Investigations of Modifications to Improve the Spin Resistance of a High-Wing, Single-Engine, Light Airplane

Manuel, Gregory S.; Dicarlo, D. J.; Stough, H. Paul; Brown, P. W.; Stuever, Robert A.

doi:10.4271/891039

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…For the past 50 years, airworthiness standards have required aircraft to comply with certain stall/spin resistance or recovery criteria, and major research efforts have been devoted to understanding and improving aircraft spin resistance and recovery from fully developed spins. [5][6][7][8][9][10][11] Combined with pilot stall/spin awareness training, this work has helped reduce the accident rates due to stall/spin significantly. 12 However, stall-related accidents remain a major cause or co-factor for accidents, 13 calling for renewed and innovative efforts.…”

Section: B Background and Previous Workmentioning

confidence: 99%

Approaches to Automatic Stall/Spin Detection Based on Small-Scale UAV Flight Testing

Bunge

Savino

Kroo

2015

AIAA Atmospheric Flight Mechanics Conference

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This paper describes concepts for automatic stall/spin detection using in-flight measurements of air data and inertial parameters. Several approaches are investigated, requiring simple computations from sensed quantities, easily implementable on modern flight systems. The performance of alternative schemes are tested and compared on subscale spin flight data obtained from two different unmanned testbeds, as well as on previouslypublished spin flight data from a full-scale general aviation aircraft. The algorithms reliably detect spins early in their development, within a fraction of the first turn. This early detection could be used to trigger a pilot alarm or engage an automatic spin recovery controller, with potential to significantly reduce altitude loss, and the risk of ground collision. More testing on subscale and full-scale flight data will be done to further evaluate the performance of the detection schemes.

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Section: B Background and Previous Workmentioning

confidence: 99%

Approaches to Automatic Stall/Spin Detection Based on Small-Scale UAV Flight Testing

Bunge

Savino

Kroo

2015

AIAA Atmospheric Flight Mechanics Conference

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“…Thus, from a practical standpoint, most advances have come from experimental testing, especially free flight tests. [3][4][5][6] Historically, due to the size and weight of the flight data systems and scaling and operational challenges of subscale testing, many of these were pursued on manned aircraft with a high cost per flight test. Although a vast number of spins were done, they were still limited to a handful of aircraft geometries and test parameters.…”

Section: Introductionmentioning

confidence: 99%

Stall/Spin Flight Test Techniques with COTS Model Aircraft and Flight Data Systems

Bunge

Savino

Kroo

2015

AIAA Flight Testing Conference

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This paper presents methodologies and techniques for stall/spin flight testing using commercially off-the-shelf model aircraft and flight data systems. Flight test procedures allowing systematic and efficient testing are outlined, as well as piloting techniques to obtain quality spin flight data. Two spin flight test campaigns with different testbeds are described, including the aircraft, flight data system and ground station setups. Flight test data for the two testbeds are presented and the incipient, developed and recovery characteristics are analyzed. The spin data is consistent across spin maneuvers for a given aircraft, and also similar between aircrafts of different scale, showing the accuracy of the flight test methodology and instrumentation. Nomenclature bwing span CG center of gravity V airspeed at the center of gravity V stallStall speed Re stall Reynolds number at stall p, q, r roll, pitch and yaw rates Ω spin rate, Ω (p 2 + q 2 + r 2 ) 1/2

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Optimal Stall Recovery via Deep Reinforcement Learning for a General Aviation Aircraft

Grillo,

Torre,

Bunge

2024

AIAA SCITECH 2024 Forum

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Investigations of Modifications to Improve the Spin Resistance of a High-Wing, Single-Engine, Light Airplane

Cited by 4 publications

References 4 publications

Approaches to Automatic Stall/Spin Detection Based on Small-Scale UAV Flight Testing

Approaches to Automatic Stall/Spin Detection Based on Small-Scale UAV Flight Testing

Stall/Spin Flight Test Techniques with COTS Model Aircraft and Flight Data Systems

Optimal Stall Recovery via Deep Reinforcement Learning for a General Aviation Aircraft

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