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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of electro-optical quantum transducers based on three-dimensional superconducting cavities

Quantum transducers enable the conversion of quantum information and signals between different physical platforms. Based on the pioneering works in three-dimensional superconducting cavity technology developed at Fermilab, we are advancing the development of three-dimensional microwave-optical transducers and exploring their applications in quantum information processing and sensing. We present our progress in the design, fabrication, and characterization of three-dimensional microwave cavities integrated with bulk lithium niobate resonators. The material characterization using three-dimensional cavities based on a resonant-type method allows for understanding of complex permittivity and loss mechanism of electro-optic materials at cryogenic temperatures. We also evaluate the potential of the high-efficiency quantum transducers in enhancing the performance of quantum sensors for applications such as dark matter detection, compared to conventional homodyne detection approaches. This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC0207CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. This work is funded by the DOE's Early Career Research Program. This research used resources of the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Superconducting Quantum Materials and Systems Center (SQMS) under Contract No. DE-AC02-07CH11359.

Zorzetti, Silvia↗
DOE OSTI2023

A centralized resource for bacterial–fungal interactions research

Research on bacterial-fungal interactions (BFIs) has revealed that fungi and bacteria frequently interact with one another within diverse ecosystems and microbiomes. Assessing the current state of knowledge within the field of BFI research, particularly with respect to what interactions between bacteria and fungi have been previously described, is very challenging and time consuming. This is largely due to a lack of any centralized resource, with reports of BFIs being spread across publications in numerous journals using non-standardized text to describe the relationships. To address this issue, we have developed the BFI Research Portal, a publicly accessible database of previously reported interactions between bacterial and fungal taxa to serve as a centralized resource for the field. Users can query bacterial or fungal taxa to see what members from the other kingdom have been observed as interaction partners. Search results are accompanied by interactive and intuitive visual outputs, and the database is a dynamic resource that will be updated as new BFIs are reported.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Historic Architectural Resource Survey of the Dosimetry Applications Research (DOSAR) Facility in the 7700 Area of the Oak Ridge National Laboratory

In May 2022, Cultural Resource Analysts, Inc., completed a historic architectural resource survey of buildings associated with the Dosimetry Applications Research Facility at the Oak Ridge National Laboratory. The laboratory is one of three Department of Energy facilities located on the Oak Ridge Reservation in Roane and Anderson Counties, Tennessee. The Dosimetry Applications Research Facility is located approximately 2 mi southeast of the main Oak Ridge National Laboratory campus. The survey included Buildings 7709, 7710, and 7712, which date to the 1960s. An additional DOSAR building (Building 7735) dates to the late 1980s and was not surveyed since it is outside the period of significance. The survey was conducted at the request of UT-Battelle, LLC, on behalf of the Department of Energy. As stipulated by the National Historic Preservation Act of 1966, as amended, the Department of Energy is required to identify any properties under its jurisdiction that are included in or eligible for inclusion in the National Register of Historic Places. In order to identify historic properties at the Oak Ridge National Laboratory, in 2017–2018 Cultural Resource Analysts, Inc., conducted a survey of the main campus as well as outlying facilities, publishing the findings in a 2018 report entitled Oak Ridge National Laboratory Historic Architectural Resource Survey. At the time of the 2017–2018 survey, buildings associated with the Dosimetry Applications Research Facility were not accessible for security reasons and the current report serves as an addendum to the 2018 report. In addition, the current survey incorporates information included in a documentation report on Building 7709 completed in 2019. The properties included in the current survey were also evaluated for their collective potential as a historic district. The identification of archaeological properties that are eligible for inclusion in the National Register of Historic Places is beyond the scope of this report. Cultural Resource Analysts, Inc., recommends that none of the buildings surveyed for the current report are individually eligible for listing in the National Register of Historic Places. However, the collective of buildings represents a facility that made notable contributions to the Oak Ridge National Laboratory’s scientific research endeavors from the 1960s to the 1980s, specifically in the field of Health Physics. The buildings and their associated features have also maintained their integrity of setting, materials, design, location, and association. Therefore, Cultural Resource Analysts, Inc., proposes the Dosimetry Applications Research Facility Historic District, which is recommended eligible for listing under Criterion A. The three buildings addressed in the current survey (Buildings 7709, 7710, and 7712) are recommended eligible as contributing resources of the historic district. The district boundary is scribed to incorporate the environs of these three facilities, as well as additional relevant features.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Overview of ARIES Research Projects Involving Inverter-Based Resources

NREL's Power Electronic Grid Interface (PEGI) Workshop, held October 13, 2020, focused on the research challenges of operating power systems with ever-higher levels of inverter-based generation and power-electronic-based load. This presentation provides an overview of ARIES research projects involving inverter-based resources.

grid↗
DOE OSTI2024

Boundary spanning increases knowledge and action on invasive species in a changing climate

Abstract Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary‐spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary‐spanning activities could support proactive, research‐informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary‐spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non‐members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non‐members and short‐term members more frequently identifying range‐shifting neonative species and their impacts on native communities as higher priorities compared to long‐term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range‐shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication : Although real‐world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary‐spanning efforts to address other global change challenges to conservation.

Evans, Annette E.↗
DOE OSTI2024

Generative AI for Power Grid Operations

Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Cryogenic Vibrationally Resolved Photoelectron Spectroscopy of OH–(H2O): Confirmation of Multidimensional Franck-Condon Simulation Results for the Transition State of the OH + H2O Reaction

We present a transition state spectroscopic study of the OH + H2O reaction using the experimental technique of cryogenic Negative Ion Photoelectron Spectroscopy (NIPES). The recorded NIPE spectrum at 193 nm exhibits multiple vibrational progressions that include excitations to the shared H atom antisymmetric stretching mode with an interval of 0.32 eV as well as other progressions, mainly involving the H bending and O…O symmetric stretching modes. The Vertical Detachment Energy (VDE) was measured at 3.53 eV, whereas an upper limit for the Adiabatic Detachment Energy (ADE) was estimated at 2.90 eV. These values are in excellent agreement with the theoretically computed values of 3.51 eV and 2.83 eV respectively, obtained at the CCSD(T)/aug-cc-pV5Z level of theory. The recorded NIPE spectrum is in very good agreement when compared to the one recently reported from four-dimensional Franck-Condon simulations, in which a similar spectral profile was predicted. Besides observing the ground state, a charge-transfer excited state in the form of [OH–(H2O)+] is identified with a relative energy of 1.39 eV, well matching the previous prediction of 1.36 eV. This work was supported by U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and performed using EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE. The theoretical calculations were conducted on EMSL’s “Cascade” Supercomputer. This research also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Cao, Wenjin↗
DOE OSTI2021

FY 2021 Mid-Year HPC Utilization Report M3UF-21IN0701018

Idaho National Laboratory (INL), supported by the Department of Energy Office of Nuclear Energy (DOE-NE) through the Nuclear Science User Facilities, provides access to supercomputer systems and data storage along with support staff for system management, software installation, cybersecurity and user support to the broader DOE-NE user community. Users include individuals at universities, industry, and government laboratories enabling a wide range of research and development and mission-supporting activities. The availability of high-performance computing (HPC) capabilities is a key foundation of collaboration and innovation in nuclear energy systems research. HPC resources and INL directly support the mission and objectives of DOE-NE. From October 2020 through March 2021, INL HPC capabilities were utilized by a diverse set of computing and applied researchers, for a wide range of research and engineering activities. This report focuses on current INL HPC systems and utilization from October 1, 2020 through March 31, 2021.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

The Hardware of Smaller Clusters (V.3.0)

Chris Saunders and three technologists are in high demand from Sandia’s deep learning teams, and they’re kept busy by building new clusters of computer nodes for researchers who need the power of supercomputing on a smaller scale. Sandia researchers working on Laboratory Directed Research & Development (LDRD) projects, or innovative ideas for solutions on short timeframes, formulate new ideas on old themes and frequently rely on smaller cluster machines to help solve problems before introducing their code to larger HPC resources. These research teams need an agile hardware and software environment where nascent ideas can be tested and cultivated on a smaller scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Laboratory for Laser Energetics Targets Inertial Confinement Fusion

The University of Rochester’s Laboratory for Laser Energetics is targeting laser-driven inertial confinement fusion, as part of National Nuclear Security Administration’s Stockpile Stewardship Program and in the quest for clean sources of energy. The Laboratory for Laser Energetics (LLE) is home to two extremely powerful lasers—OMEGA and OMEGA EP—and researchers are using them to explore laser-driven inertial confinement fusion (ICF). ICF involves compressing a small amount of fuel consisting of hydrogen isotopes, deuterium (D), and tritium (T), and heating it to temperatures greater than the center of stars. “When these conditions are reached, the fuel undergoes fusion—releasing enormous energy that can be used for research relevant to the National Nuclear Security Administration’s (NNSA) Stockpile Stewardship Program (SSP) and to drive carbon-free power plants,” explains Valeri Goncharov, distinguished scientist and director of the Theory Division at LLE. LLE was established at the University of Rochester in 1970 and is the largest U.S. Department of Energy university-based research program in the nation, supported by the National Nuclear Security Administration as part of its Stockpile Stewardship Program (SSP). “As a center for exploring the interaction of intense radiation with matter, LLE is a unique national resource for research and education in science and technology,” says Goncharov. “Our current research includes exploring fusion for the SSP program and as a future source of energy, developing new laser and materials technologies, and pursuing a better understanding of high-energy-density phenomena.”

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A Transformational Graduate Program: Mines and NREL Join Forces To Shape the Future of Energy

Developing secure, resilient, and adaptive energy infrastructure that fosters economic growth while reducing environmental impact is among the most pressing challenges—and greatest opportunities—of our time. It will require the next generation of thought leaders to capably and creatively guide this vital energy sector transition. Through a new interdisciplinary graduate program, Colorado School of Mines (Mines) and the National Renewable Energy Laboratory (NREL) are cultivating the rich opportunity landscape needed to develop these future innovators. The Mines/NREL Advanced Energy Systems (AES) degree program prepares researchers at the doctoral level and energy professionals at the master’s level to address the full complexity of tomorrow's infrastructure, economic, and environmental challenges. The combination of a thriving cleantech market in Colorado, world-class resources and researchers at NREL, and rigorous educational and technical programs at Mines create a truly one-of-a-kind opportunity for advancing fields related to energy systems. These links can uniquely equip top-caliber students to become the scientists and engineers at the forefront of our global energy economy transformation.

Advanced Energy Systems↗
DOE OSTI2024

Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm

Inspections of concrete bridges across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there is an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision to streamline the inspection process. Our experiment examined the efficacy of a state-of-the-art Visual Transformer (ViT) model combined with distinct image enhancement detector algorithms. We benchmarked against a deep learning Convolutional Neural Network (CNN) model. These models were applied to over 20,000 high-quality images from the Concrete Images for Classification dataset. Traditional crack detection methods often fall short due to their heavy reliance on time and resources. This research pioneers bridge inspection by integrating ViT with diverse image enhancement detectors, significantly improving concrete crack detection accuracy. Notably, a custom-built CNN achieves over 99% accuracy with substantially lower training time than ViT, making it an efficient solution for enhancing safety and resource conservation in infrastructure management. These advancements enhance safety by enabling reliable detection and timely maintenance, but they also align with Industry 4.0 objectives, automating manual inspections, reducing costs, and advancing technological integration in public infrastructure management.

42 ENGINEERING↗
DOE OSTI2025

ERF: Energy Research and Forecasting Model

High performance computing (HPC) architectures have undergone rapid development in recent years. As a result, established software suites face an ever increasing challenge to remain performant on and portable across modern systems. Many of the widely adopted atmospheric modeling codes cannot fully (or in some cases, at all) leverage the acceleration provided by General-Purpose Graphics Processing Units, leaving users of those codes constrained to increasingly limited HPC resources. Energy Research and Forecasting (ERF) is a regional atmospheric modeling code that leverages the latest HPC architectures, whether composed of only Central Processing Units (CPUs) or incorporating GPUs. ERF contains many of the standard discretizations and basic features needed to model general atmospheric dynamics. The modular design of ERF provides a flexible platform for exploring different physics parameterizations and numerical strategies. ERF is built on a state-of-the-art, well-supported, software framework (AMReX) that provides a performance portable interface and ensures ERF's long-term sustainability on next generation computing systems. This paper details the numerical methodology of ERF, presents results for a series of verification/validation cases, and documents ERF's performance on current HPC systems. The roughly 5× speed up of ERF (using GPUs) over Weather Research and Forecasting (CPUs only) for a 3D squall line test case highlights the significance of leveraging GPU acceleration.

17 WIND ENERGY↗
DOE OSTI2026

Project 2.8: Biological Specimen Repository for the Mayak Project

Curation of the existing specimens, including Standard Operating Procedures: The Southern Urals Biophysics Institute (SUBI) will continue to manage the day-to-day operations of the biorepository, but will have to assume the financial costs of maintaining and purchasing equipment such as freezers; Standard Operating Procedures are already in place for all aspects of the operations, and the Georgetown University team will be available on a voluntary and ad hoc basis to answer any technical questions in the future. Acquisition and tracking of new specimens: SUBI will decide on the collection of new tissues and blood samples in the future, and on what scale, depending on available resources and research needs. The Georgetown University team is willing to provide advice on a voluntary and ad hoc basis. Procedures for receiving and approving specimen requests from users: SUBI can take over this function; Chris Loffredo and other qualified research scientists at Georgetown University would be willing to serve as Tissue Review Committee members on a voluntary and ad hoc basis. Biospecimens remaining at Georgetown University: pursuant to the original terms of the Biospecimen Transfer Agreement between SUBI and Georgetown University, all unused portions of specimens (FFPE blocks, slides, and frozen tissues) will be returned to SUBI at the conclusion of the approved scientific research for which they were transferred. It was anticipated that the return shipment of biospecimens would occur in the fall of 2023. However, at this time, due to international developments, there are no shipping companies who can provide such deliveries to Russia. For now, the biospecimens can remain at Georgetown University where they are stored at the Genomics and Epigenomics Shared Resource. There have not been any storage costs to date, but this could change in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

LUCID Thrust 1 - Dataset Identification and Biodata Catalog Creation

The LUCID DOE consortium, part of the Department of Energy’s Biological and Environmental Research (BER) program, advances Low Dose Radiation (LDR) research through multidisciplinary efforts across seven key thrusts. This document focuses on Thrust 1, which centers on the creation of curated multimodal population health datasets and supports broader efforts within the LUCID program, including AI-based hypothesis generation, experimental design, and the study of LDR-induced health risks. Specifically, it describes the identification and cataloging of Thrust 1’s curated LDR datasets and biodata, emphasizing their critical role in supporting various research thrusts within the consortium, with potential applications in healthcare and public policy. In addition, the document includes an evaluation of three Large Language Models (LLMs)—GPT-4, SOLAR-10B, and Mixtral-8x7B—based on their ability to extract features from 25 LDR studies. The results indicate that GPT-4 performed the best, while Mixtral-8x7B demonstrated limited knowledge. Overall, this work advances understanding in radiation protection, risk assessment, and medical treatments, while providing valuable resources for researchers, educators, and policymakers.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Fast Grid Frequency Support from Distributed Energy Resources

This report describes research related to electric power system frequency support from inverter-coupled distributed energy resources (DERs). This research was initiated under the U.S. Department of Energy’s Grid Modernization Laboratory Consortium (GMLC) and also contains work funded through a Cooperative Research and Development Agreement with Hawaiian Electric. The purpose of this report is to summarize the findings of simulations, hardware testing, power hardware-in-the-loop (PHIL) simulation, and analysis examining the effects of DER frequency support on the Oahu power system. This report also includes recommendations for consideration in the use of DER grid frequency support functionality, and related topics. Note that a previous GMLC Technical Report from this project also provided specific recommendations for the activation of one specific grid frequency support function, frequency-watt control, for overfrequency events in Hawaii. Those recommendations included recommended frequency-watt control settings, which have since been approved by the Hawaii Public Utilities Commission on October 20, 2017, for system-wide activation. This report builds on the previous report by considering not only overfrequency events but also underfrequency events, and by considering distributed energy storage systems in addition to photovoltaic (PV) systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for The SSP-2A Parcel and Proposed Oak Ridge Enhanced Technology and Training Center (ORETTC), Oak Ridge, Tennessee

This report summarizes current knowledge of natural and cultural resources associated with potential land use changes within an 81-acre (32.8-hectare) parcel, termed SSP-2A, on the US Department of Energy’s (DOE’s) Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee (Figure 1). A primary goal for the work presented here was to evaluate potential impacts to sensitive resources within the SSP-2A parcel that might result from land disturbance and construction of the Oak Ridge Enhanced Technology and Training Center (ORETTC). In addition to on-the-ground surveys of the ORETTC footprint and SSP-2A parcel during summer 2020 (Figure 1), this report leverages historical (pre-1995) and contemporary (1995–present) data from additional sources such as the Tennessee Department of Environment and Conservation (TDEC). The individuals who obtained and compiled the data that are presented here are familiar with and routinely assess, manage, and research sensitive resources on the ORR. This report should facilitate more environmentally sound decisions during planning and development of the ORETTC, provide a foundation for further assessment of sensitive and cultural resources associated with the broader SSP-2A parcel (should additional actions take place), and help project managers address regulatory guidance and DOE policy on sustainable development. Those who reference this report must consider that the timing of surveys does not permit complete delineation of resources. Data deficiencies are indicated where possible. Additional surveys may be required to account for seasonal patterns of various threatened and endangered species (e.g., bats), and additional assessment will be required if activities extend beyond the ORETTC site (Figure 2).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrating Intelligent Hydro-informatics into an effective Early Warning System for risk-informed urban flood management

The urban drainage system constantly facing flooding issues in coastal and urban areas. Robust and accurate urban flood management, particularly considering fast-moving compound floods, is crucial to minimize the impact of flood disasters in coastal cities. Till now, Ho Chi Minh City (HCMC) lacks an effective means of urban flood management because of flood risk communication among residents. Existing flood risk communication tools rely on post-disaster flood model outcomes and data. Therefore, this research proposes a real-time Early Urban Flooding Warning System (EUFWS) integrated with a user-friendly web and app interface. The backbone of this system consists of flood models developed using machine learning (ML) algorithms, combined with big data and Web-GIS visualization, with ML serving as the core for constructing the EUFWS. EUFWS offer several key advantages: they are available at all times, accessible from anywhere, and provide a real-time, multi-user working platform. Additionally, the system is flexible, allowing for the easy addition of components and services and scalable, adjusting to workload demands. EUFWS have been successfully deployed in Thu Duc City, Vietnam, as a case study and are operating effectively. EUFWS have been successfully deployed in Thu Duc City, Vietnam, as a case study and are operating effectively. Research results indicate that EUFWS supported decision-makers to be effectively risk informed and make intelligent decisions during urban flood emergencies. Finally, this underscores the significant potential of integrating ML and information technology to enhance the management of smart urban drainage systems in flood-prone cities worldwide.

54 ENVIRONMENTAL SCIENCES↗