Synthetic Aircraft Trajectories Generated with Multivariate Density Models

Aircraft trajectory generation is a high stakes problem with a wide scope of applications, including collision risk estimation, capacity management and airspace design. Most generation methods focus on optimizing a criterion under constraints to find an optimal path, or on predicting aircraft trajectories. Nevertheless, little in the way of contribution has been made in the field of the artificial generation of random sets of trajectories. This work proposes a new approach to model two-dimensional flows in order to build realistic artificial flight paths. The method has the advantage of being highly intuitive and explainable. Experiments were conducted on go-arounds at Zurich Airport, and the quality of the generated trajectories was evaluated with respect their shape and statistical distribution. The last part of the study explores strategies to extend the work to non-regularly shaped trajectories.

Eco-efficient flight trajectories – Using a Lagrangian approach in EMAC to investigate contrail formation in the mid latitudes

<p>Air transport has for a long time been linked to environmental issues like pollution, noise and climate change. While CO2 emissions are the main focus in public discussions, non-CO2 emissions of aviation may have a similar impact on the climate as aviation's carbon dioxide, e.g. contrail cirrus, nitrogen oxides or aviation induced cloudiness. While the effects of CO2 on climate are independent of location and situation during release, non-CO2 effects such as contrail formation vary depending on meteorological background. Previous studies investigated the influence of different weather situations on aviation’s climate change contribution, identifying climate sensitive regions and generating data products which enable air traffic management (ATM) to plan for climate optimized trajectories.</p> <p>The research presented here focuses on the further development of methods to determine the sensitivity of the atmosphere to aviation emissions with respect to climate effects in order to determine climate optimized aircraft trajectories. While previous studies focused on characterizing the North Atlantic Flight Corridor region, this study aims to extend the geographic scope by performing Lagrangian simulations in a global climate model EMAC for the northern hemispheric extratropical regions and tropical latitudes. This study addresses how realistically the physical conditions and processes for contrail formation and life cycle are represented in the upper troposphere and lower stratosphere by comparing them to airborne observations (HALO measurement campaign, CARIBIC/IAGOS scheduled flight measurements), examining key variables such as temperature or humidity. Direct comparison of model data with observations using clusters of data provides insight into the extent to which systematic biases exist that are relevant to the climate effects of contrails. We perform this comparison for different vertical resolutions to assess which vertical resolution in the EMAC model is well suited for studying contrail formation. Together with this model evaluation using aircraft measurements, the overall concept for studying the life cycle of contrails in the modular global climate model EMAC is introduced. Hereby, the concept for the development of a MET service that can be provided to ATM to evaluate contrail formation and its impact on the climate along planned aircraft trajectories is presented.</p> <p>Within the ClimOP collaborative project, we can investigate which physical processes determine the effects of contrails on climate and study their spatial and temporal variation. In addition, these climate change functions enable case studies that assess the impact of contrails on climate along trajectories and use alternative trajectories that avoid these regions of the atmosphere that have the potential to form contrails with a large radiative effect.</p> <p>This study is part of the ClimOP project and has received funding from European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement N° 875503 (ClimOP) and from the SESAR Joint Undertaking under grant agreements No 699395 (FlyATM4E). </p>

Robust clustering of functional directional data

A robust approach for clustering functional directional data is proposed. The proposal adapts “impartial trimming” techniques to this particular framework. Impartial trimming uses the dataset itself to tell us which appears to be the most outlying curves. A feasible algorithm is proposed for its practical implementation justified by some theoretical properties. A “warping” approach is also introduced which allows including controlled time warping in that robust clustering procedure to detect typical “templates”. The proposed methodology is illustrated in a real data analysis problem where it is applied to cluster aircraft trajectories.

Selective Simulated Annealing for Large Scale Airspace Congestion Mitigation

This paper presents a methodology to minimize the airspace congestion of aircraft trajectories based on slot allocation techniques. The traffic assignment problem is modeled as a combinatorial optimization problem for which a selective simulated annealing has been developed. Based on the congestion encountered by each aircraft in the airspace, this metaheuristic selects and changes the time of departure of the most critical flights in order to target the most relevant aircraft. The main objective of this approach is to minimize the aircraft speed vector disorder. The proposed algorithm was implemented and tested on simulated trajectories generated with real flight plans on a day of traffic over French airspace with 8800 flights.

Effect of the Wake Vortex on the Mutual Safety of Winged Aircraft Following the Same Route

The wake vortex consists mainly of two vortices, which are formed when the stream flows around the wings of an aircraft. A semi-empirical model of a stable vortex wake is proposed and analyzed. The model allows describing the velocity field in a vortex, depending on the characteristics of the aircraft generator, as well as assessing the effect of the vortex on the subsequent aircraft. Statistical modeling was carried out to determine the safe interval between the aircrafts for the characteristic sections of the trajectory. When moving over the sea, a straight-line route, a trajectory with turns and an ascent to an altitude for flying around the island were chosen; on the land section of the movement, a flight over the relief was simulated. A significant influence of the ruggedness of the relief on the probability of an aircraft falling when it enters a wake vortex is shown. The effect of the displacement of the aircraft trajectories in the vertical and horizontal planes and the increase in the average flight speed on the safe interval between the aircrafts is investigated.

Parametric optimization of aircraft arrival trajectories for aviation noise mitigation using BADA4 performance model

Successful mitigation of aviation noise is a key enabler for sustainable aviation growth. A key focus of this effort is the noise arising from aircraft arrival operations. Arrival operations are characterized by the use of high-lift devices, deployment of landing gear, and low thrust levels, which results in the airframe being the major component of noise. In order to optimize for arrival noise, management of the flap schedule and gear deployment is crucial. This research aims to create an optimization framework for evaluating various aircraft trajectories in terms of their noise impact. A parametric representation of the aircraft arrival trajectory will be created to allow for the variation of aircraft's flap schedule. The Federal Aviation Administration's Aviation Environmental Design Tool will be used to simulate the aircraft trajectory and performance, and to compute the noise metrics. Specifically, the latest performance model from EUROCONTROL called "Base of Aircraft Data - Family 4" will be used. This performance model contains higher fidelity modeling of aircraft aerodynamics and other characteristics which allows for better parametric variation.

GEOVISUALIZATION OF AERIAL PHOTOGRAMMETRIC FLIGHTS FOR DATA QUALITY ASSESSMENT

Spatiotemporal data visualization plays an important role for simulating the changes over time and representing dynamic geospatial phenomena. In aerial photogrammetry, image acquisition is the most important stage for obtaining high-quality products; and can be affected by various factors such as the weather and illumination conditions, imaging geometry, etc. 3D simulation of the aircraft trajectories at the planning stage helps the flight planners to make better decisions especially for unmanned aerial vehicle (UAV) missions in areas with mixed land use land cover, such as rugged topography, water bodies, restricted areas, etc.; since images with poor texture or large differences in scale may deteriorate the quality of the final products. In this study, a geovisualization approach for photogrammetric flights carried out with UAVs or airplane platforms was implemented using CesiumJS Virtual Globe. The measured flight trajectory parameters, such as image perspective centre coordinates and the camera rotations, the time of acquisition, and the interior orientation parameters (IOPs) of the camera were used for spatiotemporal visualization. In the developed approach, the EOPs and IOPs of the images were utilized to reconstruct the flight paths, the camera position, the footprints of the acquired images on the ground, and the rotation of the aircraft; and to present them on a 3D web environment precisely. The approach was demonstrated by using two case studies, one from a UAV flight mission and the other one from an airplane carried out with a large-format aerial camera.

Influence of weather situation on non-CO₂ aviation climate effects: the REACT4C climate change functions

Emissions of aviation include CO2, H2O, NOx, sulfur oxides, and soot. Many studies have investigated the annual mean climate impact of aviation emissions. While CO2 has a long atmospheric residence time and is almost uniformly distributed in the atmosphere, non-CO2 gases and particles and their products have short atmospheric residence times and are heterogeneously distributed. The climate impact of non-CO2 aviation emissions is known to vary with different meteorological background situations. The aim of this study is to systematically investigate the influence of characteristic weather situations on aviation climate effects over the North Atlantic region, to identify the most sensitive areas, and to potentially detect systematic weather-related similarities. If aircraft were re-routed to avoid climate-sensitive regions, the overall aviation climate impact might be reduced. Hence, the sensitivity of the atmosphere to local emissions provides a basis for the assessment of weather-related, climate-optimized flight trajectory planning. To determine the climate change contribution of an individual emission as a function of location, time, and weather situation, the radiative impact of local emissions of NOx and H2O to changes in O3, CH4, H2O and contrail cirrus was computed by means of the ECHAM5/MESSy Atmospheric Chemistry model. From this, 4-dimensional climate change functions (CCFs) were derived. Typical weather situations in the North Atlantic region were considered for winter and summer. Weather-related differences in O3, CH4, H2O, and contrail cirrus CCFs were investigated. The following characteristics were identified: enhanced climate impact of contrail cirrus was detected for emissions in areas with large-scale lifting, whereas low climate impact of contrail cirrus was found in the area of the jet stream. Northwards of 60∘ N, contrails usually cause climate warming in winter, independent of the weather situation. NOx emissions cause a high positive climate impact if released in the area of the jet stream or in high-pressure ridges, which induces a south- and downward transport of the emitted species, whereas NOx emissions at, or transported towards, high latitudes cause low or even negative climate impact. Independent of the weather situation, total NOx effects show a minimum at ∼250 hPa, increasing towards higher and lower altitudes, with generally higher positive impact in summer than in winter. H2O emissions induce a high climate impact when released in regions with lower tropopause height, whereas low climate impact occurs for emissions in areas with higher tropopause height. H2O CCFs generally increase with height and are larger in winter than in summer. The CCFs of all individual species can be combined, facilitating the assessment of total climate impact of aircraft trajectories considering CO2 and spatially and temporally varying non-CO2 effects. Furthermore, they allow for the optimization of aircraft trajectories with reduced overall climate impact. This also facilitates a fair evaluation of trade-offs between individual species. In most regions, NOx and contrail cirrus dominate the sensitivity to local aviation emissions. The findings of this study recommend considering weather-related differences for flight trajectory optimization in favour of reducing total climate impact.

Optimal forecast algorithm based on compatible linear filtration and extrapolation

This work considers the methods of optimal linear extrapolation of the flight path of the aircraft, which provide a minimum of the mean square of the forecast error with different amounts of a priori information. The research is based on the canonical decomposition of a vectorial random process. It is determined that the development of modern technologies entails increasing requirements for quality and accuracy of control. However, since the existing methods of linear extrapolation do not provide for the maximum accuracy of the forecast due to the inherent constraints on the random process that describe the motion of aircraft, this necessitates a further development and improvement of methods for extrapolation of aircraft trajectories. The peculiarity of the developed methods for extrapolation of aircraft trajectory is that they allow within the correlation model to fully take into account the properties of a real random process that describes the motion of aircraft at the landing approach stage. This provides for the maximum possible accuracy of linear extrapolation with a variety of information support conditions. These methods allow improving the safety of flights and the efficiency of aviation. Accordingly, new capabilities of aircraft and other sophisticated technical systems can be further considered.