NTSB CAROL · Event
Event ANC10CA098
Registry · N180BS
FAA Aircraft Registry record.
Make / Model
CESSNA 180C
Year of manufacture
1959 · 51 years old at event
Engine
CONT MOTOR O-470 SERIES (230 hp)
Seats / Engines
4 seats · 1 engine
Last airworthiness date
19850523
ADS-B equipped
Yes — Mode-S A140D6
Registrant of record
SERIE DENNIS P
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
The pilot's failure to compensate for the gusting wind during takeoff, which resulted in a loss of control and impact with water.
Factual narrative
The floatplane was taking off from a seaplane base and encountered a gust of wind, which lifted the right wing. The pilot was unable to maintain control, and the airplane nosed over, sustaining substantial damage on impact with the water. About ten minutes prior to takeoff, recorded wind near the seaplane base was from 030 degrees at 24 knots gusting to 38 knots, with peak winds of 43 knots. The pilot indicated that there were no mechanical malfunctions with the airplane in reference to the accident flight. While on departure from a seaplane base, the airplane encountered a gust of wind. The right wing lifted and the pilot could not maintain control. The airplane nosed over, sustaining substantial damage upon impact with the water. A weather report indicated that, about 10 minutes prior to the accident, wind conditions were at 24 knots, gusting to 38 knots, and peaking at 43 knots. The pilot reported 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).
- C Personnel issues-Task performance-Use of equip/info-Aircraft control-Pilot - C
- — Environmental issues-Conditions/weather/phenomena-Wind-Gusts-Contributed to outcome
- C Aircraft-Aircraft oper/perf/capability-Performance/control parameters-(general)-Not attained/maintained - C
Verbatim from NTSB's published report. Source file
NTSB_2010_ANC10CA098.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 ↗