NTSB CAROL · Event
Event MIA81FLA19
Aircraft involved
Historical record (pre-1982)
NTSB recorded this accident in the pre-1982 coded-field schema — structured fields rather than free-text narrative. Decoded codes use established NTSB single-letter taxonomies; cause factors remain verbatim pending the Form 6120.4 codebook lookup.
Aircraft
STARDUSTER TOO · N333Q
Damage
Substantial
Craft type
Airplane
Classification
Accident
Light condition
Dusk
Weather
VMC
Phase of flight
Cruise — descent (EF)
Operator type
D
Airport
CRAIG
Kind of flying
B0
Weather at impact
Sky
CLEAR
Wind
130° / 4 kt
Aircraft history
Serial number
00000001-236
Total time
200 hrs
Pilot
Certificate
Commercial — instrument
Total hours
2,200
Age
45
Cause factors
- 64/A/22 A PILOT IN COMMAND IMPROPER OPERATION OF BRAKES AND/OR FLIGHT CONTROLS Cause — pilot/personnel action
- 64/A/82 A PILOT IN COMMAND FAILED TO INITIATE GO-AROUND Cause — pilot/personnel action
Decoded against the NTSB Form 6120.4 cause-factor codebook (ct_Pre1982 table). Each row shows the raw triplet, modifier (Cause / Factor / etc.), category, and specific code.
Source: NTSB pre-1982 historical archive. Docket
3 0732.
Source file
NTSB_1981_3_0732.txt.
Modern CAROL record 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. Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- arXiv 2026 · arXiv preprint
String stable platoons of all-electric aircraft with operating costs and airspace complexity trade-off
This paper formulates an optimal control framework for computing cruise airspeeds in predecessor-follower platoons of all-electric aircraft that balance operational cost and airspace complexity.
- arXiv 2026 · arXiv preprint
RotorSuite: A MATLAB/Simulink Toolbox for Tilt Multi-Rotor UAV Modeling
In recent years, aerial platforms have evolved from passive flying sensors into versatile, contact-aware robotic systems, leading to rapid advances in platform design.
- arXiv 2026 · arXiv preprint
Path Planning Optimisation for SParse, AwaRe and Cooperative Networked Aerial Robot Teams (SpArC-NARTs): Optimisation Tool and Ground Sensing Coverage Use Cases
A networked aerial robot team (NART) comprises a group of agents (e.g., unmanned aerial vehicles (UAVs), ground control stations, etc.) interconnected by wireless links.
- arXiv 2025 · arXiv preprint
UAV Marketplace Simulation Tool for BVLOS Operations
We present a simulation tool for evaluating team formation in autonomous multi-UAV (Unmanned Aerial Vehicle) missions that operate Beyond Visual Line of Sight (BVLOS).
- Embry-Riddle Scholarly Commons 2024 · Journal article (JAAER)
Development of a Safety Performance Decision-Making Tool for Flight Training Organizations
The purpose of the research was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, decision-making tool, specific to flight traini…
- Embry-Riddle Scholarly Commons 2024 · Journal article (JAAER)
Machine Learning - Hail Awareness Spatial Analysis Toolkit (HASAT)
The National Airspace System (NAS) is a sophisticated network of air traffic control, navigation, and communication systems that play a critical role in ensuring the safe and efficient flow of air tra…
Browse the full corpus — academia portal ↗