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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The optimal beam-loading in two-bunch nonlinear plasma wakefield accelerators

Abstract Due to the highly nonlinear nature of the beam-loading, it is currently not possible to analytically determine the beam parameters needed in a two-bunch plasma wakefield accelerator for maintaining a low energy spread. Therefore in this paper, by using the Broyden–Fletcher–Goldfarb–Shanno algorithm for the parameter scanning with the code QuickPIC and the polynomial regression together with k -fold cross-validation method, we obtain two fitting formulas for calculating the parameters of tri-Gaussian electron beams when minimizing the energy spread based on the beam-loading effect in a nonlinear plasma wakefield accelerator. One formula allows the optimization of the normalized charge per unit length of a trailing beam to achieve the minimal energy spread, i.e. the optimal beam-loading. The other one directly gives the transformer ratio when the trailing beam achieves the optimal beam-loading. A simple scaling law for charges of drive beams and trailing beams is obtained from the fitting formula, which indicates that the optimal beam-loading is always achieved for a given charge ratio of the two beams when the length and separation of two beams and the plasma density are fixed. The formulas can also help obtain the optimal plasma densities for the maximum accelerated charge and the maximum acceleration efficiency under the optimal beam-loading respectively. These two fitting formulas will significantly enhance the efficiency for designing and optimizing a two-bunch plasma wakefield acceleration stage.

Physics↗
DOE OSTI2022

Modeling and experimental validation of dynamical effects in Bragg coherent x-ray diffractive imaging of finite crystals

Bragg coherent diffractive imaging (BCDI) is a noninvasive microscopy technique that can visualize the shape and internal lattice deviations of crystals with nanoscale spatial resolution and picometer deformation sensitivity. Its strain imaging capability relies on Fourier transform–based iterative phase retrieval algorithms, which are mostly developed under the kinematical approximation. Such approximation prohibits the application of BCDI on larger crystals, which are commonly seen in most emerging functional materials. Understanding the dynamical effect in BCDI, as well as developing a validated method for modeling BCDI at the dynamical diffraction limit, is crucial for applying BCDI to hierarchical systems that contain micron-sized crystals and grains. Thus we report a comparative study on the impact of dynamical diffraction effects by comparing the reconstruction results from two measurements of the same crystal. Forward simulation is implemented to show subtle changes of interference fringes in the diffraction pattern due to the dynamical diffraction, and is compared directly with the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

PET Imaging of Leg Arteries for Determining the Input Function in PET/MRI Brain Studies Using a Compact, MRI-Compatible PET System

In this work, we used a compact, high-resolution, and magnetic resonance imaging (MRI)-compatible positron emission tomography (PET) camera (VersaPET) to assess the feasibility of measuring the image-derived input function (IDIF) from arteries in the leg with the ultimate goal of enabling fully quantitative PET brain imaging without blood sampling. We used this approach in five 18 F-FDG PET/MRI brain studies in which the input function was also acquired using the gold standard of serial arterial blood sampling. After accounting for partial volume, dispersion, and calibration effects, we compared the metabolic rates of glucose (MRglu) quantified from VersaPET IDIFs in 80 brain regions to those using the gold standard and achieved a bias and variability of <5% which is within the range of reported test-retest values for this type of study. We also achieved a strong linear relationship (R 2 >0.97) against the gold standard across regions. The results of this preliminary study are promising and support further studies to optimize methods, validate in a larger cohort, and extend to the modeling of other radiotracers.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Scramble

The purpose of Scramble is to provide a cross validation method to ensure machine learning model accuracy in cases where model classes have heterogeneous N values.

Elliott, ShilohN↗
DOE OSTI2022

Hyper-fidelity depletion coupled with discrete pebble motion in pebble bed reactors

Pebble bed reactors have raised new interest during the past decade due to their attractive characteristics. Therefore, accurate simulations must be performed to better understand these systems and ensure optimal and safe designs. Most current methods use lower fidelity approaches with representative unit-cells or macro-zones with uniform fluxes, which have accuracy and flexibility limitations. A novel hyper-fidelity method for pebble bed reactors depletion is presented and internally couples Serpent 2 and a pseudo-motion routine. Pseudo-motion is applied handling vertical shifts of compositions in a static pebble bed, random reinsertion of used pebbles, insertion of fresh pebbles and used pebbles discarding. Associated with individual depletion to correctly determine the flux spectrum and composition in each pebble, this hyper-fidelity approach paves the way towards more accurate depletion calculation in pebble bed reactors. Using this method, a demonstration is completed on a small-scale reactor. In this application, the core reaches equilibrium, and the following data is extracted: core-wise parameters evolution, pebble-wise spatial and statistical distribution. Discarded pebbles are analyzed, and relevant information is shown. This work proves the feasibility of hyper fidelity depletion with Serpent 2, and the range of use for this method: reactor design and analysis for equilibrium and slow transients, lower fidelity methods validation and feeding fuel performance, thermal-hydraulics, or waste management models. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

A Projected Network Model of Online Disinformation Cascades

Within the past half-decade, it has become overwhelmingly clear that suppressing the spread of deliberate false and misleading information is of the utmost importance for protecting democratic institutions. Disinformation has been found to come from both foreign and domestic actors, but the effects from either can be disastrous. From the simple encouragement of unwarranted distrust to conspiracy theories promoting violence, the results of disinformation have put the functionality of American democracy under direct threat. Present scientific challenges posed by this problem include detecting disinformation, quantifying its potential impact, and preventing its amplification. We present a model on which we can experiment with possible strategies toward the third challenge: the prevention of amplification. This is a social contagion network model, which is decomposed into layers to represent physical, ''offline'', interactions as well as virtual interactions on a social media platform. Along with the topological modifications to the standard contagion model, we use state-transition rules designed specifically for disinformation, and distinguish between contagious and non-contagious infected nodes. We use this framework to explore the effect of grassroots social movements on the size of disinformation cascades by simulating these cascades in scenarios where a proportion of the agents remove themselves from the social platform. We also test the efficacy of strategies that could be implemented at the administrative level by the online platform to minimize such spread. These top-down strategies include banning agents who disseminate false information, or providing corrective information to individuals exposed to false information to decrease their probability of believing it. We find an abrupt transition to smaller cascades when a critical number of random agents are removed from the platform, as well as steady decreases in the size of cascades with increasingly more convincing corrective information. Finally, we compare simulated cascades on this framework with real cascades of disinformation recorded on Whatsapp surrounding the 2019 Indian election. We find a set of hyperparameter values that produces a distribution of cascades matching the scaling exponent of the distribution of actual cascades recorded in the dataset. We acknowledge the available future directions for improving the performance of the framework and validation methods, as well as ways to extend the model to capture additional features of social contagion.

42 ENGINEERING↗
DOE OSTI2021

FY21 Status report on the CMVB and CNWG International Collaborations

The ART-GCR Methods area includes an international collaboration work package that covers the tasks defined for the Computational Methods Validation and Benchmark (CMVB)and Civil Nuclear Energy Research and Development Working Group (CNWG) projects. This report summarizes the status of the FY21 tasks and planned FY22 DOE contributions. The CMVB Project Arrangement (PA) is not yet formally approved by all signatories, and no work has therefore been performed in FY21 at INL related to this activity. The CNWG activities inFY21 consisted of the simulation of the High Temperature Test Reactor (HTTR) Loss Of Forced Cooling (LOFC) experimental with the Idaho National Laboratory (INL) codes Griffin, BISON and RELAP-7 based on the Multiphysics Object-Oriented Simulation Environment (MOOSE).It was found that the multiphysics coupled suite is capable of simulating all the important phenomena occurring during the Depressurized Loss of Forced Cooling (DLOFC) experiments showing promising agreement with the measurements given the number of uncertainties and approximations introduced into the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Evaluation and Validation of the n+ 63,65 Cu Cross Sections [Slides]

This presentation discusses the objective of the research which is to update n+ 63,65 Cu cross section evaluations with recently measured data to resolve discrepancies in benchmark performance. It also discusses the models used which are the R -matrix analysis and the analysis of angular distribution coefficients. Additionally, the validation methods that were used are discussed, including the Rez shielding benchmark and the ICSBEP criticality benchmarks. In conclusion, he n+ 63,65 Cu cross sections have been updated via R-matrix analysis up to 100 keV. An increased average capture cross section and the adoption of experimentally based Legendre coefficients lead to improved performance in reactivity benchmarks. In the fast region, the adoption of the JENDL-4.0 cross sections above 4.0 MeV improves the performance in shielding benchmarks. Ultimately, the n 63,65 Cu ENDF files will be submitted to ENDF/B-VIII.1.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Laser Driven Hydrothermal Processing (LDHP) for Rapid Dissolution of Glassy Nuclear Debris

Discovered in 2009 on the SLAB laser system at LLNL, Laser-Driven Hydrothermal Processing (LDHP) both spalls and transiently dissolves a wetted surface (e.g., rock, concrete, paint) when that surface is struck by a laser beam pulse under specific conditions. Previous projects have explored the application of LDHP to expediting sample dissolution for post-detonation nuclear forensics. Early results were very promising, indicating that this method could decrease material dissolution time by a factor of 10 or more. However, the large and complicated lasers previously used are impractical for this application. Under the R^3 venture we aimed to benchmark the LDHP capabilities of turn-key commercial off-the-shelf (COTS) lasers, and to establish how this process could be integrated into an analytical workflow for nuclear forensic analysis. We demonstrated that geological rock standards could be quickly processed into fine powder by LDHP followed by complete acid digestion in 15 minutes, without elemental fractionation that would skew analytical results. We determined that the COTS laser can be used for LDHP that could potentially reduce dissolution time for solid nuclear debris samples in post detonation nuclear forensics. One downside to this approach, however, is that the laser interactions are different with every material, so extensive method validation would be required for all likely material compositions. The LDHP processing rates of several materials were tested and determined to be favorable in the beginning with significant slowdown due to particulate scattering. This could be mitigated either by stopping and centrifuging the sample at specific intervals, or through design of a continuous solvent flow through mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
DOE OSTI2024

Demonstration and Validation of a Virtual Energy Audit Tool for DoD Buildings

Electricity consumption has been in the spotlight as part of the battle for sustainability resulting in legislative measures to try and reduce the amount of energy used. EISA 432 and the Energy Act of 2020 are two examples that require federal facilities to investigate buildings and find saving opportunities through energy audits. EDIFES solves this problem by providing fully virtual audits. Only five inputs are needed (15-minute interval electricity consumption, location, square footage, number of stories, and building end use) to produce complete energy audits. The virtual audit is automated, making them inexpensive and the small number of inputs allows a large number of buildings to be entered quickly. During this project, EDIFES performed energy audits on hundreds of buildings to ensure proper functionality and workflow. Over 250 DoD buildings received energy audits that then had their results posted to an interactive dashboard with portfolio rankings. Several validation methods were employed. All confirmed that EDIFES's methods worked as expected and with a high degree of accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Whole genome sequencing of Mycobacterium bovis directly from clinical tissue samples without culture

Advancement in next generation sequencing offers the possibility of routine use of whole genome sequencing (WGS) for Mycobacterium bovis (M. bovis) genomes in clinical reference laboratories. To date, the M. bovis genome could only be sequenced if the mycobacteria were cultured from tissue. This requirement for culture has been due to the overwhelmingly large amount of host DNA present when DNA is prepared directly from a granuloma. To overcome this formidable hurdle, we evaluated the usefulness of an RNA-based targeted enrichment method to sequence M. bovis DNA directly from tissue samples without culture. Initial spiking experiments for method development were established by spiking DNA extracted from tissue samples with serially diluted M. bovis BCG DNA at the following concentration range: 0.1 ng/μl to 0.1 pg/μl (10 –1 to 10 –4 ). Library preparation, hybridization and enrichment was performed using SureSelect custom capture library RNA baits and the SureSelect XT HS2 target enrichment system for Illumina paired-end sequencing. The method validation was then assessed using direct WGS of M. bovis DNA extracted from tissue samples from naturally (n = 6) and experimentally (n = 6) infected animals with variable Ct values. Direct WGS of spiked DNA samples achieved 99.1% mean genome coverage (mean depth of coverage: 108×) and 98.8% mean genome coverage (mean depth of coverage: 26.4×) for tissue samples spiked with BCG DNA at 10 –1 (mean Ct value: 20.3) and 10 –2 (mean Ct value: 23.4), respectively. The M. bovis genome from the experimentally and naturally infected tissue samples was successfully sequenced with a mean genome coverage of 99.56% and depth of genome coverage ranging from 9.2× to 72.1×. The spoligoyping and M. bovis group assignment derived from sequencing DNA directly from the infected tissue samples matched that of the cultured isolates from the same sample. Our results show that direct sequencing of M. bovis DNA from tissue samples has the potential to provide accurate sequencing of M. bovis genomes significantly faster than WGS from cultures in research and diagnostic settings.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multi-frequency General Relativistic Radiation-hydrodynamics with M 1 Closure

We report on recent upgrades to our general relativistic radiation-magnetohydrodynamics code, Cosmos++ , which expands the two-moment, M 1 , radiation treatment from gray to multi-frequency transport, including Doppler and gravitational frequency shifts. The solver accommodates either photon (Bose–Einstein) or neutrino (Fermi–Dirac) statistical distribution functions with absorption, emission, and elastic scattering processes. An implicit scheme is implemented to simultaneously solve the primitive inversion problem together with the radiation–matter coupling source terms, providing stability over a broad range of opacities and optical depths where the interaction terms can be stiff. We discuss our formulations and numerical methods, and validate our methods against a wide variety of test problems spanning optically thin to thick regimes in flat, weakly curved, and strongly curved spacetimes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

Aubourg, Eric [APC, Paris] (ORCID:000000025592023X↗
DOE OSTI2022

Initial ASME code rule analysis on Simple and Full assessment

ASME & ASTM codes present simple and full assessment methodologies to qualify nuclear grade graphite components. This report explains the theory behind the statistical portion of the codes and describes the issues discussed in a 2020 workshop in the simple assessment, as well as the full assessment. The methodology for the full assessment was developed by Hindley []. He used a validation methodology to match the experimental average failure load of test specimens from several geometries to the calculated 50% POF load to tune the grouping criteria parameters based on an RMSE penalty function. The grouping criteria consists of a minimum volume to satisfy the weakest link theory of the Weibull distribution and a minimum stress range parameter. Hindley’s work found a minimum link volume of 10 times the grain size and a stress range parameter of 7% [satisfy the validation requirements. Several studies found that the link volume of 10 times the grain size was not satisfactory for the volume grouping criteria for graphite grades with fine grains. ASME 2021 code adopted a new volume grouping criteria based on fracture toughness for calculation of the process zone volume. However, errors were found in the ASME 2021 code process zone volume equation and the question is now open as to what volume grouping criteria is satisfactory. This report presents results from sensitivity studies that were done to evaluate the volume grouping criteria effect on the full assessment POF. This report also presents results from sensitivity studies on other aspects of the code that affect the POF, the mesh size and the choice of the Weibull threshold parameter. All three sensitivity studies: the volume grouping criteria, the mesh size, and the threshold parameter choice are found to affect the component qualification decision for components of structural reliability class 1 (SRC-1). The sensitivity analysis results are presented in the body of the report for NBG-18, which is the same grade of graphite as Hindley used in his thesis. Results from NBG-17, IG-110, 2114, and PCEA are presented in the Appendix. For NBG-18, it was found that increasing the threshold increases the POF, finer meshes result in higher POFs, and that smaller link volume requirements lead to higher POFs (which is inconsistent with Hindley’s findings). This report proposes a new validation study similar to Hindley’s []. The purpose of the new validation study is to tune the threshold, mesh size and grouping criteria based on results from multiple grades of graphite, including finer grain graphites T220 (1-3 microns) and NG-CT-50 (5 microns). The test specimens will be broken at 3 labs, such that we can measure between lab measurement variability, with at least 5 test specimens per lab such that the within lab uncertainty can also be measured. Hindley’s validation method tried matching the average experimental load with the median. The future study will attempt to match failures at lower percentiles, which would be closer to the SRC POF limit. We are currently looking into what geometries make sense and the best method to measure multi-axial stress states. These design decisions are still being set.

36 MATERIALS SCIENCE↗
DOE OSTI2024

NDMAS Portal Updates

Overview of current ART-GCR Data, including fuel fabrication, irradiation monitoring, fuel and graphite, post-irradiation examination, graphite characterization, high temperature metals mechanical tests, methods validation data (including: HTTR, NSTF, and HTTF), addition of AGR fuel data, other GCR and related data, updated high temperature metals, ongoing and upcoming work, users guide, and the link to those interested in access to NDMAS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Challenges and Opportunities for HVAC + Phase Change Material Thermal Energy Storage in Buildings

Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties that diverge from manufacturer claims and evolve with cycling, and high integration and deployment costs with off-the-shelf products. These studies underscore the need for factory built, integrated systems that arrive as prepackaged modules with proven controls, reducing design and installation effort and delivering predictable performance across projects. The paper outlines steps to enable viable and scalable PCM TES HVAC and DHW systems, including 1) validated methods that can be used to characterize PCM properties and TES system performance, 2) supervisory controls that optimize charge/discharge scheduling, and 3) factory integrated packaging that eliminates bespoke field engineering.

Dutton, Spencer↗