NYC00LA181
2000-07-03 · BEVERLY, Massachusetts, United States · None · 1 aircraft · Status: Completed
Airport BVY
Aircraft involved
Probable cause & findings
The pilot's improper flare, which resulted in a loss of control.
Factual narrative
On July 3, 2000, at 0853 Eastern Daylight Time, a Cessna 152, N48858, was substantially damaged while landing at Beverly Municipal Airport (BVY), Beverly, Massachusetts. The certificated private pilot was not injured. Visual meteorological conditions prevailed, and no flight plan was filed for the local personal flight conducted under 14 CFR Part 91. According to the pilot's written statement, he departed BVY about 0800, and performed a series of touch-and-go(s). While on final approach to his last landing, he was worried about landing on the touchdown zone, and exiting the runway at taxiway "charlie". The nosewheel struck the ground first, and the airplane bounced twice. The nosewheel then collapsed, and the airplane veered off to the left side of the runway. It came to rest in the grass adjacent to the runway. The pilot reported a total flight experience of approximately 126 hours. Of his total experience, approximately 18 hours were as pilot in command; of which, 16 hours were pilot in command of the make and model accident airplane. He had flown approximately 3 hours within the 90 day period preceding the accident. Examination of the wreckage by a Federal Aviation Administration inspector revealed substantial damage to the nose gear and firewall. The inspector did not find any pre-impact mechanical malfunctions, nor did the pilot report any. The pilot stated that he was concerned about landing on the touchdown zone, to exit at a particular taxiway. The nosewheel struck the ground first, and the airplane bounced twice. The nosewheel then collapsed, and the airplane veered off the left side of the runway. The pilot reported approximately 18 hours of total pilot in command experience; of which, approximately 16 hours were in the make and model airplane. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_2000_NYC00LA181.txt.
Findings + structured fields enriched from FAA avall.mdb.
Full investigation docket on
data.ntsb.gov ↗.
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Related research
Matched on aircraft type or causal vocabulary (loss of control). All research papers
- 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.
- Semantic Scholar 2024 · Article (International Conference on Networking and Services) Risk Assessment of Loss of Control In-Flight Trajectories for Urban Air Mobility Safety
In Urban Air Mobility (UAM), maintaining a minimum separation between aircraft is a safety requirement, which becomes challenging amidst congested air traffic and off-nominal conditions, such as Loss …
- 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.