NTSB CAROL · Event
Event WPR18LA109
Registry · N1762C
FAA Aircraft Registry record.
Make / Model
LYONS ROBERT NAVAJO HKS
Year of manufacture
2007 · 11 years old at event
Engine
HKS 700E (60 hp)
Seats / Engines
2 seats · 1 engine
Last airworthiness date
20091222
ADS-B equipped
Yes — Mode-S A13218
Registrant of record
FELTY WESLEY R
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
The pilot's loss of directional control during landing. Contributing to the accident was the pilot's failure to attain a proper touchdown point, which required his use of heavy braking to stop on the remaining runway and exacerbated the uneven braking effectiveness of the main wheels.
Factual narrative
On March 11, 2018, about 1545 Pacific daylight time, an experimental Navajo HKS weight-shift-control aircraft, N1762C, was substantially damaged when it was involved in an accident near Arlington, Washington. The sport pilot sustained minor injuries. The aircraft was operated as a Title 14 Code of Federal Regulations Part 91 personal flight. The pilot reported that he was landing when, shortly after the aircraft touched down on the main landing gear, he lowered the nose wheel and applied the brakes. The aircraft skidded to the right and came to rest on its right side opposite the direction of landing. An onboard camera revealed that the aircraft touched down left of the runway centerline about 2,800 ft along the 3,431-ft-long runway; shortly thereafter, it veered to the right and nosed over on the right side of the runway, resulting in substantial damage to the wing and its supporting structure. (see Figure 1.) Figure 1. Google earth view of the accident site The ground steering system comprised a left and right foot peg attached to each side of the nose landing gear strut. Both left and right main landing gear were equipped with hydraulic disc brakes, which operated simultaneously by means of a foot-controlled lever located above the left foot steering peg. The pilot performed an examination of the brakes after the accident and reported that the right wheel brake "had more stopping power" than the left wheel brake. He also stated that his long landing resulted in his application of heavier braking than usual. The pilot was landing the weight-shift-control aircraft. Onboard video indicated that the aircraft was about 100 ft above ground level as it passed the runway midpoint and subsequently touched down with about 630 ft of runway remaining. The aircraft landed on the left side of the runway centerline then veered to the right and nosed over on the right side of the runway. The aircraft was equipped with two hydraulic disc brakes located on each of the main landing gear, which activated simultaneously by means of a foot pedal. The pilot performed an examination of the brakes after the accident and reported that the right wheel brake "had more stopping power" than the left wheel brake and attributed the loss of control to the braking power discrepancy between the two main wheels. He also stated that his long landing resulted in his application of heavier braking than usual. It is likely that the pilot's decision to continue the approach and landing despite the short runway distance remaining, and his subsequent use of heavy braking to stop on the available runway exacerbated the uneven braking effectiveness and contributed to the loss of control. Source: NTSB Aviation Accident Database Retrieved: 2026-02-12
NTSB Findings
Hierarchical cause / factor breakdown from the FAA bulk avdata database. Each finding tagged C (Cause) or F (Factor).
- C Personnel issues-Task performance-Use of equip/info-Aircraft control-Pilot
- F Personnel issues-Action/decision-Info processing/decision-Decision making/judgment-Pilot
- — Aircraft-Aircraft oper/perf/capability-Performance/control parameters-Directional control-Not attained/maintained
- — Aircraft-Aircraft systems-Landing gear system-Brake-Unnecessary use/operation
Verbatim from NTSB's published report. Source file
NTSB_2018_WPR18LA109.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.
Browse the full corpus — academia portal ↗