Spatio-Temporally Correlated Wind Uncertainty Model for Simulation of Terminal Airspace Operations

Tandale, Monish; Vaddi, Sai; Lin, Sydney; Sengupta, Prasenjit

doi:10.2514/6.2013-4404

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…WPT number (position along the orthodromic route grid axis) orders of magnitude better than the precision of the GRIB forecast data issued by the environment agencies. [23][24][25][26] The results are practically identical. A final evaluation was conducted in order to compare the difference in computation times for flight profile calculations.…”

Section: Gridmentioning

confidence: 89%

“…Different authors evaluated the incertitude associated with the atmosphere data prediction. Tandale et al 24 present a method to create an uncertainty model for the wind forecasts based on the difference between the forecast data and the real wind encountered by aircrafts, retrieved from ACARS data. The model has realistic spatio-temporal correlations and can be used in stochastic analysis of flight trajectories, to generate random wind predictions for Monte Carlo simulations.…”

Section: Introductionmentioning

confidence: 99%

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New atmospheric data model for constant altitude accelerated flight performance prediction calculations and flight trajectory optimization algorithms

Dancila

Botez

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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This article presents a new method for storing and computing the atmospheric data used in time-critical flight trajectory performance prediction calculations, such as flight performance prediction calculations in flight management systems and/or flight trajectory optimization, of constant altitude cruise segments. The proposed model is constructed based on the forecast data provided by Meteorological Service Agencies, in a GRIB2 data file format, and the set of waypoints that define the lateral component of the evaluated flight profile(s). The atmospheric data model can be constructed/updated in the background or off-line, when new atmospheric prediction data are available, and subsequently used in the flight performance computations. The results obtained using the proposed model show that, on average, the atmospheric parameter values are computed six times faster than through 4D linear interpolations, while yielding identical results (value differences of the order of 10e−14). When used in flight trajectory performance calculations, the obtained results show that the proposed model conducts to significant computation time improvements. The proposed model can be extended to define the atmospheric data for a set of cruise levels (usually multiple of 1000 ft).

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Section: Gridmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

New atmospheric data model for constant altitude accelerated flight performance prediction calculations and flight trajectory optimization algorithms

Dancila

Botez

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…The magnitudes of the prediction errors vary as a function of the forecast type (global or regional) and resolution (forecast grid size), the time of year, the time of day (day or night), region, how far ahead in time the prediction is made, etc. (27,(47)(48)(49)(50) .…”

Section: Atmospheric Datamentioning

confidence: 99%

New flight trajectory optimisation method using genetic algorithms

Dancila

Botez

2021

Aeronaut. j.

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This paper presents a new flight trajectory optimisation method, based on genetic algorithms, where the selected optimisation criterion is the minimisation of the total cost. The candidate flight trajectories evaluated in the optimisation process are defined as flight plans with two components: a lateral flight plan (the set of geographic points that define the flight trajectory track segments) and a vertical flight plan (the set of data that define the altitude and speed profiles, as well as the points where the altitude and/or speed changes occur). The lateral components of the candidate flight plans are constructed by selecting a set of adjacent nodes from a routing grid. The routing grid nodes are generated based on the orthodromic route between the flight trajectory’s initial and final points, a selected maximum lateral deviation from the orthodromic route and a selected grid node step size along and across the orthodromic route. Two strategies are investigated to handle invalid flight plans (relative to the aircraft’s flight envelope) and to compute their flight performance parameters. A first strategy is to assign a large penalty total cost to invalid flight profiles. The second strategy is to adjust the invalid flight plan parameters (altitude and/or speed) to the nearest limit of the flight envelope, with priority being given to maintaining the planned altitude. The tests performed in this study show that the second strategy is computationally expensive (requiring more than twice the execution time relative to the first strategy) and yields less optimal solutions. The performance of the optimal profiles identified by the proposed optimisation method, using the two strategies regarding invalid flight profile performance evaluation, were compared with the performance data of a reference flight profile, using identical input data: initial aircraft weight, initial and final aircraft geographic positions, altitudes and speed, cost index, and atmospheric data. The initial and final aircraft geographic positions, and the reference flight profile data, were retrieved from the FlightAware web site. This data corresponds to a real flight performed with the aircraft model used in this study. Tests were performed for six Cost Index values. Given the randomness of the genetic algorithms, the convergence to a global optimal solution is not guaranteed (the solution may be non-optimal or a local optima). For a better evaluation of the performance of the proposed method, ten test runs were performed for each Cost Index value. The total cost reduction for the optimal flight plans obtained using the proposed method, relative to the reference flight plan, was between 0.822% and 3.042% for the cases when the invalid flight profiles were corrected, and between 1.598% and 3.97% for the cases where the invalid profiles were assigned a penalty total cost.

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Research on modelling and database construction of supporting magnetic variation data and atmospheric data for flight management system simulation

Yang

Cheng

et al. 2017

2017 IEEE International Conference on Information and Automation (ICIA)

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Spatio-Temporally Correlated Wind Uncertainty Model for Simulation of Terminal Airspace Operations

Cited by 4 publications

References 13 publications

New atmospheric data model for constant altitude accelerated flight performance prediction calculations and flight trajectory optimization algorithms

New atmospheric data model for constant altitude accelerated flight performance prediction calculations and flight trajectory optimization algorithms

New flight trajectory optimisation method using genetic algorithms

Research on modelling and database construction of supporting magnetic variation data and atmospheric data for flight management system simulation

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