A new journal paper on the research line of weather prediction and artificial intelligence has been published in the Aircraft Operations Lab. Authored by Iván Martínez as main writer, the paper “Predicting Air Traffic Flow Management hotspots due to weather using Convolutional Neural Networks” addresses the pressing issue of understanding how convective weather impacts airContinue reading “Predicting Air Traffic Flow Management hotspots due to weather using Convolutional Neural Networks”
Category Archives: Publications
Advancing Multi-control Commercial Aircraft Trajectory Optimization
A new research applies singular control theory to optimize trajectories of commercial airplanes in a vertical plane. Our journal paper titled “Multi-control commercial aircraft trajectory optimization in a vertical plane with state-inequality constraints via singular control theory”, has been written by Amin Jafarimoghaddam as main author, and coauthored by prof. Manuel Soler, both from the AircraftContinue reading “Advancing Multi-control Commercial Aircraft Trajectory Optimization”
New publication: “Performance impact assessment of reducing separation minima for en-route operations”
Our paper titled “Performance impact assessment of reducing separation minima for en-route operations”, shows that a separation minima reduction can bring significant fuel savings, flight delay reduction, air traffic controller workload drop, and improve safety. It has been coauthored by prof. Javier García-Heras from the Aircraft Operations Lab UC3M and several researchers from Universidad PolitécnicaContinue reading “New publication: “Performance impact assessment of reducing separation minima for en-route operations””
CNN-based architectures can be used to increase the prediction lead time of thunderstorms
Our latest research shows that Convolutional Neural Networks (CNN)-based architectures can be used to increase the prediction lead time of thunderstorms in the aviation field. These results are published in the journal paper titled “Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks”. A study written by Aniel Jardinesa, Hamidreza Eivazib, Elias Zeab, Javier García-Herasa,Continue reading “CNN-based architectures can be used to increase the prediction lead time of thunderstorms”
GMD has published our paper linked to the CLIMaCCF python library
We are pleased to announce that Geoscientific Model Development has published in open access our paper “A python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0“. This work has been carried out in the framework of the FlyATM4E and ALARM projects, which belong to the European Union’s Horizon 2020 researchContinue reading “GMD has published our paper linked to the CLIMaCCF python library”