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At least 181 records · Page 10

Stochastic Modeling of Airlines' Scheduled Services Revenue

Airlines' revenue generated from scheduled services account for the major share in the total revenue. As such, predicting airlines' total scheduled services revenue is of great importance both to the governments (in case of national airlines) and private airlines. This importance stems from the need to formulate future airline strategic management policies, determine government subsidy levels, and formulate governmental air transportation policies. The prediction of the airlines' total scheduled services revenue is dealt with in this paper. Four key components of airline's scheduled services are considered. These include revenues generated from passenger, cargo, mail, and excess baggage. By addressing the revenue generated from each schedule service separately, air transportation planners and designers are able to enhance their ability to formulate specific strategies for each component. Estimation results clearly indicate that the four stochastic processes (scheduled services components) are represented by different Box-Jenkins ARIMA models. The results demonstrate the appropriateness of the developed models and their ability to provide air transportation planners with future information vital to the planning and design processes.

Hamed, M. M.↗

Stochastic Modeling of Airlines' Scheduled Services Revenue

Airlines' revenue generated from scheduled services account for the major share in the total revenue. As such, predicting airlines' total scheduled services revenue is of great importance both to the governments (in case of national airlines) and private airlines. This importance stems from the need to formulate future airline strategic management policies, determine government subsidy levels, and formulate governmental air transportation policies. The prediction of the airlines' total scheduled services revenue is dealt with in this paper. Four key components of airline's scheduled services are considered. These include revenues generated from passenger, cargo, mail, and excess baggage. By addressing the revenue generated from each schedule service separately, air transportation planners and designers arc able to enhance their ability to formulate specific strategies for each component. Estimation results clearly indicate that the four stochastic processes (scheduled services components) are represented by different Box-Jenkins ARIMA models. The results demonstrate the appropriateness of the developed models and their ability to provide air transportation planners with future information vital to the planning and design processes.

Hamed, M. M.↗

Preliminary Evaluation of National Campaign Scenarios for Urban Air Mobility

Urban Air Mobility and Advanced Air Mobility concepts offer a novel method for transportation of passengers and cargo. Whereas the concept may reduce congestion of roads and highways, it also introduces new complexity to the National Airspace in terms of management of such operations. NASA, in partnership with FAA and industry, approaches these complexities with research and development activities such as flight tests and simulations, in order to better understand the impacts and necessary mechanisms by which these operations could be integrated. One example of such research and development activity that NASA is conducting is the Advanced Air Mobility National Campaign effort. Flight-test scenarios were proposed as part of the National Campaign and tested in simulation for evaluation with industry partners prior to the Flight test. This simulation, exercised as an engineering evaluation, provided a data collection opportunity to better understand what iterations and modifications would be needed to successfully demonstrate the flight-test scenarios in order to mature the concept of Urban Air Mobility and Advanced Air Mobility.

urban air mobility↗

Preliminary Evaluation of National Campaign Scenarios for Urban Air Mobility

Urban Air Mobility and Advanced Air Mobility concepts offer a novel method for transportation of passengers and cargo. Whereas the concept may reduce congestion of roads and highways, it also introduces new complexity to the National Airspace in terms of management of such operations. NASA, in partnership with FAA and industry, approaches these complexities with research and development activities such as flight tests and simulations, in order to better understand the impacts and necessary mechanisms by which these operations could be integrated. One example of such research and development activity that NASA is conducting is the Advanced Air Mobility National Campaign effort. Flight-test scenarios were proposed as part of the National Campaign and tested in simulation for evaluation with industry partners prior to the Flight test. This simulation, exercised as an engineering evaluation, provided a data collection opportunity to better understand what iterations and modifications would be needed to successfully demonstrate the flight-test scenarios in order to mature the concept of Urban Air Mobility and Advanced Air Mobility.

Urban Air Mobility↗

Energy conservation and air transportation

Air transportation demand and passenger energy demand are discussed, in relation to energy conservation. Alternatives to air travel are reviewed, along with airline advertising and ticket pricing. Cargo energy demand and airline systems efficiency are also examined, as well as fuel conservation techniques. Maximum efficiency of passenger aircraft, from B-747 to V/STOL to British Concorde, is compared.

Source record↗

Rendezvous strategy impacts on CTV avionics design, system reliability requirements, and available collision avoidance maneuvers

Rockwell International is conducting an ongoing program to develop avionics architectures that provide high intrinsic value while meeting all mission objectives. Studies are being conducted to determine alternative configurations that have low life-cycle cost and minimum development risk, and that minimize launch delays while providing the reliability level to assure a successful mission. This effort is based on four decades of providing ballistic missile avionics to the United States Air Force and has focused on the requirements of the NASA Cargo Transfer Vehicle (CTV) program in 1991. During the development of architectural concepts it became apparent that rendezvous strategy issues have an impact on the architecture of the avionics system. This is in addition to the expected impact on propulsion and electrical power duration, flight profiles, and trajectory during approach.

Donovan, William J.↗

Expansion of Microbial Monitoring Capabilities on the International Space Station (ISS)

Microbial monitoring is one of the tools that the National Aeronautics and Space Administration (NASA) uses on the International Space Station (ISS) to help maintain crew health and safety. In combination with regular housekeeping and disinfection when needed, microbial monitoring provides important information to the crew about the quality of the environment. Rotation of astronauts, equipment, and cargo on the ISS can affect the microbial load in the air, surfaces, and water. The current ISS microbial monitoring methods are focused on culture-based enumeration during flight and require a significant amount of crew time as well as long incubation periods of up to 5 days there by proliferating potential pathogens. In addition, the samples require return to Earth for complete identification of the microorganisms cultivated. Although the current approach assess the quality of the ISS environment, molecular technology offers faster turn-around of information particularly beneficial in an off-nominal situation. In 2011, subject matter experts from industry and academia recommended implementation of molecular-based technologies such as quantitative real-time polymerase chain reaction (qPCR) for evaluation to replace current, culture-based technologies. The RAZOR EX (BioFire Defense, Inc, Salt Lake City, UT) a ruggedized, compact, COTS (commercial off the shelf) qPCR instrument was tested, evaluated and selected in the 2 X 2015 JSC rapid flight hardware demonstration initiative as part of the Water Monitoring Suite. RAZOR EX was launched to ISS on SpaceX-9 in July 2016 to evaluate the precision and accuracy of the hardware by testing various concentrations of DNA in microgravity compared to ground controls. Flight testing was completed between September 2016 and March 2017. Data presented will detail the hardware performance of flight testing results compared to ground controls. Future goals include additional operational ground-based testing and assay development to determine if this technology can meet spaceflight microbial monitoring requirements.

Khodadad, Christina L.↗

Airspace Operations: Vision for 2045 and Beyond

We are seeing interesting changes in airspace operations. We are experiencing growth in global aviation for passenger and cargo travel. At the same time, drones of all sizes, urban air mobility, electric aircraft, commercial space transportation, supersonics, hypersonics, and increasingly autonomous vehicles will continue to mature. These operations along with current aviation will require access to airspace operations. Such access and scalability needs will only continue to increase in the future. Given that systems and procedures that will enable and support the future density and diversity takes a considerable amount of time to build and harmonize across the globe, it is appropriate that research efforts to enable 2045 operations begin now. A perfect storm is brewing as a number of factors are coming together, including: anticipated growth in diversity and density; limitations of our current system to support the growth and diversity; lack of utilization of latest technologies in an increasingly digitized world to support air traffic management; and a long lead time to conduct research, develop requirements, and built and deploy air traffic management systems. All these factors indicate that now is the time to start thinking about the needs of 2045 and beyond. In a limited manner, Unmanned Aircraft System Traffic Management (UTM) has shown that new thinking and implementation paths for airspace operations is possible. The current system as it exists is based on many assumptions and limitations of technologies (e.g., radar, human-centered voice communications) which may not be true moving forward given the technologies around us are changing. The panel will discuss the following and related topics: 1. Expected growth in density, diversity, and needed scalability, 2. Likely requirements of air traffic management system to enable and support 2045 and beyond operations, 3. Assumptions related to air traffic management and operations that need to reevaluated based on technology trends, 4. Identification of research priorities and harmonization of research across the globe, and 5. Transition approaches from current air traffic operations to new vision 2045. The panel discussion will be useful for global air traffic management researchers, managers, strategists, airspace users, air traffic management system developers and integrators, and academic researchers.

Kopardekar, Parimal H.↗

Advanced space transportation systems

Projected growth in space transportation capabilities beyond the initial Space Shuttle is discussed in terms of earth-to-low-orbit launch vehicles as well as transportation beyond low orbit (orbit transfer vehicles). Growth versions of the Shuttle and heavy-lift derivatives of the Shuttle are shown conceptually. More advanced launch vehicle concepts are also shown, based on rocket propulsion or combinations of rocket and air-breathing propulsion. Orbit transfer vehicle concepts for personnel transport and for cargo transport are discussed, including chemical rocket as well as electric propulsion. Finally, target levels of capability and efficiencies for later time periods are discussed and compared with the prospective vehicle concepts mentioned earlier.

Disher, J. H.↗

Commercial Cargo Derivative Study of the Advanced Hybrid Wing Body Configuration with Over-Wing Engine Nacelles

LM has leveraged our partnership with the Air Force Research Laboratory (AFRL) and NASA on the advanced hybrid wing body (HWB) concept to develop a commercial freighter which addresses the NASA Advanced Air Transport Technology (AATT) Project goals for improved efficiency beyond 2025. The current Air Force Research Laboratory (AFRL) Revolutionary Configurations for Energy Efficiency (RCEE) program established the HWB configuration and technologies needed for military transports to achieve aerodynamic and fuel efficiencies well beyond the commercial industry's most modern designs. This study builds upon that effort to develop a baseline commercial cargo aircraft and two HWB derivative commercial cargo aircraft to quanitify the benefit of the HWB and establish a technology roadmap for further development.

Hooker, John R.↗

Preliminary analysis of long-range aircraft designs for future heavy airlift missions

A computerized design study of very large cargo aircraft for the future heavy airlift mission was conducted using the Aircraft Synthesis program (ACSYNT). The study was requested by the Air Force under an agreement whereby Ames provides computerized design support to the Air Force Flight Dynamics Laboratory. This effort is part of an overall Air Force program to study advanced technology large aircraft systems. Included in the Air Force large aircraft program are investigations of missions such as heavy airlift, airborne missile launch, battle platform, command and control, and aerial tanker. The Ames studies concentrated on large cargo aircraft of conventional design with payloads from 250,000 to 350,000 lb. Range missions up to 6500 n.mi. and radius missions up to 3600 n.mi. have been considered. Takeoff and landing distances between 7,000 and 10,000 ft are important constraints on the configuration concepts. The results indicate that a configuration employing conventional technology in all disciplinary areas weighs approximately 2 million pounds to accomplish either a 6500-n.mi. range mission or a 3600-n.mi. radius mission with a 350,000-lb payload.

Nelms, W. P., Jr.↗

Computational Fluid Dynamics Methods Used in the Development of the Space Launch System Liftoff and Transition Lineloads Databases

The objective of this paper is to document the reasoning and trade studies that supported the selection of appropriate tools for constructing aerodynamic lineload databases for the Liftoff and Transition phases of flight for launch vehicles. These decisions were made amid the maturation of an evolving workflow for generating databases on variants of the Space Launch System launch vehicle, with most being based on results from brief developmental studies performed in response to specific, unforeseen challenges that were encountered in analyzing a given configuration. This report is intended to provide a summary of the results and the decision-making processes chronologically over the design cycles of various configurations, starting with isolated free-air bodies for the Block 1 Crew, then the Block 1B Crew and Cargo configurations, and most recently the Block 1B Crew configuration in proximity to the launch tower. The results from these analyses led to the selection of the CREATE-AV Kestrel flowsolver for simulating these problems. The need to accurately capture the expected leeward-wake flow field characteristics required the use of Delayed Detached Eddy Simulation (DDES) method, for which the vorticity magnitude was employed as the solution Adaptive Mesh Refinement (AMR) function over the off-body Cartesian grid region. In addition, the Spalart-Allmaras (SA) model is used to account for the flow turbulence effects.

Ratnayake, Nalin A.↗

UTM to AAM

This short presentation is intended to provide a a brief overview of the background of the UAS Traffic Management (UTM) concept and the legacy of work performed in the area of human factors as part of the project's research. The introduction of UTM provides the foundation for presenting the progression of the concept from low altitude airspace with small UAS to an environment with larger passenger and cargo carrying vehicles integrating into more complex airspace as part of the Advanced Air Mobility (AAM) concept. Related research and testing plans are presented to illustrate the direction of related project efforts as well as the facilities that are available to support the necessary research ahead.

UTM↗

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗

A Prognostics Framework for Battery Health Monitoring Integrated with Thermal Modeling

Urban Air Mobility (UAM) promises to revolutionize transportation in major cities, offering passenger travel, cargo delivery, and emergency medical services through a network of electric vertical takeoff and landing (eVTOL) aircraft. However, the limited range of current eVTOLs, due to the low specific energy of lithium-ion batteries along with a possibility of thermal runaway conditions poses significant safety concerns, leading to potentially compromising operational safety. To address this critical challenge, researchers are actively evaluating the impact of flight and environmental conditions on onboard lithium-ion battery health. This involves carefully assessing the performance of battery packs under laboratory and operational conditions for developing models to estimate future health using prognostics framework. This study examines the effectiveness of evaluating battery degradation leading to catastrophic failures under varying operational conditions in laboratory. These are captured using physics based models of underlying phenomenons and integrated into the prognostics framework. A fully charged battery undergoes controlled discharge cycles at varying C-rates based on the simulated power draw profile, with current and voltage, temperature data recorded throughout the experiment. The observed data provides valuable insights into how different operating conditions and mission profiles affect battery performance. This information is crucial for developing strategies to optimize battery systems, enhance range, and ultimately ensure the safe and reliable operation of UAM vehicles.

Thermal Modeling↗

A Prognostics Framework for Battery Health Monitoring Integrated with Thermal Modeling

Urban Air Mobility (UAM) promises to revolutionize transportation in major cities, offering passenger travel, cargo delivery, and emergency medical services through a network of electric vertical takeoff and landing (eVTOL) aircraft. However, the limited range of current eVTOLs, due to the low specific energy of lithium-ion batteries along with a possibility of thermal runaway conditions poses significant safety concerns, leading to potentially compromising operational safety. To address this critical challenge, researchers are actively evaluating the impact of flight and environmental conditions on onboard lithium-ion battery health. This involves carefully assessing the performance of battery packs under laboratory and operational conditions for developing models to estimate future health using prognostics framework. This study examines the effectiveness of evaluating battery degradation leading to catastrophic failures under varying operational conditions in laboratory. These are captured using physics based models of underlying phenomenons and integrated into the prognostics framework. A fully charged battery undergoes controlled discharge cycles at varying C-rates based on the simulated power draw profile, with current and voltage, temperature data recorded throughout the experiment. The observed data provides valuable insights into how different operating conditions and mission profiles affect battery performance. This information is crucial for developing strategies to optimize battery systems, enhance range, and ultimately ensure the safe and reliable operation of UAM vehicles.

Thermal Modeling↗

A Prognostics Framework for Battery Health Monitoring Integrated with Thermal Modeling

Urban Air Mobility (UAM) promises to revolutionize transportation in major cities, offering passenger travel, cargo delivery, and emergency medical services through a network of electric vertical takeoff and landing (eVTOL) aircraft. However, the limited range of current eVTOLs, due to the low specific energy of lithium-ion batteries along with a possibility of thermal runaway conditions poses significant safety concerns, leading to potentially compromising operational safety. To address this critical challenge, researchers are actively evaluating the impact of flight and environmental conditions on onboard lithium-ion battery health. This involves carefully assessing the performance of battery packs under laboratory and operational conditions for developing models to estimate future health using prognostics framework. This study examines the effectiveness of evaluating battery degradation leading to catastrophic failures under varying operational conditions in laboratory. These are captured using physics based models of underlying phenomenons and integrated into the prognostics framework. A fully charged battery undergoes controlled discharge cycles at varying C-rates based on the simulated power draw profile, with current and voltage, temperature data recorded throughout the experiment. The observed data provides valuable insights into how different operating conditions and mission profiles affect battery performance. This information is crucial for developing strategies to optimize battery systems, enhance range, and ultimately ensure the safe and reliable operation of UAM vehicles.

Thermal Modeling↗