NTSB CAROL · Event
Event ANC06CA091
Aircraft involved
Probable cause & findings
The pilot's inadequate compensation for crosswind conditions, which resulted in a loss of control during the landing roll. Factors associated with the accident were a crosswind, and an inadvertent swerve.
Factual narrative
The private certificated pilot was landing a homebuilt, tailwheel-equipped airplane on runway 22, which required a correction for a right crosswind. The local area personal flight was conducted under Title 14, CFR Part 91. The pilot stated that on the accident landing the airplane bounced slightly, then veered to the left side of the runway. He was unable to maintain directional control, and the airplane went off the left side of the runway, and entered an area of grass-covered terrain. The airplane subsequently nosed over and sustained substantial damage to the wings, fuselage, and canopy. According to the pilot, wind conditions at the time of the accident were 270 degrees at 9 knots, with gusts to 12 knots. The pilot noted in his written report to the NTSB that there were no preaccident mechanical anomalies with the airplane. The private certificated pilot was landing a homebuilt, tailwheel-equipped airplane on runway 22, which required a correction for a right crosswind. The local area personal flight was conducted under Title 14, CFR Part 91. The pilot stated that on the accident landing the airplane bounced slightly, then veered to the left side of the runway. He was unable to maintain directional control, and the airplane went off the left side of the runway, and entered an area of grass-covered terrain. The airplane subsequently nosed over and sustained substantial damage to the wings, fuselage, and canopy. According to the pilot, wind conditions at the time of the accident were 270 degrees at 9 knots, with gusts to 12 knots. The pilot noted in his written report to the NTSB that there were no preaccident mechanical anomalies with the airplane. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_2006_ANC06CA091.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 (loss of control). Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- Embry-Riddle Scholarly Commons 2025 · Journal article (JAAER)
A Scoping Review of Aviation Loss of Control Inflight Research
Loss of control – inflight (LOC-I) contributes to aircraft accidents at unacceptably high rates. Significant industry efforts and research have aimed to improve LOC-I prevention, detection, and recove…
- SKYbrary (Eurocontrol) 2024 · SKYbrary article
Loss of Control In-Flight (LOC-I) — SKYbrary Knowledge Base
SKYbrary comprehensive knowledge-base entry on Loss of Control In-Flight — definitions, contributing factors, accident case studies (Air France 447, Colgan 3407), and prevention strategies.
- NTSB Aircraft Accident Reports 2022 · Accident report
Loss of Control on Takeoff in Icing Conditions — Citation 560XL
Cessna Citation 560XL fatal takeoff icing accident, March 2018. Investigation of a Citation 560XL loss-of-control takeoff accident in icing conditions.
- Semantic Scholar 2021 · Article (Aviation)
ANALYSIS OF GENERAL AVIATION FIXED-WING AIRCRAFT ACCIDENTS INVOLVING INFLIGHT LOSS OF CONTROL USING A STATE-BASED APPROACH
Inflight loss of control (LOC-I) is a significant cause of General Aviation (GA) fixed-wing aircraft accidents. The United States National Transportation Safety Board’s database provides a rich source…
- NASA NTRS 2021 · Presentation
Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection
Abstract—We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft.
- NASA NTRS 2021 · Conference Paper
Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection
We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft.
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