Monitoring Grass Airfield Conditions for the GARFIELD System

Pytka, Jarosław; Lyszczyk, Tomasz; Gnapowski, Ernest

doi:10.1109/metroaerospace.2018.8453558

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…Results obtained in the field experiments include courses of wheel forces and moments acting on the left wheel of the Wilga airplane, and we collected data from four days of measurements: 17 October, 5 November, and 5 December 2018, as well as 13 March 2019. The following is a presentation and analysis of the results obtained in the autumn-winter part of the measurements campaign (a so-called "dead season" in sport aviation) that was performed as a full-season measurement for the verification of the wheel-turf interaction model of the GARFIELD information system [1,2,23,24]. Figure 9 shows time courses of the vertical F Z and horizontal F X forces that act on the landing gear wheel.…”

Section: Resultsmentioning

confidence: 99%

“…(1) Figure 11 shows an example of horizontal force, FX, which is input data for calculations (upper graph) and the rolling resistance coefficient, kRR (lower graph), value determined using Equation (1). Average values are marked on the graphs (FX = 1719 N and kRR = 0.275).…”

Section: Rolling Resistance Coefficientmentioning

confidence: 99%

“…The rolling resistance coefficient, k RR , is defined as the ratio of horizontal force during free turning to vertical force [25]: Figure 11 shows an example of horizontal force, F X , which is input data for calculations (upper graph) and the rolling resistance coefficient, k RR (lower graph), value determined using Equation (1). Average values are marked on the graphs (F X = 1719 N and k RR = 0.275).…”

Section: Rolling Resistance Coefficientmentioning

confidence: 99%

“…One method is to monitor surface mechanical data, related to weather conditions. The GARFIELD information system [1] is based on a wheel-grass model that includes analysis of wheel-soil (wheel-grassy surface) interactions considering soil modeling with a special caution to loads by aircraft tires [2]. The model will respect non-linear, dynamic effects such as hyper-elastic tire deflection, rheological soil response to high rate deformation, and effects of grass and roots.…”

Section: Introductionmentioning

confidence: 99%

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Determining Wheel Forces and Moments on Aircraft Landing Gear with a Dynamometer Sensor

Pytka

Budzyński

Lyszczyk

et al. 2019

Sensors

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This paper describes airfield measurement of forces and moments that act on a landing gear wheel. For the measurement, a wheel force sensor was used. The sensor was designed and built based on strain gage technology and was embedded in the left landing gear wheel of a test aircraft. The sensor is capable of measuring simultaneously three perpendicular forces and three moments and sends data to a handheld device wirelessly. For the airfield tests, the sensor was installed on a PZL 104 Wilga 35A multipurpose aircraft. The aircraft was towed at a “marching man” speed and the measurements were performed at three driving modes: Free rolling, braking, and turning. The paper contains results obtained in the field measurements performed on a grassy runway of the Rzeszów Jasionka Aerodrome, Poland. Rolling resistance of aircraft tire, braking friction, as well as aligning moment were analyzed and discussed with respect to surface conditions.

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Section: Resultsmentioning

confidence: 99%

Section: Rolling Resistance Coefficientmentioning

confidence: 99%

Section: Rolling Resistance Coefficientmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determining Wheel Forces and Moments on Aircraft Landing Gear with a Dynamometer Sensor

Pytka

Budzyński

Lyszczyk

et al. 2019

Sensors

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“…Incidents and accidents during takeoff or landing are reported in piloting or aviation magazines quite frequently [18,19,20,21,22,23]. Therefore, future research will focus on the research and development of the described field sensor and applications in the GARFIELD online information system, that is being developed by the authors [24,25].…”

Section: Resultsmentioning

confidence: 99%

Application of the TDR Soil Moisture Sensor for Terramechanical Research

Pytka

Budzyński

Kamiński

et al. 2019

Sensors

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This paper presents examples of the application of the TDR (Time-Domain Reflectometry) sensor in terramechanical research. Examples include the determination of soil moisture content during off-road vehicle mobility tests, the determination of snow density before and after the wheeling of a snow grooming machine and an airplane, as well as the monitoring of turf moisture on a grassy airfield for the analysis and prediction of safe and efficient flight operations (takeoff and landing). A handheld TDR meter was used in these experiments. Soil moisture data were correlated with the vehicle mobility index and a simple model for this correlation was derived. Using grassy airfield research, soil moisture data were related to meteorological impacts (precipitation, sunlight, etc.). Generally, it was concluded that the TDR meter, in its handheld version, was a useful tool in the performed research, but a field sensor that operates autonomically would be an optimal solution for the subject applications.

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