444 research outputs found

    Towards climate-neutral aviation: Assessment of maintenance requirements for airborne hydrogen storage and distribution systems

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    Airlines are faced with the challenge of reducing their environmental footprint in an effort to push for climate-neutral initiatives that comply with international regulations. In the past, the aviation industry has followed the approach of incremental improvement of fuel efficiency while simultaneously experiencing significant growth in annual air traffic. With the increase in air traffic negating any reduction in Greenhouse Gas (GHG) emissions, more disruptive technologies such as hydrogen-based onboard power generation are required to reduce the environmental impact of airline operations. However, despite initial euphoria and first conceptual studies for hydrogen-powered aircraft several decades ago, there still has been no mass adoption to this day. Besides the challenges of a suitable ground infrastructure, this can partly be attributed to uncertainties with the associated maintenance requirements and the expected operating costs to demonstrate the economic viability of this technology. With this study, we address this knowledge gap by estimating changes towards scheduled maintenance activities for an airborne hydrogen storage and distribution system. In particular, we develop a detailed system design for a hydrogen-powered, fuel-cell-based auxiliary power generation and perform a comparative analysis with an Airbus A320 legacy system. That analysis allows us to (a) identify changes for the expected maintenance effort to enhance subsequent techno-economic assessments, (b) identify implications of specific design assumptions with corresponding maintenance activities while ensuring regulatory compliance and (c) describe the impact on the resulting task execution. The thoroughly examined interactions between system design and subsequent maintenance requirements of this study can support practitioners in the development of prospective hydrogen-powered aircraft. In particular, it allows the inclusion of maintenance implications in early design stages of corresponding system architectures. Furthermore, since the presented methodology is transferable to different design solutions, it provides a blueprint for alternative operating concepts such as the complete substitution of kerosene by hydrogen to power the main engines

    Admissions Magazine Fall 2023

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    Altitude: Breaking Ground in Stellar Research Education at a Higher Altitude: At Embry-Riddle Aeronautical University, Daring to Think Big and Push Boundaries is a Way Of Life. Students Soar: Where the Sky Is No Limit Engineering For a Better Tomorrow A Space Where Stars Are Born A Learning Space That Suits You: EagleSat Lab Space Physics Student Follows Her Research to A Stellar Discovery Leverage Your Experience A Wealth of International Knowledge Isabella Novo is Sure to Shine at NASA Community Through Shared Interest Eagles Reporting for Duty Fueling the Future? We Rock It! A New Space for Safety Quantum Gravity: Student Researchers Make Quantum Leaps Building Skills With Clubs Flight Training at New Altitudes Contributing to Aviation Safety Tech Research from Day One Two Degrees of Dedication SAP Partnership Produces Supply Chain Standouts Aspiring Pilot Gets a Lift On Course to the Boeing Company Empowering Student Voices Next Stepshttps://commons.erau.edu/admissions-magazine/1007/thumbnail.jp

    A reduced order modeling methodology for the parametric estimation and optimization of aviation noise

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    The successful mitigation of aviation noise is one of the key enablers of sustainable aviation growth. Technological improvements for noise reduction at the source have been countered by increasing number of operations at most airports. There are several consequences of aviation noise including direct health effects, effects on human and non-human environments, and economic costs. Several mitigation strategies exist including reduction of noise at source, land-use planning and management, noise abatement operational procedures, and operating restrictions. Most noise management programs at airports use a combination of such mitigation measures. To assess the efficacy of noise mitigation measures, a robust modeling and simulation capability is required. Due to the large number of factors which can influence aviation noise metrics, current state-of-the-art tools rely on physics-based and semi-empirical models. These models help in accurately predicting noise metrics in a wide range of scenarios; however, they are computationally expensive to evaluate. Therefore, current noise mitigation studies are limited to singular applications such as annual average day noise quantification. Many-query applications such as parametric trade-off analyses and optimization remain elusive with the current generation of tools and methods. There are several efforts documented in literature which attempt to speed up the process using surrogate models. Techniques include the use of pre-computed noise grids with calibration models for non-standard conditions. These techniques are typically predicated on simplifying assumptions which greatly limit the applicability of such models. Simplifying assumptions are needed to downsize the number influencing factors to be modeled and make the problem tractable. Existing efforts also suffer due to the inclusion of categorical variables for operational profiles which are not conducive to surrogate modeling. In this research, a methodology is developed to address the inherent complexities of the noise quantification process, and thus enable rapid noise modeling capabilities which can facilitate parametric trade-off analysis and optimization efforts. To achieve this objective, a research plan is developed and executed to address two major gaps in literature. First, a parametric representation of operational profiles is proposed to replace existing categorical descriptions. A technique is developed to allow real-world flight data to be efficiently mapped onto this parametric definition. A trajectory clustering method is used to group similar flights and representative flights are parametrized using an inverse-map of an aircraft performance model. Next, a field surrogate modeling method is developed based on Model Order Reduction techniques to reduce the high dimensionality of computed noise metric results. This greatly reduces the complexity of data to be modeled, and thus enables rapid noise quantification. With these two gaps addressed, the overall methodology is developed for rapid noise quantification and optimization. This methodology is demonstrated on a case study where a large number of real-world flight trajectories are efficiently modeled for their noise results. As each such flight trajectory has a unique representation, and typically lacks thrust information, such noise modeling is not computationally feasible with existing methods and tools. The developed parametric representations and field surrogate modeling capabilities enable such an application.Ph.D

    A comprehensive approach to assess transportation system resilience towards disruptive events. Case study on airside airport systems

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    Transportation system resilience towards events that disrupt system scheduling and nominal functioning is a key challenge for both planners and transport operators. The development of effective policies to enhance resilience requires the analysis of the relationships between the type of disruptive event, the characteristics of the transport system under analysis and its response. This paper aims to contribute to this topic by providing some vulnerability and resilience indices for a complex transport node (airport) within a comprehensive framework based on an element-by-element approach able to identify both disturbances for which transportation systems are more vulnerable (or more resilient) and responses in terms of vulnerability and resilience. Infrastructural, organizational and technological transportation system elements that are more likely affected by given disruptions are the starting point for clustering possible disruptive events. The approach has been tested by simulating four European airports, for which the effects of different types of disruption have been discussed. The obtained results show that the responses of transport system elements to the same type of disruptive events may be different, according to several factors depending on both system features and use of resources. Furthermore, the duration of the disturbance may be relevant for the system vulnerability, while resilience and vulnerability do not necessarily vary in the same way

    Optimal Sequencing and Scheduling Algorithm for Traffic Flows Based on Extracted Control Actions Near the Airport

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    This dissertation seeks to design an optimization algorithm, based on naturalistic flight data, with emphasis on safety to perform a benefits\u27 analysis when sequencing and scheduling aircraft at the runway. The viability of creating a decision-support tool to aid air traffic controllers in sequencing and optimizing airport operations is evaluated through the benefits\u27 analysis. Air traffic control is a complex and critical system that ensures the safe and efficient movement of aircraft within the airspace. This is particularly true in the immediate vicinity of an airport. Unlike in en-route or terminal area airspace where aircraft usually traverse well established routes and procedures, near the airport after completing a standard arrival procedure, the routes to the final approach are only partially defined. With safety being the foremost priority, the local tower controllers monitor and maintain separation between aircraft to prevent collisions and ensure the overall safety of the airspace. This involves constant surveillance, coordination, and decision-making to manage the dynamic movement of aircraft, changing weather conditions, and potential hazards. All the while, the controllers make decisions regarding tromboning or vectoring based on various factors, including traffic volume, airspace restrictions, weather conditions, operational efficiency, and safety considerations to ensure a safe traffic sequencing of aircraft at the runway. A novel framework is presented for modeling, characterizing, and clustering aircraft trajectories by extracting traffic control decisions of air traffic controllers. A hidden Markov model was developed and applied to transform trajectories from a sequence of temporal spatial position reports to a series of control actions. The edit distance is utilized for quantifying the dissimilarity of two variable-length trajectory strings, followed by the application of k-medoids algorithm to cluster the arrival flows. Next, a repeatable process for detecting and labeling outlier trajectories within a cluster is introduced. Through application on a set of historical trajectories at Ronald Reagan Washington National Airport (DCA), it is demonstrated that the proposed clustering framework overcomes the deficiency of the classical approach and successfully captures the arrival flows of trajectories, that undergo similar control actions. Leveraging on the set of arrival flows, statistical and machine learning models of air traffic controllers are created and evaluated when ordering aircraft to land at the runway. The potential inefficiencies are identified at DCA when sequencing aircraft. As such, there is a potential performance gap, and it appears that there is room for additional sequence optimization. With the goal of overcoming the potential inefficiencies at DCA, a mixed-integer zero-one formulation is designed for a single runway that takes into consideration safety constraints by means of separation constraints between aircraft imposed at each metering point from the entry to the airspace until landing. With the objective of maximizing runway throughput and minimizing the traversed distance, the model sequences and schedules arrivals and departures and generates safe and conflict-free arrival trajectories to actualize that scheduling. The output of the optimization shows that the model successfully recovers approximately 52% of the performance gap between the actual distance traversed and idealized (cluster centroids) distance traversed by all arrival aircraft. Moreover, each arrival aircraft, on average, traverses 2.12 nautical miles shorter than its historical trajectory and thus saving approximately 10 US gallons of jet fuel. By showcasing the potential benefits of the optimization, this dissertation takes a step towards achieving the long-term vision of developing a decision-support tool to assist air traffic controllers in optimally sequencing and scheduling aircraft. To fully leverage the potential benefits of optimization, further development and refinement of the algorithm are necessary to align it with real-world operational demands. As future work, the research would be expanded to integrate uncertainties like weather conditions, wind directions, etc. into the optimization

    Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey

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    Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, the integration of UAM into existing transportation systems is a complex task that requires a thorough understanding of its impact on traffic flow and capacity. In this paper, we conduct a survey to investigate the current state of research on UAM in metropolitan-scale traffic using simulation techniques. We identify key challenges and opportunities for the integration of UAM into urban transportation systems, including impacts on existing traffic patterns and congestion; safety analysis and risk assessment; potential economic and environmental benefits; and the development of shared infrastructure and routes for UAM and ground-based transportation. We also discuss the potential benefits of UAM, such as reduced travel times and improved accessibility for underserved areas. Our survey provides a comprehensive overview of the current state of research on UAM in metropolitan-scale traffic using simulation and highlights key areas for future research and development

    Enhancing the reliability of electric transportation motors through insulation coordination and improved qualification

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    The ambitious goals of increasing the efficiency, performance and power densities of transportation drives cannot be met with compromises in the motor reliability. For the insulation specialists the challenge will be critical as the use of wide-bandgap converters (WBG, based on SiC and GaN switches) and the higher operating voltages expected for the next generation drives will enhance the electrical stresses to unprecedented levels. It is expected for the DC bus in aircrafts to reach 800 V (split +/-400 V) and beyond, driven by the urban air mobility sector and the need for electrification of electro-mechanical/electro-hydraulic actuators (an essential part of the "More Electric Aircraft" concept). Simultaneously the DC bus in electric vehicles (EV) traction motors is anticipated to increase up to 1200 V very soon. The electrical insulation system is one of the most delicate part of the machine in terms of failure probability. In particular, the appearance of partial discharges (PD) is disruptive on the reliability of the drive, especially under fast repetitive transients. Extensive experimental activity has been performed to extend the body of knowledge on PD inception, endurance under PD activity, and explore and identify new phenomena undermining the reliability. The focus has been concentrated on the impact of the WGB-converter produced waveforms and the environmental conditions typical of the aeronautical sector on insulation models. Particular effort was put in the analysis at the reduced pressures typical of aircraft cruise altitude operation. The results obtained, after a critical discussion, have been used to suggest a coordination between the insulation PD inception voltage with the converter stresses and to propose an improved qualification procedure based on the existing IEC 60034-18-41 standard.Gli obiettivi ambiziosi di aumentare l'efficienza, le prestazioni e le densità di potenza degli azionamenti per il trasporto non possono essere raggiunti con compromessi sulla affidabilità dei motori. Per gli specialisti dell'isolamento la sfida sarà cruciale, poiché sia l'uso di convertitori a wide-bandgap (WBG) basati su semiconduttori SiC e GaN, sia le tensioni operative più elevate previste per i prossimi azionamenti, aumenteranno gli stress elettrici a livelli senza precedenti. Si prevede che il bus DC negli aeromobili raggiunga gli 800 V (split +/-400 V) e oltre, sotto la spinta del settore della mobilità aerea urbana e dalla necessità di elettrificare gli attuatori elettromeccanici/elettroidraulici (parte essenziale del concetto di "More Electric Aircraft"). Contemporaneamente, si stima che presto nei motori per trazione di veicoli elettrici il DC bus aumenterà fino a 1200 V. Il sistema di isolamento elettrico è una delle parti più delicate di una macchina elettrica in termini di probabilità di guasto. In particolare, la comparsa di scariche parziali (PD) è deleteria per l'affidabilità dell'azionamento, soprattutto in presenza di transitori veloci e ripetitivi. In questa tesi è stata condotta un'ampia attività sperimentale per ampliare le conoscenze sull'innesco di PD, sulla resistenza dei materiali in loro presenza e per identificare nuovi fenomeni che compromettono l'affidabilità dell'isolante. L'attenzione si è concentrata sull'impatto che hanno le forme d'onda prodotte da convertitori WGB e le condizioni ambientali tipiche del settore trasporti su modelli di isolamento. Particolare impegno è stato profuso nell'analisi alle pressioni ridotte tipiche del funzionamento alle quote di crociera degli aerei di linea. I risultati ottenuti, dopo una discussione critica, sono stati utilizzati per suggerire un coordinamento tra le tensione di innesco di scarica e gli stress del convertitore, al fine di proporre una procedura di qualificazione migliorata basata sulla già esistente norma IEC 60034-18-41

    Secure Communications in Next Generation Digital Aeronautical Datalinks

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    As of 2022, Air Traffic Management (ATM) is gradually digitizing to automate and secure data transmission in civil aviation. New digital data links like the L-band Digital Aeronautical Communications System (LDACS) are being introduced for this purpose. LDACS is a cellular, ground-based digital communications system for flight guidance and safety. Unfortunately, LDACS and many other datalinks in civil aviation lack link layer security measures. This doctoral thesis proposes a cybersecurity architecture for LDACS, developing various security measures to protect user and control data. These include two new authentication and key establishment protocols, along with a novel approach to secure control data of resource-constrained wireless communication systems. Evaluations demonstrate a latency increase of 570 to 620 milliseconds when securely attaching an aircraft to an LDACS cell, along with a 5% to 10% security data overhead. Also, flight trials confirm that Ground-based Augmentation System (GBAS) can be securely transmitted via LDACS with over 99% availability. These security solutions enable future aeronautical applications like 4D-Trajectories, paving the way for a digitized and automated future of civil aviation
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