NTSB CAROL · Event
Event CEN24LA172
Registry · N67183
FAA Aircraft Registry record.
Make / Model
BELL 206B
Year of manufacture
1993 · 31 years old at event
TCDS
H2SW · BELL HELICOPTER TEXTRON CANADA LTD
Engine
ROLLS-ROYC 250-C20J (420 hp)
Seats / Engines
5 seats · 1 engine
Last airworthiness date
20071019
ADS-B equipped
Yes — Mode-S A8E2FB
Registrant of record
STATE OF LOUISIANA
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
The pilot’s loss of control during takeoff that resulted in a hard landing.
Factual narrative
The helicopter was positioned on a trailer when the pilot initiated a takeoff from the trailer. The pilot reported that the helicopter began a yaw to the right upon liftoff. He attempted to correct the yaw, but the helicopter continued to yaw. The pilot managed to regain some control and made a hard landing. The pilot’s supervisor was in his office near the trailer when he heard rapid tone changes in the rotor noise. He ran outside and saw the helicopter settle to the ground. He glanced at the helicopter, and it appeared undamaged. While the helicopter was still running, he climbed into the co-pilot side of the helicopter and performed a functional check. All controls functioned properly, and the gauges indicated normal. He then repositioned the helicopter back onto the trailer without incident. The helicopter sustained substantial damage to the tailboom. The pilot reported that there were no mechanical malfunctions/failures of the helicopter that would have precluded normal operations. 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-Task performance-Use of equip/info-Aircraft control-Pilot
- — Aircraft-Aircraft oper/perf/capability-Performance/control parameters-Yaw control-Not attained/maintained
Verbatim from NTSB's published report. Source file
NTSB_2024_CEN24LA172.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.
Browse the full corpus — academia portal ↗