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Influence of atmospheric uncertainty, convective indicators, and cost-index on the leveled aircraft trajectory optimization problem
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dc.contributor.authorSoler, Manueles_ES
dc.contributor.authorGonzález Arribas, Danieles_ES
dc.contributor.authorSanjurjo Rivo, Manueles_ES
dc.contributor.authorGarcía-Heras, Javieres_ES
dc.contributor.authorSacher, Danieles_ES
dc.contributor.authorGelhardt, Ulrikees_ES
dc.contributor.authorLang, Jürgenes_ES
dc.contributor.authorHauf, Thomases_ES
dc.contributor.authorSimarro Grande, Juan Pabloes_ES
dc.date.accessioned2022-08-04T08:22:27Z-
dc.date.available2022-08-04T08:22:27Z-
dc.date.issued2020-
dc.identifier.citationTransportation Research Part C: Emerging Technologies. 2020, 120, 102784es_ES
dc.identifier.issn0968-090X-
dc.identifier.urihttp://hdl.handle.net/20.500.11765/13890-
dc.description.abstractThe existence of significant uncertainties in the models and systems required for trajectory prediction represents a major challenge for the Air traffic Management (ATM) system. Weather can be considered as one of the most relevant sources of uncertainty. Understanding and managing the impact of these uncertainties is necessary to increase the predictability of the ATM system. State-of-the-art probabilistic forecasts from Ensemble Prediction Systems are employed to characterize uncertainty in the wind and potential convective areas. A robust optimal control methodology to produce efficient and predictable aircraft trajectories in the presence of these uncertainties is presented. Aircraft motion is assumed to be at a constant altitude and variable speed, considering BADA4 as the aircraft performance model. A set of Pareto-optimal trajectories is obtained for different preferences among predictability, convective risk, and average cost index running a thorough parametric study on a North Atlantic crossing use case. Results show that the cost of reducing the arrival time window by 10 s. is between 100 and 200 kg or 3 and 6 min., depending on the cost-index. They also show that reducing the exposure to convection by 50 km is on the order of 5 and 10 min. or 100 and 200 kg. of average fuel consumption.es_ES
dc.description.sponsorshipThis work has been partially supported by project TBO-MET project (https://tbomet-h2020.com/), which has received funding from the SESAR JU under grant agreement No 699294 under European Union's Horizon 2020 research and innovation programme.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsLicencia CC: Reconocimiento–NoComercial–SinObraDerivada CC BY-NC-NDes_ES
dc.subjectOptimal controles_ES
dc.subjectRobust planninges_ES
dc.subjectConvective weatheres_ES
dc.subjectAircraft trajectory planninges_ES
dc.titleInfluence of atmospheric uncertainty, convective indicators, and cost-index on the leveled aircraft trajectory optimization problemes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.trc.2020.102784es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
Colecciones: Artículos científicos 2019-2022


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