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At least 1,621 records · Page 90

FracML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage

Poster on “FRACML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The accurate characterization of subsurface fracture networks is essential for the secure operation of carbon capture, utilization, and storage (CCUS) projects. A thorough understanding of the spatial distribution of subsurface faults and fractures is crucial for predicting CO2 plume evolution and minimizing risks such as potential leakage into overlying formations or induced seismicity. In this context, robust fracture network quantification plays a pivotal role in reservoir management, providing the data necessary to fine-tune operational parameters, and ensure the environmental and economic viability of CCUS projects. As part of the U.S. Department of Energy’s SMART (Science-informed Machine Learning for Accelerating Real-time Decisions in Subsurface Applications) initiative, we focused on the development and application of a machine learning-based tool (FRACML) designed to quantify and map fracture networks using real-world (non-synthetic) data from an active CO2 injection site. Our objective is to demonstrate the utility of this tool in improving operational efficiency and safety across CCUS sites.

artifical intelligence / machine learning (AI/ML)↗

Spectroscopic Characterization of Mn 1+ Low Oxidation State in Prussian Blue-Based Battery Anodes

Stabilization of ions in exotic oxidation states is beneficial for the development of new materials for green energy technologies. Exotic Mn 1+ was proposed to play a role in the function of sodium-based Prussian blue analogues (PBA) batteries, a highly sought-out technology for industrial energy storage. Here, we report the detailed electronic structure characterization of uncharged and charged sodium-based manganese hexacyanomanganate anodes via Mn K-edge X-ray absorption spectroscopy (XAS), Kβ nonresonant X-ray emission (XES), and resonant inelastic X-ray scattering (RIXS). The latter allowed us to obtain site-selective XANES information about two distinct Mn centers. The obtained spectroscopic data represent the first electronic structure characterization of low-spin Mn 1+ using hard X-ray RIXS and XES and allowed us to confirm its role in anode reduction. In conclusion, our experimental approach can be expanded to analysis of analogues with other 3d transition metals broadening the application of exotic ionic states in materials engineering.

36 MATERIALS SCIENCE↗

Quantitative Risk Assessment (Topical Report)

Carbon capture, utilization, and storage (CCUS) in geological formations plays a key role in mitigating anthropogenic CO 2 emissions and achieving the aggressive goal of net-zero greenhouse gas emissions. Quantitative risk assessment is crucial for ensuring the safety and reliability of geologic carbon storage (GCS) by evaluating CO 2 migration in subsurface, forecasting potential leakage and induced seismicity risks, and optimizing operational and monitoring plans. We present the use, progress, and research trends of risk assessment from the Southwest Regional Partnership on Carbon Sequestration (SWP) as an example of large-scale CCUS projects in North America. The information provided in this report can help readers understand the significance of risk and uncertainty assessment and apply them effectively in large-scale CCUS projects.

42 ENGINEERING↗

PV Degradation Modeling: Applying Geospatial Workflows with "PVDeg"

Accurate degradation modeling is essential for predicting photovoltaic (PV) module performance, estimating longevity and informing design decisions. With degradation rates varying significantly by location, geospatial analysis is critical for PV and broader applications, such as agrivoltaics, weathering and environmental data analysis. This work presents PVDeg, an open-source tool designed for geospatial degradation analysis. PVDeg integrates meteorological data from global sources, including the National Solar Radiation Database (NSRDB) and Photovoltaic Geographical Information System (PVGIS), with degradation models. The toolkit enables users to customize geospatial workflows by integrating weather data, material parameters, and user-defined Python functions. It facilitates accelerated downloads of NSRDB and PVGIS datasets and optimizes geospatial point selection to preserve data density in regions of interest. Additionally, PVDeg provides a local database for storage and spatial queries, supporting large-scale analyses without the need for high-performance computing (HPC) resources. PVDeg provides a foundational workflow that extends its utility beyond PV applications, enabling researchers to analyze geospatial processes across discipline.

14 SOLAR ENERGY↗

Some data processing requirements for precision Nap-Of-the-Earth (NOE) guidance and control of rotorcraft

Nap-Of-the-Earth (NOE) flight in a conventional helicopter is extremely taxing for two pilots under visual conditions. Developing a single pilot all-weather NOE capability will require a fully automatic NOE navigation and flight control capability for which innovative guidance and control concepts were examined. Constrained time-optimality provides a validated criterion for automatically controlled NOE maneuvers if the pilot is to have confidence in the automated maneuvering technique. A second focus was to organize the storage and real-time updating of NOE terrain profiles and obstacles in course-oriented coordinates indexed to the mission flight plan. A method is presented for using pre-flight geodetic parameter identification to establish guidance commands for planned flight profiles and alternates. A method is then suggested for interpolating this guidance command information with the aid of forward and side looking sensors within the resolution of the stored data base, enriching the data content with real-time display, guidance, and control purposes. A third focus defined a class of automatic anticipative guidance algorithms and necessary data preview requirements to follow the vertical, lateral, and longitudinal guidance commands dictated by the updated flight profiles and to address the effects of processing delays in digital guidance and control system candidates. The results of this three-fold research effort offer promising alternatives designed to gain pilot acceptance for automatic guidance and control of rotorcraft in NOE operations.

Clement, Warren F.↗

Lunar RFC Reliability Testing for Assured Mission Success

NASA's Constellation program has selected the closed cycle hydrogen oxygen Polymer Electrolyte Membrane (PEM) regenerative Fuel Cell (RFC) as its baseline solar energy storage system for the lunar outpost and manned rover vehicles. Since the outpost and manned rovers are "human-rated", these energy storage systems will have to be of proven reliability exceeding 99 percent over the length of the mission. Because of the low (TRL=5) development state of the closed cycle hydrogen oxygen PEM RFC at present, and because there is no equivalent technology base in the commercial sector from which to draw or infer reliability information from, NASA will have to spend significant resources developing this technology from TRL 5 to TRL 9, and will have to embark upon an ambitious reliability development program to make this technology ready for a manned mission. Because NASA would be the first user of this new technology, NASA will likely have to bear all the costs associated with its development. When well-known reliability estimation techniques are applied to the hydrogen oxygen RFC to determine the amount of testing that will be required to assure RFC unit reliability over life of the mission, the analysis indicates the reliability testing phase by itself will take at least 2 yr, and could take up to 6 yr depending on the number of QA units that are built and tested and the individual unit reliability that is desired. The cost and schedule impacts of reliability development need to be considered in NASA's Exploration Technology Development Program (ETDP) plans, since life cycle testing to build meaningful reliability data is the only way to assure "return to the moon, this time to stay, then on to Mars" mission success.

Bents, David J.↗

Crew Activity Analyzer

The crew activity analyzer (CAA) is a system of electronic hardware and software for automatically identifying patterns of group activity among crew members working together in an office, cockpit, workshop, laboratory, or other enclosed space. The CAA synchronously records multiple streams of data from digital video cameras, wireless microphones, and position sensors, then plays back and processes the data to identify activity patterns specified by human analysts. The processing greatly reduces the amount of time that the analysts must spend in examining large amounts of data, enabling the analysts to concentrate on subsets of data that represent activities of interest. The CAA has potential for use in a variety of governmental and commercial applications, including planning for crews for future long space flights, designing facilities wherein humans must work in proximity for long times, improving crew training and measuring crew performance in military settings, human-factors and safety assessment, development of team procedures, and behavioral and ethnographic research. The data-acquisition hardware of the CAA (see figure) includes two video cameras: an overhead one aimed upward at a paraboloidal mirror on the ceiling and one mounted on a wall aimed in a downward slant toward the crew area. As many as four wireless microphones can be worn by crew members. The audio signals received from the microphones are digitized, then compressed in preparation for storage. Approximate locations of as many as four crew members are measured by use of a Cricket indoor location system. [The Cricket indoor location system includes ultrasonic/radio beacon and listener units. A Cricket beacon (in this case, worn by a crew member) simultaneously transmits a pulse of ultrasound and a radio signal that contains identifying information. Each Cricket listener unit measures the difference between the times of reception of the ultrasound and radio signals from an identified beacon. Assuming essentially instantaneous propagation of the radio signal, the distance between that beacon and the listener unit is estimated from this time difference and the speed of sound in air.] In this system, six Cricket listener units are mounted in various positions on the ceiling, and as many as four Cricket beacons are attached to crew members. The three-dimensional position of each Cricket beacon can be estimated from the time-difference readings of that beacon from at least three Cricket listener units

Murray, James↗

Lunar Regenerative Fuel Cell (RFC) Reliability Testing for Assured Mission Success

NASA's Constellation program has selected the closed cycle hydrogen oxygen Polymer Electrolyte Membrane (PEM) Regenerative Fuel Cell (RFC) as its baseline solar energy storage system for the lunar outpost and manned rover vehicles. Since the outpost and manned rovers are "human-rated," these energy storage systems will have to be of proven reliability exceeding 99 percent over the length of the mission. Because of the low (TRL=5) development state of the closed cycle hydrogen oxygen PEM RFC at present, and because there is no equivalent technology base in the commercial sector from which to draw or infer reliability information from, NASA will have to spend significant resources developing this technology from TRL 5 to TRL 9, and will have to embark upon an ambitious reliability development program to make this technology ready for a manned mission. Because NASA would be the first user of this new technology, NASA will likely have to bear all the costs associated with its development.When well-known reliability estimation techniques are applied to the hydrogen oxygen RFC to determine the amount of testing that will be required to assure RFC unit reliability over life of the mission, the analysis indicates the reliability testing phase by itself will take at least 2 yr, and could take up to 6 yr depending on the number of QA units that are built and tested and the individual unit reliability that is desired. The cost and schedule impacts of reliability development need to be considered in NASA's Exploration Technology Development Program (ETDP) plans, since life cycle testing to build meaningful reliability data is the only way to assure "return to the moon, this time to stay, then on to Mars" mission success.

Bents, David J.↗

Characterization of Octuopole Elements for IOTA

The Integrable Optics Test Accelerator (IOTA) is a research storage ring constructed and operated at Fermilab to demonstrate the advantages of nonlinear integrable lattices. One of the nonlinear lattice configurations with one integral of motion is based on a string of short octupoles. The results of the individual magnets characterizations, which were necessary to determine their multipole composition and magnetic centers, are presented. This information was used to select and align the best subset of octupoles for the IOTA run 4.

43 PARTICLE ACCELERATORS↗

Geospatial Data Platform for All

Spatiotemporal data has evolved in scale due to augmented use in cross-domain applications. Simultaneously, there is substantial growth in the availability of Geographic Information Systems (GIS) data provided by the United States Geological Survey (USGS) along with other federal, state, county, or local agencies through open-data portals and public access APIs. However, data availability does not equate with accessibility. Large-scale analyses and applications require robust, performant data management with co-location of data storage and computing. The insufficiency of data management infrastructure compels researchers to adopt ad hoc project- specific GIS data storage solutions (e.g., copying data to High-Performance computer file systems). As an ad hoc storage strategy does not scale, it hampers cross-domain analyses causing difficulty in data reuse and utilizing existing code bases. Furthermore, GIS data is complex and requires expertise to analyze and manipulate due to its intricate data structures and data-specific projection transformations. Despite the challenges, we recognize that derived GIS data products, e.g., satellite or LIDAR-based images, can be used in downstream applications such as AI by domain, but non-GIS experts. To address the data needs and overcome the challenges, we are working towards a GIS Data Platform focused on efficient data storage, data discovery and access, and an API to enable common workflows. We propose a knowledge-graph (KG) approach for data discovery, whereby datasets are semantically linked to higher- level constructs such as projects and research areas. The semantic data links enable researchers to explore datasets in a top-down approach by specifying relevant and meaningful terms (assists in finding hidden data). An advantage is that the nodes and edges in a knowledge graph create built-in semantic documentation. Deeper spatiotemporal connections between data sources can be encoded via Graph Neural Networks (GNN) (Zhang et al., 2021). The KG approach can be extended to integrate the data itself in a Virtual KG (VKG). Our work will derive inspiration from large-scale VKG efforts that have been undertaken or are currently underway as part of the OpenStreetMap project (Ding et al., 2021). For DOE Data Days, we share the proposed geospatial data platform hybrid (cloud/on-prem) architecture, our work-to-date on storing, retrieving, and transforming LiDAR and raster data relevant to two important NREL use-cases, including the Renewable Energy Potential (reV) Model, and present our proposal for a KG based data discovery engine.

data platform↗

A Review of Remote Welding and Nondestructive Examination Technologies for the DOE Standard Canister

The U.S. Department of Energy (DOE) manages a wide variety of spent nuclear fuel (SNF) that poses a unique management challenge. To help address this challenge, the DOE Standard Canister (DOESC), designed to remain sealed during handling, storage, transportation, and disposal, was conceptualized as a standardized containment vessel to accommodate DOE-managed SNF. Since 1999, several welding and examination processes have been independently developed for the DOESC’s closure welds. However, neither the DOESC nor these processes have been realized in an operational capacity. This review paper seeks to present and compare previously developed DOESC closure weld, nondestructive examination, and repair processes and technologies. Specific processes developed for the Idaho Spent Fuel Facility, in preparation for the Yucca Mountain geological repository, and the recent Road-Ready Demonstration Project are discussed. Further, specific focus is given to how different operating constraints and the American Society of Mechanical Engineers Boiler and Pressure Vessel Code (BPVC) have driven certain welding and nondestructive examination requirements. Historical DOESC welding and examination strategies are assessed against current regulatory and BPVC requirements. The comparison of welding processes, technologies, and DOESC designs presented in this review paper will inform further construction efforts for other commercial and DOE-managed SNF containments, including the DOESC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Information Fusion & Analytics for Human Lunar Exploration

The Information Fusion & Data Analytics (IFDA) project commenced in FY20, continued through FY21, and its final platform development phase continues in FY22. The objective remains the fusion and rapid accessibility of large quantities of disparate sourced human spaceflight data. IFDA is a platform tailored for NA (S&MA) to develop highly advanced operational data integration and analysis techniques. IFDA leverages the JSC ER7 modeling, simulation,and data fusion capabilities to collect, warehouse, and augment data human exploration data integration and analysis techniques. The IFDA project’s integrated data visualizations have been demonstrated in two validation scenarios in FY21, and provided the architecture and platform basis for development of a full-scale data analysis suite and storage solution useful to all JSC organizations engaged in real time operations and safety tasks. Scenarioand prototypical development including the construction of a full scale data analysis suite and storage solution, useful to all JSC organizations engaged in real time operations and safety tasks, is central to IFDA Phase 3 and provides a demonstrable pathway for the Digital Transformation Program. IFDA Phase 3 is focused on data provider, data utilizer, and SME hands-on workshops that will conclude the Dem / Valphase and deliver a program-ready data integration tool as a product.

information fusion↗

Visualizing the SEI formation between lithium metal and solid-state electrolyte

The solid electrolyte interphase (SEI) is regarded as the most important factor affecting the durability of lithium-metal anode in all-solid-state batteries (ASSBs). Despite its significance, the nucleation and growth mechanism of SEI is not yet well understood. Here, we elucidate the thermodynamics and kinetics governing SEI formation at the Li|β-Li 3 PS 4 interface at the atomic scale via thermodynamic phase equilibrium analysis and machine-learning-potential-assisted molecular dynamics (MD) simulations. An accurate moment tensor potential using the machine-learning method is developed for a reactive model of Li|β-Li 3 PS 4 . This potential enabled us to perform large-scale MD simulations with the model size expanded to the experimental dimensions (~40 nm) while maintaining the same level of accuracy as density functional theory calculations. The results reveal a four-stage evolution process at the Li|β-Li 3 PS 4 interface, namely (i) fast ion diffusion, (ii) nucleation, (iii) Li 2 S growth, and (iv) stabilization. Notably, we demonstrate that the SEI can be categorized into crystalline and amorphous regions. The simulated SEI thickness, structure, and composition closely match experimental findings, validating the accuracy of the MD simulations. We further disclose the significant impact of ion diffusion kinetic limitations on the phase formation and crystallization of interfacial products. Furthermore, we shed light on the detailed potential energy (PE) distribution of lithium along the direction perpendicular to the interface. Finally, this information is crucial for better understanding interfacial ion mobility.

25 ENERGY STORAGE↗

Net-zero CO 2 by 2050 scenarios for the United States in the Energy Modeling Forum 37 study

The Energy Modeling Forum (EMF) 37 study on deep decarbonization and high electrification analyzed a set of scenarios that achieve economy-wide net-zero carbon dioxide (CO 2 ) emissions in North America by mid-century, exploring the implications of different technology evolutions, policies, and behavioral assumptions affecting energy supply and demand. Here, for this paper, 16 modeling teams reported resulting emissions projections, energy system evolution, and economic activity. This paper provides an overview of the study, documents the scenario design, provides a roadmap for complementary forthcoming papers from this study, and offers an initial summary and comparison of results for net-zero CO 2 by 2050 scenarios in the United States. We compare various outcomes across models and scenarios, such as emissions, energy use, fuel mix evolution, and technology adoption. Despite disparate model structure and sources for input assumptions, there is broad agreement in energy system trends across models towards deep decarbonization of the electricity sector coupled with increased end-use electrification of buildings, transportation, and to a lesser extent industry. All models deploy negative emissions technologies (e.g., direct air capture and bioenergy with carbon capture and storage) in addition to land sinks to achieve net-zero CO 2 emissions. Important differences emerged in the results, showing divergent pathways among end-use sectors with deep electrification and grid decarbonization as necessary but not sufficient conditions to achieve net zero. These differences will be explored in the papers complementing this study to inform efforts to reach net-zero emissions and future research needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Blind Benchmark Exercise for Spent Nuclear Fuel Decay Heat

The decay heat rate of five spent nuclear fuel assemblies of the pressurized water reactor type were measured by calorimetry at the interim storage for spent nuclear fuel in Sweden. Calculations of the decay heat rate of the five assemblies were performed by 20 organizations using different codes and nuclear data libraries resulting in 31 results for each assembly, spanning most of the current state-of-the-art practice. The calculations were based on a selected subset of information, such as reactor operating history and fuel assembly properties. The relative difference between the measured and average calculated decay heat rate ranged from 0.6% to 3.3% for the five assemblies. The standard deviation of these relative differences ranged from 1.9% to 2.4%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation

The arrival of direct electron detectors (DED) with high frame-rates in the field of scanning transmission electron microscopy has enabled many experimental techniques that require collection of a full diffraction pattern at each scan position, a field which is subsumed under the name four dimensional-scanning transmission electron microscopy (4D-STEM). DED frame rates approaching 100 kHz require data transmission rates and data storage capabilities that exceed commonly available computing infrastructure. Current commercial DEDs allow the user to make compromises in pixel bit depth, detector binning or windowing to reduce the per-frame file size and allow higher frame rates. This change in detector specifications requires decisions to be made before data acquisition that may reduce or lose information that could have been advantageous during data analysis. The 4D Camera, a DED with 87 kHz frame-rate developed at Lawrence Berkeley National Laboratory, reduces the raw data to a linear-index encoded electron event representation (EER). Here we show with experimental data from the 4D Camera that linear-index encoded EER and its direct use in 4D-STEM phase contrast imaging methods enables real-time, interactive phase-contrast from large-area 4D-STEM datasets. Furthermore, we detail the computational complexity advantages of the EER and the necessary computational steps to achieve real-time interactive ptychography and center-of-mass differential phase contrast using commonly available hardware accelerators.

4D-STEM↗

Quantum optical memory for entanglement distribution

Optical photons are powerful carriers of quantum information, which can be delivered in free space by satellites or in fibers on the ground over long distances. Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Quantum optical memories are devices designed to store quantum information in the form of stationary excitations, such as atomic coherence, and are capable of coherently mapping these excitations to flying qubits. Quantum memories can effectively store and manipulate quantum states, making them indispensable elements in future long-distance quantum networks. Over the past two decades, quantum optical memories with high fidelities, high efficiencies, long storage times, and promising multiplexing capabilities have been developed, especially at the single-photon level. In this review, we introduce the working principles of commonly used quantum memory protocols and summarize the recent advances in quantum memory demonstrations. We also offer a vision for future quantum optical memory devices that may enable entanglement distribution over long distances.

Lei, Yisheng↗