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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Full Technical Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processes that are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Practical Introduction to Common Grid Architecture Techniques

The focus of this white paper is to understand the uses and benefits of the practice of Grid Architecture from various stakeholder perspectives. It introduces a few selected Grid Architecture techniques based on their centrality to understanding key structural considerations and their linkage to emerging trends in electricity infrastructure. However, Grid Architecture has many dimensions, some of which exceed the scope of this limited work. This document is a work of the GridWise Architecture Council (GWAC). It is based on guidance from GWAC's Grid Architecture working group members of which have been acknowledged in the document.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Extending Ultrasonic Welding Techniques to New Material Pairs (FY 2023 Annual Progress Report)

Modern multimaterial vehicles require joining of various lightweight materials, such as aluminum (Al) and magnesium (Mg) alloys and carbon fiber reinforced polymers (CFRP), with advanced high-strength steels together to form a high-performance and lightweight body structure. A variety of joining methodologies (e.g., resistance spot welding, adhesive bonding, linear fusion welding, hemming, clinching, bolting, riveting) have been attempted by the automotive industry to join different materials. Often, these joining techniques are limited to only certain material combinations. For capital and operational cost, automobile original equipment manufacturers need to limit the number of joining technologies implemented on an assembly line.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of Accelerated High Temperature Mechanical Testing Techniques

The Advanced Materials and Manufacturing Technologies (AMMT) Program focuses on advancing materials and manufacturing techniques for nuclear energy applications, particularly in the qualification of materials for high-temperature structural use. This report presents work on refining the creep testing of small specimen geometries. Efforts include the development of a new specimen geometry for sub-sized specimens, which were subjected to uniaxial creep tests. The results contribute to the understanding of material behavior under stress at elevated temperatures and offer potential improvements in creep data collection methods. These findings support ongoing advancements in material qualification processes essential for nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synchrotron-based Characterization Techniques for Radiation Detection Materials and Devices: An Overview

High-performance room-temperature radiation detectors (high energy resolution for spectrometers, high spatial resolution for imaging devices, and low defect-density for high flux applications) are needed for photon energies (>20 keV) that are not well suited for silicon detectors. Applications for such radiation detectors include nonproliferation, synchrotron, medical, astrophysics, and homeland security. Material- and device- characterization to understand and solve the limiting factors of radiation detection materials and devices is a core element of a radiation detector development R&D program. This presentation will give an overview on the two main synchrotron-based characterization techniques that have been employed by the authors in the last ~20 years: (1) White Beam X-ray Diffraction Topography and (2) Micron-scale detector mapping. A perfect (one domain) crystal (radiation detection material) is a requirement to achieve a highperformance radiation detector. White Beam X-ray Diffraction Topography (WBXDT) allows the rapid screening of the crystallinity of the detector material. With WBXDT we can quickly screen CZT and other crystals to make sure they have only one domain, and to see the presence of extended defects and strain fields.

Camarda, Giuseppe S.↗
DOE OSTI2024

Collaborative Research: Enhancing Laser-Based Ion Sources with High Data Rate Techniques

This collaborative research project focuses on leveraging advanced machine learning techniques to analyze and optimize data from high-repetition-rate laser experiments. The main goal is to apply modern computing hardware, customized data acquisition firmware/software, and machine learning approaches to improve data analysis and experimental control. The project also explores how methodology can be developed on smaller-scale experimental setups and then translated to larger facilities within DOE's LaserNetUS network. With extensive data collection and modeling, the research aims to predict and optimize experimental parameters to enhance performance and efficiency.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Evaluation of Advanced Phased-Array Techniques: Interim Results [Slides]

Report: “Evaluation of Advanced Phased-Array Techniques: Interim Results”, August 2023 ML23216A009, PNNL-34622 Results showed that detection rate drops as microstructures/materials become more complex Standard PA had the highest detection rates overall Detection rates in the CASS-CASS mockups were lowest overall FMC had the most accurate length sizing in the fine-grained WSS mockups. All methods struggled with length sizing in coarse-grained mockups SNR vs method depended on the specimen type SNR was consistently high with standard PA SNR was consistently the lowest with PWI FMC performed best on fine-grained WSS A lack of data received from some Round Robin participants resulted in low statistics for many of the analyses.

42 ENGINEERING↗
DOE OSTI2024

Evaluation of Advanced Phased-Array Techniques: Interim Results [Slides]

Report: “Evaluation of Advanced Phased-Array Techniques: Interim Results”, August 2023 ML23216A009, PNNL-34622 Results showed that detection rate drops as microstructures/materials become more complex Standard PA had the highest detection rates overall Detection rates in the CASS-CASS mockups were lowest overall FMC had the most accurate length sizing in the fine-grained WSS mockups. All methods struggled with length sizing in coarse-grained mockups SNR vs method depended on the specimen type SNR was consistently high with standard PA SNR was consistently the lowest with PWI FMC performed best on fine-grained WSS A lack of data received from some Round Robin participants resulted in low statistics for many of the analyses.

42 ENGINEERING↗
DOE OSTI2025

Segregation of Chromium and Titanium in Sapphire Optical Fiber Grown via the Laser-Heated Pedestal Growth Technique

Our research involves growth of single crystal (SC) optical fibers to be used for sensing applications in harsh environments. Silica optical fibers are an affordable and reliable option for a wide variety of applications including optical fiber sensors and fiber lasers. However, for applications in harsh environments, such as high temperatures, radioactivity, corrosivity, etc., silica fibers are not suitable due to their instability under such conditions. Fibers composed of SC materials such as sapphire and YAG are mechanically, chemically, and thermally more robust to harsh conditions, and thus are more appropriate for sensing applications in environments such as nuclear reactors, jet engines, and boiler. However, SC fibers grown via the laser-heated pedestal growth (LHPG) technique do not intrinsically have a functional cladding layer. A cladding layer is required to reduce the modal volume for distributed sensing applications, to reduce frustrated total internal reflection induced by surface contact of the fiber in certain applications, and to improve transmissivity. Our lab investigates introduction of dopant materials during LHPG to induce an effective core-cladding structure while maintain the crystallinity of the host material. This process results in optical fiber that is not only robust to harsh environments, but also has improved optical properties for distributed sensor applications.

distributed sensing↗
DOE OSTI2025

Findings on subtask 1.6 – basin electric carbon storage research project: novel monitoring techniques

The Energy & Environmental Research Center (EERC) led a study to validate novel and emerging technologies as commercial monitoring techniques for application in carbon dioxide (CO 2 ) injection operations. This applied research was conducted at Basin Electric Power Cooperative’s (Basin Electric’s) active CO 2 -injection operations in Beulah, North Dakota, in two phases. The EERC previously completed a set of baseline (preinjection) activities in Phase 1, which included 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; and 5) advanced wellbore-monitoring methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Monitoring, Verification, and Accounting (MVA) Strategy for a North Dakota Carbon Capture and Storage Project Integrated with Ethanol Production: Developing and Demonstrating Sustainable Monitoring Techniques

Conference presentation at American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, Texas, March 28–30, 2022. An overview of the novel and sustainable monitoring techniques developed by the University of North Dakota's Energy & Environmental Research Center (EERC) and its commercial partners for the Red Trail Energy (RTE) carbon capture and storage (CCS) project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Online and Offline Analytical Techniques to Quantify Chloride Salts

This report serves as the deliverable for Milestone- M3FT-26AN080502017: Summary of Accomplishments for Online and Offline Analytical Qualification of Chloride Fuel Salts. The qualification of chloride fuel salts is a critical challenge for the development and deployment of molten salt reactors (MSRs), requiring precise control and verification of chemical and isotopic composition to ensure predictable neutronics, manageable radiological behavior, and safe plant operation. Currently, there is no universally accepted standard for fuel salt qualification, particularly for chloride-based systems, which underscores the need for robust, science-based analytical methodologies. This report presents a comprehensive evaluation of both online and offline techniques for quantifying chloride fuel salts, including multielectrode array voltammetry, differential thermal analysis (DTA) probes, inert gas fusion (IGF) analyzers, and gamma spectrometry using the Mirion NAIS-2x2 NaI(Tl) detector. The integration of these methods enables real-time monitoring of actinide concentrations, redox state, and thermophysical properties, as well as high-precision measurement of impurities and isotopic composition. The acquisition of advanced instruments such as the Bruker Leonardo G6 for IGF and the Mirion NaI detector enhances analytical capabilities, supporting the establishment of operational envelopes and impurity thresholds. These approaches provide essential data for neutronic impact evaluation, feedstock documentation, and compliance with nuclear safety standards. The methodologies developed and validated in this report lay the groundwork for future standardized protocols, bridging the gap between laboratory research and commercial reactor operation, and advancing the safe and efficient deployment of chloride-fueled MSRs.

Polke, Amber↗
DOE OSTI2022

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Application of multi-criteria decision analysis techniques and decision support framework for informing select agent designation for agricultural animal pathogens

The United States Department of Agriculture (USDA), Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents and toxins (Select Agent List) that potentially threaten agricultural health and safety, the procedures governing the transfer of those agents, and training requirements for entities working with them. Every 2 years the USDA DASAT reviews the Select Agent List, using subject matter experts (SMEs) to perform an assessment and rank the agents. To assist the USDA DASAT biennial review process, we explored the applicability of multi-criteria decision analysis (MCDA) techniques and a Decision Support Framework (DSF) in a logic tree format to identify pathogens for consideration as select agents, applying the approach broadly to include non-select agents to evaluate its robustness and generality. We conducted a literature review of 41 pathogens against 21 criteria for assessing agricultural threat, economic impact, and bioterrorism risk and documented the findings to support this assessment. The most prominent data gaps were those for aerosol stability and animal infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. The MCDA analysis supported the intuitive sense that select agents should rank high on the relative risk scale when considering agricultural health consequences of a bioterrorism attack. However, comparing select agents with non-select agents indicated that there was not a clean break in scores to suggest thresholds for designating select agents, requiring subject matter expertise collectively to establish which analytical results were in good agreement to support the intended purpose in designating select agents. The DSF utilized a logic tree approach to identify pathogens that are of sufficiently low concern that they can be ruled out from consideration as a select agent. In contrast to the MCDA approach, the DSF rules out a pathogen if it fails to meet even one criteria threshold. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making

The United States Department of Agriculture (USDA) Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents (Select Agents List) that threaten crops of economic importance to the United States and regulates the procedures governing containment, incident response, and the security of entities working with them. Every 2 years the USDA DASAT reviews their select agent list, utilizing assessments by subject matter experts (SMEs) to rank the agents. We explored the applicability of multi-criteria decision analysis (MCDA) techniques and a decision support framework (DSF) to support the USDA DASAT biennial review process. The evaluation includes both current and non-select agents to provide a robust assessment. We initially conducted a literature review of 16 pathogens against 9 criteria for assessing plant health and bioterrorism risk and documented the findings to support this analysis. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for ensuring accuracy. Scoring criteria were adopted to ensure consistency. The MCDA supported the expectation that select agents would rank high on the relative risk scale when considering the agricultural consequences of a bioterrorism attack; however, application of analytical thresholds as a basis for designating select agents led to some exceptions to current designations. A second analytical approach used agent-specific data to designate key criteria in a DSF logic tree format to identify pathogens of low concern that can be ruled out for further consideration as select agents. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

59 BASIC BIOLOGICAL SCIENCES↗