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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 397 records · Page 22

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NASA NTRS2010

Toolsets Maintain Health of Complex Systems

First featured in Spinoff 2001, Qualtech Systems Inc. (QSI), of Wethersfield, Connecticut, adapted its Testability, Engineering, and Maintenance System (TEAMS) toolset under Small Business Innovation Research (SBIR) contracts from Ames Research Center to strengthen NASA's systems health management approach for its large, complex, and interconnected systems. Today, six NASA field centers utilize the TEAMS toolset, including TEAMS-Designer, TEAMS-RT, TEAMATE, and TEAMS-RDS. TEAMS is also being used on industrial systems that generate power, carry data, refine chemicals, perform medical functions, and produce semiconductor wafers. QSI finds TEAMS can lower costs by decreasing problems requiring service by 30 to 50 percent.

Source record↗

NASA NTRS2018

Embracing Innovation in Aviation While Respecting Its Safety Tradition

Emerging markets for drones and urban air mobility are going to impact the airspace operations environment. Changes to the current system is necessary to enable new innovations without compromising safety. This presentation discusses how a UTM-inspired air traffic management system can address these needs.

UAS↗

NASA NTRS2021

Advanced Air Mobility and Safety Management Systems

Our current air transportation system has underserved markets, including local, regional, intraregional, and urban transportation of both people and cargo. Recent advances in aviation technology such as small highly-automated vehicles, electric aircraft, and automated air traffic are enabling business opportunities in these markets. Advanced Air Mobility, or AAM, refers to a community effort to overcome the gaps in operational rules, safety analysis, and overall acceptance, so that these new operations will be possible. For full details, please see: https://www.nasa.gov/aam As we think about how we can safely introduce these new operations, fundamental questions about how the structure of Safety Management Systems can be applied to AAM, and how that structure can be used to help us overcome the necessary technical and societal obstacles arise. Two of these questions are: • How do we tailor the requirements and desired level of monitoring and assessment to achieve safety given the breadth of possible operations and the associated risk of those operations? • How do we aid innovation by rapidly evaluating the safety of novel operations without losing associated rigor? We assume that a Safety Management System that enables these future systems will incorporate knowledge of the acceptable level of risk, and will utilize data science to automate the core monitor, assess and mitigate functions that will allow us to respond to risks and hazards in time to prevent safety incidents. In 2018, the National Academies proposed an In-Time Aviation Safety Management System (IASMS) that would advance these goals. (https://www.nap.edu/catalog/24962/in-time-aviation-safety-management-challenges-and-research-for-an) The National Academies made a clear distinction between in-time systems, in which hazards could be identified and risks mitigated in time to prevent incidents, and real-time systems, since many hazards and risks do not need real-time data and analysis to detect and mitigate.

In-Time Aviation Safety Management System↗

DOE OSTI2023

Connecting People to Data: Enabling Data Connected Communities through Enhancements to the Geothermal Data Repository

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented a series of new features designed to connect people to data. These features, which are based on feedback from the GDR user community and surveys of the greater geothermal research community, are designed to improve data quality and empower members of all communities to better engage with geothermal data resources by providing universal access to data and by improving the connections between data providers, subject matter experts, and the communities of people using GDR data. This paper will explore some of the recent enhancements made to the GDR to improve data discoverability, reduce submission time, and result in better quality data submissions. These improvements include the ability for users to save a list of their favorite datasets, search for insight into geothermal datasets or data availability, or sign up to receive notifications of future updates to specific datasets. These improvements aim to enhance the overall user experience of the GDR while further connecting communities to the data they need to inform decisions, advance geothermal research, and develop innovative solutions to local energy problems.

access↗

DOE OSTI2023

Nuclear waste Educator's workshop: What and how do we teach about nuclear waste?

A workshop was held at the Massachusetts Institute of Technology (MIT) on July 25th and 26th, 2022. The objective was to develop a blueprint for educating next-generation engineers and scientists about nuclear waste management and disposal, which requires knowledge from diverse disciplines, including nuclear, chemical, civil, environmental, and geological science and engineering. The 49 participants included university professors, researchers, industry experts, and government officials from different areas. First, we have developed a list of key fundamental knowledge on waste management and disposal across the nuclear fuel cycle. In addition, we discussed strategies on how to teach students with diverse backgrounds through innovative teaching strategies as well as how to attract students into this area. Through the workshop, we identified the critical needs to (1) develop community resources for nuclear waste education; (2) synthesize historical perspectives, including past contamination and the management of general hazardous waste; (3) emphasize a complete life-cycle perspective, including proper waste management as the key component for energy sustainability; (4) teach students how to communicate about the key facts and risks to technical and non-technical audiences; and (5) accelerate the use of the state-of-art-technologies to attract and retain a young workforce. Furthermore, we aim to build a diverse, inclusive community that supports students in developing their own narratives about nuclear waste, particularly in recognizing that antagonistic views have been important to improving safety and protecting public health and the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2011

Atomic Oxygen Fluence Monitor

This innovation enables a means for actively measuring atomic oxygen fluence (accumulated atoms of atomic oxygen per area) that has impinged upon spacecraft surfaces. Telemetered data from the device provides spacecraft designers, researchers, and mission managers with real-time measurement of atomic oxygen fluence, which is useful for prediction of the durability of spacecraft materials and components. The innovation is a compact fluence measuring device that allows in-space measurement and transmittance of measured atomic oxygen fluence as a function of time based on atomic oxygen erosion yields (the erosion yield of a material is the volume of material that is oxidized per incident oxygen atom) of materials that have been measured in low Earth orbit. It has a linear electrical response to atomic oxygen fluence, and is capable of measuring high atomic oxygen fluences (up to >10(exp 22) atoms/sq cm), which are representative of multi-year low-Earth orbital missions (such as the International Space Station). The durability or remaining structural lifetime of solar arrays that consist of polymer blankets on which the solar cells are attached can be predicted if one knows the atomic oxygen fluence that the solar array blanket has been exposed to. In addition, numerous organizations that launch space experiments into low-Earth orbit want to know the accumulated atomic oxygen fluence that their materials or components have been exposed to. The device is based on the erosion yield of pyrolytic graphite. It uses two 12deg inclined wedges of graphite that are over a grit-blasted fused silica window covering a photodiode. As the wedges erode, a greater area of solar illumination reaches the photodiode. A reference photodiode is also used that receives unobstructed solar illumination and is oriented in the same direction as the pyrolytic graphite covered photodiode. The short-circuit current from the photodiodes is measured and either sent to an onboard data logger, or transmitted to a receiving station on Earth. By comparison of the short-circuit currents from the fluence-measuring photodiode and the reference photodiode, one can compute the accumulated atomic oxygen fluence arriving in the direction that the fluence monitor is pointing. The device produces a signal that is linear with atomic oxygen fluence using a material whose atomic oxygen erosion yield has been measured over a period of several years in low-Earth orbit.

Banks, Bruce A.↗

NASA NTRSDate not supplied

From the Knowledge-based Digital Platform (KbDP) Concept for Advanced Air Mobility Research to a Preliminary Prototype

Advanced Air Mobility (AAM) encompasses a range of innovative operational and technological changes to aviation (electric aircraft, increasingly automated aircraft, increasingly automated airspace operations, etc.) that are transforming aviation’s role in everyday movement of people and goods. There are multiple associated concepts and use cases for AAM, all interrelated, including small Unmanned Aircraft System (UAS) Traffic Management (UTM), Upper-Class E Traffic Management (ETM), Extensible Traffic Management (xTM), Regional Air Mobility (RAM), and Urban Air Mobility (UAM). These AAM operations must integrate with traditional Air Traffic Management (ATM) operations, as well as non-aviation modes of transportation and logistics. National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from the information database, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Expected benefits of this concept include improved technology transfers from research to production, improved research portfolio investments, and research outcomes that are more integrated with all aspects of the multi-modal transportation problem. The preliminary KbDP prototype has been realized using UAM as a pathfinder use case and developed by a team of system engineer, software developer, data scientist, and interns.

Systems Engineering↗

DOE OSTI2026

Los Alamos Innovation Enables Carbon-Negative Infrastructure Through an AI Infrastructure Partnership

A material innovation first developed at Los Alamos National Laboratory (LANL) is now enabling a major step forward in carbon management. Licensed by Spiritus, the technology is being deployed in a $500 million partnership with Prometheus Hyperscale and Casper Carbon Capture to build one of the largest carbon-negative digital infrastructure projects in the world. Located in Casper, Wyoming, the initiative directly integrates permanent carbon removal with advanced computing systems, illustrating how Los Alamos research continues to advance national goals in energy, security, and innovation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Industrial Load Flexibility, the U.S. Power Grid and Ammonia

A variable renewable power grid is a new technological regime that involves real time harvesting and low-cost availability of energy resources coupled with storage to meet additional needs. Decarbonization through electrification of end uses formerly met by combustion processes will be a concurrent trend. Taken together, these two changes may make flexibility on the demand side more valuable to the grid and to industrial users. Industry accounted for 26% of US power demand in 2021. Traditionally, industrial processes for producing ammonia and other basic materials have been optimized for a system based on fossil resources, where energy can be called upon according to needs. Large capital expenditures as well as safety considerations have favored plants running at steady state at close to their maximum capacity. It is possible, however, that the renewable energy transition will offer opportunities to sectors that can operate in a more flexible manner. Innovations that make use of flexibility to enhance their business model to move forward, individuals and groups active in their development, use and regulation, together with institutions and infrastructures, can be considered as a technological innovation system (TIS). Beyond economic and technical factors on their own, the TIS is an important analysis framework for studying the development and diffusion of technologies. This work attempts to map the TIS of flexible industrial loads and their interaction with electric power in the US, with a particular focus on ammonia as a case study. We have conducted interviews with stakeholders involved in ammonia projects, working in system operators, trade groups, regulators and utilities. We assess to what extent a technological innovation system is functioning and document characteristics that allow industries to operate flexibly.

ammonia↗

DOE OSTI2023

Grand challenges in the digitalisation of wind energy

The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelised cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as “grand challenges” in the digitalisation of wind energy. They are, first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.

17 WIND ENERGY↗

DOE OSTI2023

Pillars of Innovation Across Southeast Idaho & the Interstate-15 Corridor

Since 1949, Idaho National Laboratory (INL) has been home to developing civilian and defense nuclear reactor technologies and managing spent nuclear fuel. Today, INL is the nation’s nuclear energy research laboratory, sustaining the safe and efficient operation of existing reactors, powering science in space, and breaking ground on the future fleet of advanced nuclear reactors. INL is only one of many rising technology resources in the region, however. Along the Interstate 15 (I-15) corridor, technology and cybersecurity industries and intellectual assets are rapidly expanding. Creating an innovation hub in this region would unite capabilities to solve current and future challenges in nuclear reactor sustainment and expanded deployment, integrated fuel cycle solutions, integrated energy systems, advanced materials and manufacturing for extreme environments, and secure and resilient cyber-physical systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRSDate not supplied

Simulated Evaluation of Strategic Conflict Management Capabilities for Urban Air Mobility Operations

Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and automation technologies. NASA has conducted a series of simulations to evaluate the UAM concept of operations and inform the development of airspace procedures and services for UAM operations. The latest set of simulations called “X5” were conducted to test a Provider of Services for UAM (PSU) prototype that NASA developed for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In these simulations, two strategic conflict management capabilities, Demand-Capacity Balancing (DCB) and Sequencing and Scheduling (S&S), were further investigated. This paper describes the system architecture designed for the X5 simulation activities, the sequence diagram for strategic conflict management, and the simulation environment in the Dallas/Fort Worth urban area. The simulation results based on several system performance metrics for evaluation show that a sequential application of DCB and S&S effectively works to distribute traffic demand and meet sequencing and spacing criteria by assigning ground delays, compared to the DCB only and S&S only cases.

Urban Air Mobility, Strategic Conflict Management,↗

NASA NTRSDate not supplied

Simulated Evaluation of Strategic Conflict Management Capabilities for Urban Air Mobility Operations

Simulation↗

DOE OSTI2024

Sentiment analysis of the United States public support of nuclear power on social media using large language models

This study utilized large language models (LLMs) to analyze public sentiment in the United States (US) regarding nuclear power on social media, focusing on X/Twitter, considering climate change challenges and advancements in nuclear power technology. Approximately, 1.26 million nuclear tweets from 2008–2023 were examined to fine-tune LLMs for sentiment classification. We found the crucial role of accurate data labeling for model performance, with potential implications for a 15% improvement, achieved through high-confidence labels. LLMs demonstrated better performance compared to traditional machine learning classifiers, with reduced susceptibility to overfitting and up to 96% classification accuracy. LLMs are used to segment the US public tweets into policy and energy-related categories, revealing that 68% are politically themed. Policy tweets tended to convey negative sentiment, often reflecting opposing political perspectives and focusing on nuclear deals and international relations. Energy-related tweets covered diverse topics with predominantly neutral to positive sentiment, indicating broad support for nuclear power in 48 out of 50 US states. The US public positive sentiments toward nuclear power stemmed from its high power density, reliability regardless of weather conditions, environmental benefits, application versatility, and recent innovations and advancements in both fission and fusion technologies. Negative sentiments primarily focused on waste management, high capital costs, and safety concerns. The neutral campaign highlighted global nuclear facts and advancements, with varying tones leaning towards positivity or negativity. An interesting neutral theme was the advocacy for the combined use of renewable and nuclear energy to attain net-zero goals.

Energy & Fuels↗

DOE OSTI2021

Generalizable coordination of large multiscale workflows: challenges and learnings at scale

The advancement of machine learning techniques and the heterogeneous architectures of most current supercomputers are propelling the demand for large multiscale simulations that can automatically and autonomously couple diverse components and map them to relevant resources to solve complex problems at multiple scales. Nevertheless, despite the recent progress in workflow technologies, current capabilities are limited to coupling two scales. In the first-ever demonstration of using three scales of resolution, we present a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback. We expand upon the massively parallel Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a recent, award-winning workflow, and generalize the framework beyond its original design. We discuss the challenges and learnings in executing a massive multiscale simulation campaign that utilized over 600,000 node hours on Summit and achieved more than 98% GPU occupancy for more than 83% of the time. We present innovations to enable several orders of magnitude scaling, including simultaneously coordinating 24,000 jobs, and managing several TBs of new data per day and over a billion files in total. Finally, we describe the generalizability of our framework and, with an upcoming open-source release, discuss how the presented framework may be used for new applications.

Bhatia, Harsh↗

DOE OSTI2026

JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

The integration of Non-Energy Benefits (NEBs) into energy efficiency initiatives is essential for operational excellence in manufacturing. This presentation and software demonstration explore how quantifying NEBs such as improved safety, increased quality, and enhanced productivity, can strengthen business cases for energy investments, leading to better payback periods and alignment with organizational goals. We introduce JUSTIFI, a free, open-source software by the U.S. Department of Energy that aids in the measurement of NEBs and enhances understanding of their impact on Key Performance Indicators (KPIs) and return on investment (ROI). JUSTIFI features an intuitive interface for identifying NEBs, customizable reporting tools, and comprehensive system cataloging, empowering companies to effectively communicate the value of energy efficiency projects. By leveraging this innovative tool, organizations can better navigate energy efficiency assessments and drive support for their energy management initiatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1991

Distributed Access View Integrated Database (DAVID) system

The Distributed Access View Integrated Database (DAVID) System, which was adopted by the Astrophysics Division for their Astrophysics Data System, is a solution to the system heterogeneity problem. The heterogeneous components of the Astrophysics problem is outlined. The Library and Library Consortium levels of the DAVID approach are described. The 'books' and 'kits' level is discussed. The Universal Object Typer Management System level is described. The relation of the DAVID project with the Small Business Innovative Research (SBIR) program is explained.

Jacobs, Barry E.↗

DOE OSTI2020

Smart and Efficient Building Envelopes: Thermal Switches and Thermal Storage for Energy Savings and Load Flexibility

The building envelope has traditionally been seen as a static component. Much of the past thermal advancements in building envelopes has consisted of developing higher R/inch insulation. While a suitable approach for static situations, it does not consider the dynamic nature of the ambient environment or the varying needs of the electrical grid. This paper will examine three possible ways that building envelopes can be actively managed: 1. thermal switches, 2. thermal storage, and 3. the coupling of the two. Spurring innovation to make building envelopes smarter will help reduce building energy consumption and peak energy usage and contribute to flexibility in energy demand in the future.

Mumme, Sven↗