NTSB CAROL · Event
Event DEN02LA014
Registry · N73892
FAA Aircraft Registry record.
Make / Model
CESSNA 172N
Seats / Engines
4 seats · 1 engine
ADS-B equipped
Yes — Mode-S A9EC71
Registrant of record
DELONG ERIKA DEE
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
the pilot's failure to maintain directional control of the airplane while landing. A contributing factor was the crosswind.
Factual narrative
On December 13, 2001, approximately 1255 mountain standard time, a Cessna 172N, N73892, operated by McAir Aviation, was substantially damaged when it impacted terrain following a loss of control during landing at Jeffco Airport, Broomfield, Colorado. The private pilot, the sole occupant aboard, was not injured. Visual meteorological conditions prevailed, and no flight plan had been filed for the personal flight being conducted under Title 14 CFR Part 91. The flight originated at Broomfield approximately 1230. According to the pilot, he was making his third practice touch-and-go landing on runway 29R. While on final approach, the wind velocity increased and he maintained "a little power." The indicated airspeed was 65 knots as he flared for landing. The airplane "dropped in" and bounced. He added full power in an attempt to reject the landing, but the airplane departed the left side of the runway, struck two runway signs, and skidded to a halt. Postaccident examination disclosed that both the left main and nose landing gears were torn off and the fuselage was buckled. Recorded wind was from 270 degrees at 13 knots. The pilot was making his third practice touch-and-go landing on runway 29R. While on final approach, the wind velocity increased, and he maintained "a little power." The indicated airspeed was 65 knots as he flared for landing. The airplane "dropped in" and bounced. He added full power in an attempt to reject the landing, but the airplane departed the left side of the runway, struck two runway signs, and skidded to a halt. Recorded wind was from 270 degrees at 13 knots. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_2001_DEN02LA014.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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