In het voorjaar van 2015 hebben de gemeente Eindhoven en Schiphol Real Estate het lectoraat Brainport van Fontys Hogeschool Management Economie en Recht gevraagd een serie scenario’s op te stellen voor de aanpak en toekomstige ontwikkeling van het kantorencluster Flight Forum. Dit cluster verkeert al enige tijd in zwaar weer en heeft, zoals veel vergelijkbare kantorengebieden, de voorbije jaren te kampen gehad met stagnerende ontwikkelingen en oplopende leegstand. Bij nadere beschouwing blijkt Flight Forum een aanschouwelijke casus om de stand van de Eindhovense kantorenmarkt af te lezen. Daarbij wordt eens te meer duidelijk dat kantorenleegstand, en de aanpak daarvan, niet alleen een mechanisme is van bvo’s en meterprijzen, maar inzicht vergt in de kwaliteiten van de plek, de daadwerkelijke gebruikers en de aanwezige dynamiek.
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This paper describes the concept of a new algorithm to control an Unmanned Aerial System (UAS) for accurate autonomous indoor flight. Inside a greenhouse, Global Positioning System (GPS) signals are not reliable and not accurate enough. As an alternative, Ultra Wide Band (UWB) is used for localization. The noise is compensated by combining the UWB with the delta position signal from a novel optical flow algorithm through a Kalman Filter (KF). The end result is an accurate and stable position signal with low noise and low drift.
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Reflections on skill development theory and simulation game-play practice, using MS Flight Simulator and the MSP Challenge Simulation Platform as cases.
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Sickness absenteeism among flight crews is a pervasive problem disruptive to operations and costly for the employer. According to literature, exposure to certain schedule attributes has been associated with adverse health issues. However, the relationship between schedule characteristics and sickness absenteeism remains unclear. Therefore, the aim of this study is to identify schedule characteristics increasing the odds of sickness absenteeism based on historical data. Here, data records for each flight crew member were obtained from a Dutch low-cost airline in the period between 1 January 2018 and 24 January 2020. Schedule characteristics with an adverse effect on both the circadian and/or social rhythm, as identified in literature, were extracted from the available data, and included in the model. Exploration on these potential harmful schedule attributes was done using two generalised additive models. After adjusting for the socio-demographic and work-related confounding variables, simulations revealed that employees exposed to night shifts, backward, and forward rotations over a thirty-day period were significantly more likely to report sick. Furthermore, employees who flew four sectors showed higher odds to call in sick compared to employees who flew two sectors. Based on the results, it is recommended to schedule either sufficient rest periods after exposure or limit the occurrence of the identified schedule attributes.
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For long flights, the cruise is the longest phase and where the largest amount of fuel is consumed. An in-cruise optimization method has been implemented to calculate the optimal trajectory that reduces the flight cost. A three-dimensional grid has been created, coupling lateral navigation and vertical navigation profiles. With a dynamic analysis of the wind, the aircraft can perform a horizontal deviation or change altitudes via step climbs to reduce fuel consumption. As the number of waypoints and possible step climbs is increased, the number of flight trajectories increases exponentially; thus, a genetic algorithm has been implemented to reduce the total number of calculated trajectories compared to an exhaustive search. The aircraft’s model has been obtained from a performance database, which is currently used in the commercial flight management system studied in this paper. A 5% average flight cost reduction has been obtained.
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Aircraft require significant quantities of fuel in order to generate the power required to sustain a flight. Burning this fuel causes the release of polluting particles to the atmosphere and constitutes a direct cost attributed to fuel consumption. The optimization of various aircraft operations in different flight phases such as cruise and descent, as well as terminal area movements, have been identified as a way to reduce fuel requirements, thus reducing pollution. The goal of this chapter is to briefly explain and apply different metaheuristic optimization algorithms to improve the cruise flight phase cost in terms of fuel burn. Another goal is to present an overview of the most popular commercial aircraft models. The algorithms implemented for different optimization strategies are genetic algorithms, the artificial bee colony, and the ant colony algorithm. The fuel burn aircraft model used here is in the form of a Performance Database. A methodology to create this model using a Level D aircraft research flight simulator is briefly explained. Weather plays an important role in flight optimization, and so this work explains a method for incorporating open source weather. The results obtained for the optimization algorithms show that every optimization algorithm was able to reduce the flight consumption, thereby reducing the pollution emissions and contributing to airlines’ profit margins.
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The automatic identification of unstable approaches from flight data by Coumou, Hunink and de Boer. Unstable approaches have been identified as a major risk factor in approach and landing accidents and runway excursions, but hardly ever lead to go-arounds despite strong safety initiatives.
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Several studies have shown that flying electric between the so-called ABC-islands in the Caribbean (i.e., Aruba, Bonaire and Curaçao) is feasible with the upcoming first generation of battery-electric aircraft. This paper presents a real-world case study that deals with the technical and operational characteristics of electric flight in that region. With that purpose, the Aruba Airport Authority (AAA) commissioned this investigation, which involved numerous local stakeholders, such as airlines, energy providers and navigation services. This study involves two commuter electric aircraft under development, aiming to investigate how they fit in the current operational scheme of three local airlines and three conventional aircraft types in terms of technology, capacity, schedule, performance, CO2 emissions and fuel costs. Conclusions indicate that a transition to batter-electric aircraft is feasible with regards to the aforementioned criteria and with the current technology and energy density of batteries.
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This paper presents how the application of the STPA method might support the evaluation of fighter pilots training programs and trigger procedural and technological changes. We applied the STPA method by considering the safety constraints documented in the Standard Operating Procedures (SOPs) of a South European Air Force and regard a flight of a two F-16 aircraft formation. In this context, we derived the control actions and feedback mechanisms that are available to the leader pilot during an Aircraft Combat Maneuver (ACM) mission, and we developed the control flow diagram based on the aircraft manuals. We compared the results of each analysis step with the respective flight training program, which is based on a mixed skill and rule-based decision-making, and we examined the role of the feedback mechanisms during multiple safety constraints violations. The analysis showed that: the flight training program under study does not structurally include cases of infringement of multiple safety constraints; the maintenance of some safety constraints are not supported by alerts, or rely on only one human sense; the existing procedures do not refer to the prioritization of pilot actions in cases of violation of multiple safety constraints; operation manuals do not address the cases of possible human performance deterioration when simultaneous information from feedback mechanisms is received. The results demonstrated the benefits of the STPA method, the application of which uncovered various inadequacies in the flight training program studied, some of them related to the F-16 cockpit ergonomics. The analysis lead to recommendations in regard to the amendment of the corresponding fighter pilots training program, and the conduction of further research regarding the aircraft – pilot interaction when multiple safety constraints are violated. The approach presented in this paper can be also followed for the (re)evaluation of flight training schemes in military, civil and general aviation, as well by any human-machine interface intensive domain.
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Twirre is a new architecture for mini-UAV platforms designed for autonomous flight in both GPS-enabled and GPS-deprived applications. The architecture consists of low-cost hardware and software components. High-level control software enables autonomous operation. Exchanging or upgrading hardware components is straightforward and the architecture is an excellent starting point for building low-cost autonomous mini-UAVs for a variety of applications. Experiments with an implementation of the architecture are in development, and preliminary results demonstrate accurate indoor navigation
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