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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
NASA NTRS2024

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗
NASA NTRSDate not supplied

Advancing Air Mobility: Few-Shot Learning in Airspace Research and Development

The advancement of Air Mobility, particularly in the context of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM), represents a transformative shift in aviation's role in modern society. A comprehensive understanding of requirement consistency is paramount for fostering interoperability, standardization, and cost-effectiveness within airspace systems. This paper introduces a novel approach utilizing a pretrained Sentence Transformers model and few-shot learning to address this crucial aspect task of flagging potentially inconsistent requirements. Few-shot learning supports the development of this future through ensuring the accuracy and consistency of identified requirements with little human oversight. This approach offers a promising solution to the challenges of requirement consistency identification in airspace systems. By harnessing the power of advanced NLP techniques with fine-tuned models, stakeholders can enhance efficiency, accuracy, and scalability; ultimately fostering improved interoperability, standardization, and cost-effectiveness in airspace management.

Natural Language Processing↗
NASA NTRS1990

Satellite sound broadcast propagation studies and measurements

Satellite Sound Broadcasting is an attractive satellite application. Before regulatory decisions can be made in 1992, the propagation effects encountered have to be characterized. The Electrical Engineering Research Laboratory has nearly completed a system which will allow amplitude measurements to be made over 10 MHz bandwidths in the 800 to 1800 MHz frequency range. The system uses transmission from a transportable tower, and reception inside buildings or in the shadow of trees or utility poles. The goal is to derive propagation models for use by systems engineers who are about to design satellite broadcast systems. The advance of fiber-optics technology has helped to focus future development of satellite services into areas where satellites are uniquely competitive. One of these preferred satellite applications is the broadcasting of high-quality sound for stationary or mobile reception by listeners using low-cost, consumer-grade receivers. Before such services can be provided, however, the political hurdles of spectrum allocation have to be surmounted and the technical questions of standardization for world-wide compatibility have to be resolved. In order to arrive at an optimal system design, efficient in the use of our scarce spectral resources, affordable both to the broadcaster and the listener, and providing predictable performance, the propagation effects to which the service is subjected have to be characterized. Consequently, the objective of the research project is to make basic propagation measurements for direct Satellite Sound Broadcasting Service (SSBS). The data obtained should allow the development of propagation models to be used by communications engineers designing the operational systems. Such models shall describe the effects of shadowing and multipath propagation on SSBS receivers operating in a specified environment, such as inside commercial or residential buildings of various construction and also in the shadow of trees or utility poles as might be encountered by transporting or mobile listeners.

Vogel, Wolfhard J.↗
NASA NTRS1990

Space segment configuration of the Canadian mobile satellite system

The performance requirements, the main parameters, and the configuration of the MSAT spacecraft are reviewed. The major features of the communications subsystem are discussed in some detail. Key technology items include the L-band Radio Frequency (RF) power amplifier which must operate with a high DC to RF power efficiency and generate low intermodulation when loaded with multi-carrier signals; and the large diameter deployable L-band antenna. The development status and expected performance of these spacecraft components is examined.

Bertenyi, Elemer↗
NASA NTRS1995

Network flexibility of the IRIDIUM (R) Global Mobile Satellite System

The IRIDIUM system is a global personal communications system supported by a constellation of 66 low earth orbit (LEO) satellites and a collection of earth-based 'gateway' switching installations. Like traditional wireless cellular systems, coverage is achieved by a grid of cells in which bandwidth is reused for spectral efficiency. Unlike any cellular system ever built, the moving cells can be shared by multiple switching facilities. Noteworthy features of the IRIDIUM system include inter-satellite links, a GSM-based telephony architecture, and a geographically controlled system access process. These features, working in concert, permit flexible and reliable administration of the worldwide service area by gateway operators. This paper will explore this unique concept.

Hutcheson, Jonathan↗
NASA NTRS2005

Exploration Rover Concepts and Development Challenges

This paper presents an overview of exploration rover concepts and the various development challenges associated with each as they are applied to exploration objectives and requirements for missions on the Moon and Mars. A variety of concepts for surface exploration vehicles have been proposed since the initial development of the Apollo-era lunar rover. This paper provides a brief description of the rover concepts, along with a comparison of their relative benefits and limitations. In addition, this paper outlines, and investigates a number of critical development challenges that surface exploration vehicles must address in order to successfully meet the exploration mission vision. These include: mission and environmental challenges, design challenges, and production and delivery challenges. Mission and environmental challenges include effects of terrain, extreme temperature differentials, dust issues, and radiation protection. Design methods are discussed that focus on optimum methods for developing highly reliable, long-life and efficient systems. In addition, challenges associated with delivering a surface exploration system is explored and discussed. Based on all the information presented, modularity will be the single most important factor in the development of a truly viable surface mobility vehicle. To meet mission, reliability, and affordability requirements, surface exploration vehicles, especially pressurized rovers, will need to be modularly designed and deployed across all projected Moon and Mars exploration missions.

Zakrajsek, James J.↗
NASA NTRS2011

Towards Autonomous Operation of Robonaut 2

The Robonaut 2 (R2) platform, as shown in Figure 1, was designed through a collaboration between NASA and General Motors to be a capable robotic assistant with the dexterity similar to a suited astronaut [1]. An R2 robot was sent to the International Space Station (ISS) in February 2011 and, in doing so, became the first humanoid robot in space. Its capabilities are presently being tested and expanded to increase its usefulness to the crew. Current work on R2 includes the addition of a mobility platform to allow the robot to complete tasks (such as cleaning, maintenance, or simple construction activities) both inside and outside of the ISS. To support these new activities, R2's software architecture is being developed to provide efficient ways of programming robust and autonomous behavior. In particular, a multi-tiered software architecture is proposed that combines principles of low-level feedback control with higher-level planners that accomplish behavioral goals at the task level given the run-time context, user constraints, the health of the system, and so on. The proposed architecture is shown in Figure 2. At the lowest-level, the resource level, there exists the various sensory and motor signals available to the system. The sensory signals for a robot such as R2 include multiple channels of force/torque data, joint or Cartesian positions calculated through the robot's proprioception, and signals derived from objects observable by its cameras.

Badger, Julia M.↗
NASA NTRS2019

Utilizing Shape Memory Alloys for Novel, Non-Pneumatic Tire Design - Designing for the Best of Both Worlds

Materials are a fundamental building block that often get overlooked as a critical component that shapes our world. Numerous products that impact our lives are enabled by the materials from which they are made. With regard to Martian and lunar rover applications, conventional mobility elements, such as pneumatic tires, suffer from a number of issues related to reliability. Two of the more prevalent problems are the high likelihood of single point failure owing to puncture (i.e. flat tire), and loss of efficiency due to reduction in tire pressure over time. Solid, rigid wheels suffer from the inability to handle the high, localized loads while encountering rugged terrain and also produce relatively poor traction and operating efficiency. In an effort to overcome these problems, non-pneumatic, compliant tire designs are being developed, using Nickel-Titanium (NiTi), a thermally activated shape memory alloy (SMA), that is less sensitive to temperature and exhibits much greater plastic deformation than do conventional vulcanized rubber pneumatic tires.

Padula, Santo, II↗
NASA NTRS2019

Utilizing Shape Memory Alloys for Novel, Non-Pneumatic Tire Design - Designing for the Best of Both Worlds

Materials are a fundamental building block that often get overlooked as a critical component that shapes our world. Numerous products that impact our lives are enabled by the materials from which they are made. With regard to Martian and lunar rover applications, conventional mobility elements, such as pneumatic tires, suffer from a number of issues related to reliability. Two of the more prevalent problems are the high likelihood of single point failure owing to puncture (i.e. flat tire), and loss of efficiency due to reduction in tire pressure over time. Solid, rigid wheels suffer from the inability to handle the high, localized loads while encountering rugged terrain and also produce relatively poor traction and operating efficiency. In an effort to overcome these problems, non-pneumatic, compliant tire designs are being developed, using Nickel-Titanium (NiTi), a thermally activated shape memory alloy (SMA), that is less sensitive to temperature and exhibits much greater plastic deformation than do conventional vulcanized rubber pneumatic tires.

Padula, Santo, II↗
NASA NTRS2017

Shape Memory Alloys (SMAs) for Non-Pneumatic Tires

Conventional mobility elements, such as pneumatic tires, suffer from a number of issues related to reliability. Two of the more prevalent problems are the high likelihood of single point failure owing to puncture (i.e. flat tire), and loss of efficiency due to reduction in tire pressure over time. In order to overcome these limitations, alternative compliant tire designs not requiring pneumatics have been developed. However, although current designs have significantly reduced the aforementioned issues, they tend to have their own set of limitations. First, non-pneumatic tires designed for high load applications often have restricted envelopment capability, making their performance less than optimal, especially on uneven terrain. Second, tires designed with larger envelopment capability tend to suffer from large amounts of plasticity (permanent deformation) or failure (rupture). Both of these limitations are the direct result of the choice of material being used for the design; conventional metals undergo plastic deformation at low strain while elastomer based designs are often too rigid for the localized deformations needed for high envelopment. Recent advancements at the NASA Glenn research center in a unique class of metals know as shape memory alloys (SMAs) has opened the design space for non-pneumatic compliant tire technologies allowing designs to incorporate orders of magnitude more deformation without damage. The work presented herein highlights the advantages of using SMAs as compared to conventional metals. Additionally, the development of a unique SMA compliant tire design capable of carrying up to 8.9 kN (2000 lbf) with reversible, local deformations on the order of the side wall height will be presented.

Padula, Santo↗
NASA NTRSDate not supplied

DANTi: A Tool for Assistive Detect and Avoid Research

This paper presents DANTi, a research tool developed at NASA Langley Research Center to support the validation of Assistive Detect and Avoid (ADAA) requirements for General Aviation (GA). ADAA is a future on-board aircraft technology intended to augment a pilot’s see-and-avoid capability by helping them identify and resolve traffic conflicts earlier and more efficiently. DANTi includes a realistic Electronic Flight Bag (EFB) display and a fast-time simulation environment that can be fully customized to meet different research requirements. DANTi is currently used within NASA efforts such as the Air Mobility Pathfinders project on future air transportation systems and a joint NASA/FAA Laboratory Integrated Test Environment (NFLITE) on next-generation airspace operations in urban environments. These efforts investigate ADAA requirements in advanced urban air mobility settings where new aircraft types, new services, and new traffic patterns will be integrated in an overall crowded airspace.

Detect and Avoid↗
NASA NTRS2018

Mobile Device Application for Monitoring Cyanobacteria Harmful Algal Blooms Using Sentinel-3 Satellite Ocean and Land Colour Instruments

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

Harmful Algal Bloom↗
NASA NTRS2018

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↗
NASA NTRS1990

An alternative resource sharing scheme for land mobile satellite services

A preliminary comparison between the two competing channelization concepts for the Land Mobile Satellite Services (LMSS), namely frequency division (FD) and code division (CD), is presented. Both random access and demand-assigned approaches are considered under these concepts. The CD concept is compared with the traditional FD concept based on the system consideration and a projected traffic model. It is shown that CD is not particularly attractive for the first generation Mobile Satellite Services because of the spectral occupancy of the network bandwidth. However, the CD concept is a viable alternative for future systems such as the personal access satellite system (PASS) in the Ka-band spectrum where spectral efficiency is not of prime concern. The effects of power robbing and voice activity factor are incorporated. It was shown that the traditional rule of thumb of dividing the number of raw channels by the voice activity factor to obtain the effective number of channels is only valid asymptotically as the aggregated traffic approaches infinity.

Yan, Tsun-Yee↗
NASA NTRS1991

Ka-band MMIC array feed development for deep space applications

Ka-band MMIC transmitter arrays are under development at NASA Jet Propulsion Laboratory for future deep space and ground communication needs. A high efficiency full aperture active antenna array is desired to demonstrate solid state array technology for future NASA missions. This paper reports on a 5 watt Ka-band phased array feed and a full aperture active array for a mobile terminal which are being developed to characterize the design tradeoffs and potential of solid state Ka-band MMIC array communication systems.

Cooley, T. W.↗