Results for “UAM” — Page 29

NASA NTRSDate not supplied

Data Science and Urban Air Mobility: Challenges and Opportunities

Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Urban Air Mobility↗

NASA NTRS2020

Data Science and Urban Air Mobility: Challenges and Opportunities

Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Urban Air Mobility↗

NASA NTRSDate not supplied

Data Science Challenges for Urban Air Mobility

Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Data Science↗

NASA NTRSDate not supplied

Control Concepts for Simplified Vehicle Operations of a Quadrotor eVTOL Vehicle

Urban Air Mobility (UAM) is a future mode of transportation that will require revolutionary new vehicle concepts and operations. One of the many challenges that these vehicles face is a complex flight control task in a challenging urban environment and in different flight regimes such as hover, forward flight as well as the transitions between both, with a focus on a low workload and minimum required pilot training. This paper discusses the development and evaluation of simplified vehicle operations concepts using representative aircraft models, controls, inceptors and displays. These four aspects are inseparably interconnected. This simplified vehicle operations concept will be evaluated by performing relevant operations within a realistic urban environment. Handling quality evaluations will be performed using modified Mission Task Elements, or Handling Quality Task Elements. This paper focuses on the initial development of controls, inceptors and displays.

Thomas Lombaerts↗

NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management of Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope↗

NASA NTRSDate not supplied

ATO UAS Leadership Team

ATM-X overview with a focus on UAM sub-project

ATM-X↗

NASA NTRSDate not supplied

Operational Analysis of Vertiport Surface Topology

Urban Air Mobility (UAM) concepts and technologies are being developed to safely enable operations of small, electric-powered or hybrid, pilot-optional, vertical-takeoff-and-landing (VTOL) passenger and cargo aircraft at vertiport facilities in urban and suburban environments. It is likely that many of the highest demand locations for vertiports will be in space constrained urban environments, requiring vertiport designs to maximize throughput within a compact surface footprint. This paper presents several generic vertiport topology design approaches and evaluates their relative surface area utilization and operational efficiency under different wind constrained configurations while meeting safety driven spacing constraints derived from heliport design standards and subject matter expert interviews.

Urban air mobility↗

NASA NTRSDate not supplied

Multirotor Configuration Trades Informed by Handling Qualities for Urban Air Mobility Application

Many contemporary Advanced Air Mobility (AAM), and more specifically, urban air mobility (UAM) vehicle designers are attracted to variable rotor speed-controlled designs with multiple rotors because of the great potential for mass savings compared to more traditional, variable blade pitch-controlled vehicles. These designs are based on the assumption that the stability and control of recreation or basic utility-sized drones can be scaled to larger passenger-sized vehicles. Previous work had shown the challenges in stabilizing passenger-sized quadcopters. In this study, power constraints were made less restrictive and varied, allowing more control power. Motor parameters such as efficiency, nominal voltage and current operating point, and rise time of the rotor speed controller step response were studied. By fixing the efficiency of the motor to 95% and assuming a motor voltage to current ratio of 2.0 (previously, assumed to be 1.0), the authors were able to stabilize the quadcopter in the roll axis because this allowed the vehicle to achieve adequate rise times between 0.4 and 0.8 s. This motor optimization was extended to a hexacopter and octocopter designed to the same payload size and mission as the quadcopter. The three vehicle configurations and their motor speed controllers were compared. It was found that while hexacopter and octocopter required more mass and overall power; all three configurations had similar margins required for control. However, the hexacopter and octocopter were able to use this power margin to achieve lower rise times (i.e. the vehicle responded more quickly to pilot inputs) than the quadcopter, with the octocopter having the lowest rotor response rise time of the three vehicle configurations studied.

Multirotor↗

NASA NTRSDate not supplied

Thermal Management System Design for Electrified Aircraft Propulsion Concepts

This paper describes the development of thermal management systems (TMS) for three electrified aircraft propulsion (EAP) vehicle concepts released by NASA that span the UAM, regional, and single-aisle markets. For each EAP concept, a conventional TMS is designed for two electric component technology levels: state of the art and advanced. The goals for the paper are to compare the TMS designs for the above EAP concepts, to study how changes in requirements affect the TMS subcomponents, and to develop generalized TMS sizing relations. Each conventional TMS concept utilizes a liquid-based cooling methodology and is designed to cool the EAP electrical components only. The design parameters considered in this study include TMS architecture variation due to differing vehicle cooling requirements, electrical component efficiencies, vehicle total fuel burn or energy consumption, and electrical component operating temperatures. Results show that cooling components with low temperature limits increases TMS weight and demonstrate that efficiency gains of the specific technologies can net a lower weight TMS system despite more stringent temperature limits.

Thermal Management System↗

NASA NTRSDate not supplied

Autonomous Contingency Management In Urban Air Mobility: The Communication Network Awareness Machine System

Next Generation Air Transportation System (NextGen) has begun the modernization of the nation’s air transportation system (NAS), with goals to improve system safety, increase operation efficiency and capacity, provide enhanced predictability, resilience and robustness [1]. The overall objective of the Air Traffic Management-eXploration (ATM-X) project is to facilitate the goals of NextGen by conducting research to enable the growing demand of new, mission variant, air vehicles with safe access to the NAS. The implementation and utilization of new and burgeoning technologies that are both flexible, scalable, and systematically user-focused are requisite for ATM-X to achieve its intention of NAS safe entry [2]. Researchers from NASA Langley’s Flight Deck Integration Team have developed a system architecture that would allow ATM-X to leverage the necessary capabilities of an Increasingly Autonomous System (IAS), machine-agent that will promote the safe access and operation of air vehicles within what has become the byproduct of NextGen modernization, a Net-Centric airspace architecture and an Urban Air Mobility (UAM) community. Conducting flight operations within this type of architecture constrains the human-agent’s natural ability by data management. When the massive volume of data, its types, and the acquisition speed at which the data is ingested is observed it becomes evident that the human-agent will be functioning at an operational disadvantage. Therefore, the development and integration of intelligent machine-agents into the flight deck are a necessary implementation to achieve ATM-X overall objective of safe access and operation in the NAS.

Urban Air Mobility↗

NASA NTRSDate not supplied

More / All Electric Vertical Take-Off and Landing (VTOL) Vehicle Sensitivities to Propulsion and Power Performance

Battery power and energy density are important parameters for the emerging concepts for more / all-electric vehicles. Electric propulsion and power system performance is also important. To better understand how electric propulsion and power systems component performance influences overall vehicle design, a sensitivity assessment was performed noting changes in vehicle gross weight and energy usage. Updated versions of the Revolutionary Vertical lift Technology (RVLT) Project vertical take-off and landing (VTOL) urban air mobility (UAM) reference vehicles and missions were used. NASA electric vehicle studies are discussed which were used to help select the range of electric propulsion and power system performance parameters used in this assessment. Thermal management systems (TMS) considerations are also important; new and innovative power management and distribution systems can reduce electric system weight and losses, reducing thermal management constraints often imposed by electric systems modest maximum use temperatures. Vehicles with higher disk loadings (smaller rotors) require higher power levels per unit weight for VTOL operations, which make them more sensitive to electric system weights and efficiencies. Battery, all-electric vehicles show different sensitivities to component performance than turboelectric or hybrids systems. Battery, all-electric propulsion systems may increase vehicle weight and size, but still results in lower mission energy usage than their hydrocarbon-fueled versions. Significant vehicle weight growth to electric propulsion and power system power-to-weight reductions also occurs at different levels among the various concepts. From these results, one can more readily identify required component performance levels, potential component choices or, research and development paths.

Electric Propulsion Systems (Aircraft)↗

NASA NTRSDate not supplied

Thermal Management System Design for Electrified Aircraft Propulsion Concepts

This paper describes the development of thermal management systems (TMS) for three electrified aircraft propulsion (EAP) vehicle concepts released by NASA that span the UAM, regional, and single-aisle markets. For each EAP concept, a conventional TMS is designed for two electric component technology levels: state of the art and advanced. The goals for the paper are to compare the TMS designs for the above EAP concepts, to study how changes in requirements affect the TMS subcomponents, and to develop generalized TMS sizing relations. Each conventional TMS concept utilizes a liquid-based cooling methodology and is designed to cool the EAP electrical components only. The design parameters considered in this study include TMS architecture variation due to differing vehicle cooling requirements, electrical component efficiencies, vehicle total fuel burn or energy consumption, and electrical component operating temperatures. Results show that cooling components with low temperature limits increases TMS weight and demonstrate that efficiency gains of the specific technologies can net a lower weight TMS system despite more stringent temperature limits.

Thermal management system↗

NASA NTRS2020

Demand Forecast Model Development and Scenarios Generation For Urban Air Mobility Concepts

The purpose of this project is to estimate the demand for various Urban Air Mobility Concepts (UAM) of Operations and to generate scenarios for use in analysis and simulations. The demand forecast model, previously developed under NASA/NIA Contract No: NNL13AA08B; Task Order No: NNL16AA36T, for an urban on-demand air-taxi commuter concept is the basis for this work.

M. Rimjha↗

NASA NTRS2020

Solid-state Architecture Batteries for Enhanced Rechargeability and Safety (SABERS)

All-electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria. The performance metrics for eVTOL craft, such as specific energy and cycle life, are at least 2 times greater than those of electric automobiles. Furthermore, safety is essential for operation of commercial electric aerovehicles. Preliminary systems level analysis studies have indicated that there are five key properties which must be optimized for successful implementation of battery systems. Those five key criteria are safety, energy density, power, packaging design and scalability. Current state-of-the-art (SOA) lithium-ion batteries meet or exceed the requirements for electric aviation in the areas of power and scalability, yet are insufficient in the key performance criteria of energy, safety and packaging design. The SABERS concept proposes a battery that meets all five key performance criteria through the development of a solid-state architecture cell design utilizing high energy density and power density sulfur-selenium cathode with a lithium metal anode. Data will be presented demonstrating high performing sulfur - selenium cathode that offers a balanced energy to power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This cathode is being developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. Novel processing methods allow developing solid-state electrolyte that is a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. The all solid-state lithium-sulfur-selenium cell design enables the implementation of a bipolar stack configuration, which has the advantages of reducing overall cell weight, reducing the amount of interfaced connections for the cell, and minimizing cooling requirements for the battery. In particular, the solid-state design allows for a serial stacking configuration to enable dense packaging of the cells within the bipolar stack. Lastly, optimization of battery components occurs through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a solid-state battery with operational temperatures from 0 °C to 150 °C which provides the required energy density, discharge rate, and inherent safety to meet strict aerospace performance criteria.

solid state batteries↗

NASA NTRSDate not supplied

More / All Electric Vertical Take-Off and Landing (VTOL) Vehicle Sensitivities to Propulsion and Power Performance

Battery power and energy density are important parameters for the emerging concepts for more / all-electric vehicles. Electric propulsion and power system performance is also important. To better understand how electric propulsion and power systems component performance influences overall vehicle design, a sensitivity assessment was performed noting changes in vehicle gross weight and energy usage. Updated versions of the Revolutionary Vertical lift Technology (RVLT) Project vertical take-off and landing (VTOL) urban air mobility (UAM) reference vehicles and missions were used. NASA electric vehicle studies are discussed which were used to help select the range of electric propulsion and power system performance parameters used in this assessment. Thermal management systems (TMS) considerations are also important; new and innovative power management and distribution systems can reduce electric system weight and losses, reducing thermal management constraints often imposed by electric systems modest maximum use temperatures. Vehicles with higher disk loadings (smaller rotors) require higher power levels per unit weight for VTOL operations, which make them more sensitive to electric system weights and efficiencies. Battery, all-electric vehicles show different sensitivities to component performance than turboelectric or hybrids systems. Battery, all-electric propulsion systems may increase vehicle weight and size, but still results in lower mission energy usage than their hydrocarbon-fueled versions. Significant vehicle weight growth to electric propulsion and power system power-to-weight reductions also occurs at different levels among the various concepts. From these results, one can more readily identify required component performance levels, potential component choices or, research and development paths.

electric propulsion systems (aircraft) mission ana↗

NASA NTRS2020

Data Science Challenges for Urban Air Mobility

Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Data Science↗

NASA NTRSDate not supplied

Rapid Aero Modeling for Urban Air Mobility Aircraft in Computational Experiments

Rapid Aero Modeling (RAM) applied to computational testing, RAM-C, is an approach to efficiently and automatically obtain aerodynamic models during computational investigations. RAM-C is designed to estimate models appropriate for flight dynamics studies and simulations. The approach responds to a demand for experimental efficiency and model fidelity that has increased with growing aircraft complexity and aerodynamic nonlinearities associated with hybrid and electric vertical takeoff and landing (eVTOL) aircraft. In an Urban Air Mobility (UAM) transportation system, it is expected that aircraft will embrace many features from both airplanes and rotorcraft. These vehicles present many more factors than conventional aircraft which can lead to increased computational costs and missed key factor interactions when applying traditional testing and modeling methods. RAM-C provides feedback loops around computational codes to rapidly guide testing toward aerodynamic models meeting user-defined fidelity goals. It combines and extends concepts from design of experiment theory and aircraft system identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity in terms of prediction error. RAM-C only collects enough data required to meet the user-specified prediction error requirements thus saving computational time and resources. The overall achievable fidelity of the final model also depends on the accuracy of the test facility, or in this case, the computational modeling approach. Previous studies to support development of the RAM-T process were conducted in wind tunnel tests to assess potential metrics, algorithms, and procedures. This paper presents results from the next steps taken and tests conducted for the development of RAM-C technology and highlights some of the unique features of RAM applied eVTOL configurations in a computational study.

Aerodynamics↗

NASA NTRSDate not supplied

Rapid Aero Modeling for Urban Air Mobility Aircraft in Wind-Tunnel Tests

Rapid Aero Modeling (RAM) applied to wind tunnel testing, RAM-T, is an approach to efficiently and automatically obtain aerodynamic models during testing. The approach saves time and resources by responding to the demand for experimental efficiency and model fidelity. Motivation for this demand is more acute when investigating a class of vehicles categorized as Urban Air Mobility (UAM) aircraft where many features from both aircraft and rotorcraft are present. RAM-T provides a feedback loop around the test facility to guide the test toward high-fidelity, statistically rigorous aircraft models. The general RAM approach is applicable to computational or physical experiments. It combines concepts from design of experiment theory and aircraft system identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. This paper presents results from tests conducted for development of an automated RAM-T technology. The results highlight some of the unique features of RAM applied to eVTOL configurations.

Aerodynamics↗