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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

Precision Timing in CMS at the HL-LHC: Current Progress on Validation and Production

During the High Luminosity phase of LHC, up to 200 proton-proton collisions per bunch crossing will bring severe challenges for event reconstruction. To mitigate pileup effects, an extended upgrade program of the CMS experiment is expected. Among which, a new timing layer, the MIP Timing Detector (MTD), will be integrated between the tracker and the calorimeters. With a time resolution of 30-60 ps, the MTD will enable 4D vertexing, bringing significant improvements in track-to-vertex association and object identification. The MTD is composed of two subsystems based on different technologies: the Barrel Timing Layer (BTL) consists of LYSO:Ce scintillating crystals readout by SiPMs, and the Endcap Timing Layer (ETL) is made of Low-Gain Avalanche Diodes. The BTL is currently under production, while ETL sensor prototyping and validation are ongoing. Recent system tests have confirmed the performance of the full acquisition chain. This talk will provide an overview of the MTD design, along with the physics motivation, and the current status of BTL construction and ETL development.

Safdari, Murtaza [Fermilab] (ORCID:000000018323731↗
DOE OSTI2026

ARM Radiosondes for SNPP/JPSS Validation Field Campaign Report

This field campaign extension has been a coordinated effort involving the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility, the University of Wisconsin at Madison, and the Joint Polar Satellite System (JPSS) project to validate NOAA Unique Combined Atmospheric Processing System (NUCAPS) temperature and moisture sounding products from the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments on board the NOAA-20 and NOAA-21 satellite platforms. In this arrangement, funding for radiosondes and balloons was provided by the JPSS project to ARM. These radiosondes were launched coincident with NOAA-20 and NOAA-21 satellite overpasses at the ARM field sites at Eastern North Atlantic (ENA), North Slope Alaska (NSA), and Southern Great Plains (SGP). Combined with other ARM data, an assessment of the radiosonde data quality was performed and post-processing corrections applied. The dedicated radiosondes were integrated into the NOAA Products Validation System (NPROVS+), which collocated the radiosondes with satellite products (NOAA, National Aeronautics and Space Administration [NASA], European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], Geostationary Operational Environmental Satellite [GOES], Constellation Observing System for Meteorology, Ionosphere, and Climate [COSMIC]) and numerical weather prediction (NWP) forecasts for use in product assessment and algorithm development. This work is a part of the NOAA-20 and NOAA-21 satellite retrieval validation efforts and provides critical accuracy assessments of the temperature and water vapor soundings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Position-Specific Carbon Isotope Fingerprinting of Fluorinated Organics and Degradation Products

Fluorinated organic compounds are of growing environmental and forensic relevance due to their widespread use in pharmaceuticals, agrochemicals, and consumer products, their environmental persistence, and potential ecological and human health impacts. Elucidating their sources and transformation pathways is therefore a major focus of current research. Stable carbon isotope analysis provides a powerful approach for tracing molecular origins and linking parent compounds to degradation products. Recent isotope measurements have largely relied on mass-spectrometry techniques, which provide only an average isotope ratio across a compound. In this work, we employ a novel nuclear magnetic resonance (NMR) spectroscopy tool to determine position-specific carbon isotope ratios ( 13 C/ 12 C) in organofluorine compounds and their degradation products. This approach enables isotope measurements without combustion or extensive purification and, crucially, resolves ratios at individual carbon positions rather than bulk averages. The resulting intramolecular isotope fingerprints are unique to a molecule’s source. Applied to selected pharmaceuticals and pesticides, these fingerprints allow discrimination of chemically identical compounds. Moreover, we show that the 13 C/ 12 C signature at the fluorinated carbon persists through degradation, demonstrated for lansoprazole and fipronil. The 19 F NMR data produced for the 13 C/ 12 C analyses are also well suited for impurity profiling, providing an additional dimension for fingerprinting fluorinated organics. These findings suggest that position-specific isotope analysis can serve as part of a broader suite of tools for source characterization of organofluorine compounds and their breakdown derivatives, with potential applications in product validation, forensics, and linking these compounds to their breakdown products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quantitative Particle Analysis of Neptunium-237 Oxides: Optimization of MAMA Analysis for Modified Direct Denitration Products

The production of plutonium-238 through irradiation of neptunium-237 ( 237 Np) target materials for the use in radioisotope thermoelectric generators is paramount for continued deep space exploration. This work employs scanning electron microscopy to analyze 237 Np materials coupled with a well-developed image analysis framework (Morphological Analysis for Material Attribution, or MAMA) to determine the degree of micron-scale homogeneity in the materials. This work demonstrated how the quantification of particle characteristics can validate production materials and affirm the qualitative similarities observed in micrographs. The 237 Np oxide particle analysis determined that the materials from five production runs were quantitatively homogenous (significant at α = 0.05) in particle area, circularity, equivalent circular diameter, and ellipse aspect ratio, with two of the sampling dates having statistically significant different means for one of the four characteristics. Furthermore, these metrics not only confirm general homogeneity of the material but also expand the application of MAMA workflows to 237 Np materials, demonstrating the utility of MAMA analysis for a wider breadth of nuclear materials than previously reported. In the open literature, this study is the first time that these microanalytical techniques were applied to 237 Np materials to this degree.

MAMA↗
DOE OSTI2025

Use of Captured CO2 for Production of Sustainable Polyurethane Foams in Automotive Applications

Captured CO2 has been investigated as a feedstock for the production of polyurethane (PU) foams for automotive applications. Previous work has shown successful incorporation of CO2 into polyols via three distinct reaction pathways. These CO2-derived polyols, as well as several commercially available polyols with varying CO2 content, were used to produce PU foams for automotive seating and NVH (noise, vibration, and harshness) applications. Foam formulations were optimized to maximize sustainable content while maintaining manufacturability constraints and performance requirements for each end use application. PU foams were first formulated at lab scale to confirm free rise and molded foam properties, then scaled up to pilot and industrial scales to evaluate production manufacturing feasibility. Finally, CO2-derived foams were used to produce molded components for end use product validation. Life cycle assessment (LCA) was used to quantify the environmental impact of using captured CO2 and bio-renewable content into polyols and PU foams through the metrics of global warming potential and embodied energy. Tradeoffs among environmental impacts, energy usage, manufacturability, and PU foam performance from the incorporation of CO2 and bio-renewable content will be discussed.

Lee, Ellen [Ford Motor Company]↗
DOE OSTI2026

The National Laboratory of the Rockies Strengthens U.S. Critical Minerals Supply Chains

The National Laboratory of the Rockies (NLR) is working to overcome bottlenecks and secure the U.S. critical mineral supply chain - delivering lower-cost, lower-risk pathways from unconventional and secondary feedstocks to validated products. NLR achieves this through cross-sector partnerships to advance U.S. critical minerals across the mining, processing, manufacturing, usage, and end-of-life stages.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Californium-252 production at the High Flux Isotope Reactor - I: Validation study using campaign data

This paper presents a series of 252 Cf production validation and code-to-code comparison studies performed based on data from the production campaigns at the High Flux Isotope Reactor (HFIR). These studies support efforts to convert HFIR from using highly enriched uranium (HEU) fuel to low-enriched uranium (LEU) fuel. HFIR must maintain its world-class performance and missions following this conversion, and because 252 Cf is a vital neutron-emitting radioisotope used for a variety of high-impact applications (e.g., reactor startup, cancer treatment), the ability to efficiently produce 252 Cf must be preserved. In this work, the HFIRCON, Shift, ORIGEN, and TCOMP codes were deployed, and several sets of data libraries were investigated to better understand the calculation codes and the data biases. As-loaded target composition data, as-run irradiation history data, and post-irradiation measurements from recent multi-cycle irradiation campaigns of the HEU core were used to validate and determine methodology biases. Further, the findings demonstrated a good agreement, with results falling within 3 standard deviations of measurements. This paper lays the ground work for the second paper, which evaluates and compares 252 Cf production and safety metrics with the HEU core and a proposed LEU core.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Validation of Weather Forecasting Products

Meteorological modeling plays a pivotal role in operational safety and emergency response at the Savannah River Site (SRS). This study focuses on verifying the Regional Atmospheric Modelling System (RAMS) Version 4.3 through Mean Bias Error (MBE) and Root Mean Square Error (RMSE) analyses of temperature, dew point, and wind speed over a decade. Using observed data from SRS, we assessed RAMS' accuracy, revealing seasonal biases and error trends. Results indicate RAMS' strengths in mild weather conditions but challenges during seasonal extremes and wind speed predictions due to measurement disparities. Future research aims to expand verification to other models and parameters, advocating for enhanced forecasting accuracy crucial for safeguarding personnel and community well-being.

42 ENGINEERING↗
DOE OSTI2024

Validation of Weather Forecasting Products

Weather forecasting is a tool in which the Savannah River Site relies on to complete daily tasks. The importance and integrity of forecasting systems and models is of the utmost importance to safety at SRS. By comparing and contrasting model bias, the meteorologists and employees of the Atmospheric Technologies Group will be equipped with bias data to create more accurate forecasts. Thus, furthering the safety of individuals at SRS.

Gray, Avery↗
DOE OSTI2025

Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP

In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
DOE OSTI2026

Advanced Manufacturing of Cathode Materials for Lithium-ion Batteries

Original objectives (per the Statement of Project Objectives) centered on developing and translating a continuous pilot process for cathode materials production while targeting (i) a 29% manufacturing cost reduction, (ii) an 82% energy consumption reduction for cathode production, and (iii) a doubling of manufacturing productivity. Planned validation included characterization at appropriate analytical facilities and electrochemical performance evaluation progressing from half-cells to pouch-cell formats, with a pathway to kilogram-scale production of finished cathode materials for representative testing. Scope evolution: During execution, the project team identified that the surfactant-enabled chemistry offered high selectivity for lithium precipitation from brine sources. A formal scope revision shifted the final project year from cathode manufacturing development to direct lithium extraction/lithium recovery, while maintaining the overarching intent of cost reduction and process simplification relevant to the battery supply chain.

25 ENERGY STORAGE↗
DOE OSTI2026

SPT-3G D1: Maps of the millimeter-wave sky from 2019 and 2020 observations of the SPT-3G Main field

Maps of the sky in millimeter wavelengths contain rich information on cosmology through anisotropies of the cosmic microwave background (CMB). Creating multifrequency sky maps of anisotropies in the $I$, $Q$, and $U$ Stokes parameters is one of the first steps of CMB cosmology analyses. In this work, we describe the production and validation of a set of sky maps from the South Pole Telescope's third-generation camera, SPT-3G. The maps are from data taken in frequency bands centered at 95, 150, and 220 GHz and taken during the first two years, 2019 and 2020, of the SPT-3G Main survey, which covers $4\%$ of the sky. We applied high-pass filters to time series of individual detectors and binned the filtered time series samples into map pixels. After that, we calibrated and cleaned the maps to reduce known systematic errors. In addition, we searched for other systematic errors through null tests and mitigated a significant systematic error detected therein. The white noise levels of the full-depth maps of the $I$ Stokes parameter are $5.4$, $4.4$, and $16.2$$\mathrm{μK}$-$\mathrm{arcmin}$ in the 95, 150, and 220 GHz bands, respectively, and $8.4$, $6.6$, and $25.8$$\mathrm{μK}$-$\mathrm{arcmin}$ for $Q/U$. These maps are the deepest to date used for measurements of mid-to-high-$\ell$ primary temperature and $E$-mode polarization CMB anisotropies, and reconstructions of the CMB gravitational lensing potential. We make these maps and supporting data products publicly accessible.

Quan, W. [Argonne (main); Chicago U., EFI; Chicago↗
DOE OSTI2024

Evidence for B + → K + ν ν ¯ decays

We search for the rare decay B + → K + ν ν ¯ in a 362 fb − 1 sample of electron-positron collisions at the ϒ ( 4 S ) resonance collected with the Belle II detector at the SuperKEKB collider. We use the inclusive properties of the accompanying B meson in ϒ ( 4 S ) → B B ¯ events to suppress background from other decays of the signal B candidate and light-quark pair production. We validate the measurement with an auxiliary analysis based on a conventional hadronic reconstruction of the accompanying B meson. For background suppression, we exploit distinct signal features using machine learning methods tuned with simulated data. The signal-reconstruction efficiency and background suppression are validated through various control channels. The branching fraction is extracted in a maximum likelihood fit. Our inclusive and hadronic analyses yield consistent results for the B + → K + ν ν ¯ branching fraction of [ 2.7 ± 0.5 ( stat ) ± 0.5 ( syst ) ] × 10 − 5 and [ 1.1 − 0.8 + 0.9 ( stat ) − 0.5 + 0.8 ( syst ) ] × 10 − 5 , respectively. Combining the results, we determine the branching fraction of the decay B + → K + ν ν ¯ to be [ 2.3 ± 0.5 ( stat ) − 0.4 + 0.5 ( syst ) ] × 10 − 5 , providing the first evidence for this decay at 3.5 standard deviations. The combined result is 2.7 standard deviations above the standard model expectation. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Hydrogen Production System Scaling Using a High-Fidelity Simulation-Optimization Framework

Proton exchange membrane (PEM) electrolyzers are widely used for hydrogen production, yet few validated, high-fidelity tools can reliably guide scale-up. Using measured performance from a 50-hour hardware-in-the-loop pilot test, a physics-based, plant-level model of a 1.25 MW PEM electrolyzer and its balance-of-plant (BoP) subsystems is developed and validated. The model couples electrochemistry and thermal/flow submodels and is calibrated against pilot test data via a genetic algorithm (GA) workflow. Validation yields a mean absolute percentage error (APE) of 0.43% for cell voltage and stack power. Two scale-out strategies are then benchmarked under a common 7-day wind-and-photovoltaic (PV) profile: (i) linear duplication of 1.25 MW blocks and (ii) shared-BoP architectures. Sharing BoP between stacks reduces BoP energy by 27% at 10 MW and 34% at 100 MW (vs. linear duplication) and improves system specific energy consumption (SEC) to 52.9 and 52.6 kWh/kg, respectively (from 54.0 kWh/kg with linear duplication). Partial-load studies (25-100% set-point) show that cumulative hydrogen production remains nearly constant down to 50% load because all cases use the same weekly renewable-energy input. Below 50%, the power cap limits how much energy can be used within 168 h, which reduces hydrogen output. The model further indicates that the practical operating optimum lies between 50% and 85% load, where efficiency gains begin to appear without significant loss in hydrogen output. Moreover, the efficiency gains at lower loads are offset by reduced production. The validated framework supports scenario-based engineering trade-off studies for large configurations (10-100 MW) and for operating policies under variable renewables.

08 HYDROGEN↗
DOE OSTI2024

Using Hardware-In-The-Loop Methodology to Develop Test Systems

Hardware in the Loop (HIL) testing methodologies have become widespread in industry. Typically, they focus on developing control algorithms for systems such as autonomous vehicles or aircraft. An oft overlooked aspect of product development is the design and fabrication of a test system for validating that the product meets requirements. Abstractly, a test system differs little from a control system—testers provide signals to the unit, monitor feedback, and base decisions on the results. While the time scales may differ, the functionalities are conceptually similar. Viewed in this light, it becomes natural to extend HIL approaches to tester development. By replacing a physical unit with a proxy model deployed to a real-time or pseudo real-time target, test systems can be developed in parallel with the design and fabrication of a first production unit. This saves considerable time in the life cycle from conceptual design to realized product. This manuscript demonstrates the process flow using a capacitive discharge unit as an exemplar.

42 ENGINEERING↗