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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Recommended Nuclear Structure and Decay Data for A=206 Isobars

Here, evaluated nuclear structure and decay data for all nuclei with mass number A=206 ( 206 Pt, 206 Au, 206 Hg, 206 Tl, 206 Pb, 206 Bi, 206 Po, 206 At, 206 Rn, 206 Fr, 206 Ra and 206 Ac), are presented. All available experimental data are compiled and evaluated, and best values for level and γ-ray energies, quantum numbers, lifetimes, γ-ray intensities and transition probabilities, as well as other nuclear properties, are recommended. Inconsistencies and discrepancies that exist in the literature are discussed. A number of computer codes (https://www-nds.iaea.org/public/ensdf_pgm/) developed by members of the NSDD network were used during the evaluation process. This work supersedes the earlier evaluation by F.G. Kondev (2008Ko21), published in Nuclear Data Sheets 109, 1527 (2008).

Kondev, F. G. [Argonne National Laboratory (ANL), ↗
DOE OSTI2022

Reduction of transport due to magnetic shear in gyrokinetic simulations of the scrape-off layer

We report the effect of varying magnetic shear on scrape-off layer turbulence and profiles is studied via electromagnetic gyrokinetic simulations of a helical scrape-off layer model. We develop a model helical geometry with magnetic shear and a corresponding field-aligned coordinate system, which is used for simulations with the Gkeyll code. We find that perpendicular transport is reduced in cases with stronger shear, resulting in higher peak particle and heat fluxes to the endplates. Electromagnetic effects slightly increase transport in strong shear cases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

X-ray-line coincidence photopumping in a potassium-chlorine mixed plasma

Exploiting the multiple long pulse capability and suite of x-ray diagnostics of the Orion laser, we have set out to explore line coincidence photopuming—the enhancement in population of an atomic level brought on by resonant absorption of x rays from a different emitting ion. Unlike previous work, the two ions are in the same plasma and so the experiment is an x-ray analog of the well-known Bowen resonance fluorescence mechanism that operates in astrophysical situations in the optical region. Herein, our measurements have shown enhanced fluorescence in a chlorine plasma, attributable to line coincident photopumping from co-mixed potassium ions. To detect this relatively low signal-to-noise phenomenon, the data from multiple shots are combined, and the statistical method of bootstrapping is used to assign a confidence value to the measured enhancement, resulting in an estimate of the enhancement of 39 ± 18 16 % compared to the null case, where no pumping occurs. The experimental results have been compared to coupled radiation-transport and radiation hydrodynamics simulations using the CRETIN code together with the NYM radiation hydrodynamics model and agreement has been found, with the simulations also predicting modest enhancement.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

The 2021 Annual CSEWG Meeting at Nuclear Data Week(s)

From November 15-19, 2021, CSEWG held its annual meeting during Brookhaven National Laboratory’s Nuclear Data Week(s)1. The combined event was held via zoom (due to COVID travel restrictions) and there were 175 registered attendees. This was CSEWG’s 3rd fully virtual meeting and, by all accounts, it was a success. The timetable and talks are available at https://indico.bnl.gov/event/13121/overview for registered participants. This meeting began with the welcoming of the new ENDF Library Manager, Gustavo Nobre, the announcement that ENDF/B-VIII.1’s release will be delayed until February 2024 due to COVID induced delays, and the adoption of a draft Code of Conduct. This last point is notable since CSEWG is known for its lively physics and engineering discussions. However, as professionals, we must endeavor to keep our discussions civil, collegial, and inclusive.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo: Preprint

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. Using GHEDesigner, a lookup table was created to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on agent energy bills. This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of different costing and pricing future scenarios. While the code is still under development and nationwide simulations are ongoing, initial results for two states are provided. Future work includes expanding the module to consider mixed residential and commercial districts and considering multiple costing scenarios.

ambient temperature loop↗
DOE OSTI2022

Cross-beam energy transfer in direct-drive ICF. I. Nonlinear and kinetic effects

Results are presented from a series of simulations examining the susceptibility of the cross-beam energy transfer (CBET) instability to nonlinear processes in the context of direct-drive inertial confinement fusion experiments on the OMEGA laser facility. These form the basis for the second paper of this series [A. G. Seaton, L. Yin, R. Follett, B. J. Albright, and A. Le, “Cross-beam energy transfer in direct-drive ICF. II. Theory and simulation of mitigation through increased laser bandwidth,” Phys. Plasmas 29, 042707 (2022)], where we examine the efficacy of increases in laser bandwidth at suppressing CBET. We choose laser and plasma conditions for the simulations that are favorable to CBET and promote nonlinearity. Through a comparison of outputs from the particle-in-cell code vector particle in cell (VPIC) and the linearized fluid code laser-plasma simulation environment (LPSE), a series of nonlinear effects have been identified in the kinetic simulations that include particle trapping, the two-ion wave decay, and ion-acoustic wave self-focusing. These effects produce time-dependent energy transfer, in contrast to the linearized fluid simulations in which a steady state is reached after an initial transient. Ion trapping is shown to allow for increased energy transfer relative to fluid simulations, with the remaining nonlinear processes acting to reduce the energy transfer. Nonlinear dynamics is contrasted for low- and high-intensity beams as well as between speckled and planar beams. For the parameters under consideration, beam profile has a significant effect on nonlinear dynamics, though the greatest sensitivity is to beam intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗
DOE OSTI2025

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Results of the KRUSTY Warm Critical Experiments

The Kilowatt Reactor Using Stirling TechnologY (KRUSTY) was a prototypic nuclear-powered test of a 5-kW(thermal) Kilopower space reactor. This paper presents results from the KRUSTY warm critical experiments, which were completed prior to the final system test. The first set of criticals comprised cold or zero-power criticals; i.e., the core was not heated by fission power. These were followed by three warm criticals, where fission power heated the core to 200°C, 300°C, and 450°C, respectively. These criticals provided the data, confidence, and regulatory framework that were needed to proceed with the KRUSTY nuclear system test. The criticals also provided valuable data for the benchmarking of codes applicable to all nuclear systems. Finally, a comparison of KRUSTY results to pretest predictions is provided, and overall, the models matched the experimental results very closely.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Millimeter-wave beam scattering and induced broadening by plasma turbulence in the TCV tokamak

The scattering of millimeter-wave beams from electron density fluctuations and the associated beam broadening are experimentally demonstrated. Using a dedicated setup, instantaneous deflection and (de-)focusing of the beam due to density blobs on the beam path are shown to agree with full-wave simulations. The detected time-averaged wave power transmitted through the turbulent plasma is reproduced by the radiative-transfer model implemented in the WKBeam code, which predicts a ~50% turbulence-induced broadening of the beam cross-section. Finally, the role of core turbulence for the considered geometry is highlighted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations. At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aero-elastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation.

17 WIND ENERGY↗
DOE OSTI2026

Human RNome Project draft human RNome sequence of GM12878, B-cell line, obtained by mass-spectrometry sequencing, long-read sequencing and short-read sequencing.

Here we report the first draft of the human RNome sequence, a reference map of RNA chemical modifications in a human B-cell line. RNA carries a diverse repertoire of chemical modifications that regulate gene expression, cellular function, and responses to physiological and pathological cues. Yet, unlike the genome, no reference map of RNA modifications is available for any human cell. To generate this resource, the Human RNome Project Consortium analyzed a shared RNA preparation from the well-characterized GM12878 B-cell line using short-read sequencing, long-read direct RNA sequencing, and mass spectrometry, generating more than 7.1 billion sequencing reads spanning approximately 1.2 trillion nucleotides. The resulting maps of the human RNome reveal that RNA modifications are organized according to function, transcript architecture, and cellular identity. Modifications concentrate at functional centers of ribosomal and transfer RNAs, follow the canonical topology of N6-methyladenosine in coding transcripts, and form coordinated hotspots in immune regulatory genes. This first reference human RNome provides a foundation for understanding how RNA chemistry shapes cellular identity, human disease, and the development of RNA-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Opcode counting for performance measurement

Methods, systems and computer program products are disclosed for measuring a performance of a program running on a processing unit of a processing system. In one embodiment, the method comprises informing a logic unit of each instruction in the program that is executed by the processing unit, assigning a weight to each instruction, assigning the instructions to a plurality of groups, and analyzing the plurality of groups to measure one or more metrics. In one embodiment, each instruction includes an operating code portion, and the assigning includes assigning the instructions to the groups based on the operating code portions of the instructions. In an embodiment, each type of instruction is assigned to a respective one of the plurality of groups. These groups may be combined into a plurality of sets of the groups.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Acceleration of the particle-in-cell code Osiris with graphics processing units

Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ~14 times faster and ~7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Recent progress in microscale modeling of RF sheaths

The microscale properties of RF sheaths in the ion cyclotron range of frequencies (ICRF) are investigated by means of analytical theory, nonlinear fluid and particle-in-cell (PIC) code modeling. Previous work that parametrized RF sheath properties, specifically the RF sheath impedance and the rectified (DC) sheath potential, is generalized to include the effect of net DC current flow through the sheath. Analytical results are presented in the low frequency limit where the displacement current is negligible, and tested against results from a fluid numerical model. Here, it is shown that when the sheath draws DC electron current, the voltage rectification is reduced from the zero current case, and the electron admittance is increased. In separate but related work on the microscale model, selected cases have been simulated with PIC codes to validate, further illuminate and extend fluid model results and their parametrizations. Quantitative agreement in trends for voltage rectification and sheath admittance vs. RF driving voltage is found.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2022

Development of Integrated Thermal Fluids Modeling Capability for MSRs

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad class of light-water and advanced reactor concepts. The research and development approach under thermal fluids technical area synergistically combines three length and time scales in a hierarchal multi-scale approach. To demonstrate the feasibility and capabilities of a multi-scale thermal fluids capability using these codes, a key joint effort has been pursued to develop an integrated system-and engineering-scale thermal fluids analysis capability with the MOOSE-based codes, through integration of SAM and Pronghorn, both based on the MOOSE framework. This report summarizes the progress in developing an integrated system- and engineering-scale thermal fluids analysis capability based on SAM and Pronghorn for molten salt reactors (MSRs), which gained significant interest in recently years. Two coupling approaches were studied, i.e. separate domain or domain-segregated coupling approach and the domain-overlapping approach. A series of coupled multi-physics models have been developed for a common reference molten salt fast reactor (MSFR) concept, ranging from standalone SAM system model to integrated SAM-Pronghorn-Griffin models. Both the steady state and the transient simulations are performed to the state-of-the-art simulation capabilities of NEAMS software suite in MSFR system applications. This report also covers further development and testing of the gas transport model in SAM for MSR modeling support. The presence of noncondensable gas in MSR systems would have strong impacts on fission gas removal and transport of noble metals throughout the system. Fission products removed through the off-gas system can also impact reactivity and can act as an additional point of heat removal. To ensure that the gas transport model is adequately tested, the supported modeling capabilities and features of SAM were identified, and a suite of tests were developed to test the model for each identified feature. Validation and UQ testing were also performed for the model and demonstrated that the buoyancy term, which was originally developed using non-salt/helium gas experimental data, can capture the experimental gas bubble velocity and diameter to within experimental and code uncertainty. An existing MSRE model was also modified in this work to include the gas transport model and to demonstrate the gas model behavior for realistic conditions of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Nuclear excitation functions for medical isotope production: Targeted radionuclide therapy via nat IR$(d, x)$ 193m Pt

193m Pt is an Auger emitting radionuclide which may have therapeutic potential, particularly when labeled to the chemotherapeutic drug cisplatin. One challenge to broader explorations of its clinical potential is the need for production routes with high specific activity. As part of a larger campaign to address gaps in reaction data for emerging medical radionuclides, this work seeks to characterize the nat Ir(d,x) reactions as a potential production pathway for 193m Pt. A stacked target irradiation, consisting of natural iridium, iron, nickel, and copper foils, was performed using a 33 MeV deuteron beam at the Lawrence Berkeley National Laboratory 88-Inch Cyclotron. This measurement, along with previous experimental data, suggests an energy window between 11 to 18 MeV to maximize the production and radiopurity of 193m Pt. This experiment has yielded cross sections for 43 channels of deuteron-induced reactions from threshold to 30 MeV, including the first experimental results of nat Ir(d,x) 188m1+g,190m1+g Ir (cumulative), nat Ni(d,x) 56,57,58 m,58g Co (independent), nat Cu(d,x) 61 Co (cumulative) and nat Fe(d,x) 53 Fe, 48 V (cumulative). The results were compared with literature data, the TENDL-2023 database, and default theoretical calculations from the TALYS-2.04, CoH-3.6.0, EMPIRE 3.2.3, and ALICE-2020 reaction modeling codes. Here, this work presents another example of the lack of predictive capabilities for this set of modern nuclear-reaction modeling codes, and highlights the unsatisfactory modeling of experimental cross sections. Experimental data are important to improve the codes in general, and new experimental results can be used to improve the models. Finally, this measurement has revealed the need for an updated evaluation of the nat Cu(d,x) 63 Zn deuteron monitor reaction.

193mPt↗