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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The CMS Phase 2 Outer Tracker Analyzer of Test Outputs - POTATO!

The Phase-2 upgrade of the Large Hadron Collider (LHC), also known as the High-Luminosity LHC (HL-LHC) is designed to achieve peak instantaneous luminosities which is about an order of magnitude higher than the nominal design value of $10^{34}~cm^{-2}s^{-1}$ delivering a total of atleast $3000 fb^{-1}$ data over 10 years of operation at $\sqrt{s}~=~14~TeV$. One crucial aspect of the CMS Phase-2 detector upgrade is the replacement of the existing tracking detector in order to deal with the extreme HL-LHC conditions, retaining and further expanding the physics performances achieved in the previous years. The outer part of the upgraded tracker (OT), will be equipped with over 13,000 macro Pixel-Strip (PS) and Strip-Strip (2S) modules! Module production is distributed across centers worldwide and necessitates coordinated efforts and standardized procedures. Along with production and assembly of the modules, Fermilab OT group is also working on a tool, Phase 2 Outer Tracker Analyzer of Test Outputs (POTATO) that will analyze, grade, upload and manage the large quantity of files to be stored in the centralized Database (DB). In this contribution a brief overview of the module testing and the power and dire need of POTATO to handle this large number of test outputs will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records

The U.S. Department of Energy (DOE) Advanced Fuels Campaign (AFC) is advancing transmutation fuel technologies to reduce long-lived radioactive waste by converting minor actinides into shorter-lived or stable elements through irradiation in sodium-cooled fast reactors. Key experiments such as AFC-1, AFC-2, FUels for the transmutation of Trans-URanium elements In phéniX (FUTURIX)-Fortes Teneurs en Actinides (FTA), and Experimental Breeder Reactor-II (EBR-II) X501 have provided fuel fabrication, irradiation, and performance data on various transuranic-bearing fuel forms. This report documents the creation of an artificial-intelligence assisted database, which has consolidated all DOE-owned data related to Transuranic (TRU)-bearing fuel experiments and stored across it across both the Idaho National Laboratory (INL) Nuclear Data Management and Analysis System and the INL high performance computing (HPC) infrastructure. A dedicated webpage, hosted on the INL HPC system, has been developed to support role-based access and data interaction. The database architecture allows researchers to navigate large, heterogeneous archives with far greater speed and accuracy than manual search and lays the foundation for future expansion into multimodal nuclear materials analysis environments. The database represents a major step towards a nationally integrated fuels database utilizing artificial intelligence tools.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗
DOE OSTI2024

Quality Ranking of Unary Chloride Salt Property Data Included in MSTDB-TP

Molten salt reactor developers rely on thermal property data to design, license and operate the reactors. The Molten Salt Thermal Database-Thermophysical Properties (MSTDB-TP) was established under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program and is managed by Oak Ridge National Laboratory to serve as a single source of thermophysical property values measured for a wide variety of molten salt systems for use by researchers, molten salt reactor developers, and regulators. These properties include density, viscosity and thermal diffusivity and conductivity. Published measurements of molten salt properties are lacking for many salts of interest and the data that are available are often inconsistent. This creates a challenge for MSR developers when determining which property values to use when designing their reactors. It is the purpose of this work to apply a consistent ranking system to all data entries that indicates the quality of property values listed in the database. These rankings will be the technical basis for down-selections by the database developers and alert users about the quality of the available property values. MSTDB-TP collects all available property data and indicates preferred data sets or correlations. However, all available data sets are included in the database. Quality assessments and rankings are being applied to data in MSTDB-TP to provide an indication of the quality of each data set independent of consistency with other data. Previous reports detailed the ranking system that was followed and assessments of unary fluoride data sets. Documentation of the quality of data in MSTDB-TP was continued by reviewing and assessing all available sources of density, viscosity and thermal diffusivity or conductivity values for unary chloride salts in MSTDB-TP V3.0 using the same criteria.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Leaf functional traits highlight phenotypic variation of two tree species in the urban environment

Urbanization is transforming landscapes globally, altering environmental conditions that affect ecosystem functioning, particularly in urban areas where trees are crucial for regulating microclimates, improving air quality, and sustaining biodiversity. This study investigates the environmental differences and tree leaf structure and morphology in urban and suburban sites in the Chicago Metropolitan Region. The leaf functional traits of Norway Maple and Little − leaved Linden were studied in three locations in the summer of 2023: an urban park (University of Illinois Chicago, Chicago, IL), a suburban park (Morton Arboretum, Lisle, IL), and a suburban residential site (Lombard, IL). The urban site had higher daytime and nighttime air, and land surface temperatures compared to the suburban sites with significant fluctuations observed across the sites. Cumulative growing degree days, a measure of potential photosynthetically active days, were also higher in the urban park than in the suburban sites between March and August. Norway Maple trees growing in the urban site displayed higher specific leaf area (SLA) and lower leaf dry matter content (LDMC) than in the suburban sites, resulting in thinner leaves. Similarly, Little−leaved Linden trees in the suburban residential site displayed higher SLA and lower LDMC than those in the suburban park. The values of gas exchange traits − namely photosynthetic assimilation, transpiration rates, and stomatal conductance − of Norway Maple were higher at the urban site compared to suburban sites as temperatures increased during the summer. Norway Maple gas exchange values decreased as the growing season progressed, as expected by ontogeny. In contrast, Little−leaved Linden maintained similar leaf gas exchange values throughout the growing season. Both species in the urban site exhibited lower instantaneous water use efficiency and reduced LDMC, suggesting greater water loss in response to elevated temperatures compared to suburban park and residential sites. Comparisons with existing global trait databases emphasize the need for localized data to accurately capture site−specific responses. Although some traits aligned with database values, others deviated significantly, underscoring the importance of comprehensive, site−specific datasets for robust ecosystem modeling and management strategies.

Cho, Ahram↗
DOE OSTI2024

Genomes OnLine Database (GOLD) v.10: new features and updates

The Genomes OnLine Database (GOLD; https://gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute is a comprehensive online metadata repository designed to catalog and manage information related to (meta)genomic sequence projects. GOLD provides a centralized platform where researchers can access a wide array of metadata from its four organization levels namely Study, Organism/Biosample, Sequencing Project and Analysis Project. GOLD continues to serve as a valuable resource and has seen significant growth and expansion since its inception in 1997. With its expanded role as a collaborative platform, it not only actively imports data from other primary repositories like National Center for Biotechnology Information but also supports contributions from researchers worldwide. This collaborative approach has enriched the database with diverse datasets, creating a more integrated resource to enhance scientific insights. As genomic research becomes increasingly integral to various scientific disciplines, more researchers and institutions are turning to GOLD for their metadata needs. To meet this growing demand, GOLD has expanded by adding diverse metadata fields, intuitive features, advanced search capabilities and enhanced data visualization tools, making it easier for users to find and interpret relevant information. This manuscript provides an update and highlights the new features introduced over the last 2 years.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Anthromes and forest carbon responses to global change

Human effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling. Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900-present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO 2 and temperature change for different anthromes among regions. Modeled global forest carbon stock responses are positive for CO 2 increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO 2 and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests. The net effect of anthropogenic activities—including land-use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Retrofitting Holcim Ste. Genevieve Cement Plant with CO2 Capture Plant Using Air Liquide Cryocap™ FG Technology

The global cement manufacturing industry is a major contributor to carbon dioxide emissions. The International Energy Agency's "Net Zero Emissions by 2050 Scenario" identifies CCS as a major strategy for meeting that goal. This project is among the first attempts to transfer capture technology developed at coal-fired power plants to the cement industry. The main objective of the project is to execute and complete a front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separates 95% of the total CO2 emissions at the Holcim (US) Ste. Genevieve cement manufacturing facility using Air Liquide’s Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology. The Holcim Ste. Genevieve cement plant in Missouri, US, boasts one of the largest single cement production lines in the world, with a capacity of approximately 12,000 t/day. The plant currently uses traditional fuels, namely coal and petcoke. The captured CO2 will be pipeline and geological storage grade. The industrial host site emits approximately 3.0 million tonne CO2/yr. Air Liquide’s Cryocap™ technology has been developed over the last 18+ years for CO2 capture applications. It has been shown to be applicable to a variety of industrial applications (e.g., steel, cement, SMR, Fluidized Catalytic Crackers (FCCs)). Cryocap™ FG consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The project team is led by the Prairie Research Institute at the University of Illinois at Urbana-Champaign. The tasks include: complete FEED study for retrofitting the industrial facility with a carbon capture system to support developing a detailed cost estimate; business case analysis outlining the anticipated revenue and credits if projects was built and operated; technoeconomic analysis (TEA) outlining how capture system achieves DOE capture goals; and life cycle (LCA) analysis demonstrating zero net carbon emissions. The FEED study was successfully completed. This includes completing the process basis of design; preliminary engineering; outside battery limits (OSBL) detailed engineering including a Zero Liquid Discharge (ZLD) wastewater treatment system; inside battery limits (ISBL) detailed engineering [1]. An overall project capital cost estimate within a -20%/+30% accuracy was developed. The major contributors to the Total Plant Cost (TPC), by system, are the costs associated with the Outside Battery Limit (OSBL) section of the plant which includes a new river water intake structure and a Zero Liquid Discharge (ZLD) system. By cost category, the major contributors to the TPC are equipment and subcontractor costs, followed closely by engineering, construction management, home office and contractor fees. The TEA has been created to reflect the findings of the project. It analyzes the economic performance of the Cryocap™ technology by reviewing the estimated capital costs, operating cost, and revenue. The Cost of Capture (COC) associated with the Cryocap™ technology for 95% CO2 capture, when considering NETL 2018 economic assumptions (42/58 debt/equity ratio, 5.15% interest on debt and 1.42% return on equity in real dollars) and 2022 economic assumptions (42/58 debt/equity ratio, 8.82% interest on debt and 4.90% return on equity in real dollars) was found to be much lower than that for the DOE-NETL’s base-line cases. The highest contributors to the COC are annualized capital expenditures (CAPEX) and electricity consumption which can be offset by using lower cost renewable sources. The LCA was conducted using OpenLCA which is an open-source software that is recommended by NETL. The database utilized for this study was a modified version of TRACI 2.1 (developed by the US. Environmental Protection Agency’s National Risk Management Research Laboratory and modified by NETL). The Cryocap™ FG technology does not consume fuels in significant quantities and does not utilize specialized chemical solvents subject to decomposition, such as those utilized in amine-based carbon capture systems. The Cryocap™ FG technology mainly utilizes electricity as its energy input; hence, its calculated emissions are mainly associated with the generation of electricity offsite and are dependent on the energy matrix of the grid at the time of project implementation. The water consumption impact of the Cryocap™ FG is mostly for makeup of the water lost by evaporation in the cooling tower; however, the carbon capture plant will be equipped with a ZLD system to avoid effluent streams and minimize water consumption. The successful construction and operation of this plant based on this study results will provide a means to demonstrate an economically attractive and transformational capture technology that can be used to retrofit existing plants and be deployed at new plants.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Osprey Framework v0.2.2

The Alpha Berkeley Framework is a software architecture for building agentic AI systems that coordinate multi-step workflows in scientific and industrial environments. It is based on a plan-first orchestration model, where natural language requests are translated into execution plans with explicit dependencies and optional human approval. The framework includes capability classification, which selects relevant tools on a per-task basis to keep orchestration efficient as the number of available tools grows. It incorporates task extraction methods that compress conversational context and integrate external resources such as databases, APIs, and knowledge bases into structured, machine-readable tasks. Execution is supported by modular services with checkpointing, artifact management, and error handling, allowing workflows to be paused, inspected, and resumed. The system is designed for deployment in production environments, supporting both local and containerized execution as well as integration with HPC clusters. Interfaces include command-line tools, browser-based workflows, and containerized services. The framework has been demonstrated in tutorial examples and deployed at the Advanced Light Source, where it coordinates accelerator control and analysis workflows.

Hellert, Thorsten [Lawrence Berkeley National Labo↗
DOE OSTI2026

Modernizing GlideinWMS Factory Monitoring with Prometheus & Grafana

Large-scale scientific experiments like CMS and DUNE rely on the distributed workload management system GlideinWMS to efficiently utilize computing resources across heterogeneous computing environments. GlideinWMS currently records Factory statistics using Round Robin Databases (RRDBs), XML, and JSON files, and these statistics are displayed via custom monitoring Web pages, thereby limiting integration with modern observability platforms. This project investigates the use of Prometheus-based instrumentation to expose Factory metrics using OpenTelemetry principles. Factory statistics related to Glidein submission and job execution are exported as Prometheus metrics through the Prometheus Python Client Library and are served via an HTTP metrics endpoint. The collected metrics are inspected using the Prometheus web-based interface and are visualized through Grafana dashboards within the Landscape monitoring infrastructure at Fermilab. This project significantly streamlines the integration of modern monitoring technologies into GlideinWMS and establishes a framework for extending observability across additional system components.

Appiah, Gideon [Grambling State U.]↗
DOE OSTI2025

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Mineral Database and Dashboard

The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.

produced water management↗
DOE OSTI2024

Constituent Data Replacement Tool

The purpose of this tool is to estimate key parameters that may be missing in public wastewater composition datasets. The tool can be applied to develop complete treatment and critical mineral extraction profiles for leachate, produced water and other aqueous waste streams. The tool applies machine learning algorithms to replace missing data in a user’s water data set that are adjusted based on user preferences for options including algorithm type, number of features, and classification variables. The tool can use the user’s data alone or combine user data with the NEWTS USGS Produced Water Database for more robust training. This research was funded by the U.S. Department of Energy’s Office Fossil Energy and Carbon Management (FECM) through National Energy Technology Laboratory’s ongoing research under the Water Management for Power System Field Work Proposal, DE-FECM 1022428 and Critical Minerals Field Work Proposal, DE-FECM 1022420.

Aqueous Chemistry↗
DOE OSTI2025

Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach

With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Integrated Energy-Water Data for Cross-Sector Resilience

This white paper focuses on the “energy-for-water” domain, addressing the urgent need for integrated, empirical data to support regional management, benchmarking, and research on improving efficiency and developing technologies for water and wastewater management systems. The costs and energy required for the supply, treatment, and distribution of water and wastewater lack a standard data collection mechanism and centralized database or storage infrastructure, limiting data-driven decision-making across interdependent infrastructure systems.

42 ENGINEERING↗
DOE OSTI2025

Overview of Fish Passage Facilities at Hydropower Developments across the Conterminous United States

This dataset contains geo-referenced information on the presence and types of fish passage facilities at hydropower developments across the conterminous United States (CONUS) presented in the ORNL Hydropower Fish Passage Database Webmap (https://www.ornl.gov/project/quantifying-national-fish-passage-data/webmap). It was developed through collaborative partnerships with fish passage engineers and biologists at both the US Fish and Wildlife Service (USFWS) and the National Marine Fisheries Service (NMFS), and hydropower experts at the Low Impact Hydropower Institute (LIHI). Information contained within this dataset has been provided by many different sources, including State and Federal resource management agencies, non-governmental organizations, hydropower industry members, and published datasets=. This dataset is intended to provide a high-level overview of the distribution of fish passage infrastructure at hydropower developments across CONUS; a more comprehensive database is anticipated to be released later in 2025. This dataset contains one data file in comma-separate (*.csv) format and the information within it was last updated on 24 March 2025.

13 HYDRO ENERGY↗