NTSB CAROL · Event
Event DEN00LA070
Aircraft involved
Probable cause & findings
On ground loss of control resulting in collision with airport markings due to inadequate compensation for wind conditions during landing roll. Factors were inaccurate in flight planning by landing with a tail wind component and lack of total pilot experience.
Factual narrative
On April 7, 2000, at 2130 mountain daylight time, a Cessna 172P, N65312, departed the side of the runway during landing roll at Loveland/Fort Collins Municipal Airport, Loveland, Colorado. The private pilot was not injured and the aircraft sustained substantial damage. Visual meteorological conditions prevailed for this personal flight being operated under Title 14 CFR Part 91 and no flight plan was filed. The flight originated from Limon, Colorado, at 2030. According to the pilot, he was conducting a practice ILS (instrument landing system) approach to a full stop landing. When the aircraft touched down, it immediately swerved to the right and departed the side of the runway. During this excursion, the aircraft struck runway lights and a runway/taxiway sign before the pilot brought it to a stop. The landing was being performed on runway 33 and the wind was from 180 degrees at 8 knots. Reported damage to the aircraft was to the right horizontal stabilizer, main landing gear, and a crack in the empennage. The pilot provided information that he had a total of 84 hours flight time, all of which was in the Cessna 172. He had 55 hours as pilot in command, 22 hours night experience, and 21 hours in the last 30 days before the accident. At the destination airport on a cross-country flight, the pilot was conducting a practice ILS approach to runway 33. The wind was from 180 degrees at 8 knots. Upon touch down, the aircraft swerved to the right, departed the side of the runway, and struck runway lights and a runway/taxiway sign. Damage was done to the right horizontal stabilizer, empennage, and main landing gear. The pilot had 84 hours total flight time and 55 hours as pilot in command. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_2000_DEN00LA070.txt.
Findings + structured fields enriched from FAA avall.mdb.
Full investigation docket on
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Related research
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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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