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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,207 records · Page 67

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Baseline vs. DER Scenario

Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

PA-BCI Meteorological dataset 1985-2018

This data package contains a QA/QC-ed meteorological time series dataset from 1985 to 2018, including relative humidity, temperature, solar radiation, rainfall, wind speed, and barometric pressure at Barro Colorado Island (PA-BCI) in Panama. The data were collected at the elevations of 42 m and 48 m at the BCI Lutz station, except for rainfall that was collected at the BCI Clearing station at the elevation of 1 m. Individual time series datasets were collected using electro-mechanical (electronic sensors, data loggers, chart recorders, etc.). The rainfall dataset was collected using the tipping bucket method, and the data could have been underestimated by 13-17% (likely the large values). The data is included as a single CSV file.

54 ENVIRONMENTAL SCIENCES↗

Materials laboratories of the future for alloys, amorphous, and composite materials

In alignment with the Materials Genome Initiative and as the product of a workshop sponsored by the US National Science Foundation, we define a vision for materials laboratories of the future in alloys, amorphous materials, and composite materials; chart a roadmap for realizing this vision; identify technical bottlenecks and barriers to access; and propose pathways to equitable and democratic access to integrated toolsets in a manner that addresses urgent societal needs, accelerates technological innovation, and enhances manufacturing competitiveness. Spanning three important materials classes, this article summarizes the areas of alignment and unifying themes, distinctive needs of different materials research communities, key science drivers that cannot be accomplished within the capabilities of current materials laboratories, and open questions that need further community input. Here, we provide a broader context for the workshop, synopsize the salient findings, outline a shared vision for democratizing access and accelerating materials discovery, highlight some case studies across the three different materials classes, and identify significant issues that need further discussion.

36 MATERIALS SCIENCE↗

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗

Carbon Storage Planning Framework Dashboard

The Carbon Storage Planning Framework dashboard (beta version) provides easy access to explore, query, and evaluate multiple data layers to support and accelerate carbon storage resource and feasibility assessments and planning efforts. The interactive dashboard currently contains a range of authoritative datasets associated with geologic, technical, social, and environmental factors. The data sets can be filtered geographically for an area of interest to update statistics and charts within the dashboard. Terms of Use: NETL is sharing this beta/prototype tool with the request that users will provide feedback to NETL about the function and content of the dashboard, alerting NETL to any bugs or providing suggestions for additional resources to help mature the platform.

CCS,EDX4CCS,carbon storage,dashboard↗

Carbon Transport and Storage Planning and Viability Support Tools

The EDX disCO2ver Carbon Transport and Storage Planning and Viability Support Tools are made up of the Carbon Storage Planning Inquiry Tool (CS PlanIT, Justman et al. 2024) and the Carbon Storage Technical Viability Approach Support Tool (CS TVA). Together, these tools support data access to support understanding data availability to support planning efforts for carbon transport and storage. The Carbon Storage Planning Inquiry Tool (CS PlanIT) is an online web mapping application designed to help users explore, query, and evaluate multiple data layers to support and accelerate carbon storage resource and feasibility assessments and planning efforts. CS PlanIT currently contains a range of datasets associated with geologic, technical, and infrastructure factors. The data sets can be filtered geographically for an area of interest to update statistics and charts within the dashboard. The dashboard is divided into different sections called widgets, relating to different steps in the carbon storage planning process. The resources in this submission include a link to PlanIT, as well as a data catalog and link to user documentation. The original citation for the CS PlanIT tool, which has now been integrated into the toolset here, was: - Devin Justman, Scott Pantaleone, Maneesh Sharma, Lucy Romeo, Paige Morkner, CS PlanIT (Carbon Storage Planning Inquiry Tool) , 6/28/2024, https://edx.netl.doe.gov/dataset/cs-planit-carbon-storage-planning-inquiry-tool, DOI: 10.18141/2377953 The Carbon Storage Technical Viability Approach Support (CS TVA) Tool displays spatial data availability for the many components of Geologic Carbon Storage (GCS) technical viability assessment (Creason al 2025). Identifying sites suitable for GCS requires evaluating the intersection of myriad factors, including reservoir conditions, subsurface and surface hazards, infrastructure requirements, and energy community metrics. The technical viability of a site can only be confirmed for instances where all these factors have data available, and where those data support viability. Additional Resources related to the Technical Viability Assessment Tool: - Julia Mulhern, Casey White, Araceli Lara, Neyda Cordero Rodriguez, Zachary Jackson, Jacob Shay, Gabriel Creason, MacKenzie Mark-Moser, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Database, 3/26/2025, https://edx.netl.doe.gov/dataset/edx4ccs-carbon-storage-technical-viability-approach-database , DOI:10.18141/1984655 - Julia Mulhern, MacKenzie Mark-Moser, Gabriel Creason, Casey White, Araceli Lara, Neyda Cordero Rodriguez, Zach Jackson, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Matrix, 3/27/2025, https://edx.netl.doe.gov/dataset/carbon-storage-technical-viability-approach-cs-tva-matrix , DOI: 10.18141/2539979 - Gabriel Creason, Zach Jackson, Neyda Cordero Rodriguez, Julia Mulhern, Casey White, Araceli Lara, MacKenzie Mark-Moser, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database, 3/27/2025, https://edx.netl.doe.gov/dataset/carbon-storage-technical-viability-approach-cs-tva-data-availability-results-database, DOI:10.18141/2538557

Carbon storage↗

Transverse BBU Suppression with Feedback for Energy-Recovery Linacs

The Electron–Ion Collider (EIC) achieves its design luminosity by cooling the ion beam with a high-current electron beam generated in an energy-recovery linac (ERL). The baseline ERL lattice employs a BNL five-cell cavity that is frequency-scaled to 197 MHz, 591 MHz, and 1.773 GHz, raising concerns about multibunch beam-breakup (BBU) instabilities. Threshold currents for each frequency option are established with two independent BBU tracking codes, providing cross-validated operating margins that guide cavity selection. To further increase the current limit, we incorporate a digital transverse feedback (FB) system that targets the dominant higher-order modes (HOMs). Simulations show the FB raises the BBU threshold by roughly an order of magnitude: power-spectral-density analysis of the beam centroid at the linac exit confirms strong suppression of the aliased HOM peak, although some spectral growth appears at secondary frequencies. This combined study quantifies baseline BBU limits, demonstrates effective active mitigation, and charts a practical path toward robust, high-current operation of the EIC ERL.

Accelerator Physics↗

Coupled Geomechanical Modeling to Assess Cap Rock Integrity and Mechanical Fault Stability: Application to Farnsworth Field Unit Project

Abstract The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations in the Farnsworth, Texas, USA. Anthropogenic CO2 is sourced from a fertilizer and an ethanol plant. This work utilizes Farnsworth’s full-field, history-matched, compositional hydrodynamic coupled geomechanical model for assessing the impact of stress changes observed through the history matched field life. Production and injection induced stress changes, fault stability and caprock integrity investigations are performed to project the potential for fault reactivation and the loss of caprock integrity under shear failure. A static mechanical earth model (MEM) was constructed for use in transient coupled geomechanical model based on the existing Southwest Regional Partnership (SWP) geological model. The static MEM inherits the stratigraphic and structural features of the geologic model and incorporates additional overburden, underburden, and sideburden formations required to impose mechanical boundary conditions. Mechanical properties were distributed in the 3D MEM through integration of geophysical logs and 3-dimensional seismic elastic inversion properties using a combination of Bayesian and stochastic interpolation methods. These data are further enhanced by lab derived strength and failure criteria for the caprock interval. Additionally, interpreted faults and other geological features were included as part of the static structural framework to fully represent subsurface hydraulic and mechanical systems and appropriately integrate heterogeneity. Two-way coupling of hydrodynamic flow and geomechanical simulations incorporates the Kozeny-Carman relationship for updating permeability and is history matched through primary, secondary (waterflooding) and tertiary (CO2 WAG) recovery periods before performing a twenty year forecast. Two-way simulations are performed to understand the effective stress perturbations imposed by field operations: water injection and the more recent implementation of WAG. Evaluation of Mohr circles with liquid production and field pressure charts as well as slip tendency and distance to failure metrics indicate that neither our faults or cap rock are critically stressed. This paper presents the results of the Farnsworth initial attempts to integrate the seismic driven 3D MEM into coupled hydrodynamic geomechanical history match simulation workflow.

02 PETROLEUM↗

Advanced Instrumentation and Control Methods for Small and Medium Reactors with IRIS Demonstration

Development and deployment of small-scale nuclear power reactors and their maintenance, monitoring, and control are part of the mission under the Small Modular Reactor (SMR) program. The objectives of this NERI-consortium research project are to investigate, develop, and validate advanced methods for sensing, controlling, monitoring, diagnosis, and prognosis of these reactors, and to demonstrate the methods with application to one of the proposed integral pressurized water reactors (IPWR). For this project, the IPWR design by Westinghouse, the International Reactor Secure and Innovative (IRIS), has been used to demonstrate the techniques developed under this project. The research focuses on three topical areas with the following objectives. Objective 1 - Develop and apply simulation capabilities and sensitivity/uncertainty analysis methods to address sensor deployment analysis and small grid stability issues. Objective 2 - Develop and test an autonomous and fault-tolerant control architecture and apply to the IRIS system and an experimental flow control loop, with extensions to multiple reactor modules, nuclear desalination, and optimal sensor placement strategy. Objective 3 - Develop and test an integrated monitoring, diagnosis, and prognosis system for SMRs using the IRIS as a test platform, and integrate process and equipment monitoring (PEM) and process and equipment prognostics (PEP) toolboxes. The research tasks are focused on meeting the unique needs of reactors that may be deployed to remote locations or to developing countries with limited support infrastructure. These applications will require smaller, robust reactor designs with advanced technologies for sensors, instrumentation, and control. An excellent overview of SMRs is described in an article by Ingersoll (2009). The article refers to these as deliberately small reactors. Most of these have modular characteristics, with multiple units deployed at the same plant site. Additionally, the topics focus on meeting two of the eight needs outlined in the recently published 'Technology Roadmap on Instrumentation, Control, and Human-Machine Interface (ICHMI) to Support DOE Advanced Nuclear Energy Programs' which was created 'to provide a systematic path forward for the integration of new ICHMI technologies in both near-term and future nuclear power plants and the reinvigoration of the U.S. nuclear ICHMI community and capabilities.' The research consortium is led by The University of Tennessee (UT) and is focused on three interrelated topics: Topic 1 (simulator development and measurement sensitivity analysis) is led by Dr. Mike Doster with Dr. Paul Turinsky of North Carolina State University (NCSU). Topic 2 (multivariate autonomous control of modular reactors) is led by Dr. Belle Upadhyaya of the University of Tennessee (UT) and Dr. Robert Edwards of Penn State University (PSU). Topic 3 (monitoring, diagnostics, and prognostics system development) is led by Dr. Wes Hines of UT. Additionally, South Carolina State University (SCSU, Dr. Ken Lewis) participated in this research through summer interns, visiting faculty, and on-campus research projects identified throughout the grant period. Lastly, Westinghouse Science and Technology Center (Dr. Mario Carelli) was a no-cost collaborator and provided design information related to the IRIS demonstration platform and defining needs that may be common to other SMR designs. The results of this research are reported in a six-volume Final Report (including the Executive Summary, Volume 1). Volumes 2 through 6 of the report describe in detail the research and development under the topical areas. This volume serves to introduce the overall NERI-C project and to summarize the key results. Section 2 provides a summary of the significant contributions of this project. A list of all the publications under this project is also given in Section 2. Section 3 provides a brief summary of each of the five volumes (2-6) of the report. The contributions of SCSU are described in Section 4, including a summary of undergraduate research experience. The project management organizational chart is provided as Figure 1. Appendices A, B, and C contain the reports on the summer research performed at the University of Tennessee by undergraduate students from South Carolina State University.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SMALL-SCALE SAFETY TEST REPORT FOR RDX (SECOND CALIBRATION)

RDX was provided by Indian Head and was dried at 60 C for 16 hours, cooled and kept in a desiccator before use. Please note that the impact testing was done on both pellets and loose powder which resulted in different data. The impact sensitivity on pressed pellets was 34 cm that is greater than that on loose powder, as expected. The impact test data on the loose powder was similar to what Indian Head and LANL got. Remarkable consistent results were observed for test results of loose powder RDX. The average impact sensitivyt (DH{sub 50}) was 21.8 cm and the average friction sensitivity (F{sub 50}) for loose powder was 24.9 kg, respectively. DSC charts showed that peak temperatures and onset temperatures for all 3 runs of RDX samples were almost identical. All electrostatic spark sensitivity was 0/10 at 1.0 J with a 510-ohm resistor in the discharge circuit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy-water analysis of the 10-year WECC transmission planning study cases.

In 2011 the Department of Energy's Office of Electricity embarked on a comprehensive program to assist our Nation's three primary electric interconnections with long term transmission planning. Given the growing concern over water resources in the western U.S. the Western Electricity Coordinating Council (WECC) requested assistance with integrating water resource considerations into their broader electric transmission planning. The result is a project with three overarching objectives: (1) Develop an integrated Energy-Water Decision Support System (DSS) that will enable planners in the Western Interconnection to analyze the potential implications of water stress for transmission and resource planning. (2) Pursue the formulation and development of the Energy-Water DSS through a strongly collaborative process between the Western Electricity Coordinating Council (WECC), Western Governors Association (WGA), the Western States Water Council (WSWC) and their associated stakeholder teams. (3) Exercise the Energy-Water DSS to investigate water stress implications of the transmission planning scenarios put forward by WECC, WGA, and WSWC. The foundation for the Energy-Water DSS is Sandia National Laboratories Energy-Power-Water Simulation (EPWSim) model (Tidwell et al. 2009). The modeling framework targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. This framework provides an interactive environment to explore trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., state, county, watershed, interconnection). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. The framework currently supports modules for calculating water withdrawal and consumption for current and planned electric power generation; projected water demand from competing use sectors; and, surface and groundwater availability. WECC's long range planning is organized according to two target planning horizons, a 10-year and a 20-year. This study supports WECC in the 10-year planning endeavor. In this case the water implications associated with four of WECC's alternative future study cases (described below) are calculated and reported. In future phases of planning we will work with WECC to craft study cases that aim to reduce the thermoelectric footprint of the interconnection and/or limit production in the most water stressed regions of the West.

13 HYDRO ENERGY↗

NGNP Data Management and Analysis System Analysis and Web Delivery Capabilities

Projects for the Very High Temperature Reactor (VHTR) Technology Development Office provide data in support of Nuclear Regulatory Commission licensing of the very high temperature reactor. Fuel and materials to be used in the reactor are tested and characterized to quantify performance in high-temperature and high-fluence environments. The NGNP Data Management and Analysis System (NDMAS) at the Idaho National Laboratory has been established to ensure that VHTR data are (1) qualified for use, (2) stored in a readily accessible electronic form, and (3) analyzed to extract useful results. This document focuses on the third NDMAS objective. It describes capabilities for displaying the data in meaningful ways and for data analysis to identify useful relationships among the measured quantities. The capabilities are described from the perspective of NDMAS users, starting with those who just view experimental data and analytical results on the INL NDMAS web portal. Web display and delivery capabilities are described in detail. Also the current web pages that show Advanced Gas Reactor, Advanced Graphite Capsule, and High Temperature Materials test results are itemized. Capabilities available to NDMAS developers are more extensive, and are described using a second series of examples. Much of the data analysis efforts focus on understanding how thermocouple measurements relate to simulated temperatures and other experimental parameters. Statistical control charts and correlation monitoring provide an ongoing assessment of instrument accuracy. Data analysis capabilities are virtually unlimited for those who use the NDMAS web data download capabilities and the analysis software of their choice. Overall, the NDMAS provides convenient data analysis and web delivery capabilities for studying a very large and rapidly increasing database of well-documented, pedigreed data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Estimated United States Residential Energy Use in 2005

A flow chart depicting energy flow in the residential sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 11,000 trillion British Thermal Units (trBTUs) of electricity and fuels were used throughout the United States residential sector in lighting, electronics, air conditioning, space heating, water heating, washing appliances, cooking appliances, refrigerators, and other appliances. The residential sector is powered mainly by electricity and natural gas. Other fuels used include petroleum products (fuel oil, liquefied petroleum gas and kerosene), biomass (wood), and on-premises solar, wind, and geothermal energy. The flow patterns represent a comprehensive systems view of energy used within the residential sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗