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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Complementary Subsurface Characterization Methods to Develop a Geologic Model for the EGS Collab Experiment, Sanford Underground Research Facility

The EGS (Enhanced Geothermal Systems) Collab project was performed within the Sanford Underground Research Facility (SURF) with a goal of understanding processes and evaluation of models related to hydraulic simulation of rock at depth. The present work deals with the development of Testbed 2 where experiments were conducted at a depth of 1.25 km and were located within a well-characterized testbed in a metamorphic, amphibolite host rock. A total of eleven boreholes varying in length between 10.6 m and 81.2 m were continuously cored to develop the testbed. In addition to the continuous coring of the amphibolite host rock, geophysical instrumentation supporing electrical resisivity tomography (ERT), microearthquake (MEQ) detection, and optical fiber providing distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) were installed in the monitoring boreholes, all of which produced a comprehensive complementary suite of characterization and monitoring technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Characterization Inform Sustainable Recovery of Critical Minerals from Fossil Energy Waste Feedstocks

Rare earth elements (REE) and other critical minerals (CM, e.g., Co, Ni, Li) have important uses in green energy and modern technologies, yet are vulnerable to potential supply chain disruptions. One potential domestic CM source is fossil energy wastes, such as acid mine drainage (AMD) and treatment solids (AMD solids), coal combustion ash, and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters). While they can contain lower CM concentrations then traditional ore, the quantity and fast availability as waste feedstock makes them a promising CM resource. To explore their promise, researchers at DOE’s National Energy Technology Laboratory (NETL) have collected and analyzed CM data for aforementioned fossil energy wastes, and utilized advanced geochemical characterization (e.g., synchrotron microprobe and sequential extraction) to identify the CM speciation and binding environments, and developed sustainable and targeted CM recovery. Successful examples include: (1) the discovery of easily mobile REE phases in Ca-rich coal combustion ash and developing a patented REE recovery process from Ca-rich Powder River Basin coal ash; (2) the successful identification of REE/Co/Ni/Zn hosting phases in acid mine drainage treatment solids (AMD solids) with diverse chemical composition (Al, Mn, or Fe-rich) informing the sequential recovery of different REE/CMs from AMD solids; (3) the recovery potential of Li and other CMs in O&G produced waters and drill cuttings. The innovations driven by characterization have the potential to offset the cost of waste management and wastewater treatments while reducing the cost and environmental footprint of CM extraction.

Stuckman, Mengling↗
DOE OSTI2025

Characterizing falling particle curtain receivers at commercially relevant scales: Research Performance Progress Report (RPPR-1)

Sandia will construct a cold flow receiver test platform in order to characterize falling particle curtain receivers at commercially relevant scales. While Sandia has extensive experience in R&D of falling particle curtain receivers, most have been at pilot scale and smaller - on the order of 1 MW th with characteristic dimensions of nominally 1-2 m to adequately collect solar energy from the heliostat field at the National Solar Thermal Test Facility (NSTTF). However, scaling up receivers to commercially relevant scales (25 MW th and above) will require a thorough understanding of particle curtain dynamics at larger scales, especially longer drop heights, for design certainty. The goal of this project will be to construct a cold falling particle curtain test rig capable of simulating particle characteristics that are expected in a commercial scale CSP plant, namely the drop height, curtain thickness, and particle mass flow rate (normalized by length of curtain). This will enable data collection on curtain opacity and spread, both of which are correlated to receiver efficiency and reliable construction, for commercially relevant scales. It will also permit validation of numerical models that will enable detailed receiver characterization and design past currently validated scales.

14 SOLAR ENERGY↗
DOE OSTI2024

H3D Characterization Memo

The H3D was characterized using GADRAS 19.3.5 using data sent by the IAEA. Everything related to the measurement setup was provided by the IAEA. The sources measured were detailed and the distance from the detector was also provided. The data sheets of the sources were used to determine the source activity at the time of calibration, as needed for characterization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Met-Ocean Characterization for the Atlantic Marine Energy Center’s (AMEC’s) Gulf of Maine Wave Test Sites

Comprehensive and consistent analysis, characterization, and classification of the wave climate at open-ocean wave energy converter (WEC) test sites guided by international standards enables commensurable evaluation and comparison of met-ocean characteristics, including wave energy resources and wave load conditions. Herein, we present results from a comprehensive feasibility-level met-ocean characterization for two Atlantic Marine Energy Center (AMEC) WEC test sites in the Gulf of Maine.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗
DOE OSTI2025

Fracture Network Quantification for Enhanced Reservoir Characterization in CO2 Storage Sites

Presentation slides on “Fracture Network Quantification for Enhanced Reservoir Characterization in CO2 Storage Sites” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. Accurate reservoir characterization is fundamental for the safe and efficient operation of carbon capture, utilization, and storage (CCUS) projects. This process is not only critical during initial site selection but also plays a key role in continuously updating reservoir geomodels throughout injection operations to effectively manage subsurface storage sites. Our primary objective is to develop a comprehensive understanding of fracture networks within CO2 injection reservoirs, which are critical for predicting the behavior of injected fluids, ensuring storage integrity post-injection, and mitigating risks such as leakage or induced seismicity.

artifical intelligence / machine learning (AI/ML)↗
DOE OSTI2025

Enhanced Feedstock Characterization and Modeling to Facilitate Optimal Preprocessing and Deconstruction of Corn Stover (Final Report)

This project addresses the challenge of processing corn stover by fractionating this biomass feedstock to both streamline processing and generate new potential co-products. Additionally, the project developed new field-deployable analytical tools that can be coupled with empirical models that were used to predict feedstock properties and processing performance. The overall scope of this project was: (1) identify conditions for optimal corn stover fractionation using a two- stage physical fractionation, (2) assess how physical fractionation impacts properties, partitioning of biomass, and response to processing, (3) further adapt, develop, and validate several advanced characterization tools for assessing biomass properties that can be linked to processing behavior, and (4) develop and validate predictive models based on measurements that can be performed “in the field” or “at the biorefinery gate” to predict feedstock processing behavior (preprocessing and deconstruction). The first objective employed pre-separation processing (size reduction) which was next subjected to enhanced separations to yield fractions enriched or depleted in select compositional components or properties. For the second objective, fractions were screened for their response to post-separation processing (pretreatment and enzymatic hydrolysis). Detailed characterization profiles were developed and dynamic image analysis to assess distribution of particle size and morphology. For the final objective, we utilized these tools to develop empirical models to assess the relative abundance of tissue type in order to assess fractionation efficacy and to predict fraction performance during pretreatment and enzymatic hydrolysis.

09 BIOMASS FUELS↗
DOE OSTI2025

Characterizing Microwave Losses in Superconducting Coaxial Cables for Quantum Systems

As superconducting quantum systems scale up to enable applications like large-scale quantum computing, challenges such as fabrication yield, wiring complexity, and microwave crosstalk drive the need for high-fidelity, low-loss, modular interconnects. In recent experiments, the performance of these interconnects is often limited by cable loss, a factor that becomes even more critical as we aim for higher fidelity operations and connect increasingly coherent modules. In this talk, we present a detailed characterization of microwave losses in commercially available superconducting cables and discuss how material characterization techniques can be useful for understanding their microscopic origin.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Characterization of the Multi-Coincident Bismuth Germanate Oxide Spectrometer at the Nuclear Counting Facility

A multi-detector γ-ray spectroscopy system including 3 high-purity germanium (HPGe) detectors has been developed at the Nuclear Counting Facility at Lawrence Livermore National Laboratory. This system operates not only in conventional singles γ-ray detection mode but also incorporates features like coincidence and anti-coincidence techniques. These advanced detection modes can significantly enhance the system’s sensitivity, making it a powerful tool for isotope identification and quantification, especially for complex samples with high background and overlapping peaks. In this re port, we present a comprehensive performance characterization of the Multi-Coincident Bismuth Oxide Spectrometer (MCBOS) using a variety of sample types, including 60 Co, 48 Sc, and mixed fission product samples. Each sample provides unique tests for the MCBOS capabilities. Additionally, a GEANT4 model of the MCBOS has been generated to aid with the characterization of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterization of Microbial Consortia and the Products Associated with Selenium Reduction in Real Flue Gas Desulfurization (FGD) Wastewater

Biological treatment is a recognized approach for removing toxic selenate and selenite oxyanions present in flue gas desulfurization (FGD) wastewater. However, the knowledge on the specific microbial species or communities responsible for reducing water-soluble selenium oxyanions to insoluble elemental selenium remains limited. In addition, the selenium oxyanion reduction genes and pathways have yet to be understood in these wastewaters. This study characterizes selenium oxyanion reducing bacteria (SeRB) native to FGD wastewater, and the resulting elemental selenium particles formed. By selecting for native SeRB microbes in a defined media, a novel resolution of these organisms has been achieved. This research identifies previously unrecognized selenium oxyanion reducing capabilities in Anaerosolibacter, alongside predominant SeRB from Mesobacillus and Tepidibacillus genera. This work encompasses both 16S and metagenomic techniques to recover novel metagenome assembled genomes (MAGs), distinct to this environment. The biogenic selenium produced by these organisms were predominantly of elemental selenium, in either amorphous or with a hexagonal structure. In addition, the elemental selenium particles formed where shown to increase in purity as the microbes were enriched. This study identifies the SeRB present in FGD wastewater and characterizes their selenium products, offering crucial insights to enhance the efficiency of biological treatment strategies and the potential of selenium recovery from this industrial waste.

microbiology↗
DOE OSTI2024

PRIME - A Software Toolkit for the Characterization of Partially Observed Epidemics in a Bayesian Framework

PRIME is a modeling framework designed for the “real-time’” characterization and forecasting of partially observed epidemics. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. We include examples using publicly available COVID-19 data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Characterizing falling particle curtain receivers at commercially relevant scales: Research Performance Progress Report (RPPR-1)

Sandia will construct a cold flow receiver test platform in order to characterize falling particle curtain receivers at commercially relevant scales. While Sandia has extensive experience in R&D of falling particle curtain receivers, most have been at pilot scale and smaller - on the order of 1 MWth with characteristic dimensions of nominally 1-2 m to adequately collect solar energy from the heliostat field at the National Solar Thermal Test Facility (NSTTF). However, scaling up receivers to commercially relevant scales (25 MWth and above) will require a thorough understanding of particle curtain dynamics at larger scales, especially longer drop heights, for design certainty. The goal of this project will be to construct a cold falling particle curtain test rig capable of simulating particle characteristics that are expected in a commercial scale CSP plant, namely the drop height, curtain thickness, and particle mass flow rate (normalized by length of curtain). This will enable data collection on curtain opacity and spread, both of which are correlated to receiver efficiency and reliable construction, for commercially relevant scales. It will also permit validation of numerical models that will enable detailed receiver characterization and design past currently validated scales.

14 SOLAR ENERGY↗
DOE OSTI2025

EVs@Scale NextGen Profiles: EVSE Characterization 2024

As part of the U.S. Department of Energy's EVs@Scale consortium, the Next-Generation Profiles (NextGen Profiles) project presents analysis and results from the characterization of high-power conductive and wireless charging infrastructure. High power charging equipment is capable of recharging electric vehicle traction batteries at power levels of 200KW and above. EVSE characterization was conducted over a wide range of DC output current and DC voltage charging for nominal and off-nominal test conditions. Test plans and procedures were developed and refined to define the test configurations and requirements, measurement parameters, and test procedures used throughout NextGen Profiles testing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Residential Building Stock Characterization in Palm Beach County, Florida

This building stock characterizations is intended to help Palm Beach County (PBC) Office of Resilience (OOR) and municipalities composing the Municipal Resilience Partnership prioritize building energy efficiency investments to reduce energy costs and increase resilience for the county's most vulnerable residents. The analysis utilizes NREL’s ResStock model to characterize PBC’s residential building stock, including building type, renter/owner status, size (square footage), age of buildings (vintage), HVAC system types, and, for multi-family buildings, number of units. Building energy efficiency, weatherization, and electrification upgrade packages were assessed for approximate cost, customer bill-savings, and emissions reductions potential and findings will help guide OOR financial assistance program design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Testing and Characterization to Develop a Mechanistic Explanation for Unsaturated Drift of Fiber Optic Sensors during High-Dose Irradiation

The primary limitation for any optical fiber-based sensor for nuclear reactor applications is radiation-induced attenuation (RIA) of the transmitted and/or reflected signals. Based on several recent studies, RIA is tolerable for some fused silica optical fibers with the proper choice of sensing wavelength and fiber dopants. For extreme temperature applications (> 1000°C), sapphire optical fibers have been proposed; however, recent optical transmission measurements performed on bulk sapphire samples showed prohibitively large RIA. For some sensors, radiation-induced dimensional changes in the fiber materials can also cause significant drift. Moreover, the drift that was observed in numerous experiments performed in the High Flux Isotope Reactor (HFIR), the Advanced Test Reactor, the Massachusetts Institute of Technology Reactor, and other international facilities far exceeded what would be expected based on compaction of fused silica glass. Clearly, additional work is needed to better understand the origins of both RIA and radiation-induced drift in both silica and sapphire optical fiber-based sensors before these sensors can be reliably deployed for nuclear applications. This work evaluated the underlying mechanisms that may be responsible for RIA and drift in silica and sapphire materials. First, detailed characterization was performed on bulk fused silica glass samples that were previously irradiated to different neutron fluences at different temperatures to better understand the structural changes that drive radiation-induced drift in the absence of coating effects that are discussed later. Results show that the non-monotonic compaction that occurs with increasing neutron fluence continues up to fast neutron fluences approaching 10 22 n/cm 2 , which has important implications for physics-based models that may be used to compensate for the sensor drift. Initial Raman spectroscopy and synchrotron x-ray diffraction provide insights into the nature of the structural changes. Next, detailed characterizations were performed on silica fibers with various coatings that were subjected to several different thermal treatments. The hypothesis is that the coatings convert to carbon-rich materials that compact under irradiation, putting a large compressive strain on the fiber. Out-of-pile testing confirms that both polyimide and acrylate fiber coatings convert to glassy carbon (GC) materials when heated under inert conditions, and the degree of order (i.e., graphitization) increases with increasing temperature. The results provide increasingly strong evidence that the combination of polymeric coatings and inert (or vacuum) conditions render fiber optic sensors susceptible to significant radiation-induced drift that would not otherwise exist in uncoated fibers. Finally, transmission electron microscopy was performed on bulk sapphire samples that were irradiated to two neutron fluences at different temperatures to gain insights into the potential mechanisms driving the prohibitive RIA at higher neutron fluences and temperatures. Contrary to previous hypotheses, results show that scattering from radiation-induced voids cannot explain the observed RIA. Similarly, models for scattering losses from dislocation loops also do not agree with the experimental results. Instead, fitting to the experimental data shows that increased absorption from aluminum vacancy centers is the most likely explanation for the the prohibitively large RIA that was observed at high irradiation temperature and dose. In addition, the voids that formed in these single-crystal samples were found to align along the basal plane (a-axis) as opposed to that seen in previous observations of c-axis alignment in polycrystalline samples, which could have important implications for anisotropic swelling and other phenomena that could affect sensor performance at high neutron fluence.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

NCERC-CL TREAT Free Field Characterization Foil Reaction Rate Results

This report summarizes the analysis and preliminary MCNP reaction rate modeling of free field characterization measurements performed in the Transient Reaction Test Facility (TREAT) at Idaho National Laboratory (INL) between 12/18/2023 and 2/22/2024. A series of seven irradiations were performed using the Big-BUSTER (Broad Use Specimen Transient Experiment Rig) core configuration. Foil sets including 19.5% LEU-Zr alloy wire, S, Au, Fe, Ni, Co, Ti, and Zr were deployed in each irradiation. Identical foil sets were supplied to Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and INL. All foils were supplied by INL. Additional details on the experiment can be found in [2]. The foil sets were shipped to the National Criticality Experiments Research Center Counting Laboratory (NCERC-CL) branch at LANL (NCERC-CL NISC) and were received on 3/25/2024. Additional details on receipt and counting are reported in [3]. All reactor dosimetry measurements were performed in adherence to the ASTM standards applicable to reactor dosimetry. Measured reaction rates from Au, Co, Fe, Ni, and Ti are reported. Select reaction rate ratios and simulated reaction rates and ratios are discussed. Reaction rates for all measured reaction products were modeled with MCNP 6.3.1 and a TREAT input deck supplied by Edward Lum. Neutron emission estimates calculated using the measured and simulated reaction rates show excellent agreement between the three fast-threshold n-p reactions with the percent differences being < 9% between the three reactions. The capture reactions had poorer, but still reasonable, agreement with < 20% percent differences between the neutron emission estimates of the three capture reactions. The percent difference between the fast-threshold and capture reactions is ∼ 100% for each reaction. This supports the TREAT model is not accurately modeling the neutron spectrum and additional measurements are required to characterize TREAT and match measurements to simulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗