Detección probabilística de conflictos entre aeronaves utilizando transformación de variables aleatorias

En este proyecto se estudia la situación de conflicto en la que dos aeronaves se aproximan con velocidad, rumbo y altitud constante en el mismo nivel de vuelo, bajo la presencia de vientos desconocidos definidos por su función de densidad de probabididad. Se considera que un conflicto se produce cuando se predice que en el futuro las aeronaves se encontrarán en pérdida de separación, es decir, cuando se predice que las aeronaves se encontrarán a una distancia entre ellas menor que un margen mínimo de separación. El conflicto se caracteriza por una serie de indicadores, tales como la mínima distancia entre aeronaves, el instante de tiempo en el que se alcanza esta distancia o la probabilidad de que este se produzca. En este proyecto se realiza un estudio probabilístico usando transformación de variables aleatorias. Con este método, es posible obtener la función de densidad de los indicadores a partir de una transformación de la función de densidad del viento. Los resultados obtenidos son comparados y validados usando el método de Monte Carlo. Para dos escenarios diferentes, se estudian los efectos de las propiedades estadísticas del viento, tales como su media o varianza, y de la velocidad de las aeronaves sobre los indicadores.The aim of this project is to analyse the conflict between two approaching aircraft flying at a constant airspeed, course and altitude for uncertain winds, which are defined by their probability density functions (PDFs). The conflict is characterized by a series of indicators, such as the minimum distance between aircraft, the time to minimum distance or the probability of conflict. A loss of separation is considered to exist if the minimum distance is found to be smaller than a minimum separation margin. A probabilistic analysis is performed using transformation of random variables. In this method, the indicator’s PDFs are computed by a transformation of the wind speed PDFs. The results are validated using the Monte Carlo method. The effects of the statistical parameters of the wind and the aircraft airspeeds are analysed for two different scenarios.Universidad de Sevilla. Máster en Ingeniería Aeronáutic

Probabilistic Aircraft Conflict Detection Considering Ensemble Weather Forecast

In this paper, the effects of wind uncertainty on the problem of conflict detection are analyzed. The wind components are modeled as random variables; the wind uncertainty is obtained from weather forecasts. The case of two en-route aircraft flying at constant altitude, constant airspeed, constant course, and subject to the same wind is considered. The conflict is caracterized by several indicators, such as the minimum distance between aircraft, the time to minimum distance, and the conflict probability. The analysis is based on the transformation of random variables, which evolves the wind probability density functions to obtain the probability density functions of the indicators. Numerical results are presented for a given particular scenario with uniformly-distributed winds.Ministerio de Economía y Competitividad TRA2014-58413-C2-1-

Metaheuristic Approach to Probabilistic Aircraft Conflict Detection and Resolution Considering Ensemble Prediction Systems

International audienceThis paper presents a methodology to tackle theproblem of strategic aircraft conflict detection and resolution, upto 60 minutes in advance, considering wind and temperatureuncertainties. The problem of hundreds of en-route aircraftflying multi-segmented 2D trajectories is considered. The weatheruncertainty is retrieved from Ensemble Prediction Systems. Theconflict detection is based on ensemble trajectory prediction,and is performed using an efficient grid-based procedure. Ametaheuristic approach is developed to solve the conflicts, basedon simulated annealing, which generates resolution trajectoriesby modifying the location of the route waypoints (vectoring),with the aim of lowering the probabilities of the conflicts whilealso minimising the deviation from the nominal paths. Realisticapplications in scenarios with different traffic densities arepresented

Spatiotemporal Characteristics of the Largest HIV-1 CRF02_AG Outbreak in Spain: Evidence for Onward Transmissions

Background and Aim: The circulating recombinant form 02_AG (CRF02_AG) is the predominant clade among the human immunodeficiency virus type-1 (HIV-1) non-Bs with a prevalence of 5.97% (95% Confidence Interval-CI: 5.41–6.57%) across Spain. Our aim was to estimate the levels of regional clustering for CRF02_AG and the spatiotemporal characteristics of the largest CRF02_AG subepidemic in Spain.Methods: We studied 396 CRF02_AG sequences obtained from HIV-1 diagnosed patients during 2000–2014 from 10 autonomous communities of Spain. Phylogenetic analysis was performed on the 391 CRF02_AG sequences along with all globally sampled CRF02_AG sequences (N = 3,302) as references. Phylodynamic and phylogeographic analysis was performed to the largest CRF02_AG monophyletic cluster by a Bayesian method in BEAST v1.8.0 and by reconstructing ancestral states using the criterion of parsimony in Mesquite v3.4, respectively.Results: The HIV-1 CRF02_AG prevalence differed across Spanish autonomous communities we sampled from (p < 0.001). Phylogenetic analysis revealed that 52.7% of the CRF02_AG sequences formed 56 monophyletic clusters, with a range of 2–79 sequences. The CRF02_AG regional dispersal differed across Spain (p = 0.003), as suggested by monophyletic clustering. For the largest monophyletic cluster (subepidemic) (N = 79), 49.4% of the clustered sequences originated from Madrid, while most sequences (51.9%) had been obtained from men having sex with men (MSM). Molecular clock analysis suggested that the origin (tMRCA) of the CRF02_AG subepidemic was in 2002 (median estimate; 95% Highest Posterior Density-HPD interval: 1999–2004). Additionally, we found significant clustering within the CRF02_AG subepidemic according to the ethnic origin.Conclusion: CRF02_AG has been introduced as a result of multiple introductions in Spain, following regional dispersal in several cases. We showed that CRF02_AG transmissions were mostly due to regional dispersal in Spain. The hot-spot for the largest CRF02_AG regional subepidemic in Spain was in Madrid associated with MSM transmission risk group. The existence of subepidemics suggest that several spillovers occurred from Madrid to other areas. CRF02_AG sequences from Hispanics were clustered in a separate subclade suggesting no linkage between the local and Hispanic subepidemics

Probabilistic Aircraft Conflict Detection and Resolution under the Effects of Weather Uncertainty

This PhD thesis addresses the problem of aircraft conflict detection and resolution (CD&R) considering weather uncertainty. The general framework of this study is the development of methodologies to integrate weather uncertainty into the Air Traffic Management planning process. The study considers the analysis of both a single pair of aircraft and multi-aircraft conflict scenarios, with two- and three-dimensional trajectories. The weather uncertainty data is retrieved from Probabilistic Weather Forecasts, in particular Ensemble Prediction Systems. Different methodologies to probabilistic CD&R are described, and their applicability is presented and discussed. Firstly, an approach to statistically quantify the severity of aircraft conflicts subject to wind forecast uncertainty is presented. The conflicts are characterized by two indicators: conflict intensity and conflict probability. The conflict intensity is measured by the distance of closest approach between the aircraft. The probability of conflict is obtained in terms of the probability density function of the distance of closest approach, which is obtained from the probability density functions of the wind components using the Probabilistic Transformation Method. The case of two en-route aircraft flying at constant altitude and subject to the same random wind is considered first, and results are presented to analyze the influence the wind uncertainty and the traffic configuration have on the conflict detection problem. Then, this methodology is extended to the problem of three-dimensional multi-segment trajectories and a numerical application is presented. Secondly, a probabilistic method for conflict detection and resolution considering the effects of wind forecast uncertainty is presented. The wind components are modeled as random variables, described by a joint probability density function. The probabilistic conflict detection problem is tackled again using the Probabilistic Transformation Method. The probabilistic conflict resolution consists in modifying the aircraft trajectories so that the probability of conflict between any pair of aircraft be less than a predefined safety threshold. This problem is formulated as a constrained nonlinear programming problem, where the optimality criterion is the minimization of the deviation of the aircraft resolution trajectories from their nominal trajectories and the safety condition, i.e. keeping the conflict probability below a threshold, is enforced as a problem constraint. The case of multiple en-route aircraft flying with constant airspeed and flight level is considered, where they follow approaching multi-segment trajectories and are affected by the same uncertain wind. Numerical results are presented for a particular application and the cost of the resolution process is analyzed. Lastly, a methodology to tackle the problem of strategic aircraft conflict detection and resolution, up to 60 minutes in advance, considering wind and temperature uncertainties is presented. The problem of hundreds of aircraft flying multi-segment 3D trajectories is considered. The conflict detection is based on ensemble trajectory prediction, and it is performed using an efficient grid-based procedure. A metaheuristic approach based on the Simulated Annealing algorithm is developed to solve the conflicts. The proposed CR method generates resolution trajectories by modifying the location of the route waypoints (vectoring), with the objective of lowering the probabilities of the conflicts while also minimising the deviation from the nominal paths. The methodology is then applied to a realistic case study that considers the actual flight plans for hundreds of aircraft in the European airspace; numerical results are presented and analyzed. The work presented in this thesis constitutes a step toward the development of future decision support tools for air traffic controllers that integrate weather uncertainties, expanding the capabilities of conflict detection tools currently in use in Europe and contributing to reduce the negative impact of weather on the safety and efficiency of the air traffic

Probabilistic Aircraft Conflict Detection and Resolution Considering Wind Uncertainty

A probabilistic aircraft conflict detection and reso- lution method considering wind uncertainty is proposed in this paper. The wind components are modeled as random variables, described by a joint probability density function. The case of two en-route aircraft flying with constant airspeed in the same airspace and flight level with approaching multi-segment trajectories and affected by the same wind is considered. The conflict is characterized by the minimum distance between the aircraft and the probability of conflict. The probabilistic conflict detection is performed using the Probabilistic Transformation Method. The conflict resolution problem is formulated as a parametric optimization problem subject to constraints, being the optimality criterium the minimization of the spatial deviation from the nominal trajectory. Numerical results are presented for statistically-independent and uniformly distributed constant winds obtained from Ensemble Weather Forecasts.Ministerio de Economía y Competitividad (España) TRA2014-58413-C2-1-

Metaheuristic Approach to Probabilistic Aircraft Conflict Detection and Resolution Considering Ensemble Prediction Systems

This paper presents a methodology to tackle the problem of strategic aircraft conflict detection and resolution, up to 60 minutes in advance, considering wind and temperature uncertainties. The problem of hundreds of en-route aircraft flying multi-segmented 2D trajectories is considered. The weather uncertainty is retrieved from Ensemble Prediction Systems. The conflict detection is based on ensemble trajectory prediction, and is performed using an efficient grid-based procedure. A metaheuristic approach is developed to solve the conflicts, based on simulated annealing, which generates resolution trajectories by modifying the location of the route waypoints (vectoring), with the aim of lowering the probabilities of the conflicts while also minimising the deviation from the nominal paths. Realistic applications in scenarios with different traffic densities are presented.Ministerio de Ciencia, Innovación y Universidades(España) RTI2018-098471-B-C3

Probabilistic Aircraft Conflict Detection in the Terminal Maneuvering Area

Understanding and managing weather uncertainty is a necessity that the future Air Traffic Management system must address to increase its capacity, efficiency and safety levels. In this paper, a methodology to tackle the problem of aircraft conflict detection in the terminal maneuvering area of an airport considering wind uncertainty is presented. The wind components are modelled as random processes, characterized by a nominal and a stochastic term. The problem of two aircraft following three-dimensional multi-segment converging trajectories in the same airspace is considered. The conflict is characterized by two indicators: the distance of closest approach between the aircraft, and the conflict probability. The statistical characterization of these conflict indicators is obtained using the Probabilistic Transformation Method. Numerical results are presented for a particular conflict scenario and an uncertain vertical wind profile, obtained from a high resolution numerical weather prediction model. The results are compared with those obtained with the Monte Carlo method.Ministerio de Economía y Competitividad ( España) TRA2014-58413-CRCentro Nacional de Investigaciones Atmosféricas (NCAR), Boulder Colorad

Integrating weather impact in air traffic controller shift scheduling in remote and conventional towers

Weather affects the work of air traffic controllers, however, for staff scheduling in Remote Tower Centers (RTCs) it has not been taken into account. We study the impact of various weather phenomena on air traffic controller (ATCO) taskload through structured interviews with ATCOs. We deduce taskload-driven impact factors and the corresponding thresholds for the intensity of the weather phenomena at several Swedish airports. To account for the uncertainty in the weather prediction, we obtain probabilistic weather data from Ensemble Prediction Systems (EPSs). Then we adjust our prior Mixed Integer Programming (MIP) model for RTC staff scheduling to account for uncertain impactful weather occurrences and yield a distribution for the necessary number of ATCOs for RTC staff scheduling. Our framework can be used for conventional towers as well. We quantify the impact of weather by comparing the number of controllers necessary to operate at five Swedish airports from a remote tower during two example days in 2020, with and without taking weather events into account. In our calculations we use historical weather and flight data to show that ignoring weather impact may lead to significant understaffing at a RTC.Funding Agencies|Swedish Transport Administration (Trafikverket); SESAR JU under the European Union [783287]</p

Un paseo por el Nilo

El trabajo obtuvo un premio de la Modalidad A de los Premios Tomás García Verdejo a las buenas prácticas educativas en la Comunidad Autónoma de Extremadura para el curso 2011Se describe una experiencia de animación a la lectura a través del conocimiento de una de las grandes civilizaciones de la historia: la egipcia. Las actividades se llevaron a cabo desde la biblioteca del centro y tomando como partida la lectura de dos libros: 'Mi nombre es Stilton' y 'El misterio de la pirámide de queso'ExtremaduraES