NTSB CAROL · Event
Event DCA91MA033
Registry · N270AS
FAA Aircraft Registry record.
Make / Model
SCHLEICHER ASW-27
Engine
NONE NONE
Seats / Engines
1 seats · 1 engine
Last airworthiness date
20010524
ADS-B equipped
Yes — Mode-S A2A68D
Registrant of record
WECK GEOFFREY E
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
THE LOSS OF CONTROL IN FLIGHT AS A RESULT OF A MALFUNCTION OF THE LEFT ENGINE PROPELLER CONTROL UNIT WHICH ALLOWED THE PROPELLER BLADE ANGLES TO GO BELOW THE FLIGHT IDLE POSITION. CONTRIBUTING TO THE ACCIDENT WAS THE DEFICIENT DESIGN OF THE PROPELLER CONTROL UNIT BY HAMILTON STANDARD AND THE APPROVAL OF THE DESIGN BY THE FEDERAL AVIATION ADMINISTRATION. THE DESIGN DID NOT CORRECTLY EVALUATE THE FAILURE MODE THAT OCCURRED DURING THIS FLIGHT, WHICH RESULTED IN AN UNCOMMANDED AND UNCORRECTABLE MOVEMENT OF THE BLADES OF THE AIRPLANE'S LEFT PROPELLER BELOW THE FLIGHT IDLE POSITION. (NTSB REPORT AAR-92/03)
Factual narrative
WITNESSES REPORTED THAT THE AIRPLANE SUDDENLY TURNED OR ROLLED LEFT UNTIL THE WINGS WERE PERPENDICULAR TO THE GROUND. THE AIRPLANE THEN FELL IN A NOSE-DOWN ATTITUDE. EXAM OF THE LEFT PROP COMPONENTS INDICATED A BLADE ANGLE OF ABOUT 3 DEG, WHILE THE LEFT PROP CONTROL UNIT (PCU) BALLSCREW POSITION WAS CONSISTENT WITH A COMMANDED BLADE ANGLE OF 79.2 DEG. EXTREME WEAR ON THE PCU QUILL SPLINE TEETH, WHICH NORMALLY ENGAGED THE TITANIUM-NITRIDED SPLINES OF THE PROP TRANSFER TUBE, WAS FOUND. THE TITANIUM-NITRIDED SURFACE WAS MUCH HARDER AND ROUGHER THAN THE NITRIDED SURFACE OF THE QUILL. THEREFORE, THE TRANSFER TUBE SPLINES ACTED LIKE A FILE AND CAUSED ABNORMAL WEAR OF THE GEAR TEETH ON THE QUILL. WEAR OF THE QUILL WAS NOT CONSIDERED DURING THE CERTIFICATION OF THE PROPELLER SYSTEM. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_1991_DCA91MA033.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.
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