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DOE OSTI2024

When do different scenarios of projected electricity demand start to meaningfully diverge?

Resource adequacy studies look at balancing electricity supply and demand on 10- to 15-year time horizons while asset investment planning typically evaluates returns on 20- to 40-year time horizons. Projections of electricity demand are factored into the decision-making in both cases. Climate, energy policy, and socioeconomic changes are key uncertainties known to influence electricity demands, but their relative importance for demands over the next 10-40 years is unclear. The power sector would benefit from a better understanding of the need to characterize these uncertainties for resource adequacy and investment planning. In this study, we quantify when projected United States (U.S.) electricity demands start to meaningfully diverge in response to a range of climate, energy policy, and socioeconomic drivers. Here we use a wide yet plausible range of 21st century scenarios for the U.S. The projections span two population/economic growth scenarios (Shared Socioeconomic Pathways 3 and 5) and two climate/energy policy scenarios, one including climate mitigation policies and one without (Representative Concentration Pathways 4.5 and 8.5). Each climate/energy policy scenario has two warming levels to reflect a range of climate model uncertainty. We show that the socioeconomic scenario matters almost immediately – within the next 10 years, the climate/policy scenario matters within 25-30 years, and the climate model uncertainty matters only after 50+ years. This work can inform the power sector working to integrate climate change uncertainties into their decision-making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2015

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Rendezvous↗

NASA NTRS2010

Ares I-X Flight Test Development Challenges and Success Factors

The NASA Constellation Program's Ares I-X rocket launched successfully on October 28, 2009 collecting valuable data and providing risk reduction for the Ares I project. The Ares I-X mission was formulated and implemented in less than four years commencing with the Exploration Systems Architecture Study in 2005. The test configuration was founded upon assets and processes from other rocket programs including Space Shuttle, Atlas, and Peacekeeper. For example, the test vehicle's propulsion element was a Shuttle Solid Rocket Motor. The Ares I-X rocket comprised a motor assembly, mass and outer mold line simulators of the Ares I Upper Stage, Orion Spacecraft and Launch Abort System, a roll control system, avionics, and other miscellaneous components. The vehicle was 327 feet tall and weighed approximately 1,800,000 pounds. During flight the rocket reached a maximum speed of Mach 4.8 and an altitude of 150,000 feet. The vehicle demonstrated staging at 130,000 feet, tested parachutes for recovery of the motor, and utilized approximately 900 sensors for data collection. Developing a new launch system and preparing for a safe flight presented many challenges. Specific challenges included designing a system to withstand the environments, manufacturing large structures, and re-qualifying heritage hardware. These and other challenges, if not mitigated, may have resulted in test cancellation. Ares I-X succeeded because the mission was founded on carefully derived objectives, led by decisive and flexible management, implemented by an exceptionally talented and dedicated workforce, and supported by a thorough independent review team. Other major success factors include the use of proven heritage hardware, a robust System Integration Laboratory, multi-NASA center and contractor team, concurrent operations, efficient vehicle assembly, effective risk management, and decentralized element development with a centralized control board. Ares I-X was a technically complex test that required creative thinking, risk taking, and a passion to succeed.

Askins, Bruce↗

NASA NTRSDate not supplied

TriTruss Packaging and Deployment Trade Study

A trade study was conducted that evaluated viable concepts of operation for the packaging and deployment (P&D) of novel deployable modular truss modules, called TriTruss modules, that can be assembled to form a large aperture In-Space Assembled Telescopes (iSAT). In this first phase of an ongoing more comprehensive trade study, concepts were proposed and then evaluated based on initial metrics representing features of an ideal P&D concept. The ideal TriTruss P&D concept is defined as one that: allows for efficient packaging, has sufficient geometric versatility to be launch vehicle independent, provides a stiff and lightweight structure, has low mechanical complexity, and has component modularity. The P&D concept should allow for prelaunch subsystem or utility integration if required. The concept should be kinematically simple and be robotically deployed using a minimum number of specialized tools. The P&D concepts evaluated are categorized as: core collapse, face collapse, and erectable structures. Sub-scale models were constructed to help understand the kinematics and mechanical complexity required to enable P&D. Based on a weighting scale, the most promising candidate P&D concepts have been selected and will undergo more rigorous structural design, analysis, and testing in the study’s next phase. The ultimate goal of the comprehensive trade study will be to recommend a single TriTruss design and associated P&D concept that will be built and evaluated at NASA Langley Research Center’s In-Space Assembly Laboratory.

in-space assembly (ISA)↗

NASA NTRS2006

Promoting Lifelong Ocean Education: Shaping Tomorrow's Earth Stewards and the Science and Technology Workforce

The coming ocean observing systems provide an unprecedented opportunity to change both the public perception of our oceans, and to inspire, captivate and motivate our children, our young adults and even our fellow adults to pursue careers allied with the oceans and to become stewards of our Planet's last unexplored environment. Education plans for the operational component, the Integrated Ocean Observing System (IOOS), and for the research component, Ocean Research Interactive Observatory Networks (ORION), are designed to take advantage of this opportunity. In both cases, community recommendations were developed within the context of the following assumptions: 1. Utilize research on how people learn, especially the four-pronged model of simultaneous learner-centered, knowledge-center, assessment-centered and community-centered learning 2. Strive for maximum impact on national needs in science and technology learning 3. Build on the best of what is already in place 4. Pay special attention to quality, sustainability, and scalability of efforts 5. Use partnerships across federal, state and local government, academia, and industry. Community recommendations for 100s and ORION education have much in common and offer the opportunity to create a coherent education effort allied with ocean observing systems. Both efforts focus on developing the science and technology workforce of the future, and the science and technology literacy of the public within the context of the Earth system and the role of the oceans and Great Lakes in that system. Both also recognize that an organized education infrastructure that supports sustainability and scalability of education efforts is required if ocean observing education efforts are to achieve a small but measurable improvement in either of these areas. Efforts have begun to develop the education infrastructure by beginning to form a community of educators from existing ocean and aquatic education networks and by exploring needs and issues associated with using ocean observing information assets in education. Likewise efforts are underway to address workforce issues by a systematic analysis of current and future workforce and educational needs. These activities will be described as will upcoming opportunities for the community to participate in these efforts.

Meeson, Blanche↗

NASA NTRSDate not supplied

TriTruss Packaging and Deployment Trade Study

An architecture and feasibility study of next generation In-Space Assembled Telescopes (iSAT) concluded that robotic in-space assembly of modular components is necessary to enable large (>15-meter diameter) primary apertures. The iSAT study recommended that the foundational structure be assembled from modular TriTruss modules that are packaged for launch, deployed on-orbit and robotically assembled into the final configuration. This paper will describe and summarize the results of a trade study that investigated viable concept of operations (ConOps) for the packaging and deployment (P&D) of individual planar TriTruss modules that could be assembled to form a large aperture iSAT. The ideal TriTruss P&D concept is defined as one that: allows for efficient packaging; has sufficient geometric versatility to be launch vehicle independent; provides a stiff and lightweight structure; has low mechanical complexity; and has component modularity. The P&D concept should allow for prelaunch subsystem or utility integration if required. The concept would be kinematically simple and be robotically deployed using a minimum number of specialized tools. In this first phase of an ongoing more comprehensive trade study, concepts were proposed and then evaluated based on initial metrics representing features of an ideal P&D concept. The P&D concepts evaluated are categorized as: core collapse, face collapse, and erectable structures. Sub-scale models were constructed to help understand the kinematics and mechanical complexity required to enable P&D. Based on a weighting scale, the most promising candidate P&D concepts have selected and will undergo more rigorous structural design, analysis, and testing in the study’s next phase. The ultimate goal of the comprehensive trade study will be to recommend a single TriTruss design and associated P&D concept that will be built and evaluated at NASA Langley Research Center’s In-Space Assembly Laboratory.

in-space assembly (ISA)↗

NASA NTRS2009

Monitoring Disasters by Use of Instrumented Robotic Aircraft

Efforts are under way to develop data-acquisition, data-processing, and data-communication systems for monitoring disasters over large geographic areas by use of uninhabited aerial systems (UAS) robotic aircraft that are typically piloted by remote control. As integral parts of advanced, comprehensive disaster- management programs, these systems would provide (1) real-time data that would be used to coordinate responses to current disasters and (2) recorded data that would be used to model disasters for the purpose of mitigating the effects of future disasters and planning responses to them. The basic idea is to equip UAS with sensors (e.g., conventional video cameras and/or multispectral imaging instruments) and to fly them over disaster areas, where they could transmit data by radio to command centers. Transmission could occur along direct line-of-sight paths and/or along over-the-horizon paths by relay via spacecraft in orbit around the Earth. The initial focus is on demonstrating systems for monitoring wildfires; other disasters to which these developments are expected to be applicable include floods, hurricanes, tornadoes, earthquakes, volcanic eruptions, leaks of toxic chemicals, and military attacks. The figure depicts a typical system for monitoring a wildfire. In this case, instruments aboard a UAS would generate calibrated thermal-infrared digital image data of terrain affected by a wildfire. The data would be sent by radio via satellite to a data-archive server and image-processing computers. In the image-processing computers, the data would be rapidly geo-rectified for processing by one or more of a large variety of geographic-information- system (GIS) and/or image-analysis software packages. After processing by this software, the data would be both stored in the archive and distributed through standard Internet connections to a disaster-mitigation center, an investigator, and/or command center at the scene of the fire. Ground assets (in this case, firefighters and/or firefighting equipment) would also be monitored in real time by use of Global Positioning System (GPS) units and radio communication links between the assets and the UAS. In this scenario, the UAS would serve as a data-relay station in the sky, sending packets of information concerning the locations of assets to the image-processing computer, wherein this information would be incorporated into the geo-rectified images and maps. Hence, the images and maps would enable command-center personnel to monitor locations of assets in real time and in relation to locations affected by the disaster. Optionally, in case of a disaster that disrupted communications, the UAS could be used as an airborne communication relay station to partly restore communications to the affected area. A prototype of a system of this type was demonstrated in a project denoted the First Response Experiment (Project FiRE). In this project, a controlled outdoor fire was observed by use of a thermal multispectral scanning imager on a UAS that delivered image data to a ground station via a satellite uplink/ downlink telemetry system. At the ground station, the image data were geo-rectified in nearly real time for distribution via the Internet to firefighting managers. Project FiRE was deemed a success in demonstrating several advances essential to the eventual success of the continuing development effort.

Wegener, Steven S.↗

NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗

NASA NTRS2011

External Tank - The Structure Backbone

The External Tank forms the structural backbone of the Space Shuttle in the launch configuration. Because the tank flies to orbital velocity with the Space Shuttle Orbiter, minimization of weight is mandatory, to maximize payload performance. Choice of lightweight materials both for structure and thermal conditioning was necessary. The tank is large, and unique manufacturing facilities, tooling, handling, and transportation operations were required. Weld processes and tooling evolved with the design as it matured through several block changes, to reduce weight. Non Destructive Evaluation methods were used to assure integrity of welds and thermal protection system materials. The aluminum-lithium alloy was used near the end of the program and weld processes and weld repair techniques had to be refined. Development and implementation of friction stir welding was a substantial technology development incorporated during the Program. Automated thermal protection system application processes were developed for the majority of the tank surface. Material obsolescence was an issue throughout the 40 year program. The final configuration and tank weight enabled international space station assembly in a high inclination orbit allowing international cooperation with the Russian Federal Space Agency. Numerous process controls were implemented to assure product quality, and innovative proof testing was accomplished prior to delivery. Process controls were implemented to assure cleanliness in the production environment, to control contaminants, and to preclude corrosion. Each tank was accepted via rigorous inspections, including non-destructive evaluation techniques, proof testing, and all systems testing. In the post STS-107 era, the project focused on ascent debris risk reduction. This was accomplished via stringent process controls, post flight assessment using substantially improved imagery, and selective redesigns. These efforts were supported with a number of test programs to simulate combined environments. Processing improvements included development and use of low spray guns for foam application, additional human factors considerations for production, use of high fidelity mockups during hardware processing with video review, improved tank access, extensive use of non destructive evaluation, and producibility enhancements. Design improvements included redesigned bipod fittings, a bellows heater, a feedline camera active during ascent flight, removal of the protuberance airload ramps, redesigned ice frost ramps, and titanium brackets replaced aluminum brackets on the liquid oxygen feedline. Post flight assessment improved due to significant addition of imagery assets, greatly improving situational awareness. The debris risk was reduced by two orders of magnitude. During this time a major natural disaster was overcome when Katrina damaged the manufacturing facility. Numerous lessons from these efforts are documented within the paper.

Welzyn, Kenneth↗

DOE OSTI2025

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗

DOE OSTI2025

Alaska Liquid Natural Gas Pipeline Front-End Engineering & Design (Final Technical Report)

The Alaska Gasline Development Corporation (AGDC) is Alaska’s natural gas infrastructure development corporation established in 2013. AGDC’s mission is to maximize the benefit of Alaska’s vast North Slope natural gas resources for Alaskans through the development of infrastructure necessary to move the gas into local and international markets. AGDC was identified for a Congressionally Directed Spending (CDS) project for funding in the Energy and Water Development and Related Agencies Appropriations Act, 2023 under the heading: “Congressionally Directed Energy Efficiency and Renewable Energy Projects.” The CDS included $\$$4,000,000 of direct funding, with required match funds, to move the project forward. Alaska’s North Slope holds America’s largest proven and conventional natural gas supply. The integrated Alaska LNG Project will deliver 3.5 billion cubic feet of natural gas per day from Alaska’s North Slope gas fields to Alaskans as well as to a marine terminal located at tidewater in Cook Inlet. Alaska LNG is an integrated gas infrastructure project with three major components: a gas treatment plant (GTP) located at Prudhoe Bay, an 807-mile (1,287 km) gas pipeline (Mainline Pipeline) to Southcentral Alaska with interconnections for in-state gas use, and a natural gas liquefaction facility (LNG Facility) in Nikiski, Alaska. The integrated Alaska LNG Project has several strategic advantages including proven gas resources, existing upstream infrastructure, an advantageous arctic climate for LNG production, proximity to LNG markets, a track record of reliability from a state that first began exporting LNG to Japan in 1969, and broad support from Alaskans. North Slope natural gas is a conventional resource and can be produced with minimal drilling at a fraction of the carbon dioxide emissions of shale gas from the Lower 48 states. Through the development of the Alaska LNG Project, Alaska can provide energy security to Alaskans and a stable source of LNG to the Asia-Pacific region for generations. The Alaska LNG Project has been progressed through Pre-Front-End Engineering Design (Pre-FEED) and has obtained all major federal and State of Alaska permits and authorizations to construct the project, including the Federal Energy Regulatory Commission (FERC) Order Granting Authorization Under Section 3 of the Natural Gas Act. On September 5, 2024, the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) awarded Project No. DE-FE0032307 to AGDC with the objective to progress the project to Front-End Engineering Design (FEED) entry for the Alaska LNG Project Phase 1 Pipeline. The award Start Date was made effective July 1, 2023, with a Period of Performance through June 30, 2025. On March 27, 2025, AGDC announced the execution of definitive commercial agreements with Glenfarne Alaska LNG, LLC, an affiliate of Glenfarne Group, LLC, (together as “Glenfarne”), to lead the development of the Alaska LNG Project and enter FEED for the Phase 1 Pipeline. Project activities are now funded and directed by this private sector partner who holds a 75% interest in 8 Star Alaska, LLC (8 Star). 8 Star holds the assets of the Alaska LNG Project. As planned, AGDC continues to hold 25% minority interest in 8 Star and will play a governance role moving forward with Alaska LNG. This definitive commercial agreement milestone led to the successful completion of AGDC’s Statement of Project Objectives (SOPO) for FEED entry and led to the completion of DOE Project No. DE-FE0032307. At conclusion of the SOPO, AGDC also reached the award’s maximum federal cost share of $\$$4,000,000. AGDC is, therefore, providing Final Technical Report to close out DOE Project No. DE-FE0032307.

02 PETROLEUM↗

NASA NTRSDate not supplied

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗

NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗

NASA NTRSDate not supplied

Independent Technical Assessment of NASA and External Quantum Sensing Capability

The recent FY 2020 federal Research and Development Budget Priorities memo addresses the leadership need in Quantum Information Science (QIS) directing agencies to “prioritize QIS research and development (R&D), which will build the technical and scientific base necessary to explore the next generation of QIS theory, devices, and applications.” Quantum Sensing (QS) is an integral part of QIS. NASA is a key part of the directive to forward American space exploration and commercialization by providing “capabilities that have broad potential applications in space and on Earth.” QS provides an arena for NASA to demonstrate leadership in both areas of the administrative directive. QS uses quantum properties to achieve unprecedented measurement sensitivity and performance, including quantum-enhanced methodologies that outperform their classical counterparts. Typical quantum sensors exploit techniques such as atomic systems, matter waves, quantum entanglement, quantum superposition of states, quantum illumination methods, and manipulation of photons and atoms, in general. Guided by advancements in our ability to generate, manipulate, and control quantum systems, the emerging quantum sensing technologies promise unrivalled sensitivity, resolution, and precision, potentially leading to game-changing applications. Significant gains include technologies important for a range of NASA missions such as remote sensing, in situ measurements, metrology, interferometry, quantum communication, ranging, imaging, radar and lidar receivers, and gravity measurements. NASA Engineering and Safety Center has convened an independent external panel, comprising of Quantum Sensing Experts from Government, DoD, academia, and Federally funded Research and Development Center to conduct an independent technical assessment of the agency's capabilities in Quantum Sensing to understand NASA's internal needs and competencies related to Quantum Sensing and compare agency capabilities with those available externally including industry, academia, and other government agencies. The outcomes of the assessment will help the agency in establishing appropriate strategies and investments to develop and maintain the state-of-the-art sensing competence and capabilities required to meet the agency’s future needs. The External Experts Panel (EEP) is collaborating with HQ, various NASA Center and the representatives in the NASA Quantum Sensing Community of Practice (QS CoP), a part of NASA Sensors and Instrumentation Technical Fellow Technical Discipline Team, in obtaining common, current understanding of agency mission needs where QS can be an important enabler for future needs, and any programs, projects, assets, and technologists working in QS. The EEP organized a Quantum Sensing Workshop of practitioners from industry, academia, other government agencies, external experts, and interested NASA personnel to gather the assessment information. EEP also conducted information gathering on the industry at large, educational institutions, and other government agency research efforts for capture in the assessment database. At the conclusion of this assessment, EEP team will develop findings and conclusions describing NASA’s capabilities for the mission needs, NASA's relative position on new, enabling technologies, and an analysis of the gaps that may present any risks to near-term or far-term mission needs. This presentation will give details of the NASA and External Quantum Sensing Assessment outcomes, findings, observations, and its recommendation to NASA as how it can advance Quantum Sensing technologies and techniques for its science and explorations related missions.

External Quantum Sensing Capability↗

NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗

NASA NTRS2001

Challenges and Lessons Learned in the Application of Autonomy to Space Operations

NASA's Space Operations Management Office (SOMO) is working toward a goal of providing an integrated infrastructure of mission and data services for space missions undertaken by NASA enterprises. A significant portion of this effort is focused on reducing the cost of these services. We are interested in the potential of autonomy to reduce operations costs. SOMO services support space missions, but are not part of the mission objectives; therefore the level of acceptable risk is very low. In fact, SOMO could be effective ly prevented from applying autonomy if customers merely perceive it as adding risk to their mission(s). We are interested in this workshop from the standpoint of understanding what can be done to realize the potential cost savings due to autonomy while maintaining acceptable risk and serving the needs of our customers. We would like to present our lessons learned so far in adopting autonomy and automation, which we think will contribute to clarifying the challenges facing the use of such technology. SOMO provides services to a diverse and ambitious set of mission customers. Many of these missions are groundbreaking missions for which communications, data, and other operations requirements sometimes cannot be clearly articulated early in the program. This motivates a need for systems that are robust in the face of unanticipated situations so that customer missions are not unreasonably constrained or impacted by "shortcomings" in SOMO services. One of SOMO's primary goals is to realize a paradigm in which SOMO acts as a service provider to organizations that fly space missions for NASA, other government agencies, and even the commercial sector. These organizations purchase SOMO services "by the pound" as customers. We have to provide systems that are not experiments themselves, but rather stable bases from which to do bold experiments. To this end, SOMO also seeks to work closely with industry to see that robust autonomy technology gets infused into products and services for the space industry and beyond. The potential for application of these technologies spans space-based communications networks (e.g. TDRSS) and ground-based assets including communication and tracking antenna systems, data networks, and control centers. There are several problems that are candidates for the application of autonomy, if it can be made reliable enough, including: antenna control, antenna scheduling, communication link scheduling and operation, navigation, attitude determination, fault detection, isolation, and reconfiguration (for spacecraft or ground assets), and mission-level planning and scheduling. Some attempts have been made to apply autonomy and automation in these areas in the past with varying degrees of success. We will present relevant case histories and the lessons inferred from them. Combining this past experience with anticipated future needs, we can clarify the challenges that must be met in order to realize the benefits of autonomy.

Forrest, David J.↗

DOE OSTI2026

Use of Hardware-in-the-Loop to De-Risk Field Deployment of Hydrogen Assets

Grid-forming assets are required in microgrids to act as voltage-frequency masters. These grid-forming assets can operate in two modes of operation: grid-following mode and grid-forming mode. In grid-following mode of operation, these assets will follow real power and reactive power setpoints and in grid-forming mode of operation these assets will follow voltage and frequency setpoints. Traditionally, diesel generators or natural gas-based generators are widely used to act as a voltage-frequency master. However, many utilities are aiming to replace generators with grid forming-inverters supplied by solar photovoltaics (PV), batteries or fuel cells. Since grid-forming assets need a long-term reliable energy source, fuel cells are a reasonable and viable choice to supply the grid-forming inverters, but some of the challenges facing the wide deployment of grid-forming fuel cell inverters need to be addressed. Specifically, in our proposed work, we aim to focus on the interconnection and interoperability requirements of grid-forming fuel cell inverters. Currently, state-of-the-art fuel cell inverters follow the general interconnection requirements of distributed energy resources (DERs) and general interoperability requirements of DERs, but these requirements were built with PV and battery systems in mind. Fuel cells have different operational requirements, and therefore these requirements need to be appropriately modified for the grid operators to use. These additional steps add to the investment and operational cost to the grid operators. Through the ARIES platform, this proposed project aims to bridge this gap and use power hardware-in-the-loop (PHIL) and controller hardware-in-the-loop (CHIL) experiments to inform the creation of open-source interconnection and interoperability information that can aid in faster and cheaper installation and operation of grid-forming fuel cell inverters.

08 HYDROGEN↗

NASA NTRS2019

A Detect and Avoid System in the Context of Multiple-Unmanned Aircraft Systems Operations

NASA's Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgements about a potential threat of a loss of well clear with another aircraft. NASA's Phase 1 research supported the development of a Detect and Avoid (DAA) system that supports the ground-based pilot's ability to detect potential traffic conflicts and determine a resolution maneuver, but existing display/alerting requirements did not account for multiple UAS control (1:N). Demands for increased scalability of UAS in the NAS operations are expected to create a need for simultaneous control of UAs, and thus, a new DAA HMI design will likely be necessary. Previous research, however, has found performance degradations as the number of vehicles under operator control has increased. The purpose of the current human-in-the-loop (HITL) simulation was to examine the viability of 1:N operations with the Phase 1 DAA alerting and guidance. Sixteen UAS pilots flew three scenarios with varying number of UAs under their control (1:1, 1:3, 1:5). In addition to their supervisory and sensor mission responsibilities, pilots were to utilize the DAA system to remain DAA well clear (DWC) during scripted conflicts of mixed severity. Measured response times, separation performance, mission task data, and subjective feedback were collected to assess how the multi-UAS control configuration impacted pilots' ability to maintain DAA well clear and perform the mission tasks. Overall, the DAA system proved surprisingly adaptive to multi-UAS control for preventing losses of DAA well clear (LoDWC). The findings suggest that, while multi-UAS operators are able to maintain safe separation (DWC) from other traffic, their ability to efficiently perform missions drastically decreases with their number of controlled vehicles. Pilot feedback indicated that, for this context, the use of automation support tools for completing and managing mission tasks would be appropriate and desired, especially for ensuring efficient use of assets. Finally, human-machine interface (HMI) design considerations for multi-UAS operations are discussed.

Monk, Kevin J.↗