NTSB CAROL · Event
Event ANC21LA086
Registry · N6476M
FAA Aircraft Registry record.
Make / Model
STINSON 108-3
Year of manufacture
1948 · 73 years old at event
Engine
FRANKLIN 6A4165 SERIES (165 hp)
Seats / Engines
4 seats · 1 engine
Last airworthiness date
19580709
ADS-B equipped
Yes — Mode-S A88272
Registrant of record
SAFECO LEASING LLC
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
A loss of directional control for reasons that could not be determined based on the available information.
Factual narrative
On September 12, 2021, about 0900 Alaska daylight time, a Stinson 108-3, N6476M, was substantially damaged when it was involved in an accident near Port Alsworth, Alaska. The pilot was not injured. The airplane was operated as a Title 14 Code of Federal Regulations Part 91 personal flight. The pilot reported that, during the landing roll while applying the brakes, the right brake “went flat.” The airplane veered to the left, impacted a stump, and nosed over, resulting in substantial damage to the fuselage and left wing. A postaccident examination revealed no mechanical anomalies with the brake system that would have precluded normal operation. The pilot reported that, during the landing roll while applying the brakes, the right brake “went flat.” The airplane veered to the left, impacted a stump, and nosed over, resulting in substantial damage to the fuselage and left wing. A postaccident examination revealed no mechanical anomalies with the brake system that would have precluded normal operation. Based on the available information, the reason for the loss of control during landing could not be determined. 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 systems-Landing gear system-Brake-Failure
Verbatim from NTSB's published report. Source file
NTSB_2021_ANC21LA086.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 ↗