Advanced Aircraft Performance Modeling for ATM: Enhancements to the Bada Model

Nuić, Angela; Poinsot, C.; Iagaru, Mihai; Gallo, Eduardo; Navarro, Francisco; Querejeta, C.

doi:10.1109/dasc.2005.1563320

Cited by 59 publications

(47 citation statements)

References 1 publication

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“…We use the following general parameters for calculating the relevant altitude dependent quantities necessary for our governing equations of motion. We use the performance characteristics of the Boeing 777-300 for both our IM and target aircraft, as well as for the lift coefficient c l , which is a function of  [26].…”

Section: Simulation Parametersmentioning

confidence: 99%

Comparison of aircraft models and integration schemes for interval management in the tracon

Neogi

Hagen

Herencia-Zapana

2012

2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC)

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Reusable models of common elements for communication, computation, decision and control in air traffic management are necessary in order to enable simulation, analysis and assurance of emergent properties, such as safety and stability, for a given operational concept.Uncertainties due to faults, such as dropped messages, along with nonlinearities and sensor noise are an integral part of these models, and impact emergent system behavior. Flight control algorithms designed using a linearized version of the flight mechanics will exhibit error due to model uncertainty, and may not be stable outside a neighborhood of the given point of linearization. Moreover, the communication mechanism by which the sensed state of an aircraft is fed back to a flight control system (such as an ADS-B message) impacts the overall system behavior; both due to sensor noise as well as dropped messages (vacant samples). Additionally simulation of the flight controller system can exhibit further numerical instability, due to selection of the integration scheme and approximations made in the flight dynamics.We examine the theoretical and numerical stability of a speed controller under the Euler and Runge-Kutta schemes of integration, for the "Maintain" phase for a " Mid-Term (2035-2045 Interval Management (IM) Operational Concept" for descent and landing operations.We model uncertainties in communication due to missed ADS-B messages by vacant samples in the integration schemes, and compare the emergent behavior of the system, in terms of stability, via the boundedness of the final system state. Any bound on the errors incurred by these uncertainties will play an essential part in a composable assurance argument required for real-time, flight-deck guidance and control systems,. Thus, we believe that the creation of reusable models, which possess property guarantees, such as safety and stability, is an innovative and essential requirement to assessing the emergent properties of novel airspace concepts of operation.

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Section: Simulation Parametersmentioning

confidence: 99%

Comparison of aircraft models and integration schemes for interval management in the tracon

Neogi

Hagen

Herencia-Zapana

2012

2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC)

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“…It is based on mass-varying, kinetic approach that models an aircraft as a point and requires modeling of underlying forces that cause aircraft motion [6]. With the help of complex formulas aircraft performances are calculated from aircraft characteristics provided by manufacturers.…”

Section: Past Achievementsmentioning

confidence: 99%

Machine learning model for aircraft performances

Hrastovec¹,

Solina

2014

2014 IEEE/AIAA 33rd Digital Avionics Systems Conference (DASC)

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Abstract-Aircraft performances are a very important input for trajectory calculations. All known models distinguish performances mainly on aircraft type. We know there are many other factors influencing aircraft performances like operator, aerodrome, take-off weight, etc. We propose to build a machine learning model that would predict aircraft performances based on all known attributes about the flight. The model learns from real flights in the past and makes predictions based on accumulated knowledge. For instance: A full flight to a distant holiday destination has different performances than a short regular flight with the same aircraft. Our model would recognize the difference in that case and predict aircraft performances best suited for each flight. aircraft performances; machine learning; data mining

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“…For this experiment, the aircraft dynamics were again based on a BADA Boeing 747-200 model. 23,24 One of the characteristics of this model is that idle thrust is assumed to be 0% of the maximum thrust. All approaches are flown in International Standard Atmosphere (ISA) conditions and wind conditions were absent during the whole experiment.…”

Section: Vb3 Simulation Environmentmentioning

confidence: 99%

“…The performance model which SAMI used for this research was a Base of Aircraft Data (BADA) Boeing 747-200 model. 23,24 A possible output of SAMI is the descent rate of a constant-CAS profile. This can then be used to determine the flight-path angle for this constant-CAS profile.…”

Section: Ivd Algorithmmentioning

confidence: 99%

Continuous Descent Approaches with Variable Flight-Path Angles under Time Constraints

Sopjes

Jong

Borst

et al. 2011

AIAA Guidance, Navigation, and Control Conference

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In order to reduce noise nuisance around Schiphol Airport, a Continuous Descent Approach procedure was introduced in the late '90s. Unfortunately, because unpredictable individual aircraft behavior lead to increased landing intervals for this procedure, it is currently only applied during night time operations. Time-of-Arrival control in the terminal area could reduce the landing interval for this procedure. The research presented in this paper investigates the influence of multiple segments with different flight-path angles on the time of arrival. A new procedure with Variable Flight-path angle (VFA) involving active planning of the approach from the pilot through a pilot support interface, presented in the Vertical Situation Display. A preliminary pilotin-the-loop evaluation was conducted, to investigate pilot performance, workload and interface usability. Three scenarios were tested, all with different Required Time of Arrival. Workload was low for all scenarios and performance good for the two scenarios with early arrival times. For the scenario with a late arrival time, performance was mediocre. Changes in representation of the flap and gear cues and the addition of Estimated Time of Arrival information might improve the performance.

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Advanced Aircraft Performance Modeling for ATM: Enhancements to the Bada Model

Cited by 59 publications

References 1 publication

Comparison of aircraft models and integration schemes for interval management in the tracon

Comparison of aircraft models and integration schemes for interval management in the tracon

Machine learning model for aircraft performances

Continuous Descent Approaches with Variable Flight-Path Angles under Time Constraints

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