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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 235 records · Page 13

All sources NASA NTRS DOE OSTI

DOE OSTI2025

2022 Kauai Ground Transportation Survey

# 2022 Kauai Ground Transportation Survey The 2022 Kauai Ground Transportation Survey was designed to improve understanding of the transportation preferences of residents and visitors of the Hawaiian island of Kauai. For residents of Kauai, the survey focused on mode-choice decisions for commute, leisure, and shopping activities and whether they would consider using alternative modes instead of driving if such options were available. For visitors, the survey focused on whether they would consider alternatives to rental cars if such options were available. Ultimately, survey results will inform the development of sustainable transportation strategies for the island. ## Data Collection Agency NREL and the Kauai Office of Economic Development conducted the study as part of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. ## Survey Methodology The survey was conducted July—October 2022. Respondents were recruited via direct email invitation, a press release on the Kauai County website and Facebook page, and posters at community outreach events. ## Survey Records, Data, and Documentation Survey records include 1,437 participants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Kauai Ground Transportation Survey

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Kauai Ground Transportation Survey

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1987

Applications considerations in the system design of highly concurrent multiprocessors

A flow model processor approach to parallel processing is described, using very-high-performance individual processors, high-speed circuit switched interconnection networks, and a high-speed synchronization capability to minimize the effect of the inherently serial portions of applications on performance. Design studies related to the determination of the number of processors, the memory organization, and the structure of the networks used to interconnect the processor and memory resources are discussed. Simulations indicate that applications centered on the large shared data memory should be able to sustain over 500 million floating point operations per second.

Lundstrom, Stephen F.↗

NASA NTRS1990

CCSDS Reed Solomon VLSI chip set

A highly efficient error correcting code has been selected by NASA as a CCSDS standard: the 16 symbol error correcting Reed Solomon code. A VLSI implementation of this decoder is described in this paper. A total of 4 full custom VLSI chips are needed that correct data in real time at an sustained rate of up to 80 Mbits/second.

Cameron, K.↗

NASA NTRS1993

High performance quarter-inch cartridge tape systems

Within the established low cost structure of Data Cartridge drive technology, it is possible to achieve nearly 1 terrabyte (10(exp 12)) of data capacity and more than 1 Gbit/sec (greater than 100 Mbytes/sec) transfer rates. The desirability to place this capability within a single cartridge will be determined by the market. The 3.5 in. or smaller form factor may suffice to serve both the current Data Cartridge market and a high performance segment. In any case, Data Cartridge Technology provides a strong sustainable technology growth path in the 21st century.

Schwarz, Ted↗

NASA NTRS2017

The Integrated Medical Model: Outcomes from Independent Review

In 2016, the Integrated Medical Model (IMM) v4.0 underwent an extensive external review in preparation for transition to an operational status. In order to insure impartiality of the review process, the Exploration Medical Capabilities Element of NASA's Human Research Program convened the review through the Systems Review Office at NASA Goddard Space Flight Center (GSFC). The review board convened by GSFC consisted of persons from both NASA and academia with expertise in the fields of statistics, epidemiology, modeling, software development, aerospace medicine, and project management (see Figure 1). The board reviewed software and code standards, as well as evidence pedigree associated with both the input and outcomes information. The board also assesses the models verification, validation, sensitivity to parameters and ability to answer operational questions. This talk will discuss the processes for designing the review, how the review progressed and the findings from the board, as well as summarize the IMM project responses to those findings. Overall, the board found that the IMM is scientifically sound, represents a necessary, comprehensive approach to identifying medical and environmental risks facing astronauts in long duration missions and is an excellent tool for communication between engineers and physicians. The board also found IMM and its customer(s) should convene an additional review of the IMM data sources and to develop a sustainable approach to augment, peer review, and maintain the information utilized in the IMM. The board found this is critically important because medical knowledge continues to evolve. Delivery of IMM v4.0 to the Crew Health and Safety (CHS) Program will occur in the 2017. Once delivered for operational decision support, IMM v4.0 will provide CHS with additional quantitative capability in to assess astronaut medical risks and required medical capabilities to help drive down overall mission risks.

medical equipment↗

NASA NTRSDate not supplied

Applications of NASA’s LANCE Earth Observations for Ecosystem Assessments

As one of NASA's open and free data systems, NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) provides a wide range of near real-time, low latency and expedited data products from NASA and other earth science satellite missions to support users in their understanding of the value and distribution of ecosystem services. LANCE data can support the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework by both facilitating the creation of ecosystem spatial extent and condition accounts, as well as the quantification and mapping of ecosystem services, much more quickly than routine data processing allows. During the past 13 years, LANCE near real-time satellite data products (e.g., surface reflectance, albedo, vegetation height, thermal anomalies, soil moisture, snow cover etc.) have been used to produce ecosystem-related indicators such as vegetation indexes, biomass, land cover maps, fire, and flood products. These ecosystem-related indicators can be integrated into ecosystem services models, tools, and platforms to monitor land cover and land use changes in ecosystem composition in support of land and natural resource management. When using ecosystem services accounts in decision-making, low latency is essential because having up-to-date information can be critical to support decisions being made. With adequate spatial resolution, long time series length, and low latency data products, LANCE would promote the sustainable use of land and natural resources.

Tian Yao↗

DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗

DOE OSTI2021

Do We Need a New Sustainability Assessment Method for the Circular Economy? A Critical Literature Review

The goal of the circular economy (CE) is to transition from today's take-make-waste linear pattern of production and consumption to a circular system in which the societal value of products, materials, and resources is maximized over time. Yet circularity in and of itself does not ensure social, economic, and environmental performance (i.e., sustainability). Sustainability of CE strategies needs to be measured against their linear counterparts to identify and avoid strategies that increase circularity yet lead to unintended externalities. The state of the practice in quantitatively comparing sustainability impacts of circular to linear systems is one of experimentation with various extant methods developed in other fields and now applied here. While the proliferation of circularity metrics has received considerable attention, to-date, there is no critical review of the methods and combinations of methods that underlie those metrics and that specifically quantify sustainability impacts of circular strategies. Our critical review herein analyzes identified methods according to six criteria: temporal resolution, scope, data requirements, data granularity, capacity for measuring material efficiency potentials, and sustainability completeness. Results suggest that the industrial ecology and complex systems science fields could prove complementary when assessing the sustainability of the transition to a CE. Both fields include quantitative methods differing primarily with regard to their inclusion of temporal aspects and material efficiency potentials. Moreover, operations research methods such as multiple-criteria decision-making (MCDM) may alleviate the common contradictions which often exist between circularity metrics. This review concludes by suggesting guidelines for selecting quantitative methods most appropriate to a particular research question and making the argument that while there are a variety of existing methods, additional research is needed to combine existing methods and develop a more holistic approach for assessing sustainability impacts of CE strategies.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

SERVIR - Connecting Space to Village in Africa, Asia and the Americas

SERVIR is a joint NASA and USAID program that partners with countries and organizations to support locally led efforts to strengthen climate resilience, food and water security, forest and carbon management, and air quality. This unique program integrates NASA’s world class scientists and data with USAID’s development expertise and network of partners and relationships around the world. SERVIR harnesses the power of satellite data and science collaboration to support healthy, sustainable communities, livelihoods and environments. SERVIR’s name is derived from Latin, meaning "to serve.” We serve and partner with leading local, national, and regional institutions in Africa, Asia, and Latin America and in partnership with scientists and subject matter experts to co-develop and implement activities called “services.” Each of SERVIR’s services provide a comprehensive suite of geospatial data, software, and training materials, all of which are tailored to the unique needs of SERVIR’s end users. Each service is collaboratively designed and implemented with the help of partners and users, such as local governments and NGOs, to better support decision-making. When SERVIR plans new services, it prioritizes long-term dialogue and engagement with communities to ensure that services are sustainable, socially inclusive, and suited to local needs. SERVIR strives to make the power of Earth science more accessible and inclusive. All web tools are made publicly available to help promote greater uptake and long-term use of SERVIR’s services.

SERVIR↗

DOE OSTI2024

Aboveground Biomass Estimation Using NISAR Simulated ALOS-2 Time Series Data

Aboveground biomass (AGB) is a critical parameter to better understand the global carbon cycle and to develop sustainable forest management. However, a large uncertainty prevails. L-band SAR data have demonstrated strong potential to accurately retrieve AGB over low-biomass regions (<100 Mg ha-1). The upcoming NASA-ISRO Synthetic Aperture Radar mission will collect data at L- and S-band over earth’s landmass with a repeat period of 12 days, allowing us to have ample data for monitoring biomass and its dynamics. One of the key science requirements of the mission is to produce annual AGB maps at 1-ha resolution with RMS accuracy of 20 Mg/ha for 80 percentage of area over low-biomass regions in Calibration/Validation sites. The NISAR biomass algorithm will generate AGB maps based on the parameterization of semi-empirical model along with NISAR time-series dual pol data (HH and HV). To calibrate and validate the model for mission requirements, the mission will use reference estimates of AGB produced from ground inventory plots and airborne LiDAR data collected over selected sites distributed across different global ecoregions. This paper presents the initial results of the calibration/validation of the NISAR AGB retrieval algorithm over the Lenoir Landing (LENO), Alabama, USA site using NISAR simulated ALOS-2 time series data. Five multi-temporal dual-pol HH and HV NISAR Simulated ALOS 2 data collections were used as input to assess the performance of the model. The model AGB retrieval results shows that the NISAR model was able to achieve RMS accuracy within 20 Mg/ha.

Ramachandran, Naveen [Jet Propulsion Laboratory, C↗

NASA NTRS1979

Quantitative energy extraction measurements in a photoionization-stabilized self-sustained XeF laser

Detailed time-correlated gain, fluorescence, and laser energy measurements were used to obtain quantitative data on energy extraction efficiencies for a photoionization-stabilized self-sustained XeF laser. A current pulse of 25 ns full width at half-maximum produced an 80-cu-cm XeF plasma in NF3:Xe:He gas mixtures with a maximum output energy of 80 mJ. The results show that the maximum small-signal gain and the maximum specific output energy is proportional to the NF3 content of the gas mixture. This suggests that there is an optimum fractional utilization of the NF3 molecules in the discharge. Under high-gain conditions, 30-40% of the energy stored in XeF(asterisk) can be extracted in a gain-switched pulse. The output energy represents less than 1% of the input energy.

Lee, C. M.↗

DOE OSTI2023

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Industry case studies: Finance

This article, the third in a series on the U.S. Department of Energy and IDEA collaboration, focuses on financial strategies used by institutions to support district energy system modernization and decarbonization. It highlights how effective funding models, long-term cost analysis, and leadership support are critical to implementing large-scale infrastructure upgrades. The case studies show different approaches to financing. Ball State University demonstrates how life-cycle cost analysis and phased funding—supported by state funding, bonds, and grants—enabled a transition to geothermal energy. Penn State’s Hershey Medical Center emphasizes the importance of financial leadership, shifting from reactive budgeting to data-driven, proactive investment in infrastructure. The University of Washington highlights how comprehensive data collection and analytics can justify investments and even create self-sustaining funding mechanisms like green revolving funds. Overall, the article shows that combining strong financial planning, data-driven decision-making, and innovative funding approaches is essential for advancing sustainable district energy systems while managing high upfront costs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗

NASA NTRSDate not supplied

NASA’s Commercial Smallsat Data Acquisition (CSDA) Program Data System

The National Aeronautic and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) Program was established to identify, evaluate, and acquire data from commercial satellite companies that support and complement NASA’s Earth sciences missions and research goals. Since becoming a sustained program in 2020, CSDA has been developing a data system to provide scalable, efficient, continuous, and repeatable data management processes for all commercial data acquired by NASA. This includes providing access to commercial data to approved science investigators through NASA developed and vendor operated interfaces. As the commercial data user community and volume of data acquired by CSDA has grown, the team managing these data has adapted technologies and services to better address the data and information search, discovery, and access needs of the science user community. This presentation will provide an overview of CSDA Program data system activities including data availability, development of CSDA user interfaces, challenges in managing large-volume diverse datasets, and long-term data preservation activities to retain data for scientific reproducibility.

data management↗

NASA NTRSDate not supplied

Science Utilizing Data from Spire Global as Part of the NASA Commercial SmallSat Data Acquisition (CSDA) Program

As part of the Commercial SmallSat Data Acquisition (CSDA) Program, NASA has evaluated data from Spire Global, Inc. and subsequently established a sustained purchase agreement with them. The primary goal of this agreement is to acquire and make available Spire datasets to the research community with the aim of enhancing the science objectives through the Earth Science Division (ESD), though there are noted applications to the NASA Heliophysics Division as well. This talk will present the data access details and holdings of Spire data by the CSDA Program, including those from radio occultation and reflectometry. It will also present selected scientific results and applications of these data from both the pilot evaluation and the sustained purchase stages to highlight their use within the ESD research portfolio.

Wil McCarty↗