A state-based approach to modeling general aviation accidents
Semantic Scholar · Article (Reliability Engineering & System Safety) · 5fadd7853aecab5364a3c6af2a3d250f6a115ad1 · Published 2020-01-01 · Reliability Engineering & System Safety · 2 authors
Abstract and citation only, verbatim from Semantic Scholar; full text lives there. All credit to the authors and Reliability Engineering & System Safety.
Abstract
Abstract This paper develops a state-based accident model that we apply to General Aviation (GA) accidents recorded in the National Transportation Safety Board (NTSB) accident database. We demonstrate our approach on 6180 helicopter accidents that occurred in the United States between 1982 and 2015, with emphasis on inflight loss of control (LOC-I) accidents. Our model helps remove the redundancies in the NTSB coding system by logically grouping various NTSB accident codes that convey the same meaning. Further, this model checks for logical gaps or omissions in NTSB accident records, and potentially fills the omissions in. This approach uses NTSB coding data to define a set of states (safe or hazardous) for a system and triggers that move the system into (or out of) these states. We identify the most frequent triggers for LOC-I and compare the results from the state-based approach with those obtained from a conventional analysis of NTSB accident codes.
Authors
- Arjun H. Rao
- Karen B. Marais
Keywords
- Computer Science
- Engineering
Citation
Arjun H. Rao, Karen B. Marais (2020). A state-based approach to modeling general aviation accidents. Reliability Engineering & System Safety. Semantic Scholar ID 5fadd7853aecab5364a3c6af2a3d250f6a115ad1. https://doi.org/10.1016/j.ress.2019.106670 ↗