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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design of Experiments for Dynamic Test Runs in Solvent-Based CO 2 Capture Pilot Plants

Test runs in the pilot plants consume significant resources, and therefore, the learning from test runs should be maximized. Test runs conducted in the pilot plants are often steady state. It takes several hours for reaching steady-state in the pilot plants, and thus, the duration of the test runs needs to be long even for collecting few steady-state data points. On the other hand, a large number of measurements can be collected through dynamic test runs in a short span of time. This paper presents a systematic design of dynamic experiments (DoDEs) for identifiability of model parameters, which is achieved by persistently exciting the inputs signals. A pseudorandom binary sequence (PRBS) is designed as the input signal for DoDE due to its efficiency in obtaining sufficient spectral content. However, due to the long sequence size of the PRBS signal, a Schroeder-phase input signal, which is a multisine signal, is also designed. Tests for both types of signals are run in the Pilot Solvent Test Unit (PSTU) at the National Carbon Capture Center in Wilsonville, Alabama. The transient data are used to solve dynamic data reconciliation and parameter estimation problem. The estimated parameters are found to be not only superior to those estimated from using data collected from hundreds of steady-state test runs in a nonreactive (air–water) system, but the parameters could be estimated by using the dynamic data collected for about 24 h from the pilot plant for the MEA-H 2 O–CO 2 system.

CO2 capture↗
DOE OSTI2025

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗
DOE OSTI2025

Assessing High Burnup U-19Pu-10Zr Fuel Performance against Historical and Modeled Behavior

Advancing the deployment of sodium-cooled fast reactors (SFRs) requires thorough testing of metallic fuel pins under accident conditions to establish safe operational limits of high burnup fuel. To conduct transient testing, a comprehensive understanding of steady-state fuel behavior obtained through both experimental characterization and accurate predictive capabilities is needed. This study comparatively assesses the steady-state irradiation performance of two high burnup U-19Pu-10Zr fuel pins, DP-36 and DP-40, irradiated under prototypic fast reactor conditions in preparation for planned safety testing at the Transient Reactor Test Facility. Since DP-40 was designated for use in the test and DP-36 serves as its sibling pin, non-destructive, engineering-scale post-irradiation examinations (PIE) were conducted on both pins while destructive examinations were performed exclusively on DP-36. The results were then assessed against historical performance data from similar fuel pins irradiated in the Experimental Breeder Reactor-II. Additionally, the steady-state irradiation of each pin was modeled using the BISON fuel performance code to assess the accuracy of current modeling capabilities in predicting the baseline irradiation behavior. Non-destructive examinations included neutron radiography to measure fuel column elongation, gamma scanning to verify pin integrity and fission product migration, and profilometry to assess dimensional changes. Benchmarking against existing PIE data revealed consistent patterns in axial fuel column growth and cladding diametral strain, though both pins exhibited longer low-density “fluff” structures, which can have implications for core reactivity and source term calculations. Destructive examinations on DP-36 included fission gas release analysis and sectioning for optical microscopy, which showed more complex constituent redistribution patterns than the traditionally accepted 3-ring model. The axial evolution of fractional areas and porosities of each of the redistributed zones were quantified and presented. Modeling comparisons showed agreement in fractional fission gas release but consistently overestimated axial and radial swelling and disagreed with measured axial porosity patterns. These conservative overpredictions suggested that the pins would appear closer to failure or operational limits at the start of transient tests, potentially leading to higher strain accumulation during the transient. While conservative estimates provide safety margins, they can negatively impact fuel economics. A review of the swelling models identified areas for improvement in the gaseous swelling, solid swelling, and fuel hot-pressing models when applied to ternary fuel. The results of this study highlight the critical importance of conducting pre-test characterization on both test and sibling pins to accurately capture steady-state fuel behavior, providing a precise baseline for post-test evaluations and essential inputs for transient modeling of the planned experiments. The analysis also revealed significant data gaps that require further investigation to enhance the understanding and prediction of fuel swelling and pore dynamics. Collecting comprehensive data across different irradiation conditions, burnup levels, and fuel compositions are essential for refining existing models and developing mechanistic models for both binary and ternary metallic fuels, ultimately improving the integration of modeling and experimental approaches in accident testing.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Adaptive Dynamic Digital Twin for Test Scenario Generation

Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.

Chen, Hanlin [ORNL] (ORCID:0000000165087715)↗
DOE OSTI2025

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.

Bayesian optimization↗
DOE OSTI2026

Dataset for "A primer on forest structure measurement with lidar for ecologists"

This repository includes data and code accompanying the case study included in the manuscript "A primer on forest structure measurement with lidar for ecologists" (submitted to Ecosphere). We compiled lidar datasets from multiple platforms in a common area to: 1. Demonstrate how differences in sensor characteristics influence density and resolution of lidar data. 2. Provide open-source, co-located datasets for users to further inspect differences in lidar data. 3. Provide example code to perform basic lidar analysis. This case study is meant to allow readers to get hands-on experience with real-world data from different platforms. This case study is not meant to be a rigorous comparison of derived ecological metrics among all sensors; such comparisons can be found throughout other publications referenced throughout the main manuscript. Code includes basic functions in R commonly used to visualize and manipulate lidar data accessible with a normal laptop computer; more sophisticated algorithms for advanced users are also referenced throughout the main manuscript. Terrestrial laser scanning (TLS), mobile laser scanning (MLS), UAS laser scanning (ULS), airborne laser scanning (ALS), and spaceborne laser scanning (SLS) data were collected within the Smithsonian Environmental Research Center (SERC) forest dynamics plot in Maryland, USA. TLS, MLS, and ALS data were collected within 1 month of the 2021 growing season; ULS data were collected in November 2020 (“leaf-off” data) and July 2022 (“leaf-on” data).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Time of Flight Secondary Ion Mass Spectrometry for Characterization of Pt-Coated Porous Transport Layers in PEM Water Electrolyzers

Titanium-based porous transport layers (PTLs) and iridium-based catalyst layers (CLs) are two main components of proton exchange membrane water electrolyzers (PEMWEs). PTLs are typically coated with platinum to minimize interfacial losses and to support long-term operation. Optimizing coatings and the PTL-CL interface requires comprehensive characterization. This study establishes time-of-flight secondary ion mass spectrometry (ToF-SIMS) as a valuable technique for PTL characterization, addressing capabilities and limitations related to PTL morphology. A methodology was developed that uses a Cs + sputter beam for dynamic depth profiling, with data collected in both positive-ion (MCs + ) and negative-ion modes to generate depth profiles, 2D ion maps, and 3D ion reconstructions. ToF-SIMS detected relative differences in platinum-layer thickness between samples; these trends were validated by cross-sectional scanning transmission electron microscope (STEM) measurements and flat-titanium substrate controls. Interfacial oxide layers are identified in both ion modes, with enhanced oxide sensitivity in negative mode. The technique’s high sensitivity enables detection of nanometer-scale coatings and trace impurities within the bulk PTL structure. These results provide a methodological framework for analyzing Pt-coated PTLs, with the potential to extend to other components in PEMWEs and other electrolyzer systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Glovebox Fires Phase 1: Simulations of Open Burner Experiments

Understanding the duration of a fire required to breach a glovebox via glove ports and/or windows within a facility is important in developing mitigation strategies for safety. To facilitate this understanding, both simulation and experiments are utilized. The approach is to first validate the Computation Fluid Dynamics (CFD) code, Fire Dynamics Simulator (FDS), with experimental data collected by New Mexico Tech (NMT) and then perform simulations of full-scale rooms containing gloveboxes to assess numerous scenarios which would otherwise be cost-prohibitive experimentally. This report provides comparison to first-phase experiments involving a fire without a glovebox. A subsequent report will provide comparison to experiments involving a glovebox. The results indicate good agreement with FDS tending to over predict the pre-mixed and diffusion-mode tests by 6% and 10%, respectively.

42 ENGINEERING↗
DOE OSTI2025

Observation of D + → η ′ μ + ν μ and First Experimental Study of D + → η ′ ℓ + ν ℓ Decay Dynamics

Using 20.3 fb − 1 of e + e − collision data collected at the center-of-mass energy 3.773 GeV with the BESIII detector, we report the first observation of the semileptonic decay D + → η ′ μ + ν μ with significance of 8.6 σ including systematic uncertainties, and an improved measurement of D + → η ′ e + ν e . The branching fractions of D + → η ′ μ + ν μ and D + → η ′ e + ν e are determined to be ( 1.92 ± 0.2 8 stat ± 0.0 8 syst ) × 10 − 4 and ( 1.79 ± 0.1 9 stat ± 0.0 7 syst ) × 10 − 4 , respectively. The ratio of the two branching fractions is determined to be R μ / e = 1.07 ± 0.1 9 stat ± 0.0 3 syst , which agrees with the theoretical expectation of lepton flavor universality within the standard model. From an analysis of the D + → η ′ ℓ + ν ℓ decay dynamics, the product of the hadronic form factor f + η ′ ( 0 ) and the Cabibbo-Kobayashi-Maskawa matrix element | V c d | is measured for the first time, giving f + η ′ ( 0 ) | V c d | = ( 5.92 ± 0.5 6 stat ± 0.1 3 syst ) × 10 − 2 . The η − η ′ mixing angle in the quark flavor basis is determined to be ϕ P = ( 39.8 ± 0.8 stat ± 0.3 syst ) ° . Published by the American Physical Society 2025

Ablikim, M.↗
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 OSTI2026

Synoptic NO3 in Slate River Watershed, Colorado (2022)

The synoptic nitrate (NO3) dataset in the Slate River Watershed, Colorado consists of NO3 data collected at 19 locations three times during the summer of 2022. Stream samples were collected in early summer (early July), mid summer (late August), and late summer (late September). The samples include mainstem, tributary, and point source input water samples. These data were collected to evaluate spatiotemporal variability in stream NO3 during the summer, and evaluate anthropogenic controls on stream NO3 dynamics. This data package contains: (1) a csv of all NO3 samples and (2) a csv of locations for each sampling site. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATE↗
DOE OSTI2026

Fast and accurate calculation of EXAFS Debye-Waller factors in U⁢O2 using the dynamical matrix method

Theoretical modeling of bonding dynamics in metal oxides is required for predicting their thermal conductivity, catalytic activity, and mechanical properties. A primary challenge is the scarcity of experimental methods for validating theoretical predictions of these atomic-scale dynamics. This work presents a workflow that uses experimental extended x-ray absorption fine structure (EXAFS) data collected at high temperatures to validate an interatomic force field for uranium dioxide (UO2), an important model material. The validated force field is then used to drive computationally intensive molecular dynamics (MD) simulations and as input for the much faster dynamical matrix Debye-Waller (DMDW) method. The predicted values of the Debye-Waller factors from the DMDW calculations are in good agreement with those obtained from the MD simulations, with residual pair-specific differences attributable to quantum zero-point motion at low temperatures and lattice anharmonicity at high temperatures. We further show that theoretical EXAFS spectra constructed directly from DMDW-derived Debye-Waller factors reproduce the experimental data (at relatively low temperatures) with accuracy comparable to full MD-EXAFS, providing an additional validation of the choice of the potential. This study establishes a validated, rapid computational pathway for modeling bond dynamics, naturally incorporating quantum nuclear\\\\r\\\\nstatistics absent in classical simulations, which are essential for the mechanistic understanding of complex oxide materials.

58 GEOSCIENCES↗
DOE OSTI2025

An Overview of the Molten Salt Thermal Properties Database–Thermophysical, Version 4.0 (MSTDB-TP V.4.0)

A central repository of thermophysical and thermochemical properties of molten salt compositions of relevance to molten salt reactors (MSRs) is vital in supporting the broad community of MSR developers, who are at various stages of developing and deploying their reactor designs. In general, these MSR designs differ significantly from developer to developer (e.g., with respect to the hardness of the neutron spectra, level of fissile loading, target multicomponent temperatures and power levels, and moderating capabilities). Therefore, the fuel and coolant salts being considered vary greatly: they may be chlorides or fluorides, they utilize different actinides at different ratios, and the cations in the melt are selected based on perceived advantages and disadvantages. Considering the general need for thermal properties, and the vastness of the array of potential candidate salt mixtures, the Molten Salt Thermal Properties Database (MSTDB) was initiated in 2018 with the goal of providing thermophysical and thermochemical characterization of key molten salt compounds and mixtures across their temperature and compositional domains. The MSTDB is thus divided into the thermophysical arm (MSTDB-TP) and the thermochemical arm (MSTDB-TC). The MSTDB is an effort funded by the Department of Energy, Office of Nuclear Energy (DOE-NE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, and the MSR Campaign. This report provides an overview of the MSTDB-TP v4.0 in terms of the data contained within, the state of the tools used to access the data, the availability of predictive models that leverage the raw data in the database, the preliminary status of developmental efforts that are currently underway, and an account of future goals for MSTDB-TP. The primary goal for the update from MSTDB-TP v.3.1 to v4.0 was the incorporation of surface tension data into the database; this property is important for thermal hydraulics modeling and species transport in other tools that have been developed under the NEAMS program. A breakdown of the surface tension data that have been added into MSTDB-TP v4.0 is provided herein, and the manner in which the quality of the data has been assessed is also documented. For MSTDB-TP v4.0, newly published thermophysical property data—primarily from collaborative experimental efforts under the MSR Campaign—have been incorporated into the database, and the resulting expansion is documented here. Because of the size to which MSTDB-TP has grown, the raw data format has now been recast into JavaScript Object Notation (JSON) format for easier connection with the MSTDB-TP application programming interface (API). Saline; the pre-existing comma-separated value (CSV) format has been deprecated but is still maintained, accessible, and up to date. As a final effort in packaging the MSTDB-TP v4.0 update, the graphical user interface (GUI) for MSTDB has been updated to allow full accessibility to the density and viscosity predictive models, which are based on Redlich-Kister expansions of MSTDB-TP raw data. Some other major aspects of this report, in terms of preliminary and future work, include: (1) documentation of the formalism and preliminary testing of a kinetic theory model that may act as a predictive model for thermal conductivity; (2) documentation of the candidate predictive models that may be considered in the future for surface tension, making use of the surface tension data now in MSTDB-TP v4.0; (3) a preliminary account of a data collection process that will enable the filling of additional gaps within MSTDB-TP, namely with data which have been collected computationally (e.g., through ab initio molecular dynamics).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Experimental and Computational Characterization of a Modified Sioutas Cascade Impactor for Respirable Radioactive Aerosols

Oak Ridge National Laboratory is collecting and characterizing aerosols released when spent nuclear fuel (SNF) rods are fractured in bending. An aerosol collection system was designed and tested to collect respirable sized (<10 μm aerodynamic diameter [AED]) particulates inside a hot cell facility. The setup is a modified version of the commercially available Sioutas cascade impactor, to which additional stages were added to expand the aerosol collection range from 2.5 to ~15 μm AED. To accommodate the additional stages and specific test conditions, the operating flow rate for aerosol collection was reduced, and testing was conducted by using pressure drop measurements, surrogate dust collection, and particle size characterization. The fluid flow distribution within the cascade and its stages was simulated in STAR-CCM+, and the stage-wise pressure drops obtained using the computational fluid dynamics model were then compared to experimental data. Lagrangian particle simulations were also performed, and stage-wise collection statistics were obtained from the simulation for comparison with the experimental data obtained using SNF-surrogate dust particles. The results provide valuable insights into the stage-wise particle collection characteristics of the modified cascade impactor and can also be used to improve the prediction accuracy of the manufacturer-determined analytical correlations.

aerosol modeling↗
DOE OSTI2025

S-MODE Sonde

These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.

17 WIND ENERGY↗
DOE OSTI2025

S-MODE Saildrone

These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.

17 WIND ENERGY↗
DOE OSTI2025

S-MODE Saildrone

These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.

17 WIND ENERGY↗