CHI97LA242
1997-07-30 · LONE ROCK, Wisconsin, United States · None · 1 aircraft · Status: Completed
Airport LNR
Current FAA registration · N75939
- Make / Model
- BOEING B75N1
- Engine
- P&W R-985 SERIES (450 hp)
- Seats / Engines
- 2 seats · 1 engine
- Last airworthiness date
- 20040908
- ADS-B equipped
- Yes — Mode-S AA3E5B
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
a locked right brake which resulted in the pilot's inability to maintain direction control of the airplane during the landing roll.
Factual narrative
On July 30, 1997, at 1600 central daylight time (cdt), a Boeing B75N1, N75939, operated by a commercial pilot collided with the terrain following a loss of control while landing at the Tri- County Regional Airport, Lone Rock, Wisconsin. The airplane was substantially damaged. The pilot was not injured. Visual meteorological conditions prevailed and it is unknown if a flight plan was filed. The airplane departed from Norman, Oklahoma, at 0630 cdt. The pilot reported that during the landing roll the airplane veered "uncontrollably" to the right. During the turn the left wing contacted the ground. The airplane continued the turn until it came to rest on its nose, 180 degrees opposite the landing direction. Post accident inspection of the airplane by a Federal Aviation Administration Airworthiness Inspector revealed the crankcase breather tube was routed down the right main landing gear strut thus allowing oil residue to contaminate the right brake. The pilot reported the airplane veered 'uncontrollably' to the right during the landing roll. The left wing contacted the ground and the airplane continued the turn until coming to rest on its nose 180 degrees opposite the direction of landing. Post accident inspection of the airplane revealed the crankcase breather tube was routed down the right main landing gear strut allowing oil residue to contaminate the brake system. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_1997_CHI97LA242.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.