Sergio Ruiz

A causal model to explore the ACAS induced collisions

Current Air Traffic Management research programs (i.e. Single European Sky ATM (air traffic management) Research (SESAR), next generation air transportation system (NextGen)), try to overcome airside capacity shortages while improving cost-efficient operations and safety. An increment in the airspace traffic density can lead to congested traffic scenarios for which it becomes necessary to develop new safety procedures that address multithread threats. This paper considers some of the difficulties in establishing validation of the airborne collision avoidance system (ACAS), which constitutes the last-resort for reducing the risk of near mid-air collision between aircraft in a multithread scenario. A causal model that is specified in Colored Petri Net (CPN) formalism is presented as a key approach to analyze the state space of a congested traffic scenario in which the events that could transform a conflict into a collision are identified, providing a challenging tool not only for validation but also for the implementation of a new ACAS logic. The InCAS EuroControl simulator has been used to illustrate the importance of cause–effect analysis for the relationships between various encounters that arise in a multithread scenario, in which TCAS II v. 7.1 fails to avoid a collision when two Resolution Advisories are issued without consideration of the downstream effects.

Relational Time-space Data Structure to Enable Strategic De-confliction with a Global Scope in the Presence of a Large Number of 4D Trajectories

This paper introduces an innovative framework for the design and implementation of new air traffic management (ATM) decision support tools for strategic de-confliction. The main key implementation aspects to support an efficient state space analysis of more than 4000 4D Trajectories in the entire European ATM is described. The paper focuses on the innovative aspects developed to improve Spatial Data Structures, i.e. the paper focuses on the new Relational Space Data Structures and Time-Space Data Structures concepts, that allow supporting strategic Conflict Detection (CD) between a large number of 4D trajectories and a wide airspace region. Results have been tested in the WP-E project STREAM, whose aim is to coordinate the entire European ATM traffic at strategic and tactical levels, thus requiring the processing of large number of trajectories under heavy traffic conditions. The new and efficient CD algorithms presented in this paper may contribute to increase airspace capacity in the SESAR framework for the period up to 2020.

A Novel Performance Framework and Methodology to Analyze the Impact of 4D Trajectory Based Operations in the Future Air Traffic Management System

The introduction of new Air Traffic Management (ATM) concepts such as Trajectory Based Operations (TBO) may produce a significant impact in all performance areas, that is, safety, capacity, flight efficiency, and others. The performance framework in use today has been tailored to the operational needs of the current ATM system and must evolve to fulfill the new needs and challenges brought by the TBO content. This paper presents a novel performance assessment framework and methodology adapted to the TBO concept. This framework can assess the key performance areas (KPAs) of safety, capacity, and flight efficiency; equity and fairness are also considered in this research, in line with recent ATM trends. A case study is presented to show the applicability of the framework and to illustrate how some of the complex interdependencies among KPAs can be captured with the proposed approach. This case study explores the TBO concept of “strategic 4D trajectory deconfliction,” where the early separation tasks of 4D trajectories at multisector level are assessed. The framework presented in this paper could potentially support the target-setting and performance requirements identification that should be fulfilled in the future ATM system to ensure determined levels of performance.

Reduction of the surface colour variability of thermally modified Eucalyptus globulus wood by colour pre-grading and homogeneity thermal treatment

A new method that consists of combining wood pre-grading by surface colour followed by the application of homogeneity thermal treatments is proposed to reduce the surface colour variability of the thermally modified blue gum wood. To identify the conditions of the homogeneity thermal treatment for two pre-graded groups with different initial surface colours (pinkish and yellowish), the effects of applying 25 different thermal treatment intensities to such groups were analysed. The effects of this method on mass loss and volumetric swelling were also analysed. Results show that an optical pre-grading of the wood samples and treatments under different conditions can reduce the colour variability of the blue gum wood samples, as well as the volumetric swelling. Mass loss was not homogenised after the treatment, but the difference of masses between the two groups was similar to their untreated state. The application of this new methodology may be of interest for the sawn timber industry to bring more uniform boards on the markets and to promote Eucalyptus globulus as a price-competitive and sustainable alternative timber.