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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Determination of water surface temperature based on the use of Thermal Infrared Multispectral Scanner data

A straightforward method for compensating Thermal Infrared Multispectral Scanner (TIMS) digital data for the influence of atmospheric path radiance and the attenuation of target energy by the atmosphere is presented. A band ratioing model useful for estimating water surface temperatures, which requires no ground truth measurements, is included. A study conducted to test the potential of the model and the magnitudes of the corrections for atmosphere encountered is presented. Results of the study, which was based on data collected during an engineering evaluation flight of TIMS, indicate errors in the estimate of the surface temperature of the water fall from +/- 1.0 C for uncorrected data to +/- 0.4 C when data have been corrected according to the model presented. This value approaches the noise-limited thermal resolution of the sensor at the time of the flight.

Anderson, James E.↗
NASA NTRS2005

Quantitative Electron Probe Microanalysis: State of the Art

Quantitative electron-probe microanalysis (EPMA) has improved due to better instrument design and X-ray correction methods. Design improvement of the electron column and X-ray spectrometer has resulted in measurement precision that exceeds analytical accuracy. Wavelength-dispersive spectrometer (WDS) have layered-dispersive diffraction crystals with improved light-element sensitivity. Newer energy-dispersive spectrometers (EDS) have Si-drift detector elements, thin window designs, and digital processing electronics with X-ray throughput approaching that of WDS Systems. Using these systems, digital X-ray mapping coupled with spectrum imaging is a powerful compositional mapping tool. Improvements in analytical accuracy are due to better X-ray correction algorithms, mass absorption coefficient data sets,and analysis method for complex geometries. ZAF algorithms have ban superceded by Phi(pz) algorithms that better model the depth distribution of primary X-ray production. Complex thin film and particle geometries are treated using Phi(pz) algorithms, end results agree well with Monte Carlo simulations. For geological materials, X-ray absorption dominates the corretions end depends on the accuracy of mass absorption coefficient (MAC) data sets. However, few MACs have been experimentally measured, and the use of fitted coefficients continues due to general success of the analytical technique. A polynomial formulation of the Bence-Albec alpha-factor technique, calibrated using Phi(pz) algorithms, is used to critically evaluate accuracy issues and can be also be used for high 2% relative and is limited by measurement precision for ideal cases, but for many elements the analytical accuracy is unproven. The EPMA technique has improved to the point where it is frequently used instead of the petrogaphic microscope for reconnaissance work. Examples of stagnant research areas are: WDS detector design characterization of calibration standards, and the need for more complete treatment of the continuum X-ray fluorescence correction.

Carpernter, P. K.↗
DOE OSTI2020

The Data Foundry: Secure Collaboration for the Geothermal Industry: Preprint

The Data Foundry provides secure, cloud-based storage and universal access to digital information, enabling the greater geothermal industry to collaborate seamlessly with the Department of Energy (DOE), national labs, universities, and private organizations. Originally developed to support the EGS Collab project, the Data Foundry has been expanded to support FORGE, EDGE, and other DOE-funded projects, some collaborative, some private, by providing each project with a secure space and the ability to fine-tune individual access controls. In response to user feedback, it now also features improved integration with DOE’s Geothermal Data Repository (GDR), to provide a clear and convenient pathway from collaboration to publication, and to register collaborative data projects with well-known data registries like Data.gov and the National Geothermal Data System (NGDS). This paper will explore how recent concerns raised by data-centric, proprietary projects have informed development on the Data Foundry and highlight improvements designed to streamline workflows, improve access control, and promote the timely dissemination of information to the geothermal industry.

Data Foundry↗
DOE OSTI2024

A Blockchain and PKI-Based Secure Vehicle-to-Vehicle Energy-Trading Protocol

With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.

Stackelberg game↗
DOE OSTI2025

Securing Flexible Demand [Slides]

This briefing presents some prior work on security needs for virtual power plants (VPPs). This presentation introduces virtual power plants (VPPs) and discusses why they are an emerging participant in our power grid. We will look at several examples where they have been critical for grid reliability. We will then take a dive into some of the risks associated with wide-area digital coordination of VPP assets, and finally conclude with an outlook on what's next.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2020

Bioinspired multilayered cellular composites with enhanced energy absorption and shape recovery

Inspired by the multiscale configuration of the microstructure of cork, the paper describes the design, 3D printing, and evaluation of a new type of multilayered cellular composite (MCC) structure composed of hard brittle and soft flexible phases. The mechanical behavior of 3D printed MCC structures have been investigated both experimentally and numerically. The experiments show that the MCC structure absorbs four times the amount of energy of a conventional cellular configuration under compressive strains up to 70%. Finite element simulations and 2D digital image correlation (DIC) also show that the multilayered architecture provides a more uniform strain distribution and higher stress transfer efficiency, with a resulting progressive failure mode rather than a catastrophic one. Cyclic loading tests demonstrate that the MCC structure also possesses exceptional shape recoverability under compressive deformations up to 40%. These remarkable performance characteristics result from synergies between the properties of the two constituent materials and the chosen multilayered cellular microstructure. The soft phase, in particular, plays a pivotal role in absorbing elastic energy during loading and then releasing the stored energy while unloading. The volume fraction of the soft phase is also essential to control energy absorption and the transition of failure modes. The deformation mechanisms demonstrated here are robust and applicable to other architected cellular materials across multiple length scales and suggest new ways to design lightweight and high-resilience structural materials.

bioinspired composites↗
DOE OSTI2023

Intelligent Optimization of the Digital Low Level RF Control System for LANSCE LINAC

The LINAC at the Los Alamos Neutron Science Center (LANSCE) accelerates protons from 750 keV to its final energy at 800 MeV via 48 radio frequency (RF) modules. However, the startup and recovery process of the low-level RF (LLRF) systems, the primary controls for the RF modules, cost significant time for the beam operation, while the process itself is highly prone to human errors. With the new conversion from the analog LLRF (aLLRF) to digital LLRF (dLLRF) system under the recent LANSCE Modernization Project, new approaches with the new dLLRF capabilities can be achieved to address this issue. We propose to develop an intelligent optimization scheme that can significantly lower the downtime caused by the LLRF systems. This directly address the MFR problem statement that asks for “innovative engineering improvements to ancillary systems such as RF and pulsed power that improve reliability, maintainability, and/or performance.”

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

The Steel Equivalency Workbook: An X-Ray Transmission Calculator

The Steel Equivalency Spreadsheet was created as a robust, user-friendly method for the following: 1. Determining if it is possible to image an object. 2. Reducing time needed when selecting equipment and preparing for field imaging activities. 3. Reducing the amount of equipment taken for field imaging activities. 4. Determining a starting point for exposure settings prior to imaging an object. 5. Reducing the amount of dose deposited to complete an imaging operation (in the spirit of As Low As Reasonably Achievable, ALARA). The spreadsheet was developed using various physical models to account for different phenomena. Future implementations aim to expand beyond the Digital Radiography and Computed Tomography Single Munition Scanner (DRCT SMS) in standard configuration to include high energy XRGs (Betatrons) and sub-MeV pulsed XRGs (XRS4). Alternative computational methods that compensate for incoherent scattering when calculating relative transmission are also being pursued. Ultimately the spreadsheet exceeded the developmental goal of having less than 10% average error when comparing calculations to real-world images.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Power at Sea: Use of Wave Energy Converters for Powering Offshore Oil and Gas Operations

New innovative services and goods based on artificial intelligence, next-generation robotics, autonomy, digitization, and electrification are taking root in the ocean economy. More typical competitive forces, such as value enhancement and safety improvement, are also present, as suppliers constantly strive to improve their competitive positioning. Concurrently, the Oil and Gas sector is experiencing mounting pressure to decrease its operational carbon emissions, forcing efforts to reduce or eliminate liquid fuel consumption offshore. Companies in the ocean economy are having to react to this combination of macro- and micro-level drivers and innovate at an ever more rapid pace. However, before many of these new capabilities can be implemented, new, clean, reliable power sources are needed, especially as liquid fuel grows increasingly out of favor. For many of these loads—both old and new and ranging from watts to megawatts—wave energy systems provide the best solution for remote power generation. As such, research, development and demonstration activities are underway to prove wave energy's ability to provide reliable, consistent energy supplies for certain offshore Oil and Gas activities, paving the way for near term commercialization. Furthermore, this paper outlines these drivers, competitive reaction to them, and why and how wave energy can be a preferable choice for power at sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data

To address grid variability caused by renewable energy integration and to maintain grid reliability and resilience, hydropower must quickly adjust its power generation over short time periods. This changing energy generation landscape requires advance technology integration and adaptive parameter optimization for hydropower systems via digital twin effort. However, this is difficult owing to the lack of characterization and modeling for the nonlinear nature of hydroturbines. To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. To assess the performance of the proposed optimal parametric tuning technique, operational data from a real-world Kaplan hydroturbine unit are collected and used to model the relationship between the gate opening and the generated power production. The findings show that the proposed technique can effectively and adaptively learn the unknown dynamics of the Kaplan hydroturbine while optimally tune the unknown coefficients to match the generated power output from the real hydroturbine unit with an inaccuracy of less than 5%. The method can be used to provides optimal tuning of parameters critical for controller design, operational optimization and daily maintenance for hydroturbines in general.

13 HYDRO ENERGY↗
NASA NTRS1978

Nuclear Science Symposium, 4th, and Nuclear Power Systems Symposium, 9th, San Francisco, Calif., October 19-21, 1977, Proceedings

Consideration is given to the following types of high energy physics instrumentation: drift chambers, multiwire proportional chambers, calorimeters, optical detectors, ionization and scintillation detectors, solid state detectors, and electronic and digital subsystems. Attention is also paid to reactor instrumentation, nuclear medicine instrumentation, data acquisition systems for nuclear instrumentation, microprocessor applications in nuclear science, environmental instrumentation, control and instrumentation of nuclear power generating stations, and radiation monitoring. Papers are also presented on instrumentation for the High Energy Astronomy Observatory.

Source record↗
DOE OSTI2024

Digital Twin + AI: Control Room of the Future

A digital twin enhances power grid control room operations by providing real-time monitoring, predictive insights, simulation capabilities, remote control, training opportunities, data integration, and decision support. This technology empowers control room operators to effectively manage the grid, optimize performance, and ensure reliable and efficient energy distribution.

control room of the future↗
DOE OSTI2023

Calibration of the sub-aperture backscatter system on OMEGA EP

The sub-aperture backscatter (SABS) diagnostic on the OMEGA EP Laser System is a diagnostic that is used to measure the backscattered and sidescattered light during laser–plasma interaction experiments that are relevant to high-energy-density physics and inertial confinement fusion. The diagnostic collects stimulated Brillouin scattering (SBS) UV light at around 351 nm and stimulated Raman scattering (SRS) in the visible-light regime in the 420–720-nm-wavelength range and provides spectrally and temporally resolved information. Five 1-in. light collectors, composed of a lens, ground glass diffuser, and coupling into a 300-μm fiber, are positioned behind the last steering mirror on one of the four beamlines to catch a portion of the beam cross section (~1.5%) of the emission that is scattered into the beamline. The SRS light is collected in two light collectors, combined, and transported via graded index fibers to a streaked spectrometer. The SABS-SRS streak spectrometer has a temporal and spectral resolution of 100 ps and 1 nm, respectively. Three other light collectors collect, combine, and transport the SBS signal to a Hamamatsu high-voltage photodiode, where an oscilloscope digitizes the data, providing a time resolution of better than 1 ns. To obtain an absolute energy calibration of SRS measurements, light signals of known energy and wavelength were injected into the light collectors one at a time. The resulting counts on the streak camera charge-coupled device for SRS are then correlated with the incident fluence of scattered light at the light collector in order to allow a quantitative assessment of streak camera sensitivity to determine the energy of the scattered light during experiments. The measurements were performed in situ from the light collectors to the detectors. Other offline measurements provided the transmission of the optics between the target chamber center and the light collectors.

47 OTHER INSTRUMENTATION↗
NASA NTRS1983

EGRET - The high energy gamma ray telescope for NASA's Gamma Ray Observatory

The EGRET high energy gamma-ray telescope under development for NASA's Gamma Ray Observatory will have an energy range of approximately 12 to 30,000 MeV, energy resolution of about 15 percent FWHM over most of that range, an effective area of about 2000 sq cm at high energies, and single photon angular accuracy of approximately 2 deg at 100 MeV, less than 0.1 deg above 5 GeV. This instrument can locate strong sources to an accuracy of about 5 arc min. The instrument utilizes a set of digital spark chambers interleaved with tantalum foils for detection and identification of gamma-ray events, and a large NaI(Tl) scintillator for energy determination. The system is triggered by a coincidence matrix using two arrays of plastic scintillation counters and a large plastic scintillator anticoincidence dome that rejects incident charged particles.

Fichtel, C. E.↗
DOE OSTI2022

Grid Energy Storage: Supply Chain Deep Dive Assessment

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the Federal Government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the Federal Government to build more secure and diverse U.S. supply chains, including energy supply chains. To combat the climate crisis and avoid the most severe impacts of climate change, the U.S. is committed to achieving a 50 to 52 percent reduction from 2005 levels in economy-wide net greenhouse gas pollution by 2030, creating a carbon pollution-free power sector by 2035, and achieving net zero emissions economy-wide by no later than 2050. The U.S. Department of Energy (DOE) recognizes that a secure, resilient supply chain will be critical in harnessing emissions outcomes and capturing the economic opportunity inherent in the energy sector transition. Potential vulnerabilities and risks to the energy sector industrial base must be addressed throughout every stage of this transition. The DOE energy supply chain strategy report summarizes the key elements of the energy supply chain as well as the strategies the U.S. Government is starting to employ to address them. Additionally, it describes recommendations for Congressional action. DOE has identified technologies and crosscutting topics for analysis in the one-year time frame set by the Executive Order. Along with the capstone policy report, DOE is releasing 11 deep dive assessment documents, including this one, covering the following technology sectors: carbon capture materials; electric grid including transformers and high voltage direct current (HVDC); energy storage; fuel cells and electrolyzers; hydropower including pumped storage hydropower (PSH); neodymium magnets; nuclear energy; platinum group metals and other catalysts; semiconductors; solar photovoltaics (PV); and wind. DOE is also releasing two deep dive assessments on the following crosscutting topics: Commercialization and competitiveness; and cybersecurity and digital components. More information can be found at www.energy.gov/policy/supplychains.

25 ENERGY STORAGE↗
DOE OSTI2024

EDX ClaiMM: Digital Resources for the Critical Minerals and Materials Community

Securing critical mineral supply chains is essential for transitioning to a clean energy economy and for maintaining national security. Big-data analytics can serve as a cost-effective means of identifying new domestic critical mineral resources but only if data can be easily located and digested. Using ArcGIS Enterprise Sites, EDX ClaiMM was developed to increase the accessibility of critical minerals data, reducing time spent on data collection and integration. Hosted tools provide rapid visualization and exploration of key datasets, unlocking insights to support resource assessments.

Yesenchak, Rachel↗