NTSB CAROL · Event
Event ERA25LA022
Registry · N89S
FAA Aircraft Registry record.
Make / Model
CESSNA T206H
Year of manufacture
2017 · 7 years old at event
Engine
LYCOMING TIO-540-AJ1A (310 hp)
Seats / Engines
6 seats · 1 engine
Last airworthiness date
20171219
ADS-B equipped
Yes — Mode-S AC448B
Registrant of record
GALAXY AVIATION LLC
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
The pilot’s failure to maintain directional control during takeoff and subsequent rejected takeoff, which resulted in a runway excursion. Contributing to the accident was the pilot’s failure to verify rudder trim setting prior to takeoff.
Factual narrative
The pilot reported that the airplane yawed left during takeoff and initial climb. At about 15 ft above ground level, he was unable to regain directional control and reduced engine power to land back onto the runway. The airplane landed left of the runway centerline, veered left, and then exited the left side of the runway. During the excursion, the nose and right main landing gear collapsed, and the right wing impacted the ground. The airplane came to rest in a grassy area adjacent to the runway. The airplane sustained substantial damage to its fuselage and right wing. Post-accident examination of the airplane by a Federal Aviation Administration inspector revealed the rudder trim indicator was positioned to a partial nose left trim setting. Flight control continuity was established from the cockpit to all flight control surfaces. The examination revealed that there were no preaccident mechanical malfunctions or failures that would have precluded normal operation. The pilot stated that additional right rudder input could have prevented the accident. Source: NTSB Aviation Accident Database Retrieved: 2026-02-12
NTSB Findings
Hierarchical cause / factor breakdown from the FAA bulk avdata database. Each finding tagged C (Cause) or F (Factor).
- — Aircraft-Aircraft oper/perf/capability-Performance/control parameters-Directional control-Not attained/maintained
- — Personnel issues-Task performance-Use of equip/info-Aircraft control-Pilot
- — Personnel issues-Task performance-Use of equip/info-Use of checklist-Pilot
Verbatim from NTSB's published report. Source file
NTSB_2024_ERA25LA022.txt.
Findings + structured fields enriched from FAA avall.mdb.
Full investigation docket on
data.ntsb.gov ↗.
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Related research
What the literature says.
Academic papers and agency reports matching this event's aircraft type or causal vocabulary (runway excursion). Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- SKYbrary (Eurocontrol) 2024 · SKYbrary article
Runway Excursion — SKYbrary Knowledge Base
SKYbrary runway excursion review — RE-OE (overruns) + RE-LO (lateral). Risk drivers: long landing, high approach speed, contaminated surface, tailwind, mis-set autobrakes.
- NTSB Aircraft Accident Reports 2019 · Accident report
Embraer ERJ 175 Runway Excursion at Charlotte Douglas
Republic Airline ERJ-175 runway excursion CLT, January 2018. Examines a low-energy runway excursion involving misuse of autobrakes + thrust reverser response after a high-crosswind landing on a contam…
- NASA NTRS 2025 · Presentation
Uncovering Resilient Behavior in the Aviation Safety Reporting System Using Large Language Models
Resiliency is present in everyday life, both in system design and exhibited by the operators that function within these systems.
- NASA NTRS 2025 · Conference Paper
Uncovering Resilient Behavior in the Aviation Safety Reporting System Using Large Language Models
Resiliency is present in everyday life, both in system design and exhibited by the operators that function within these systems.
- Flight Safety Foundation 2024 · FSF / AeroSafety World
Runway Safety Initiative Final Report (RSI)
Foundation Runway Safety Initiative final report — comprehensive analysis of runway excursion + incursion risk drivers worldwide.
- Semantic Scholar 2020 · Article
Towards online prediction of safety-critical landing metrics in aviation using supervised machine learning
Abstract In recent years, due to the increased availability of data and improvements in computing power, application of machine learning techniques to various aviation safety problems for identifying,…
Browse the full corpus — academia portal ↗