Author ORCID Identifier

Huang - https://orcid.org/0000-0003-2087-8745

Document Type

Article

Publication Date

4-5-2020

Publication Title

Collegiate Aviation Review International

Volume

38

Issue

1

DOI

https://doi.org/10.22488/okstate.20.100206

Abstract

Data from the National Transportation Safety Board (NTSB)reveal that general aviation (GA) accounted for 76% of total air transport related accidents and incidents in the U.S.between 2014 and 2019. The identification of causes is one of the most important tasks in aircraft accident investigation and a criticalstrategy for proactive aircraft accident prevention. Aircraft and flight crew perform differently in each phase of flight given the changes of aircraft configuration, flight operation environment and flight crew workload, therefore, the causes of aircraftaccident may vary by phase of flight. Most accidents occur inthe phases of final approach and landing have been investigated by many researchers from various perspectives. Few studies, however, have been published on flight safety for the phase of takeoff,which has the second-highest number of GA aircraft accidents and incidents. A good understanding of the causes of GA aircraft accidents during takeoff is crucial to develop more effective countermeasures for aircraft takeoff risk mitigation and accidentprevention. The objective of this study is to understand the causes of GA aircraft takeoff accidents by analyzing aircraft accident investigation reports published by the NTSB. To better understand the causes of GA aircraft takeoff accidents, the following research design has been implemented. First, comparative analysis was applied to depict the statistical features of GA takeoff accidents compared to other air transport categories.Temporal change of GA takeoff accidents was analyzed using a linear-by-linear association test. Secondly, primary accident causes were identified by analyzing the NTSB investigation reports.Text mining techniques were applied to further explore contributing factors associated with the identified causes to enrich discovered knowledge. Finally, logistic regression analysis was applied to explore risk factors for fatal GA aircraft takeoff accidents. Lists of key causal and contributing factors were revealed and discussed from the analytical results. The identification of causal factors, contributing factors and risk factors for GA aircraft takeoff accidents are expected to be a valuable supplement to existing knowledge for aircraft accident prevention.

Comments

This is an open access article.

Download

Share

COinS