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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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NASA NTRS2014

Influence of Cultural, Organizational, and Automation Capability on Human Automation Trust: A Case Study of Auto-GCAS Experimental Test Pilots

This paper discusses a case study that examined the influence of cultural, organizational and automation capability upon human trust in, and reliance on, automation. In particular, this paper focuses on the design and application of an extended case study methodology, and on the foundational lessons revealed by it. Experimental test pilots involved in the research and development of the US Air Force's newly developed Automatic Ground Collision Avoidance System served as the context for this examination. An eclectic, multi-pronged approach was designed to conduct this case study, and proved effective in addressing the challenges associated with the case's politically sensitive and military environment. Key results indicate that the system design was in alignment with pilot culture and organizational mission, indicating the potential for appropriate trust development in operational pilots. These include the low-vulnerability/ high risk nature of the pilot profession, automation transparency and suspicion, system reputation, and the setup of and communications among organizations involved in the system development.

trust↗

NASA NTRS2018

Mega-Drivers to Inform NASA Space Technology Strategic Planning

The National Aeronautics and Space Administration (NASA) Space Technology Mission Directorate (STMD) has been developing a new Strategic Framework to guide investment prioritization and communication of STMD strategic goals to stakeholders. STMD’s analysis of global trends identified four overarching drivers which are anticipated to shape the needs of civilian space research for years to come. These Mega-Drivers form the foundation of the Strategic Framework. The Increasing Access Mega-Driver reflects the increase in the availability of launch options, more capable propulsion systems, access to planetary surfaces, and the introduction of new platforms to enable exploration, science, and commercial activities. Accelerating Pace of Discovery reflects the exploration of more remote and challenging destinations, drives increased demand for improved abilities to communicate and process large datasets. The Democratization of Space reflects the broadening participation in the space industry, from governments to private investors to citizens. Growing Utilization of Space reflects space market diversification and growth. This paper will further describe the observable trends that inform each of these Mega Drivers, as well as the interrelationships between them within STMD’s new Strategic Framework.

Grande, Melanie L.↗

NASA NTRS2018

Mega-Drivers to Inform NASA Space Technology Strategic Planning

Melanie L Grande↗

NASA NTRSDate not supplied

Overview of Exploration Medical Capability Systems Engineering Level 4 Requirements for Medical Level-of-Care IV in Space Lunar Orbit Habitat

This paper presents how the Exploration Medical Capability Element of the National Aeronautics and Space Administration’sHuman Research Program usingModel-Based System Engineering is defining Level 4 Foundational Requirements to provide Medical Level-of-Care IV in a space Habitat during exploration missions.

Space Habitat Medical System Engineering Requireme↗

NASA NTRS2011

Full-Scaled Advanced Systems Testbed: Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on the Full-Scale Advance Systems Testbed (FAST) in January of 2011. The research addressed technical challenges involved with reducing risk in an increasingly complex and dynamic national airspace. Specific challenges lie with the development of validated, multidisciplinary, integrated aircraft control design tools and techniques to enable safe flight in the presence of adverse conditions such as structural damage, control surface failures, or aerodynamic upsets. The testbed is an F-18 aircraft serving as a full-scale vehicle to test and validate adaptive flight control research and lends a significant confidence to the development, maturation, and acceptance process of incorporating adaptive control laws into follow-on research and the operational environment. The experimental systems integrated into FAST were designed to allow for flexible yet safe flight test evaluation and validation of modern adaptive control technologies and revolve around two major hardware upgrades: the modification of Production Support Flight Control Computers (PSFCC) and integration of two, fourth-generation Airborne Research Test Systems (ARTS). Post-hardware integration verification and validation provided the foundation for safe flight test of Nonlinear Dynamic Inversion and Model Reference Aircraft Control adaptive control law experiments. To ensure success of flight in terms of cost, schedule, and test results, emphasis on risk management was incorporated into early stages of design and flight test planning and continued through the execution of each flight test mission. Specific consideration was made to incorporate safety features within the hardware and software to alleviate user demands as well as into test processes and training to reduce human factor impacts to safe and successful flight test. This paper describes the research configuration, experiment functionality, overall risk mitigation, flight test approach and results, and lessons learned of adaptive controls research of the Full-Scale Advanced Systems Testbed.

Pavlock, Kate M.↗

NASA NTRS2022

A History of the NASA Planetary Astronomy Program: 1958-2022

For decades, the public has been enraptured by popular high-resolution images and data taken of our multicolored planets by space-based telescopes. However, at the time NASA was established in October 1958, there was limited astronomical interest in planetary science with ground-based telescopes. Instead, stellar astronomy dominated most of the observing time at facilities, as astrophysics was considered the forefront of astronomical research. Once NASA determined that it wanted launch planetary missions to explore the solar system in detail, it became obvious that there were not enough high-quality solar system observations to lay the foundation for these missions. Therefore, the NASA Planetary Astronomy program (PAST) was established to fund ground-based research on solar system objects. This research covers the history of this important but little-known NASA program, which not only provided necessary support for planetary missions but also was responsible for rejuvenating astronomer interest in solar system research.

NASA PAST Program↗

NASA NTRS1991

Research accomplished at the Knowledge Based Systems Lab: IDEF3, version 1.0

An overview is presented of the foundations and content of the evolving IDEF3 process flow and object state description capture method. This method is currently in beta test. Ongoing efforts in the formulation of formal semantics models for descriptions captured in the outlined form and in the actual application of this method can be expected to cause an evolution in the method language. A language is described for the representation of process and object state centered system description. IDEF3 is a scenario driven process flow modeling methodology created specifically for these types of descriptive activities.

Mayer, Richard J.↗

NASA NTRS1993

Small Business Innovations

Under an Army Small Business Innovation Research (SBIR) grant, Symbiotics, Inc. developed a software system that permits users to upgrade products from standalone applications so they can communicate in a distributed computing environment. Under a subsequent NASA SBIR grant, Symbiotics added additional tools to the SOCIAL product to enable NASA to coordinate conventional systems for planning Shuttle launch support operations. Using SOCIAL, data may be shared among applications in a computer network even when the applications are written in different programming languages. The product was introduced to the commercial market in 1993 and is used to monitor and control equipment for operation support and to integrate financial networks. The SBIR program was established to increase small business participation in federal R&D activities and to transfer government research to industry. InQuisiX is a reuse library providing high performance classification, cataloging, searching, browsing, retrieval and synthesis capabilities. These form the foundation for software reuse, producing higher quality software at lower cost and in less time. Software Productivity Solutions, Inc. developed the technology under Small Business Innovation Research (SBIR) projects funded by NASA and the Army and is marketing InQuisiX in conjunction with Science Applications International Corporation (SAIC). The SBIR program was established to increase small business participation in federal R&D activities and to transfer government research to industry.

Source record↗

NASA NTRS2001

STIS Observations of the Ly\Alpha Bright Jet Associated with the Herbig Ae Star HD163296

We present follow-up HST/Space Telescope Imaging Spectrograph (STIS) observations of the Ly-alpha bright jet associated with the near-ZAMS Herbig Ae star HD163296. The proper motions and radial velocities of the knots in the flow are consistent with a collimated outflow inclined by 40 deg relative to the plane of the sky with a flow velocity that varies from 350 to 500 km/s along the jet. A new knot is visible in the jet at a projected distance of 0.33 arcsec (40 AU) from the central star. The knot has a dynamical age of only seven months, making it the youngest HH knot ever observed. We did not detect any emission from the counterjet within 2.5 arcsec of the source, which is consistent with absorption due to a uniform 450 AU radius disk tilted at 50 deg relative to the line of sight. We also present observations made with the Goddard Fabry-Perot Imager which show additional, more distant knots along the blue and red shifted outflow lobes, and discuss the collimation of the jet and implications for a magnetosphere associated with HD 163296. Support for this study was provided by HST STIS GTO funding through support to the NOAO, in response to the NASA A/O OSSA-4-84 through the Hubble Space Telescope Project at GSFC, as well as NASA grant NRA-98-03-UVG-O11. NOAO is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under cooperative agreement with the National Science Foundation. Data analysis facilities were provided by the Laboratory for Astronomy & Solar Physics, NASA/GSFC.

Devine, David↗

NASA NTRS2003

Solar/Stellar Irradiance Comparison Experiment (SOLSTICE) on the Upper Atmosphere Research Satellite (UARS)

A final report on the operational activities related to the UARS Solar Stellar irradiance Comparison Experiment (SOLSTICE) is presented. Scientific activities of SOLSTICE has also been supported. The UARS SOLSTICE originated at the University of Colorado in 1981. One year after the UARS launch in 1991, the operations and research support activities for SOLSTICE were moved to the High Altitude Observatory (HAO) of the National Center for Atmospheric Research (NCAR). The SOLSTICE program continued at HAO with the National Science Foundation, and after four years, it was moved once again back to the University of Colorado. At the University after 1997 this subject grant was issued to further extend the operations activities from July 2001 through September 2002. Although this is a final report for one particular activity, in fact the SOLSTICE operations activity -first at the University, then at HAO, and now again at the University -has continued in a seamless fashion.

Rottman, Gary J.↗

NASA NTRS2016

An Overview of Low-Emission Combustion Research at NASA Glenn

An overview of research efforts at NASA Glenn Research Center (GRC) in low-emission combustion technology that have made a significant impact on the nitrogen oxides (NOx) emission reduction in aircraft propulsion is presented. The technology advancements and their impact on aircraft emissions are discussed in the context of NASA's Aeronautics Research Mission Directorate (ARMD) high-level goals in fuel burn, noise and emission reductions. The highlights of the research presented here show how the past and current efforts laid the foundation for the engines that are flying today as well as how the continued technology advancements will significantly influence the next generation of aviation propulsion system designs.

Low-Emission↗

NASA NTRS2017

HRP Chief Scientist's Office: Conducting Research to Enable Deep Space Exploration

The HRP Chief Scientist's Office sets the scientific agenda for the Human Research Program. As NASA plans for deep space exploration, HRP is conducting research to ensure the health of astronauts, and optimize human performance during extended duration missions. To accomplish this research, HRP solicits for proposals within the U.S., collaborates with agencies both domestically and abroad, and makes optimal use of ISS resources in support of human research. This session will expand on these topics and provide an opportunity for questions and discussion with the HRP Chief Scientist. Presentations in this session will include: NRA solicitations - process improvements and focus for future solicitations, Multilateral Human Research Panel for Exploration - future directions (MHRPE 2.0), Extramural liaisons - National Science Foundation (NSF) and Department of Defense (DOD), Standardized Measures for spaceflight, Ground-based Analogs - international collaborations, and International data sharing.

Charles, J. B.↗

NASA NTRS2016

Overview of Low Emission Combustion Research At NASA Glenn

Combustion↗

NASA NTRS2020

Global earth mineral inventory: A data legacy

Minerals contain important clues to understanding the complex geologic history of Earth and other planetary bodies. Therefore, geologists have been collecting mineral samples and compiling data about these samples for centuries. These data have been used to better understand the movement of continental plates, the oxidation of Earth's atmosphere and the water regime of ancient martian landscapes. Datasets found at ‘RRUFF.info/Evolution’ and ‘mindat.org’ have documented a wealth of mineral occurrences around the world. One of the main goals in geoinformatics has been to facilitate discovery by creating and merging datasets from various scientific fields and using statistical methods and visualization tools to inspire and test hypotheses applicable to modelling Earth's past environments. To help achieve this goal, we have compiled physical, chemical and geological properties of minerals and linked them to the above-mentioned mineral occurrence datasets. As a part of the Deep Time Data Infrastructure, funded by the W.M. Keck Foundation, with significant support from the Deep Carbon Observatory (DCO) and the A.P. Sloan Foundation, GEMI (‘Global Earth Mineral Inventory’) was developed from the need of researchers to have all of the required mineral data visible in a single portal, connected by a robust, yet easy to understand schema. Our data legacy integrates these resources into a digestible format for exploration and analysis and has allowed researchers to gain valuable insights from mineralogical data. GEMI can be considered a network, with every node representing some feature of the datasets, for example, a node can represent geological parameters like colour, hardness or lustre. Exploring subnetworks gives the researcher a specific view of the data required for the task at hand. GEMI is accessible through the DCO Data Portal (https://dx.deepcarbon.net/11121/6200-6954-6634-8243-CC). We describe our efforts in compiling GEMI, the Data Policies for usage and sharing, and the evaluation metrics for this data legacy.

data legacy↗

NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗

NASA NTRS2017

NEEMO 21: Tools, Techniques, Technologies and Training for Science Exploration

The 21st mission of the National Aeronautics and Space Administration (NASA) Extreme Environment Mission Operations (NEEMO) was a highly integrated operational field test and evaluation of tools, techniques, technologies, and training for science driven exploration during extravehicular activity (EVA). The mission was conducted in July 2016 from the Aquarius habitat, an underwater laboratory, off the coast of Key Largo in the Florida Keys National Marine Sanctuary. An international crew of eight (comprised of NASA and ESA astronauts, engineers, medical personnel, and habitat technicians) lived and worked in and around Aquarius and its surrounding reef environment for 16 days. The integrated testing (both interior and exterior objectives) conducted from this unique facility continues to support current and future human space exploration endeavors. Expanding on the scientific and operational evaluations conducted during NEEMO 20, the 21st NEEMO mission further incorporated a diverse Science Team comprised of planetary geoscientists from the Astromaterials Research and Exploration Science (ARES/XI) Division from the Johnson Space Center, marine scientists from the Department of Biological Sciences at Florida International University (FIU) Integrative Marine Genomics and Symbiosis (IMaGeS) Lab, and conservationists from the Coral Restoration Foundation. The Science Team worked in close coordination with the long-standing EVA operations, planning, engineering, and research components of NEEMO in all aspects of mission planning, development, and execution.

Graff, T.↗

NASA NTRS1995

Aviation Research and the Internet

The Internet is a network of networks. It was originally funded by the Defense Advanced Research Projects Agency or DOD/DARPA and evolved in part from the connection of supercomputer sites across the United States. The National Science Foundation (NSF) made the most of their supercomputers by connecting the sites to each other. This made the supercomputers more efficient and now allows scientists, engineers and researchers to access the supercomputers from their own labs and offices. The high speed networks that connect the NSF supercomputers form the backbone of the Internet. The World Wide Web (WWW) is a menu system. It gathers Internet resources from all over the world into a series of screens that appear on your computer. The WWW is also a distributed. The distributed system stores data information on many computers (servers). These servers can go out and get data when you ask for it. Hypermedia is the base of the WWW. One can 'click' on a section and visit other hypermedia (pages). Our approach to demonstrating the importance of aviation research through the Internet began with learning how to put pages on the Internet (on-line) ourselves. We were assigned two aviation companies; Vision Micro Systems Inc. and Innovative Aerodynamic Technologies (IAT). We developed home pages for these SBIR companies. The equipment used to create the pages were the UNIX and Macintosh machines. HTML Supertext software was used to write the pages and the Sharp JX600S scanner to scan the images. As a result, with the use of the UNIX, Macintosh, Sun, PC, and AXIL machines, we were able to present our home pages to over 800,000 visitors.

Scott, Antoinette M.↗

NASA NTRSDate not supplied

Implementing Artificial Thinking Autonomy with Model-Based System Engineering

Complex autonomous systems capable of successfully operating independently under ‘known unknowns’ and harsh conditions require paradigm innovation in modern development strategies. In the field of autonomy, developing a system-of-systems which can ostensibly think for itself in the face of ‘unknown unknowns’ is still a field of ongoing research. Maturing the systems architecting and modeling methodologies for developing henceforth named Thinking Autonomous Systems, which are verified with digital mission simulation, can potentially usher in the next generation of artificial intelligence for space exploration. The concept presented in this paper incorporates multiple Model-Based Systems Engineering and simulation methodologies combined as a new paradigm to design a novel, biomimetic thinking autonomy strategy. Anachronistic concepts from classical Kantian philosophy will be leveraged to inspire architectural designs that could be used for complex distributed systems in deep space. To accomplish this, digital transformation of a document-based implementation plan for Thinking Autonomous Systems, generated by experienced NASA software engineers, is implemented for NASA’s Platform for Autonomous Systems by creating descriptive and executable software models in SysML to prototype real-time operating capabilities. This conceptual implementation has been developed by incorporating model-based digital simulations to theorize how a cyberphysical thinking system would achieve specific strategies without crew reliance, while simultaneously being resilient to all operating conditions and remaining functional when devoid of ground communication. Additionally, ensuring that an autonomous system framework is an ethical Artificial Intelligence requires careful consideration of system behavior and accountability, human factors for teaming with a thinking autonomous system, and comparison to other modern approaches used for implementing true autonomy. This paper presents the first steps in formalizing the metacognition required for instantiating a truly Thinking Autonomous System; the approach described symphonizes autonomy characteristics from classical philosophical into a unified software architecture describing human thought. In the future, the foundational models described in this paper can be further leveraged to help advance research into thinking autonomy requirements for future deep space missions as well as for current near-term applications, i.e., living aboard crewed spacecraft like a NASA Gateway cislunar habitat.

Artificial Thought↗