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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Calculating Reactivity and Fusion Energy Yield

During my time at Lawrence Livermore National Lab, I had the opportunity to intern at the HEDS (High Energy Density Science) Center and become an IFE (Inertial Fusion Energy) summer student for three weeks with Dr. Veronika Kruse as my mentor. Within this time frame, my research project’s goal was to develop an understanding of nuclear fusion while building technical skills in calculating and analyzing the required data. The following report outlines the process of calculating reactivity curves and energy yields of specific fusion reactions. For context, nuclear fusion is when two atomic nuclei combine, and energy is released. NIF (the National Ignition Facility), located at LLNL, uses laser-based inertial confinement fusion to achieve ignition. To simplify the process, NIF uses lasers to heat a small sphere or capsule, made up of primarily deuterium and tritium, to extremely high temperatures and densities to achieve fusion ignition, where more energy is released than the lasers introduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Adaptive Cyber-Physical Resilience for Building Control Systems

The main goal of the project is to develop an AI-based process layer cybersecurity suite for detection, isolation and mitigation of cyber-attack effects on operation of building energy management systems (BEMS). The following constituent key technologies were developed under the program towards fulfilling the program objectives: (1) developed a high fidelity BEMS testbed for generation of training data and validation of developed technologies; (2) developed a physics informed ML based attack detection and localization module (ADL) capable of detecting high impact stealthy attacks (HISA - attacks causing 30% energy utilization but no immediate visible impact otherwise) with 98% accuracy; (3) developed a methodology to determine ’representative days’ to limit the data required for training; (4) developed a virtual sensing system that can reconstruct affected sensors with 10% error for the same HISA set; (5) developed a resilient model predictive control system that can continue operation of the BEMS without jeopardizing stability for the HISA set; and (6) integrated and deployed all the constituent modules and demonstrated the efficacy of the technology in real-time in a hardware in loop simulation.

42 ENGINEERING↗
DOE OSTI2024

New Matrix Framework to Determine Carbon Storage Technical Viability

Carbon storage is an integral component of reducing CO2 emissions. Research over the past two decades has developed workflows for volume assessments and economic project feasibility, providing necessary and useful tools to progress geologic carbon storage (GCS) projects. These workflows and assessments have focused primarily on determining the in-situ storage resource based on geologic and engineering parameters and do not integrate subsurface characterization with surface conditions, social factors, and environmental factors that may pose a benefit or impediment to the implementation of GCS. Furthermore, the data required to assess the technical viability of GCS are myriad and disparate. There is no current methodology that identifies technical viability criteria and systematically informs how to aggregate these factors for spatial assessments. To address this gap, the National Energy Technology Laboratory has developed a Carbon Storage Technical Viability Approach (CS TVA) Matrix that incorporates a wide variety of factors to inform and accelerate screening for GCS site selection in the United States.

Mulhern, Julia↗
DOE OSTI2024

Method for Real-Time Salt Aerosol Concentration and Size Measurements for Molten Salt Reactor Safety Assessments

Licensing a new nuclear reactor involves evaluating credible accident scenarios by developing models that simulate accident progression to predict possible outcomes and their impact on safety. The formation of radionuclide-bearing aerosols in the respirable size range can significantly affect dose consequence and threaten human health and is therefore a focus of nuclear reactor safety assessments. Recent reviews of the literature identified a lack of existing experimental data describing the mechanisms of formation and properties (size, concentration, and composition) of radionuclide-bearing aerosols that may be produced from molten salt reactor (MSR) facilities during postulated accident scenarios. Experiments on aerosol formation from molten salt systems are a high priority need that will support MSR licensing by indicating the radiological consequences of aerosol formation and providing the data required for model development and validation. The evolving conditions that occur during a MSR accident, such as a spill of molten fuel salt, may affect aerosol formation mechanisms and aerosol properties over time. There is a need to conduct experiments that simulate credible MSR accidents in a laboratory to generate aerosols with realistic characteristics and behaviors and a need to measure these aerosols in real time under accident-relevant conditions. This report describes the development of a method that can be used to quantify the size and concentration of salt aerosol particles that form from molten salt systems in real time. This method will be employed in future integral effects tests that are conducted at an engineering scale to simulate realistic MSR accidents and in future separate effects tests that will provide mechanistic insight into aerosol formation and properties to support process model development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

M3SF-24LL010301052-Summary of SUPCRTNE testing and Rev0 database

This progress report (Level 3 Milestone Number M3SF-24LL010301052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Disposal R&D work package SF-24LL01030105. SUPCRTNE is being developed as the primary engine for thermodynamic database development in support of geologic disposal of high-level nuclear waste. As used here, “SUPCRT” refers to both a computer program and its supporting database. Additional letters or numbers refer to specific variants (SUPCRT92, (Johnson et al., 1992); SUPCRTBL, (Zimmer et al., 2016); and SUPCRTNE). A SUPCRT database contains the data required to calculate the thermodynamic properties of solid, gas, and aqueous species over a wide range of temperature and pressure. Normally, SUPCRT is used to create a higher-level database that directly supports modeling and simulation codes such as EQ3/6, GWB, PHREEQC, and PFLOTRAN.

58 GEOSCIENCES↗
DOE OSTI2024

Pacific Northwest National Laboratory Annual Site Environmental Report for Calendar Year 2023

Pacific Northwest National Laboratory (PNNL), one of the U.S. Department of Energy (DOE) Office of Science’s 10 national laboratories, provides innovative science and technology development in the areas of energy and the environment, fundamental and computational science, and national security. There are three DOE offices within the Richland area. Two are responsible for the Hanford Site, whereas the Pacific Northwest Site Office oversees PNNL. PNNL prepares an Annual Site Environmental Report to meet the requirements of DOE Order 231.1B, Environment, Safety and Health Reporting, and DOE Order 458.1, Radiation Protection of the Public and the Environment, thus assuring that the public is informed of any PNNL-Richland campus or PNNL-Sequim campus event that could adversely affect the health and safety of the public, site staff, or the environment. The report provides a synopsis of ongoing environmental management performance and compliance activities for operations that occur at the PNNL-Richland campus in Richland, Washington, and at the PNNL-Sequim campus near Sequim, Washington. It describes the location of and background for each facility; addresses compliance with applicable DOE, federal, state, and local regulations, and site-specific permits; documents environmental monitoring efforts and their status; presents potential radiation doses to staff and the public in the surrounding areas; and describes DOE-required data quality assurance methods used for data verification. The ASER report describes Compliance with Federal, State, and Local Laws and Regulations in 2023, Environmental Sustainability, Environmental monitoring and dose assessment, Natural and Cultural Resource Management, and Quality Assurance activities that took place during Calendar Year 2023.

40 CFR 61 Subpart H↗
DOE OSTI2024

A Framework for Addressing Hydropower Modeling Gaps in Electric Grid Planning and Operational Studies [Slides]

Realistic representation of hydropower in power system planning and operation studies is extremely important as it helps in avoiding under/over-estimation of the services the hydro power units can provide. A framework and tools have been developed to account for hydrological conditions and modify power system models accordingly. For example, HyDat – data and AI driven platform, that provides that data required for editing the power system model files Collaborative effort with V&R Energy. Also, development of POM based tools have been performed, a) Tool1: editing .raw files with realistic current and maximum hydrogeneration and redispatch of other units, and b) Tool2: Editing .dyr files to represent water head, current and maximum generation. Finally the framework, HASP framework combines HyDat and V&R energy tools to produce modified power system model files. Key Take-away points from contingency analysis studies include a) the number of critical contingencies increases as the water levels are reduced (70%>75%>80%), and b) both the extent and the quality of dynamic response of the Hydropower unit is different with varying water head levels.

13 HYDRO ENERGY↗
DOE OSTI2025

Summary of Pilot Project State Technical Assistance on Multi-Sector Analysis for Electric and Petroleum Fuels

The Oregon Energy Security Plan, (ODOE 2024) published in September 2024, builds a strong case for the state to give acute attention to the fuel supply chain. In December 2024, Pacific Northwest National Laboratory (PNNL) in partnership with Oregon Department of Energy (ODOE), announced a pilot project to conduct an analysis that synthesizes current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors, such as transportation electrification, sponsored by the Department of Energy’s (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER). The study, is intended to leverage existing modeling and frameworks from a recent 2024 sector coupling analysis supported by the DOEs Office of Electricity (OE) (B. Mitra, S. Pal, et al., Coupling of the Electricity and Transportation Sectors - Part I: Sector Overviews 2024) (B. Mitra, S. Pal and J. Reeve, et al. 2024). While the PNNL team set out to conduct a quantitative risk analysis driven by detailed data that synthesizes current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors. The intention was to provide an approach that could be extendable to other parts of the country. They encountered data limitations and adjusted their approach accordingly. This report summarizes PNNL's original plan for executing the study, including limitations for obtaining data requirements for fuel flows and interim products, as well as a risk matrix that can be used to identify supply chain risks.

02 PETROLEUM↗
DOE OSTI2026

FY25 Ion Exchange Processing for the West Area Risk Management (WARM) Project

The West Area Risk Management (WARM) Project was established to enable near-term retrieval and pretreatment of tank waste from Hanford’s 200 West Area and to support deployment of an ion exchange (IX) system capable of producing cesium-depleted supernate suitable for offsite treatment and disposal. The WARM experimental campaign was designed to provide key data for design and operational planning of the 200 W IX system, which plans to utilize crystalline silicotitanate (CST) as the active media for cesium removal. This report documents a comprehensive FY25 experimental campaign designed to produce key technical data required for design and operational planning of the WARM IX system. Testing includes assessing Cs and Sr breakthrough performance in a 4-column system, Cs capacity batch contact testing, phosphate precipitation assessments, reduced-hydroxide feed displacement evaluation, and Sr speciation impacts on Sr removal. The experimental results provide detailed trends in Cs and Sr loading behavior, breakthrough performance across a 4-column staged IX system, distribution profiles within CST beds, and projections of operational flowrates relative to Waste Acceptance Criteria (WAC) limits. Batch contact testing established equilibrium partitioning behavior for the S1–S5 simulants and characterized how matrix chemistry influenced Cs sorption onto CST. Additionally, further evaluations on waste matrix as it pertains to precipitation potential were also determined. Collectively, these datasets support engineering design choices for WARM system throughput and pretreatment planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

AI-Ready Data Pilot Project Report

The proliferation of artificial intelligence in scientific research has created an urgent need to define "AI-ready data" for researchers and, more importantly, provide resources to help them produce AI-ready data. At Pacific Northwest National Laboratory, we conducted a pilot study with three data scientists evaluating three CSV datasets from different scientific domains, followed by semi-structured interviews capturing assessment practices. Our findings reveal that AI-readiness evaluation is intuition-based, with practitioners asking "How fast can I go from raw data to my machine learning pipeline?" Data scientists consistently prioritized workflow efficiency, human interpretability, and quality stewardship signals. From these insights, we developed a practical evaluation framework comprising data requirements, metadata standards, and validation tests that provides actionable criteria for producing and curating AI-ready datasets, addressing the gap between theoretical understanding and practical implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Pacific Northwest National Laboratory Annual Site Environmental Report for Calendar Year 2024

The report provides a synopsis of ongoing environmental management performance and compliance activities for operations that occur at the PNNL-Richland campus in Richland, Washington, and at the PNNL-Sequim campus near Sequim, Washington. It describes the location of and background for each facility; addresses compliance with applicable DOE, federal, state, and local regulations, and site-specific permits; documents environmental monitoring efforts and their status; presents potential radiation doses to staff and the public in the surrounding areas; and describes DOE-required data quality assurance methods used for data verification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

DrEVL Radiometer Calibration

This report details the calibration procedures that were used for the spectral and radiometric part of the DrEVL radiometers. Our goal was to develop a highly repeatable and low cost spectral radiometer that could be deployed at numerous sites to collect a catalog of lightning data. Maximizing the re-usability of that data requires a well-calibrated instrument.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Ceramic Composite Experimental Testing Status

Over recent years, ceramic matrix materials such as SiC–SiC and C–C have been gaining interest for use in fusion reactors, light water reactors (LWRs), and high-temperature reactors (HTRs). These materials are good candidates to operate in very high temperature and moderate to high radiation environments. The evaluation of composite materials, in general, is challenging because of variations in precursor materials, variations in the fabrication process across fabricators, and the wide range of potential fiber architectures, to name a few. However, the need to evaluate neutron-irradiated properties adds another layer of complexity, which includes cost, timeline, and specimen size limitations (often associated with irradiation testing). A qualification methodology for the use of ceramic composites is provided in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code Section III-5-HHB. The methodology is supported by ASTM International (ASTM) guides, which provide a pathway to accomplish this effort. Part of the qualification strategy is for the designer to collect material property data on environmental conditions representative of its design envelope. These data include irradiation effects. This report presents an experimental study and test campaign developed to partially address this gap by providing initial mechanical and physical property data required for design. A variety of different materials using different manufacturing techniques are considered as part of this campaign. The test plan suggests performing a screening or partial irradiation study to assist the designer during the material selection process. The designer can then perform a more comprehensive qualification study if the material performance is promising. This work focuses on the status of the specimen preparations (machining of samples), the current test methods and failure analysis as well as the preparation of irradiation vehicles for the irradiation campaign. The irradiation will be performed at Oak Ridge National Laboratory (ORNL) in the High Flux Isotope Reactor (HFIR) and at Idaho National Laboratory (INL) in the Advanced Test Reactor (ATR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Anomaly Detection in the SBND Experiment Based on Graph Neural Networks

Traditional anomaly detection in SBND experiments require data reconstruction and manual supervision, and thus has the drawbacks of long detection time, being labour intensive and incapable of predicting potential future anomalies. Machine learning models, especially autoencoders, have been widely applied in anomaly detection, and developing an autoencoder for anomaly detection in SBND experiment is going to tremendously improve the efficiency and accuracy of the experiment. The autoencoder has the advantage of automation, efficiency, and can be used to predict future anomalies in the SBND experiment.

Fu, Jiayu [U. Chicago (main)]↗
DOE OSTI2026

Integration of Online Cross-Section Generation Capability with Depletion and Transient Solvers in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE)-based reactor multiphysics analysis application jointly developed by Argonne and Idaho National Laboratories under the DOENE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In FY25, an online crosssection generation capability based on the Self-Shielding Application Programming Interface (SSAPI) was demonstrated for TRISO-fueled reactor problems under steady-state conditions. This fiscal year, that capability was extended to support depletion and transient multiphysics calculations, enabling high-fidelity analyses that generate self-shielded cross sections on the fly from the actual evolving composition and temperature states rather than from pre-tabulated libraries. For depletion, a two-way coupling was established in which SSAPI computes compact-averaged self-shielded cross sections that the depletion solver then uses to advance the Bateman equations, with the updated compositions returned to SSAPI at each step; the depletion module was refactored to support both library-based and SSAPI-based cross sections, and additional logic was added to track daughter isotopes and to exclude minor isotopes for efficiency. For transient analysis, the SSAPI multigroup library was extended with the kinetics data required for time-dependent calculations, the Improved Quasi-Static (IQS) scheme was coupled with SSAPI, and several supporting capabilities were implemented, including a self-shielding treatment that lets control rods and drums move within a self-shielded model, which had previously been impossible and had ruled out rod- and drum-movement transients with on-the-fly cross sections altogether, a new mixing scheme for delayed-neutron precursor decay constants, a checkpoint-based restart workflow, and performance improvements such as pointwise cross-section interpolation and the bypassing of unnecessary Dancoff factor calculations. The implemented capabilities were verified against Serpent Monte Carlo solutions. For depletion, a prismatic pin-cell problem based on a Next Generation Nuclear Plant (NGNP) Very High Temperature Reactor benchmark showed excellent agreement, with eigenvalue differences within 200 pcm over the entire burnup range (up to 140 MWD/kgU) and fission-product and actinide inventories agreeing to within 0.8% and 2.5%, respectively; a heat-pipe microreactor assembly problem with a much higher fuel loading confirmed the same behavior and quantified the bias introduced when the multigroup equivalence effect is neglected. For transient analysis, a pin-cell problem with a step reactivity insertion and temperature feedback reproduced the analytically expected asymptotic power and showed close agreement between the direct and IQS solutions, and a two-dimensional microreactor core problem with control-drum rotation exercised the new moving-drum self-shielding treatment and demonstrated successful coupling of the online crosssection generation with both the direct and IQS transient methods. The capability was further exercised on a full-core pebble-bed problem, in which Griffin was coupled with the System Analysis Module (SAM) to simulate load-following operation of the gPBR with the Doppler feedback resolved at the TRISO fuel kernel temperature. These developments in Griffin provide a convenient, high-fidelity approach to cross-section generation for advanced thermal reactors with geometrically complex and highly heterogeneous configurations, including TRISO-fueled prismatic and pebble-bed systems, and support steady-state, depletion, and transient multiphysics calculations. They also enable self-shielded cross sections to be evaluated directly at the actual coupled state of the system, thereby establishing a foundation for high-fidelity, fully coupled multiphysics analysis of advanced reactors

Park, H.↗
DOE OSTI2022

OC6 Phase Ia: CFD Simulations of the Free-Decay Motion of the DeepCwind Semisubmersible

Currently, the design of floating offshore wind systems is primarily based on mid-fidelity models with empirical drag forces. The tuning of the model coefficients requires data from either experiments or high-fidelity simulations. As part of the OC6 (Offshore Code Comparison Collaboration, Continued, with Correlation, and unCertainty (OC6) is a project under the International Energy Agency Wind Task 30 framework) project, the present investigation explores the latter option. A verification and validation study of computational fluid dynamics (CFD) models of the DeepCwind semisubmersible undergoing free-decay motion is performed. Several institutions provided CFD results for validation against the OC6 experimental campaign. The objective is to evaluate whether the CFD setups of the participants can provide valid estimates of the hydrodynamic damping coefficients needed by mid-fidelity models. The linear and quadratic damping coefficients and the equivalent damping ratio are chosen as metrics for validation. Large numerical uncertainties are estimated for the linear and quadratic damping coefficients; however, the equivalent damping ratios are more consistently predicted with lower uncertainty. Some difference is observed between the experimental and CFD surge-decay motion, which is caused by mechanical damping not considered in the simulations that likely originated from the mooring setup, including a Coulomb-friction-type force. Overall, the simulations and the experiment show reasonable agreement, thus demonstrating the feasibility of using CFD simulations to tune mid-fidelity models.

17 WIND ENERGY↗
DOE OSTI2023

A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts

This article proposes a generalizable, data-driven framework for qualifying laser powder bed fusion additively manufactured parts using part-specific in situ data, including powder bed imaging, machine health sensors, and laser scan paths. To achieve part qualification without relying solely on statistical processes or feedstock control, a sequence of machine learning models was trained on 6299 tensile specimens to locally predict the tensile properties of stainless-steel parts based on fused multi-modal in situ sensor data and a priori information. A cyberphysical infrastructure enabled the robust spatial tracking of individual specimens, and computer vision techniques registered the ground truth tensile measurements to the in situ data. The co-registered 230 GB dataset used in this work has been publicly released and is available as a set of HDF5 files. The extensive training data requirements and wide range of size scales were addressed by combining deep learning, machine learning, and feature engineering algorithms in a relay. The trained models demonstrated a 61% error reduction in ultimate tensile strength predictions relative to estimates made without any in situ information. Lessons learned and potential improvements to the sensors and mechanical testing procedure are discussed.

36 MATERIALS SCIENCE↗