3D Cruise Trajectory Optimization Inspired by a Shortest Path Algorithm

Murrieta-Mendoza, Alejandro; Romain, Charles; Botez, Ruxandra Mihaela

doi:10.3390/aerospace7070099

Cited by 18 publications

(3 citation statements)

References 40 publications

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“…Kawser et al (2020) used the shortest path algorithm to create the ideal flight trajectory. Mendoza et al (2020) proposed a model that minimizes flight costs and fuel consumption and provides an alternative route using the Floyd–Warshall methodology. Liu et al (2021) explored potential ways to increase the fuel efficiency of flight operations.…”

Section: Literature Reviewmentioning

confidence: 99%

An algorithmic application with flexible airspace approach

Kökhan

Gökdalay

2023

AEAT

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Purpose The purpose of this study is to develop an operational level decision support system model for air traffic controllers (ATCos) within the framework of the Flexible Use of Airspace (FUA) concept to enable more efficient use of airspace capacity. This study produces a systematic solution to the route selection process so that the ATCo can determine the most efficient route with an operational decision support system model using Dijkstra’s Shortest Path Algorithm. Design/methodology/approach In this study, a new decision support system model for ATCos in decision-making positions was recommended and used. ATCos use this model as a main model for determining the shortest and safest route for aircraft as an operational-level decision support system. Dijkstra Algorithm, used in the model, is defined step by step and then explained with the pseudocode. Findings It has been determined that when the FUA concept and DSS are used while the ATCo chooses a route, significant fuel, time and capacity savings are achieved in flight operations. Emissions resulting from the negative environmental effects of air transportation are reduced, and significant capacity increase can be achieved. The operational level decision support system developed in the study was tested with 55 scenarios on the Ankara–Izmir flight route compared to the existing fixed route. The results for the proposed most efficient route were achieved at 11.22% distance (nm), 9.36%-time (min) savings and 837.71 kg CO2 emission savings. Originality/value As far as the literature is reviewed, most studies aimed at increasing airspace efficiency produce solutions that try to improve rather than replace the normal process. Considering the literature positioning of this study compared to other studies, the proposed model provides a new systematic solution to the problems that cause human-induced route inefficiency within the framework of the FUA concept.

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Section: Literature Reviewmentioning

confidence: 99%

An algorithmic application with flexible airspace approach

Kökhan

Gökdalay

2023

AEAT

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“…We consider these variables because they are input variables for SOPHIA and included in GFS data, and it is a known fact that temperature and wind are crucial for trajectory optimization. The ground speed (m/s), i.e., the speed of an aircraft relative to the ground, can be calculated [21] with (m/s); V T is the true airspeed (m/s) relative to the still air; Z Wind and Z Temp are the wind vector and temperature (K); Mach denotes the Mach number, the vehicle airspeed relative to the speed of sound at current atmosphere condition; and k and R are constant for heat capacity ratio and gas constant, respectively. From this equation, we can see the importance of temperature and wind on the key parameters describing the status of an aircraft.…”

Section: Data Descriptionmentioning

confidence: 99%

Importance of Weather Conditions in a Flight Corridor

Chen

Fricke

Okhrin

et al. 2022

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Current research initiatives, such as the Single European Sky Air Traffic Management Research Program, call for an air traffic system with improved safety and efficiency records and environmental compatibility. The resulting multi-criteria system optimization and individual flight trajectories require, in particular, reliable three-dimensional meteorological information. The Global (Weather) Forecast System only provides data at a resolution of around 100 km. We postulate a reliable interpolation at high resolution to compute these trajectories accurately and in due time to comply with operational requirements. We investigate different interpolation methods for aerodynamic crucial weather variables such as temperature, wind speed, and wind direction. These methods, including Ordinary Kriging, the radial basis function method, neural networks, and decision trees, are compared concerning cross-validation interpolation errors. We show that using the interpolated data in a flight performance model emphasizes the effect of weather data accuracy on trajectory optimization. Considering a trajectory from Prague to Tunis, a Monte Carlo simulation is applied to examine the effect of errors on input (GFS data) and output (i.e., Ordinary Kriging) on the optimized trajectory.

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“…Consequently, the approach needs to account for trajectory optimization. Typically, aircraft trajectory optimizations minimize cruise fuel consumption but they can also be used to improve data collection [12], search efficiency [13], energy efficiency [14], fuel consumption [15] or environmental impact [16]. This work focuses on a single multi-segment trajectory optimization considering take-off, climb and cruise portions while respecting the flight path continuity.…”

Section: Introductionmentioning

confidence: 99%

Concurrent Trajectory Optimization and Aircraft Design for the Air Cargo Challenge Competition

Matos

Marta

2022

Aerospace

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A coupled aerostructural aircraft design and trajectory optimization framework is developed for the Air Cargo Challenge competition to maximize the expected score based on cargo carried, altitude achieved and distance traveled. Its modular architecture makes it easily adaptable to any problem where the performance depends not only on the design of the aircraft but also on its flight trajectory. It is based on OpenAeroStruct, an aerostructural solver that uses analytic derivatives for efficient gradient-based optimization. A trajectory optimization module using a collocation method is coupled with the option of using b-splines to increase computational efficiency together with an experimentally-based power decay model that accurately determines the aircraft propulsive response to control input depending on the battery discharge level. The optimization problem totaled 206 variables and 283 constraints and was solved in less than 7 h on a standard computer with 12% reduction when using b-splines for trajectory control variables. The results revealed the need to consider the multi-objective total score to account for the different score components and highlighted the importance of the payload level and chosen trajectory. The wing area should be increased within allowable limits to maximize payload capacity, climb to maximum target height should be the focus of the first 60 s of flight and full throttle should be avoided in cruise to reduce losses and extend flight distance. The framework proved to be a valuable tool for students to easily obtain guidelines for both the model aircraft design and control to maximize the competition score.

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3D Cruise Trajectory Optimization Inspired by a Shortest Path Algorithm

Cited by 18 publications

References 40 publications

An algorithmic application with flexible airspace approach

An algorithmic application with flexible airspace approach

Importance of Weather Conditions in a Flight Corridor

Concurrent Trajectory Optimization and Aircraft Design for the Air Cargo Challenge Competition

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