Eurocontrol

The EUROCONTROL Performance Review Commission launched a data challenge in 2025 for machine-learning-based fuel burn prediction, in collaboration with OpenSky Network and TU Delft. This paper describes the dataset built for the challenge. It pairs ACARS fuel telemetry, crowdsourced through airframes.io, with ADS-B trajectory data from the OpenSky Network, augmented with flight list information from EUROCONTROL over the period April to October 2025. Consumer-grade ACARS receivers supply fuel-on-board reports at irregular intervals; ADS-B provides dense kinematic trajectories at sub-second resolution. We fuse these two sources and validate fuel labels against physics-based predictions from TU Delft's OpenAP model to infer ambiguous reporting units and filter erroneous records. The resulting training set is approximately 5 GB and includes real-world noise, coverage gaps, and operational variability. We describe the data collection pipeline, the unit inference methodology, quality assurance procedures, and the structure of the released dataset.

Recent advances in Neural Ordinary Differential Equations (Neural ODE) have shown that high-fidelity aircraft dynamics can be learned from flight recorder data, but such proprietary datasets remain largely inaccessible. In this study, we extend these principles to open trajectory data by training a Neural ODE model on Automatic Dependent Surveillance–Broadcast (ADS-B) and Mode~S Enhanced Surveillance (EHS) information retrieved from the OpenSky Network. The model focuses on reconstructing the vertical dynamics of transport aircraft using only openly available surveillance variables. The resulting framework learns continuous-time dynamics that remain physically consistent through embedded kinematic relations, demonstrating that realistic vertical profiles can be generated solely from open surveillance data. This work contributes to reproducible, data-driven performance modelling and supports the broader adoption of open, physics-guided learning methods in aviation research.

<strong class="journal-contentHeaderColor">Abstract.</strong> Aviation's climate impact includes not only CO₂ emissions but also significant non-CO₂ effects, especially from contrails. These ice clouds can alter Earth's radiative balance, potentially rivaling the warming effect of aviation CO₂. Physics-based models provide useful estimates of contrail formation and climate impact, but their accuracy depends heavily on the quality of atmospheric input data and on assumptions used to represent complex processes like ice particle formation and humidity-driven persistence. Observational data from remote sensors, such as satellites and ground cameras, could be used to validate and calibrate these models. However, existing datasets don't explore all aspect of contrail dynamics and formation: they typically lack temporal tracking, and do not attribute contrails to their source flights. To address these limitations, we present the Ground Visible Camera Contrail Sequences (GVCCS), a new open data set of contrails recorded with a ground-based all-sky camera in the visible range. Each contrail is individually labeled and tracked over time, allowing a detailed analysis of its lifecycle. The dataset contains 122 video sequences (24,228 frames) and includes flight identifiers for contrails that form above the camera. As reference, we also propose a unified deep learning framework for contrail analysis using a panoptic segmentation model that performs semantic segmentation (contrail pixel identification), instance segmentation (individual contrail separation), and temporal tracking in a single architecture. By providing high-quality, temporally resolved annotations and a benchmark for model evaluation, our work supports improved contrail monitoring and will facilitate better calibration of physical models. This sets the groundwork for more accurate climate impact understanding and assessments.

Background: the Skill, Rule, and Knowledge (S-R-K) model is a framework used to describe and analyze human behaviour and decision-making in complex environments based on the nature of the task and kind of cognitive control required. The S-R-K model is particularly useful in fields like human factor engineering, system design, and safety-critical industries because it helps to understand human errors and how they relate to different levels of cognitive control. However, the S-R-K model is still qualitative and lacks specific and quantifiable metrics for determining what kind of cognitive control a person is using at any given time. This aspect makes difficult to directly measure and compare performance across the three levels. This study aimed therefore to characterize the S-R-K model from a neurophysiological perspective by analyzing the operator’s cerebral cortical activity. Methods: in this study, participants carried out experimental tasks able to replicate the Skill (tracking task), Rule (rule-based navigation) and Knowledge conditions (unfamiliar situations). Results: participants’ Electroencephalogram (EEG) was recorded during tasks execution and then Global Field Power (GFP) was estimated in the different EEG frequency bands. Brodmann areas (BAs) and EEG features were then used to characterize the S-R-K pattern over the cerebral cortex and as inputs to build up the machine learning-based model to estimate participants’ cognitive control behaviours while dealing with tasks. Conclusions: the results demonstrate the possibility of objectively measuring the different S, R and K levels in terms of brain activations. Furthermore, such evidence is consistent with the scientific literature in terms of cognitive functions corresponding to the different levels of cognitive control.

Abstract The resurgence of labor unions in the U.S., evidenced by recent unionization successes across various industries, reflects a broader revival of organized labor's role in workplace advocacy. These developments counter a long-term decline in union membership, with global efforts also seeing modest gains. As is demonstrated in this series of contributions, labor unions remain critical in promoting occupational health and safety, mitigating workplace hazards, and addressing psychosocial risks such as stress and harassment. Historically, unions have shaped labor standards and influenced the development of safety regulations. Today, they contribute to broader societal benefits, including democratic participation, workplace well-being, and public health innovation. Despite their significant contributions, unions face challenges from globalization, technological changes, the rise of non-standard work arrangements, and political polarization. Despite the critical role unions play in occupational health and organizations more generally, organizational scientists have paid relatively little attention to unions. In response, this series of contributions highlights the need for renewed scholarly attention, particularly in industrial-organizational psychology, to support unions in safeguarding workers' rights and well-being.

In the Latin America and Caribbean (LAC) region climate change effects such as higher temperatures, sea level rise and stronger storms are already threatening critical airport infrastructure and operations, with this exposure increasing as climate change accelerates. Given the social and economic criticality of airports to the region, it is vital that they adapt and build resilience to the resulting impacts. This paper presents the first evaluation of the climate risk assessment and adaptation status of airports in the LAC region. Drawing on a survey of airport professionals from 35 LAC airports and airport groups (representing a total of 54 airports) it finds that although 80% are already experiencing climate change effects, just 14% have carried out a climate change risk assessment to establish what impacts they may face and only 3% (one airport) have developed a climate adaptation plan. This is a significant exposure-adaptation gap which it is essential to address. This urgently requires (i) enhanced awareness raising of climate effects and impacts; (ii) increased provision of data and guidance; and (iii) development and promotion of capacity building mechanisms such as risk assessment tools and training. A crucial role is identified for national governments and sector bodies to continue and augment support for airports in the region to adapt. While this study focuses on the LAC region, the recommendations are likewise applicable for supporting adaptation action by airports in other regions.

Abstract As part of a major project, the operator was faced with the need to abandon an open borehole in the vicinity of a planned infrastructure. To complicate matters, the borehole contained a fish and, close by, was another fully cased borehole and a second, which had multiple side-tracks containing steel components, but which had the casing milled out and been fully abandoned with cement to surface. It was necessary to drill a new borehole to intercept the old borehole, which raised several challenges including ranging detection through salt, safe drilling among multiple boreholes, effective integration of three independent ranging technologies, and re-entry into and abandonment of the open borehole. The problem of intersecting and sealing an open borehole in the presence of offset cased boreholes and fish left in the ground was unique and required multiple ranging technologies to be employed. Adding to the complexity of this interception was the presence of up to six sidetracks from other (older) boreholes in the immediate (less than 5 meters) vicinity of the intercept and target boreholes. Initial forensic analysis of all the borehole data was made to see if a borehole intersection project was feasible. Following this, the planning and execution of the work followed the usual oil and gas industry practices for relief well interception, including the established locate, follow, and intercept process. The planning phase highlighted the need for combining advanced survey management with active acoustic, active magnetic and passive magnetic ranging methods. Project success hinged on the effective integration of these three technologies. By integrating all survey and ranging data, the lower section of the target borehole was located, re-entered and cemented on the first attempt without incident. Despite the combination of ranging technologies, it proved impossible to locate and re-enter the upper section of the borehole due to the propagation of survey uncertainties. The outcomes highlight the efficacy, and limitations of this integration for complex abandonment scenarios using: Active Magnetic Ranging (AMR) to track the nearby casing down to the abandoned fish,Passive Magnetic Ranging (PMR) to locate offset casing stubs and fishes especially through the salt layer, andActive Acoustic Ranging (AAR) to locate offset casing and open-hole intervals. Intercepting a 6½" open hole at 1,031m MD in the presence of two other boreholes within two meters within a specific interval is the first of its kind and would have been impossible with conventional magnetic ranging technologies. For the first time in a relief well setting, it required the integration of magnetic and acoustic systems, where a science-based engineering approach was applied to make use of proven passive and active magnetic ranging in combination with acoustic ranging. This case study demonstrates the benefit of combining different technologies to achieve a safe and effective abandonment in a congested subsurface situation. It offers insights for similar challenges which might be encountered in the O&amp;G industry.

The European Meteorological Aircraft Derived Data Centre (EMADDC) is an operational centre in development to utilize all aircraft in the European airspace to derive upper air wind and temperature observations.The lecture will provide a high level overview of EMADDC and focus on the origination, the methods used, the EMADDC data and use cases and the unique partnerships. Also, the latest developments concerning global geographical coverage will be presented. &amp;#160;&amp;#160;New air traffic control surveillance technologies such as Mode-S Enhanced Surveillance radars (Mode- S EHS) present great opportunities to obtain or derive large quantities of wind direction, wind speed and temperature observations in numbers unprecedented in the European region.EMADDC is a EUMETNET program, led by the Royal Netherlands Meteorological Institute (KNMI), for the collection, processing and dissemination of quality controlled meteorological upper air observations, based on aircraft data. Observations derived from sensors onboard aircraft are more or less instantaneously collected by Mode-S EHS radars of Air Traffic Control Centres and by local Mode-S/ADS-B receivers. By agreement, EMADDC receives these observations from Air Navigation Service Providers and local Mode-S/ADS-B operators, such as UK Met Office and Air Support, directly.EMADDC is a true partnership program linked to the meteorological and aeronautical domain and is supported by several commercial and non-commercial organisations. EMADDC is co-funded by the European Union via the Connecting Europe Facility (SESAR Deployment).Each day approximately 25 million temperature and 35 million wind observations, quality controlled, are being made available to stakeholders for use in data assimilation by NWP centres such as ECMWF, or to be used operationally in meteorological forecasting offices.Information about EMADDC is available at https://emaddc.com