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At least 847 records · Page 47

Automated Airspace Management: Concept, Development, and Testing

For many decades, researchers at NASA Ames Research Center have worked to make the air-transportation system more efficient, predictable, and effective. Since about 2005 one important aspect of this research has been the development of an autonomous system for air-traffic control. This system, known as the Autoresolver, is designed to perform most of the roles that air-traffic controllers perform including ensuring separation between aircraft, creating routes around weather and other avoidance volumes, and sequencing and scheduling aircraft across points in space. The recent, rapid expansion of new aircraft operations and types, including urban air mobility aircraft and small unmanned aerial systems, have only increased the need for highly automated systems to control the predicted traffic demand. This talk will focus on the development of the Autoresolver - from concept to testing. It will also discuss the National Airspace (NAS) Digital Twin simulation platform, created to facilitate rapid testing and improvement of the algorithm and with the hope of proving the automation in a high-fidelity environment. An open question that will be discussed is how to ensure that the system-level emergent behavior of independently developed autonomous algorithms is what is desired.

autonomy↗

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

In the concept envisioned for Urban Air Mobility (UAM) operations, fleets of electric vertical takeoff and landing (eVTOL) vehicles would operate between vertiports distributed within a densely populated area. These operations would be largely independent from the existing air traffic control system and would place the responsibility for flight planning and aircraft separation on fleet operators. The fourth major level on the UAM Maturity Level scale, UML-4, relies on “collaborative and responsible” automation to enable operations in non-visual conditions with medium traffic density (hundreds of aircraft in one metropolitan region) and medium complexity. This level of service places many requirements on automation systems to assist the operators of these aircraft. NASA has developed the Autonomous Operations Planner (AOP), a reference prototype Flight Path Management automation system, and has modified AOP to support research of anticipated UML-4 operations. AOP creates a four-dimensional flight plan conforming to the constraints of these operations, evaluates and modifies the flight plan during flight as conditions and constraints evolve, and coordinates the flight plan with other airspace users and with service providers. This version of AOP has been integrated into the Sikorsky Autonomy Research Aircraft and used in a flight test activity. In this paper we discuss anticipated characteristics of UAM operations, modifications that were made to AOP to adapt to that environment or to support the flight test, and observations of software and aircraft performance during the flight test. The aircraft achieved four-dimensional conformance with the flight plan and AOP provided adequate planning in almost all cases. We discuss improvements that could be made to AOP to address deficiencies that were observed.

Autonomous Operations Planner↗

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

In the concept envisioned for Urban Air Mobility (UAM) operations, fleets of electric vertical takeoff and landing (eVTOL) vehicles would operate between vertiports distributed within a densely populated area. These operations would be largely independent from the existing air traffic control system and would place the responsibility for flight planning and aircraft separation on fleet operators. The fourth major level on the UAM Maturity Level scale, UML-4, relies on “collaborative and responsible” automation to enable operations in non-visual conditions with medium traffic density (hundreds of aircraft in one metropolitan region) and medium complexity. This level of service places many requirements on automation systems to assist the operators of these aircraft. NASA has developed the Autonomous Operations Planner (AOP), a reference prototype Flight Path Management automation system, and has modified AOP to support research of anticipated UML-4 operations. AOP creates a four-dimensional flight plan conforming to the constraints of these operations, evaluates and modifies the flight plan during flight as conditions and constraints evolve, and coordinates the flight plan with other airspace users and with service providers. This version of AOP has been integrated into the Sikorsky Autonomy Research Aircraft and used in a flight test activity. In this paper we discuss anticipated characteristics of UAM operations, modifications that were made to AOP to adapt to that environment or to support the flight test, and observations of software and aircraft performance during the flight test. The aircraft achieved four-dimensional conformance with the flight plan and AOP provided adequate planning in almost all cases. We discuss improvements that could be made to AOP to address deficiencies that were observed.

Autonomous Operations Planner↗

U.S. Spacesuit Knowledge Capture – Chronicling Spacesuit Design for the Future

With less than 4 years until the United States is scheduled to land the first woman and next man on the Moon, NASA is leveraging 60 years of experience to build a spacesuit to assist in the success of this and future human space exploration missions. This experience comes from the achievements of retired and employed spacesuit experts, innovations that were conceived from existing ideas and inventions, and a plethora of archived knowledge. The U.S. Spacesuit Knowledge Capture (SKC) Program’s primary function is to capture, archive, and share current and legacy spacesuit-related knowledge with scientists, engineers, and technicians. To capture valuable spacesuit-related knowledge, the program uses various methods that have included hosting and recording classroom and online courses, workshops, and vignettes, and preserving thousands of legacy spacesuit-related files. In 2019, the SKC Program added to its role when it began coordinating the electronic recording of the new spacesuits’ buildup. This new, next-generation spacesuit is named the Exploration Extravehicular Mobility Unit (xEMU) and is a compilation of many components. As each component is tested and assembled into the suit, the SKC Program is chronicling this buildup using high-speed video production and photography that includes time-lapsed images. To complement the recording of the components, the SKC Program plans to record and photograph the design verification testing. In 2020, the SKC Program was given the initiative to research and identify the custodianship of historical spacesuit equipment that resides within the Crew and Thermal Systems Division. These archives will be added to the SKC Program’s expansive archived collection of spacesuit-related knowledge that represents over 5 decades of spacesuit legacy from the Apollo era to the pursuit of Mars and beyond. This paper describes the electronic documentation of the xEMU’s buildup and identifies the SKC Program’s 2020 accomplishments.

Cinda Chullen↗

U.S. Spacesuit Knowledge Capture – Chronicling Spacesuit Design for the Future

With less than 4 years until the United States is scheduled to land the first woman and next man on the Moon, NASA is leveraging 60 years of experience to build a spacesuit to assist in the success of this and future human space exploration missions. This experience comes from the achievements of retired and employed spacesuit experts, innovations that were conceived from existing ideas and inventions, and a plethora of archived knowledge. The U.S. Spacesuit Knowledge Capture (SKC) Program’s primary function is to capture, archive, and share current and legacy spacesuit-related knowledge with scientists, engineers, and technicians. To capture valuable spacesuit-related knowledge, the program uses various methods that have included hosting and recording classroom and online courses, workshops, and vignettes, and preserving thousands of legacy spacesuit-related files. In 2019, the SKC Program added to its role when it began coordinating the electronic recording of the new spacesuits’ buildup. This new, next-generation spacesuit is named the Exploration Extravehicular Mobility Unit (xEMU) and is a compilation of many components. As each component is tested and assembled into the suit, the SKC Program is chronicling this buildup using high-speed video production and photography that includes time-lapsed images. To complement the recording of the components, the SKC Program plans to record and photograph the design verification testing. In 2020, the SKC Program was given the initiative to research and identify the custodianship of historical spacesuit equipment that resides within the Crew and Thermal Systems Division. These archives will be added to the SKC Program’s expansive archived collection of spacesuit-related knowledge that represents over 5 decades of spacesuit legacy from the Apollo era to the pursuit of Mars and beyond. This paper describes the electronic documentation of the xEMU’s buildup and identifies the SKC Program’s 2020 accomplishments.

Cinda Chullen↗

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↗

The Evolution of Extravehicular Activity Operations to Lunar Exploration Based on Operational Lessons Learned During 2009 NASA Desert RATS Field Testing

This paper will present options to evolutionary changes in several philosophical areas of extravehicular activity (EVA) operations. These areas will include single person verses team EVAs; various loss of communications scenarios (with Mission Control, between suited crew, suited crew to rover crew, and rover crew A to rover crew B); EVA termination and abort time requirements; incapacitated crew ingress time requirements; autonomous crew operations during loss of signal periods including crew decisions on EVA execution (including decision for single verses team EVA). Additionally, suggestions as to the evolution of the make-up of the EVA flight control team from the current standard will be presented. With respect to the flight control team, the major areas of EVA flight control, EVA Systems and EVA Tasks, will be reviewed, and suggested evolutions of each will be presented. Currently both areas receive real-time information, and provide immediate feedback during EVAs as well as spacesuit (extravehicular mobility unit - EMU) maintenance and servicing periods. With respect to the tasks being performed, either EMU servicing and maintenance, or the specific EVA tasks, daily revising of plans will need to be able to be smoothly implemented to account for unforeseen situations and findings. Many of the presented ideas are a result of lessons learned by the NASA Johnson Space Center Mission Operations Directorate operations team support during the 2009 NASA Desert Research and Technology Studies (Desert RATS). It is important that the philosophy of both EVA crew operations and flight control be examined now, so that, where required, adjustments can be made to a next generation EMU and EVA equipment that will complement the anticipated needs of both the EVA flight control team and the crews.

Bell, Ernest R., Jr.↗

Internship in Augmented and Virtual Reality - Rapid Model Import Tool

The integration of virtual and augmented reality, sometimes called mixed reality, is an emerging technology which will likely skyrocket overnight much in the way smartphones did a decade ago. Kennedy Space Center's Augmented and Virtual Reality (AVR) Lab is developing a Rapid Model Import Tool (RMIT) to create a quick and efficient way to bring NASA's complex engineering 3D models into virtual and augmented environments. The long-term objective is to create a tool that will ultimately benefit KSC engineers. Its various uses within NASA can potentially span from astronaut training, to marketing, to public outreach, to name a few. Unity is a prolific cross-platform game engine that allows users to build high quality 2D and 3D games for desktop, mobile, web, and game console platforms. It is perhaps also the most widely used software for virtual reality game development. At the AVR lab, we are looking at alternative uses of Unity to build tools for NASA engineers to perform design, development, testing, and training on spacecraft, rocket delivery systems, ground support equipment, and facilities at KSC. As an intern for the RMIT project, I am charged with the task of performing research on Unity-compatible file types to develop an efficient, affordable, preservative process to bring models from CATIA 3D engineering software into the Unity environment. With a tool called the NASA Enterprise Visualization Application (NEVA), developed by the Boeing Design Visualization group at KSC, we are able to easily convert CATIA's design models to. DAE (also known as COLLADA) and .OBJ file formats. I first reduce the polygon count of the model within CATIA itself, make any necessary tweaks to reduce the model further, and then export using NEVA. The .OBJ or. DAE files that I am left with are then converted by another intern to a Unity-compatible file format using a custom Python script. I have generated extensive documentation of this process in a NEVA User Guide. By the end of this semester, we will have built a solid framework for RMIT based on a thorough understanding of virtual reality specifications and file requirements, allowing future software development teams to go forward with development on the custom tool.

Leap Motion↗

The Acquisition, Containment, and Curation of Mars Samples on Earth

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (henceforth AACO) is responsible for receiving and curating all of NASA’s extraterrestrial samples, current and future (as per NASA Policy Directive (NPD) 7100.10E “Curation of Extraterrestrial Materials”). As such, the AACO coordinates sample capture, containment, and transportation to the curation facility as well as documents, preserves, prepares, and distributes all of the samples within NASA’s astromaterial collections for research, education, and public outreach. Since the lunar rock and soil samples returned during the Apollo Program, NASA’s first Class V Restricted Earth Return Missions, the AACO curates six other astromaterials collections. Lessons learned from each collection and respective missions (e.g. Apollo, Genesis, Stardust) as well as advancements in science and technology have informed the AACO’s plan for acquiring and curating Martian samples. Given the nature of the collection, a mobile and modular facility is recommended. The two broad requirements a Mars sample facility must maintain are: 1) the ability to contain the samples to protect the public from exposure of an “unknown unknown” biological agent and 2) ensure the scientific integrity of the samples are maintained (while maximizing scientific outcome). Although Apollo samples were eventually deemed safe and released to the scientific community for evaluation, there is no guarantee that this will be the case for Martian samples. Therefore, the facility in which the samples will be contained and investigated must be modular and able to accommodate an array of instrumentation that could be highly variable depending on the initial scientific outcomes. Furthermore, in order to facilitate proper sample capture and containment upon landing as well as sample distribution to other laboratories with proper containment, a mobile facility is a valuable investment.

Harrington, Andrea D.↗

Examining the Changing Roles and Responsibilities of Humans in Envisioned Future In-Time Aviation Safety Management Systems

Advances in technology are enabling new concepts of operations that will trans-form aviation including increasingly autonomous capabilities to handle evolving complex dynamic ecosystems like those associated with Advanced Aerial Mobility. A major challenge is how to ensure today’s safety levels are maintained as the system scales for rapid detection and timely mitigation of safety issues. NASA has developed a concept of operation for In-Time Aviation Safety Management Systems (IASMS) that represents a system-of-system perspective on interconnected capabilities needed to proactively reduce risk in complex operational environments where unknown hazards may exist. As a result, NASA research priorities include under-standing how the balance between humans and automation changes in such envisioned systems, which may lead to novel human-machine interaction paradigms and human-autonomy teaming for informed contingency management.

Lawrence Prinzel↗

Overview of Model-Based Systems Engineering Efforts to Evolve the Airspace Research Roadmap

NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution requires a plan to effectively organize, integrate, and communicate NASA’s research and development. The planning tool, called the UAM airspace research roadmap, or just roadmap, is key to the execution of NASA’s UAM airspace research over the next ten years. Implemented through Model-Based Systems Engineering (MBSE) methodology, the roadmap will help to prioritize and coordinate research efforts, and to integrate results that build towards NASA’s research goals of evolving UAM airspace for integration of UAM operations into the National Airspace System (NAS). This paper presents an overview of on-going MBSE efforts to meet these overarching goals.

Model-Based Systems Engineering↗

A Blockchain Case Study for Urban Air Mobility Operational Intent

The next generation of aerial passenger and cargo transportation may leverage the concept of Urban Air Mobility (UAM). UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) or short takeoff and landing (STOL) aircraft to overcome increasing surface congestion [1]. The UAM concept leverages a decentralized service-based architecture for airspace solutions. Within the environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within the UAM environment. Also, various views of UAM flight information are provided to the public and public safety entities [2]. The Federal Aviation Administration (FAA) can coordinate flight information between the FAA controlled National Airspace System (NAS) and the UAM environments through the FAA-Industry Data Exchange Protocol (FIDXP). To realize the potential of UAM, an assurance of cybersecurity is critical for public acceptance. Cybersecurity has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. As these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well [3]. This research focuses on the secure data exchange and storage of this decentralized UAM environment to address these challenges. This research intends to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment. Blockchain technologies can be used for tracking transactions and verifying negotiated agreements between stakeholders in the NAS environment. For example, the record of the submitted flight plan and the approved flight plan could be verified using the Blockchain-based immutable ledger.

UAM↗

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.↗

The Multirotor Test Bed – A New NASA Test Capability for Advanced VTOL Rotorcraft Configurations

In November 2019, NASA completed the first wind tunnel test entry of the Multirotor Test Bed (MTB), a new test capability for advanced VTOL rotorcraft configurations. The MTB had been under development since 2017 when the need arose for an easily reconfigurable test stand for multirotor aircraft configurations. With the wide-ranging assortment of aircraft currently targeted at Urban Air Mobility and Unmanned Aircraft System applications, there is a need for validation data that will increase confidence in the computational modeling tools being used to develop these platforms. The MTB fills this need. This paper describes the key features of the MTB as well as its first wind tunnel test entry. A selection of results from the test is presented here, demonstrating the flexible configuration of the MTB and the types of data researchers can generate using this new test capability.

Multirotor Test Bed↗

A Queuing Theory Approach to Pilot-Controller Coordination for m:N Operations

In recent years, attention and interest by industry and researchers has grown in a control paradigm for remotely piloted aircraft termed “m:N operations.” In an m:N operation, a team of m remote pilots in command (RIPCs) collaboratively manage the flights of N aircraft. A consequence of an m:N concept of operations is that the RPICs will have to switch attention from one aircraft to another and from one task to another. Previous research in m:N operations has focused on the workload experienced by an RPIC and their level of situation awareness on their flights. Researchers have found that RPIC workload and situation awareness are generally sensitive to increasing N, although NASA’s Multi-Vehicle (m:N) Working Group has suggested that the driver of workload/situation awareness is the number of exceptions requiring human intervention as opposed to the value of N itself. In any case, a natural antecedent of workload is task load. In this paper, queueing theory is applied to a 1:N Urban Air Mobility (UAM) air taxi operation in order to estimate pilot task load for managing radio communications with air traffic controllers (ATCs) under increasing N. An M/M/1 queueing system is used to model the RIPC’s servicing of calls and clearance requests (e.g., departure, arrival, or airspace transition) to ATC for the N aircraft. Important parameters for the queueing model are the task arrival rate and the average service time for task completion. Radio communication times from past human-in-the-loop simulation studies are used to measure service times for a 1:4 and 1:12 UAM operation and to interpolate service times for 4 < N < 12. A Monte Carlo method is then employed, using the measured and interpolated service times, to estimate arrival rate and related queueing statistics. The paper concludes by considering the estimated queuing statistics, particularly the RPIC’s utilization (i.e., proportion of time actively servicing tasks), the length of the task queue over time, and the implications for task-balanced system design.

task load↗

A robotic system for automation of logistics functions on the Space Station

Spacecraft inventory management is currently performed by the crew and as systems become more complex, increased crew time will be required to perform routine logistics activities. If future spacecraft are to function effectively as research labs and production facilities, the efficient use of crew time as a limited resource for performing mission functions must be employed. The use of automation and robotics technology, such as automated warehouse and materials handling functions, can free the crew from many logistics tasks and provide more efficient use of crew time. Design criteria for a Space Station Automated Logistics Inventory Management System is focused on through the design and demonstration of a mobile two armed terrestrial robot. The system functionally represents a 0 gravity automated inventory management system and the problems associated with operating in such an environment. Features of the system include automated storage and retrieval, item recognition, two armed robotic manipulation, and software control of all inventory item transitions and queries.

Martin, J. C.↗