NTSB CAROL · Event
Event ERA23LA222
Aircraft involved
Probable cause & findings
The pilot’s failure to maintain adequate clearance from obstacles during takeoff at night.
Factual narrative
The pilot stated that he and the pilot-rated passenger were practicing full-stop landings from the turf runway on a dark, moonless night. The passenger had already completed three full-stop landings and he had completed two. The accident flight was going to be his last landing. During a takeoff, he lost visual reference of the tree line along the side of the runway and contacted some treetops. The airplane subsequently impacted the ground and the leading edges of the wings, and fuselage were substantially damaged. The pilot and the passenger were seriously injured. The pilot reported that there were no preimpact mechanical malfunctions or failures with the airplane that would have precluded normal operation. 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).
- — Personnel issues-Action/decision-Info processing/decision-Identification/recognition-Pilot
- — Environmental issues-Physical environment-Object/animal/substance-Tree(s)-Awareness of condition
- — Environmental issues-Conditions/weather/phenomena-Light condition-Dark-Effect on operation
Verbatim from NTSB's published report. Source file
NTSB_2023_ERA23LA222.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 (icing). Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- NASA NTRS 2026 · Contractor Report (CR)
Icing Physics Studies Using the 3D SIDRM Test Article: 2023 Icing Tests Analysis
In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation…
- arXiv 2025 · arXiv preprint
Multi-Agent Deep Reinforcement Learning for UAV-Assisted 5G Network Slicing: A Comparative Study of MAPPO, MADDPG, and MADQN
The growing demand for robust, scalable wireless networks in the 5G-and-beyond era has led to the deployment of Unmanned Aerial Vehicles (UAVs) as mobile base stations to enhance coverage in dense urb…
- Embry-Riddle Scholarly Commons 2025 · Journal article (JAAER)
A Mathematical Model on the Temporal Dynamics of Aviation Competitive Pricing
This study investigates the competitive dynamics of airport pricing using U.S. airport data to validate the findings. It employs linear and nonlinear ordinary differential equation models to analyze t…
- NASA NTRS 2025 · Presentation
NASA Icing Update – March 2025
This NASA Icing Update was prepared for presentation to the SAE International AC-9C Inflight Icing Technology Committee. This update includes the following topics: planned Rotational Icing Scaling tes…
- arXiv 2024 · arXiv preprint
An energy-stable phase-field model for droplet icing simulations
A phase-field model for three-phase flows is established by combining the Navier-Stokes (NS) and the energy equations, with the Allen-Cahn (AC) and Cahn-Hilliard (CH) equations and is demonstrated ana…
- NASA NTRS 2024 · Presentation
NASA Icing Update – Oct 2024
This presentation provides a status update on select NASA icing research activities for the SAE AC-9C Icing Technical Committee Meeting on Oct 21, 2024.
Browse the full corpus — academia portal ↗