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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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24 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design of the Electromagnetic Particle Injector (EPI) for Tokamak Deployment

Both predicting and controlling disruptions are critical and urgent issues for ITER as some disruptions with a short warning time may be unavoidable. For these cases, a rapid response disruption mitigation system (DMS) referred to as the electromagnetic particle injector (EPI) is being developed. The primary advantages of the EPI are its fast response time and high velocity, which have been demonstrated in offline experiments (Raman et al., 2021). The EPI is capable of accelerating a metallic sabot electromagnetically using a rail gun to the required velocities ( > 2 km/s) within 2 ms. Two high-field racetrack magnets able to generate fields over 2 T are positioned above and below the rails to permit high velocity at low rail currents, a requirement to minimize electrode erosion. At the end of the acceleration phase, a sabot capture mechanism retains the spent sabot inside the vacuum chamber that houses the EPI. At this point, it releases well-defined microspheres, or a shell pellet, of a radiative payload into the disrupting plasma. A remotely operated sabot loading system positioned behind the injector contains several pre-equipped sabots that can be loaded by an operator from the tokamak control room. The injector is interfaced to the tokamak through a guide tube attached to the front of the EPI vacuum chamber. Finally, the advantages of the EPI system over other DMSs under consideration are described in conjunction with the details of an EPI system designed for near-term test on an existing large tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Studying the Impact of Momentary Cessation of IBRs Compliant With IEEE Std. 2800-2022 on Transmission Line Protection Elements

This paper examines the impact of inverter-based resource (IBR) momentary cessation timing on transmission system protection relays. IEEE Std. 2800 mandates voltage ride-through, requiring IBRs to remain online during voltage disturbances. However, for severe voltage dips (|V| = 0.1 p.u.), the standard permits current blocking. In practice, vendors implement momentary cessation with varying delays, potentially affecting relay operation if IBRs cease too early. This article studies the impact of the time IBRs enter momentary cessation on transmission line protective relays. Using an electromagnetic transient (EMT) simulation, this study models IBR momentary cessation with tunable delays in a realistic transmission network. COMTRADE files generated from EMT simulations are analyzed in MATLAB using detailed protective relay models. Results indicate that IBRs must sustain operation for at least one cycle to ensure proper relay response; otherwise, relays may fail to oper- ate. These findings guide IBR vendors in optimizing momentary cessation settings to enhance transmission line protection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A Community Guide to Regulatory Barriers Affecting Microgrids (Reports 1-3)

In response to growing risks of power outages from extreme weather and aging infrastructure, communities are increasingly exploring the potential of microgrids to provide reliable energy access. Microgrids offer promising solutions to meet this challenge but face a complex landscape of non-technical barriers, particularly regulations concerning the provision and distribution of energy. Most existing legal and regulatory frameworks were designed for a centralized, one-way power system, and are often poorly suited to handle systems that independently balance distributed energy resources with local load. This three-part report series provides a strategic analysis of existing regulatory and legal factors affecting microgrid deployments to help non-technical community leaders and decision-makers better understand the feasibility of a microgrid in their community. -Report No. 1: Foundational Issues Facing Microgrids details the universal policy barriers all microgrids face, including utility interconnection processes, rate structures, and local permitting. -Report No. 2: Single Property Microgrids outlines how direct asset ownership and operating behind-the-meter can bypass some regulatory oversight, using the Blue Lake Rancheria microgrid as a case study. -Report No. 3: Multi-Property Microgrids tackles the complex challenges of crossing public rights-of-way and navigating utility franchise rights, highlighting the Coventry microgrid project. The series equips decision-makers with phased frameworks to navigate financial and regulatory complexities, engage effectively with local utilities and Authorities Having Jurisdiction (AHJs), and structure successful microgrid projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process–structure–property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process–structure–property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗