Results for “data conditioning” — Page 29

DOE OSTI2023

Electrochemical Compression for Ammonia Storage and Refrigeration System (Phase 2)

In this project, we studied the performance of the ammonia EC compressor under a variety of different conditions. We replicated preliminary data and using a small cell with 5 cm 2 of active area. We demonstrated the operation of larger cells with 100 cm 2 of active area. Further, we used a commercially available hydrogen EC compressor stack to analyze the scaled-up compressor performance. While previous experiments examined only the transient EC compressor performance, we developed test facilities that allowed the compressor to reach steady state.

25 ENERGY STORAGE↗

DOE OSTI2026

Lessons Learned from Ecosystem-Scale Experimental Field Studies (Workshop Report)

Efforts to understand and predict ecosystem responses to environmental change require long-term, large-scale, spatially representative experiments and observations that capture natural variability, test predictive models, and generate transferable knowledge. Such studies are indispensable for unraveling the complexities of terrestrial ecosystems and their responses to disturbances and evolving environmental conditions, while generating the data necessary for developing mechanistic models and predictive tools that inform decision-making processes. Having a rich history of designing and executing large-scale ecosystem experiments, the U.S. Department of Energy’s Environmental System Science program convened a workshop in January 2025 that brought together leaders in the field to distill critical lessons from decades of experience in large-scale experiments. The workshop aimed to (1) provide an ecosystem experiment primer for best practices, thus ensuring a high scientific return on investment for funding agencies, and (2) offer a robust framework for the design and management of future research initiatives. This report synthesizes insights and experiences from workshop participants and is structured to capture the entire research life cycle, from goal setting and design to operations, adaptive management, team dynamics, collaborations, and the often overlooked aspect of decommissioning. By synthesizing decision-making and lessons learned across diverse research approaches, the report aims to provide a template of essential factors to consider when designing successful long-term, large-scale ecosystem experiments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Biological methane production and accumulation under sulfate-rich conditions at Cape Lookout Bight, NC

Introduction: Anaerobic oxidation of methane (AOM) is hypothesized to occur through reverse hydrogenotrophic methanogenesis in marine sediments because sulfate reducers pull hydrogen concentrations so low that reverse hydrogenotrophic methanogenesis is exergonic. If true, hydrogenotrophic methanogenesis can theoretically co-occur with sulfate reduction if the organic matter is so labile that fermenters produce more hydrogen than sulfate reducers can consume, causing hydrogen concentrations to rise. Finding accumulation of biologically-produced methane in sulfate-containing organic-rich sediments would therefore support the theory that AOM occurs through reverse hydrogenotrophic methanogenesis since it would signal the absence of net AOM in the presence of sulfate. Methods: 16S rRNA gene libraries were compared to geochemistry and incubations in high depth-resolution sediment cores collected from organic-rich Cape Lookout Bight, North Carolina. Results: We found that methane began to accumulate while sulfate is still abundant (6–8 mM). Methane-cycling archaea ANME-1, Methanosarciniales, and Methanomicrobiales also increased at these depths. Incubations showed that methane production in the upper 16 cm in sulfate-rich sediments was biotic since it could be inhibited by 2-bromoethanosulfonoic acid (BES). Discussion: We conclude that methanogens mediate biological methane production in these organic-rich sediments at sulfate concentrations that inhibit methanogenesis in sediments with less labile organic matter, and that methane accumulation and growth of methanogens can occur under these conditions as well. Our data supports the theory that H2 concentrations, rather than the cooccurrence of sulfate and methane, control whether methanogenesis or AOM via reverse hydrogenotrophic methanogenesis occurs. We hypothesize that the high amount of labile organic matter at this site prevents AOM, allowing methane accumulation when sulfate is low but still present in mM concentrations

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Possibility to Identify the Contributions from Collapsars, Supernovae, and Neutron Star Mergers from the Evolution of the r-process Mass Abundance Distribution

We study the evolution of rapid neutron-capture process (r-process) isotopes in the galaxy. We analyze relative contributions from core-collapse supernovae (CCSNe), neutron star mergers, and collapsars under a range of astrophysical conditions and nuclear input data. Here we show that, although the r-process in each of these sites can lead to a similar (universal) elemental distribution, the detailed isotopic abundances can differ from one site to another. These differences may allow for the identification of which sources contributed to the early evolution of r-process material in the galaxy. Our simulations suggest that the early evolution was dominated by CCSNe and collapsar r-process nucleosynthesis. This conclusion may be testable if the next generation of observatories can deduce isotopic r-process abundances.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

HD 222925: A New Opportunity to Explore the Astrophysical and Nuclear Conditions of r-process Sites

Abstract With the most trans-iron elements detected of any star outside the solar system, HD 222925 represents the most complete chemical inventory among metal-poor stars enhanced with elements made by the rapid neutron capture (“ r ”) process. As such, HD 222925 may be a new “template” for the observational r -process, where before the (much higher-metallicity) solar r -process residuals were used. In this work, we test under which conditions a single site accounts for the entire elemental r -process abundance pattern of HD 222925. We found that several of our tests—with the single exception of the black hole–neutron star merger case—challenge the single-site assumption by producing an ejecta distribution that is highly constrained, in disagreement with simulation predictions. However, we found that ejecta distributions that are more in line with simulations can be obtained under the condition that the nuclear data near the second r -process peak are changed. Therefore, for HD 222925 to be a canonical r -process template likely as a product of a single astrophysical source, the nuclear data need to be reevaluated. The new elemental abundance pattern of HD 222925—including the abundances obtained from space-based, ultraviolet (UV) data—call for a deeper understanding of both astrophysical r -process sites and nuclear data. Similar UV observations of additional r -process–enhanced stars will be required to determine whether the elemental abundance pattern of HD 222925 is indeed a canonical template (or an outlier) for the r -process at low metallicity.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Gas Adsorption Analyzer

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

3Flex,BET specific surface area and pore volume, A↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) X-Ray Diffraction

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Cryogenic Refrigerator Applied to Freezing Test

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Aerodynamic Particle Sizer, Condensation Particle Counter, and Meteorological Instrument Data Analysis

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Vegetation Warming Experiment: Thaw depth and dGPS locations, Utqiagvik, Alaska, 2019

Thaw depth measurements within and around warming chambers, and in ambient plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Measurements were taken at the start and end of chamber deployment, and two intermediate times during the 2019 growth season. dGPS measurements of chamber and ambient plot locations are also included. The files included in this data package are in .csv format, and include 3 data files and 3 metadata files. This data was recorded as part of the Zero Power Warming (ZPW) vegetation warming experiment. See related data files for environmental conditions, leaf physiology, leaf traits, and landscape and plot phenocam images. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

DOE OSTI2020

Concurrent conditions access across validity intervals in CMSSW

The CMS software system, known as CMSSW, has a generalized conditions, calibration, and geometry data products system called the EventSetup. The EventSetup caches results of reading or calculating data products based on the 'interval of validity', IOV, which is based on the time period for which that data product is appropriate. With the original single threaded CMSSW framework, updating only on an IOV boundary meant we only required memory for a single data product of a given type at any time during the program execution. In 2016 CMS transitioned to using a multi-threaded framework as away to save on memory during processing. This was accomplished by amortizing the memory cost of EventSetup data products across multiple concurrent events. To initially accomplish that goal required synchronizing event processing across IOV boundaries, thereby decreasing the scalability of the system. In this presentation we will explain how we used 'limited concurrent task queues' to allow concurrent IOVs while still being able to limit the memory utilized.

Dagenhart, David↗

DOE OSTI2022

Electrochemical Ammonia Compression

An electrochemical (EC) compressor is a solid-state compression device. For decades, researchers have been studying EC compressors for applications for a variety of energy systems. As the world transitions away from fossil fuel energy sources, EC compression emerges as a promising technique for energy storage, specifically energy stored in the form of pressurized ammonia. Ammonia is also a commonly used refrigerant. The present studies examine the viability of EC compression for ammonia storage and refrigeration. EC ammonia compression increases the concentration of an ammonia-hydrogen mixture via the input of electrical energy and a series of chemical reactions. A polymer electrolyte membrane separates the low-concentration side from the high-concentration side of the device. On the low-pressure (anode) side hydrogen atoms oxidize and react with ammonia molecules, forming positively charge ammonium ions. The ions traverse the membrane electrolytically. The ammonium ions are reduced and revert back to hydrogen and ammonia upon reaching the high-pressure (cathode). An external circuit provides the current needed to sustain the reactions. In this project, we studied the performance of the ammonia EC compressor under a variety of different conditions. We replicated preliminary data and using a small cell with 5 cm2 of active area. We demonstrated the operation of larger cells with 100 cm2 of active area. Further, we used a commercially available hydrogen EC compressor stack to analyze the scaled-up compressor performance. While previous experiments examined only the transient EC compressor performance, we developed test facilities that allowed the compressor to reach steady state. We analyzed the effects of pressure and current on the EC compressor performance. We measured the flow rates of gas leaving the compressors and analyzed the composition using gas chromatography. We tested methods of separating ammonia from the effluent vapor, which contained hydrogen and water vapor. We found that back diffusion adversely affected the performance, especially when we maintained high pressure lifts.

25 ENERGY STORAGE↗

DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Maintaining Microstructure – The Path to Successful Technology Maturation in Fluidized Systems

Scaling circulating fluidized bed risers has been a point of contention for nearly a century. There have been numerous attempts to define various methodologies. These have all fallen short of providing a robust approach, primarily due to a lack of maintaining microstructure dynamics – a key factor in maintain interphase heat and mass transfer. Recent work by the author put forward an approach based up maintaining dynamic similarity at different scales by ensuring that the microstructure remained similar by maintaining statistical and chaotic parameters across the scale. That work relied on a dimensionless regime map in which the x-axis was defined by the ratio of the solids flux to the saturation carrying capacity. This latter property was only good within the range of the data and it became evident that extrapolation beyond the limits of the data could induce unrealistic conditions. Therefore, literature was reviewed to develop a better correlation for the saturation carrying capacity. In doing so, a critical diameter concept was developed and applied to the correlations for both Geldart Group A and B materials. The critical diameter for Geldart Group A and B materials is 0.2 m and 0.3 m, respectively. The paper then gives examples on how to use the scaling approach to maintain dynamic similarity across the scales.<br>

Breault, Ronald↗

DOE OSTI2023

Transport Modeling of As-Run ATR Cycles to Support U-10Mo Research Reactor Fuel Qualification Experiment

The Department of Energy’s (DOE) Office of Materials Management and Minimization has been tasked with converting the five remaining United States High Performance Research Reactors (U.S. HPRR) from highly enriched uranium to low-enriched uranium. The Nuclear Regulatory Commission (NRC) regulates Massachusetts Institute of Technology Reactor (MITR), Missouri University Research Reactor (MURR), and National Bureau of Standards Reactor (NBSR); and DOE regulates the High Flux Isotope Reactor and Advanced Test Reactor (ATR). To meet the high demands of these reactors, the U.S. HPRR program has chosen to use 90% uranium - 10% molybdenum (U-10Mo) monolithic fuel. This plate-type fuel will undergo multiple irradiation experiment campaigns in ATR, from mini-plates to full element tests, over a large range of operating conditions. This will provide data in support of the fuel qualification of each reactor. This summary focuses on the as-run neutronic analysis of the first series of mini-plate (MP-1) experiments, which have been irradiated in the ATR. MP-1 experiment’s main goal is to demonstrate the fabrication process and meet the fuel irradiation performance requirements with primary focus on the fuel plates associated with the three NRC reactors, with a small focus on the low power requirements of the ATR fuel. The MP-1 experiments are planned to be the basis of the monolithic U-10Mo fuel for qualification through the NRC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

The German Site Selection Process - Implementation and Challenges - 20528

Federal Company for Radioactive Waste Disposal (Bundesgesellschaft fuer Endlagerung mbH; hereinafter referred to as BGE) is a state-owned company established in September 2016 following the 'Act on the Organisational Restructuring in the Field of Radioactive Waste Storage'. 'Repository Site Selection Act' (hereinafter referred to as StandAG) defines the site selection procedure, aiming to ensure the best possible safety for storing high-level radioactive waste in Germany for the duration of one million years. The selection procedure is a participatory, transparent, learning and self-questioning process based on scientific expertise. Possible repository sites are sought all over Germany, without excluding or predetermining any potential site at the beginning. The procedure consists of three phases. After each phase, the legislative decides on the regions for further consideration in the next phase of the site selection procedure. The current first phase (Phase I) is divided into two steps. Objective of Step 1 is to determine subareas of favorable geological conditions based on available data. Step 2 of Phase I will lead to identification of specific regions that are considered for further surface-based geoscientific and geophysical exploration. Potential host rocks are rock salt, clay rock and crystalline rock. As part of the site selection procedure, an overview of the status of the planning and implementation of R and D activities is given. Topics of particular interest are, for example, the adaptation of the maximum temperature of 100 deg. C at the container surface, the impact of long-term climate variations as well as minimally invasive exploration methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Transport Modeling of As-Run ATR Cycles for U-10Mo Fuel Qualification Experiment

The Department of Energy’s (DOE) Office of Materials Management and Minimization has been tasked with converting the five remaining United States High Performance Research Reactors (U.S. HPRR) from highly enriched uranium to low-enriched uranium. The Nuclear Regulatory Commission (NRC) regulates Massachusetts Institute of Technology Reactor (MITR), Missouri University Research Reactor (MURR), and National Bureau of Standards Reactor (NBSR); and DOE regulates the High Flux Isotope Reactor and Advanced Test Reactor (ATR). To meet the high demands of these reactors, the U.S. HPRR program has chosen to use 90% uranium - 10% molybdenum (U-10Mo) monolithic fuel. This plate-type fuel will undergo multiple irradiation experiment campaigns in ATR, from mini-plates to full element tests, over a large range of operating conditions. This will provide data in support of the fuel qualification of each reactor. This summary focuses on the as-run neutronic analysis of the first series of mini-plate (MP-1) experiments, which have been irradiated in the ATR. MP-1 experiment’s main goal is to demonstrate the fabrication process and meet the fuel irradiation performance requirements with primary focus on the fuel plates associated with the three NRC reactors, with a small focus on the low power requirements of the ATR fuel. The MP-1 experiments are planned to be the basis of the monolithic U-10Mo fuel for qualification through the NRC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗