In Safe Practices By Pilots Operating General Aviation Aircraft In Weather Conducive For Icing, Douglas Boyd Phd, Thomas Guinn Phd

Journal of Aviation Technology and Engineering

Introduction: Flights of general aviation aircraft in icing conditions pose safety hazards especially since few airplanes are equipped with ice protection systems (FIKI). Herein, we sought to answer the following questions not previously addressed: (i) Has the general aviation icing-related accident rate declined over time? (ii) Which phase(s) of flight lead(s) to the highest fraction of fatal accidents? (iii) Do general aviation pilots adhere to safe practices when operating in forecasted icing?

Methods: Retrospectively, icing-related accidents were per the National Transportation Safety Board database. Prospectively, non-FIKI single-engine airplanes, operating in forecasted icing, were tracked (January–March 2023) using FlightAwareR. Presumptive icing …


Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi Jan 2024

Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi

Journal of Aviation Technology and Engineering

Weather is responsible for approximately 70% of air transportation delays in the National Airspace System, and delays resulting from convective weather alone cost airlines and passengers millions of dollars each year due to delays that could be avoided. This research sought to establish relationships between environmental variables and airport efficiency estimates by data mining archived weather and airport performance data at ten geographically and climatologically different airports. Several meaningful relationships were discovered from six out of ten airports using various machine learning methods within an overarching data mining protocol, and the developed models were tested using historical data.