SUPRA - Enhanced Upset Recovery Simulation

Groen, Eric L.; Ledegang, W.D.; Field, Joris; Smaili, Hafid; Roza, Manfred; Fucke, Lars; Nooij, Sae; Goman, Mikhail; Mayrhofer, Michael; Zaichik, Larisa; GRIGORYEV, M.N.; Biryukov, Vladimir

doi:10.2514/6.2012-4630

Cited by 17 publications

(9 citation statements)

References 3 publications

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“…The envelope still shows the steepest climb by a green dot 5 , and the corresponding velocity is indicated in green on the velocity strip 6 . The red bars for stall and maximum speeds 7 are made dynamic to reflect speed limits for the current configuration.…”

Section: B Integration With Vsd Designmentioning

confidence: 96%

“…Research and industry are taking action at large to improve pilot training for LOC scenarios, such as the Manual on Aeroplane Upset Prevention and Recovery Training by the FAA, the project to create extended aircraft simulation envelopes by SUPRA, and over 130 companies offering upset prevention and recovery training worldwide [5][6][7]. These organizations agree that more focus should be placed on training pilots for situation awareness and manual skills in preventing upsets.…”

Section: Introductionmentioning

confidence: 99%

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Design and Evaluation of Vertical Situation Display Reflecting Configuration Changes

Geel

Borst

Paassen

2020

AIAA Scitech 2020 Forum

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Loss of control is the largest contributor to the yearly aviation death toll, with energy mismanagement in low-energy conditions as one of its main causal factors. This has led to a large emphasis from both scientific and aviation safety communities on the prevention of aircraft upset conditions. Changes in aircraft configuration largely impact performance, and improved insight therein should allow pilots to better predict potentially dangerous situations, maintain suitable safety margins and more effectively react to unforeseen events. This paper presents the design and experimental evaluation of a Vertical Situation Display (VSD) with enhancements visualizing changes in the flight performance envelope. Sixteen pilots were tasked to fly approach and go-around scenarios with both a baseline and an ecological VSD, some of the scenarios containing flight control failures. Results show that the new display makes pilots maintain larger margins in velocity, thus spending less time below the advised minimum speed limit in final approach. However, these larger velocity margins also led to larger errors with respect to target velocities. Flight control failures were more often and more quickly discovered, and pilots reported feeling better able to predict dangerous situations. No significant differences in workload were recorded. These results conclude that the new VSD design enhances safety performance, but simultaneously raise the question whether the effect of enlarged safety margins is desirable if it causes a reduction in velocity tracking.

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Section: B Integration With Vsd Designmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Vertical Situation Display Reflecting Configuration Changes

Geel

Borst

Paassen

2020

AIAA Scitech 2020 Forum

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“…At present, research is being conducted into the improvement of commercial transport aircraft flight modeling and control through the NASA Aviation Safety and Security Program (AvSSP) [7][8][9][10][11] and the European Union Simulation and Upset Recovery in Aviation project. [12][13][14][15][16] The importance attached to commercial transport aircraft is understandable given that passenger safety is of the utmost importance to the transportation industry. However, according to the Aircraft Owners and Pilots Association Air Safety Institute 2010 Nall Report, 17 for fixed wing aircraft over the past decade, the average accident rate was 67% higher for non-commercial flights and the rate of fatal accidents was 120% higher in comparison with commercial flights.…”

Section: Introductionmentioning

confidence: 99%

Stall/Post-Stall Modeling of the Longitudinal Characteristics of a General Aviation Aircraft

Ananda

Selig

2016

AIAA Atmospheric Flight Mechanics Conference

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The high rate of accidents in general aviation due to pilot loss of control has necessitated the need to find better methods of training pilots. Pilot control and awareness in the stall/post-stall regime can be improved through the use of higher fidelity flight simulators. To create a high fidelity aerodynamic model in the stall/post-stall regime to be implemented in a flight simulator, both steady and unsteady aircraft characteristics need to be represented. In this paper, the detailed development of a steady-state general aviation aircraft stall/post-stall longitudinal aerodynamic model is described. The steady-state model uses a component buildup approach that uses strip theory to output the aerodynamic forces and moments of an aircraft. An integrated non-linear lifting-line theory approach is used to model the wing and horizontal tail. Longitudinal effects due to elevator deflections are also included. Validation studies are performed against static wind tunnel datasets for a typical single-engine low-wing general aviation aircraft design. Nomenclatureairfoil moment coefficient at quarter chord C M c/4 = surface moment coefficient at quarter chord (= M/ 1 2 ρV 2 ∞ S ref c) C N = surface normal force coefficient (= N/ 1 2 ρV 2 ∞ S ref ) C n = local normal-force coefficient per unit length * Graduate Student (Ph.D. Candidate), 104 S. Wright St., AIAA Student Member. anandak1@illinois.edu † Professor, 104 S. Wright St., AIAA Associate Fellow. m-selig@illinois.edu 1 of 25 American Institute of Aeronautics and Astronautics Downloaded by PURDUE UNIVERSITY on June 22, 2016 | http://arc.aiaa.org | AIAA Aviation d F = fuselage cross-section diameter D = drag D ind = induced drag k = corner radius l ref = reference length l F = fuselage length L = lift M = moment n P = number of lifting surface panels N = normal force r F = fuselage cross-section radius Re = Reynolds number based on mean aerodynamic chord (= V ∞ c/ν) S = lifting surface area S f = flap area S ref = reference area V ∞ = freestream velocity V F = fuselage volume w ind = velocity induced by shed vortices V rel = relative velocity w F = fuselage width x F = axial distance from fuselage nose x ac F = distance from nose to aerodynamic center of fuselage x c F = distance from nose to centroid of fuselage planform area x m F = distance from nose to centroid of fuselage pitching-moment reference center x P S , y P S , z P S = location of spanwise panel station points x LLT , y LLT , z LLT = location of lifting-line points Y = side force α ef f = effective angle of attack α geo = geometric angle of attack α ind = induced angle of attack β = sideslip angle δ f = flap deflection angle η = flap effectiveness correction factor η f use = fuselage crossflow drag proportionality factor Γ = circulation Γ 0 = circulation at center-span Γ LLT = circulation at the lifting-line points Γ SV = shed vortex circulation τ = flap effectiveness factor θ f = factor relating flap to chord ratio to flap effectiveness factor ν = kinematic viscosity ρ = density of air Subscripts c/4 = ...

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“…For example, a recent European effort into stall modeling has been performed in the SUPRA project. 14 During this project a stall model for a generic transport aircraft, low-wing configuration and engines positioned under the wings, was created based on wind tunnel and computational fluid dynamics (CFD) data. 15,16 NASA has pursued the development of a large transport aircraft model for upset conditions, which was created using wind tunnel data and validated with flight data.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Stall and Buffet Modeling for the Cessna Citation II Based on Flight Test Data

Horssen

Visser

Pool

2018

2018 AIAA Modeling and Simulation Technologies Conference

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To meet the required flight simulator-based stall recovery training that will become mandatory for all aircarrier pilots in 2019, many flight simulators will need to be updated with accurate flight models at high anglesof-attack. Using a database of 69 symmetrical and quasi-steady recorded stalls performed with TU Delft's Cessna Citation II laboratory aircraft, this paper aims to show to what extent relevant stall characteristics can still be modeled using flight test data from such "natural" stall flight test data (i.e., without additional flight test inputs). For modeling the (low-frequency) changes to the aerodynamic characteristics, the well-known stall model structure based on Kirchoff's flow separation theory is used. This aerodynamic stall model is augmented with a high-frequency stall buffet model identified based on power spectral density analysis of the flight test linear acceleration data. The stall model identification results obtained from a proposed methodology in which the aerodynamic and buffet model parameters were deliberately jointly estimated shows that the dynamic parameters capturing the stall hysteresis effect can indeed be estimated using quasi-steady stall maneuvers. Aerodynamic terms related to the pitch rate, however, are difficult to estimate for such quasi-steady maneuvers, given the correlation between pitch rate and angle-of-attack. It was found that estimating stall transient effects (i.e., hysteresis time constants), which normally require highly dynamic flight test maneuvers, was found to be improved with with explicit use of the measured accelerations caused by the stall buffet in the identification methodology.

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SUPRA - Enhanced Upset Recovery Simulation

Cited by 17 publications

References 3 publications

Design and Evaluation of Vertical Situation Display Reflecting Configuration Changes

Design and Evaluation of Vertical Situation Display Reflecting Configuration Changes

Stall/Post-Stall Modeling of the Longitudinal Characteristics of a General Aviation Aircraft

Aerodynamic Stall and Buffet Modeling for the Cessna Citation II Based on Flight Test Data

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