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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

First Sagittarius A* Event Horizon Telescope Results. V. Testing Astrophysical Models of the Galactic Center Black Hole

In this paper we provide a first physical interpretation for the Event Horizon Telescope's (EHT) 2017 observations of Sgr A*. Our main approach is to compare resolved EHT data at 230 GHz and unresolved non-EHT observations from radio to X-ray wavelengths to predictions from a library of models based on time-dependent general relativistic magnetohydrodynamics simulations, including aligned, tilted, and stellar-wind-fed simulations; radiative transfer is performed assuming both thermal and nonthermal electron distribution functions. We test the models against 11 constraints drawn from EHT 230 GHz data and observations at 86 GHz, 2.2μm, and in the X-ray. All models fail at least one constraint. Light-curve variability provides a particularly severe constraint, failing nearly all strongly magnetized (magnetically arrested disk (MAD)) models and a large fraction of weakly magnetized models. A number of models fail only the variability constraints. We identify a promising cluster of these models, which are MAD and have inclination i ≤ 30°. They have accretion rate (5.2–9.5) × 10$^{−9}$ M $_{⊙}$ yr$^{−1}$, bolometric luminosity (6.8–9.2) × 10$^{35}$ erg s$^{−1}$, and outflow power (1.3–4.8) × 10$^{38}$ erg s$^{−1}$. We also find that all models with i ≥ 70° fail at least two constraints, as do all models with equal ion and electron temperature; exploratory, nonthermal model sets tend to have higher 2.2μm flux density; and the population of cold electrons is limited by X-ray constraints due to the risk of bremsstrahlung overproduction. Finally, we discuss physical and numerical limitations of the models, highlighting the possible importance of kinetic effects and duration of the simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Coupling laser physics to radiation-hydrodynamics

In order to accurately model implosion hydrodynamics in a radiation-hydrodynamics code, it is essential to include accurate accounting for energy deposition physics. In inertial confinement fusion (ICF), where capsules are driven by lasers or laser-driven x-rays, energy deposition profiles and energy transport have a strong impact on the development and evolution of capsule dynamics and hydrodynamic instabilities. Nevertheless, accurately modeling laser beam propagation in radiation-hydrodynamics codes presents unique challenges associated with disparate resolution requirements, the potential to seed spurious noise in highly unstable systems, and computational expense. We discuss a new method for coupling laser ray-tracing physics to a radiation hydrodynamics code, developed in the process of implementing the Mazinisin laser ray-trace into the xRAGE radiation hydrodynamics code. In contrast to previous approaches, in which laser ray-tracing is performed on the radiation-hydrodynamics mesh, our method involves a mesh generation and evolution strategy that addresses the unique requirements of the laser ray-trace in a separate mesh, enabling performance enhancements and strategies to reduce noise seeded by the discretization of beams into computational rays. In addition, we have employed several methods to ensure that spurious mesh imprinting is minimized. These involved optimizing the laser and radiation-hydrodynamics meshes as well as interpolation between them and requires the use of an exact initialization method for the radiation-hydrodynamics mesh. Furthermore, these techniques have enabled efficient computation of laser-driven implosions and other experiments with minimal introduction of spurious noise.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Study of Helium Irradiation Effect on Al6061 Alloy Fabricated by Additive Friction Stir Deposition

Additive friction stir deposition (AFS-D) is considered a productive method of additive manufacturing (AM) due to its ability to produce dense mechanical parts at a faster deposition rate compared to other AM methods. Al6061 alloy finds extensive application in aerospace and nuclear engineering; nevertheless, exposure to radiation or high-energy particles over time tends to deteriorate their mechanical performance. However, the effect of radiation on the components manufactured using the AFS-D method is still unexamined. In this work, samples from the as-fabricated Al6061 alloy, by AFS-D, and the Al6061 feedstock rod were irradiated with He+ ions to 10 dpa at ambient temperature. The microstructural and mechanical changes induced by irradiation of He+ were examined using a scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), and nanoindentation. This study demonstrates that, at 10 dpa of irradiation damage, the feedstock Al6061 produced a bigger size of He bubbles than the AFS-D Al6061. Nanoindentation analysis revealed that both the feedstock Al6061 and AFS-D Al6061 samples have experienced radiation-induced hardening. These studies provide a valuable understanding of the microstructural and mechanical performance of AFS-D materials in radiation environments, offering essential data for the selection of materials and processing methods for potential application in aerospace and nuclear engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gamma radiation sterilization of N95 respirators leads to decreased respirator performance

In response to personal protective equipment (PPE) shortages in the United States due to the Coronavirus Disease 2019, two models of N95 respirators were evaluated for reuse after gamma radiation sterilization. Gamma sterilization is attractive for PPE reuse because it can sterilize large quantities of material through hermetically sealed packaging, providing safety and logistic benefits. The Gamma Irradiation Facility at Sandia National Laboratories was used to irradiate N95 filtering facepiece respirators to a sterilization dose of 25 kGy(tissue). Aerosol particle filtration performance testing and electrostatic field measurements were used to determine the efficacy of the respirators after irradiation. Both respirator models exhibited statistically significant decreases in particle filtering efficiencies and electrostatic potential after irradiation. The largest decrease in capture efficiency was 40–50% and peaked near the 200 nm particle size. The key contribution of this effort is correlating the electrostatic potential change of individual filtration layer of the respirator with the decrease filtration efficiency after irradiation. This observation occurred in both variations of N95 respirator that we tested. Electrostatic potential measurement of the filtration layer is a key indicator for predicting filtration efficiency loss.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗
DOE OSTI2023

Coded-mask-based X-ray phase-contrast and dark-field imaging

Phase contrast and dark-field X-ray imaging enable imaging of objects that absorb or reflect very little X-ray light. Disclosed is a method and systems for performing coded-mask-based multi-contrast imaging (CMMI). The method includes providing radiation to a coded mask that has a known phase and absorption profile according to a pre-determined pattern. The radiation is then impingent upon a sample, and the radiation is detected to perform phase-reconstruction and image processing. The method and associated systems allow for the use of maximum-likelihood and machine learning methods for reconstruction images of the sample from the detected radiation.

Shi, Xianbo↗
DOE OSTI2025

Estimation of the radiation budget during MOSAiC based on ground-based and satellite remote sensing observations

An accurate representation of the radiation budget is essential for investigating the impact of clouds on the climate system, especially in the Arctic, an environment highly sensitive to complex and rapid environmental changes. In this study, we analyse a unique dataset of observations from the central Arctic made during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in conjunction with state-of-the-art satellite products from CERES (Clouds and the Earth's Radiant Energy System) to investigate the radiative effect of clouds and radiative closure at the surface and the top of the atmosphere (TOA). We perform a series of radiative transfer simulations using derived cloud macro- and microphysical properties as inputs to the simulations for the entire MOSAiC period, comparing our results to collocated satellite products and ice-floe observations. The radiative closure biases were generally within the instrumental uncertainty, indicating that the simulations are sufficiently accurate to reproduce the radiation budget during MOSAiC. Comparisons of the simulated radiation budget relative to CERES show similar values in the terrestrial flux but relatively large differences in the solar flux, which are attributed to a lower surface albedo and a possible underestimation of atmospheric opacity by CERES. While the simulation results were consistent with the observations, more detailed analyses reveal an overestimation of simulated cloud opacity for cases involving geometrically thick ice clouds. In the annual mean, we found that, during the MOSAiC expedition, the presence of clouds leads to a loss of 5.2 W m −2 of the atmosphere–surface system to space, while the surface gains 25.0 W m −2 and the atmosphere is cooled by 30.2 W m −2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tetris-inspired detector with neural network for radiation mapping

Abstract Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Saturn Radiation Dose Environment Characterization

To understand the environment where a time-resolved hard x-ray spectrometer (AXIOM) might be fielded, experiments and simulations were performed to analyze the radiation dose environment underneath the Saturn vacuum dome. Knowledge of this environment is critical to the design and placement of the spectrometer. Experiments demonstrated that the machine performance, at least in terms of on-axis dose, has not significantly changed over the decades. Simulations of the off-axis dose were performed to identify possible spectrometer locations of interest. The effects from the source and dome hardware as well as source distributions and angles of incidence on the radiation environment were also investigated. Finally, a unified radiation transport model was developed for two widely used radiation transport codes to investigate the off-axis dose profiles and the time-dependent x-ray energy spectrum. The demonstrated equivalence of the unified radiation transport model between the radiation transport codes allows the team to tie future time-dependent x-ray environment calculations to previous integral simulations for the Saturn facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Oak Ridge National Laboratory Shutdown Dose Rate Code Suite

The Oak Ridge National Laboratory (ORNL) shutdown dose rate (SDDR) code suite calculates gamma dose rates at a location of interest due to activation of materials. The code suite is based on the rigorous two-step (R2S) method that involves two radiation transport calculations: (1) neutron radiation transport to determine neutron fluxes in the material for which activation calculations will be performed and (2) gamma radiation transport to determine dose rates at a location of interest, due to material activation. The ORNL SDDR code suite is used to determine an importance function that characterizes the neutron’s importance to the final SDDR when the Monte Carlo radiation transport method is used. This report demonstrates how the ORNL SDDR code suite is implemented through the following codes: Monte Carlo N-Particle (MCNP) code Version 5-1.60, Oak Ridge Isotope Generator (ORIGEN), MSX suite of utilities, Neutron Activation Gamma Source Sampler (NAGSS), and Automated Variance Reduction Generator (ADVANTG). For this demonstration, the International Thermonuclear Experimental Reactor (ITER) SDDR benchmark problem is used and the dose rate result is compared to previously published work.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Investigation of Flux Spreading in a Light-Trapping, Planar-Cavity Receiver for Enclosed Solar Particle Heating

Concentrating solar thermal power (CSP) technology development has recently focused on increasing the operating temperatures to accommodate high efficiency power cycles and thermochemical processes. Inert solid particles as heat transfer media enable solar receivers to operate above 700 degrees Celsius resulting in increased system thermal efficiency compared to the conventional molten salt based CSP system. An open-cavity falling-particle solar receiver that can efficiently heat particles by direct heating from concentrated solar radiation faces challenges with large particle losses from wind and unable to support thermochemical reactions. A light-trapping, planar cavity reiver (LTPCR) where particles are indirectly heated can significantly minimize the particle losses during the operation, support thermochemical reactions, and offer scalability potential. The LTPCR features an array of vertical planar receiver/absorber panels arranged within a cavity configuration. Concentrated solar radiation from heliostats is focused onto the receiver walls, where heat is indirectly transferred to solid particles flowing inside the receiver channels. Heat transfer occurs through direct contact between the receiver panel walls and particles, and can be enhanced by fluidizing particles with air. This fluidization increases particle-wall contact and extends particle residence time, maximizing heat transfer efficiency. The unique vertical planar receiver structure originated from a near-blackbody tubular light absorber, effectively distributing the incoming solar beam spread across the panel walls and trapping light. This flux spreading effect, driven by cosine projection, converts high incident solar flux into a lower, more uniform heat flux on the panel walls. This redistribution enhances heat transfer efficiency between particle-wall or reaction gases-wall, while preventing localized overheating of the receiver panel. Indirect planar cavity solar receivers completely separate solid particles from the ambient environment that can greatly reduce the thermal losses in heated particles resulting in high efficiency at high temperatures above 700 degrees Celsius. This design ensures no particle losses to the environment during the operation while open-cavity designs can experience significant particle losses from wind. An experimental investigation was conducted to observe flux spreading on the receiver panel wall. A lab-scale prototype planar receiver, fabricated using Haynes 230 alloy, was tested under direct concentrated solar radiation using the high-flux solar furnace (HFSF) facility at NREL. The experiment was performed under normal peak radiative heat fluxes ranging from 800 to 1900 kW/m2. A temperature distribution on the panel wall was measured using a thermal imaging camera (FLIR A 6600). To prevent overheating at the receiver front tip, prism-shaped heat shields (Zircar UNIFROM C1) were placed in front of the receiver, and their influence on flux spreading was also studied. Absorbed flux distribution on the panel wall was modeled using SolTrace. The total solar power and flux distributions delivered from HFSF were determined based on the heliostat mirror optical properties, direct normal irradiance (DNI) on the on-sun testing days, peak flux measurement during the on-sun testing, and shutter/attenuator settings Due to the large incident angles of the solar beam on the panel wall, the angular optical properties of Haynes 230 alloy and Zircar heat shields were incorporated into the model. This flux distribution model was then integrated into a computational fluid dynamics (CFD) simulation to predict the receiver panel wall temperature, which was compared with the experimental measurements. Both prediction and measurements identified a temperature hotspot at the backside of the panel, indicating that the incident solar beam can fully reach to the rear of the receiver. The heat shields positioned at the front of the receiver effectively reduced the excessive temperature rise at the receiver front tip. Overall, the temperature was well distributed over the panel wall, with a minor hotspot at the back of the receiver. The model slightly overpredicted the temperature, possibly due to discrepancies in optical properties of the panel and an underprediction of thermal loss in the receiver. The advancement of the particle LTPCR offers a viable alternative to open-cavity receivers by addressing particle loss issues. Additionally, it presents a pathway for enabling solar thermochemical processes, extending CSP technology beyond power generation to fuel and chemical production.

14 SOLAR ENERGY↗
DOE OSTI2021

Coupled Multiphysics Simulations of Heat Pipe Microreactors Using DireWolf

DireWolf is a multiphysics software driver application designed to simulate heat pipe–cooled nuclear microreactors. Developed under the U.S. Department of Energy, Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the DireWolf software application’s objective is to provide the nuclear community with a design and safety analysis simulation capability. Based upon the NEAMS program Multiphysics Object-Oriented Simulation Environment (MOOSE) computational framework, DireWolf tightly couples nuclear microreactor physics, reactor physics, radiation transport, nuclear fuel performance, heat pipe thermal hydraulics, power generation, and structural mechanics to resolve the interdependent nonlinearities. DireWolf is capable of simulating both steady and transient normal reactor operation and several postulated failure scenarios. We will present the fundamental physics of heat pipe–cooled nuclear microreactors and the MOOSE-based software employed in DireWolf. Both steady and transient results for coupled reactor physics, radiation transport, and nuclear fuel performance are demonstrated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗
DOE OSTI2022

Performance of Cloud 3D Solvers in Ice Cloud Shortwave Radiation Closure Over the Equatorial Western Pacific Ocean

Abstract For retrieving cloud optical properties from satellite images or computing these properties from climate model output, computationally efficient treatments of cloud horizontal inhomogeneity include the Monte Carlo Independent Column Approximation (McICA) and the Tripleclouds method. Computationally efficient treatment of cloud horizontal radiation exchanges includes the SPeedy Algorithm for Radiative TrAnsfer through CloUd Sides (SPARTACUS). As a test to derive properties from satellite images, we collocate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud retrievals with near‐nadir Cloud and the Earth's Radiant Energy System (CERES) footprints in July 2008 over an equatorial western Pacific Ocean region to compare the performance of the McICA, Tripleclouds, and SPARTACUS solvers to the conventional plane‐parallel homogeneous (PPH) treatment. PPH overestimates cloud albedo, and the three solvers effectively reduce overestimation with root mean square error of shortwave upwelling irradiance decreasing between 15.72 and 18.53 W m −2 , or about 22%–25%. Although cloud top variability does not get fed into the simulations, all three solvers also reduce the effect of cloud top variability on cloud albedo. Entrapment (energy reflected downward from clouds) and horizontal radiation transfer have opposite effects on the SPARTACUS cloud albedo simulation. The net effect depends on the cloud vertical extent, the unawareness of which limits the performance of the SPARTACUS solver.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Introduction to an MCGIDI Mini-App and Performance Comparisons with XSBench

In high-performance Monte Carlo (MC) radiation transport codes, cross section lookups often account for the majority of computational expens. In response to this observation, a number of nuclear data mini-apps have been developed to profile and optimize the lookup process. A review of these mini-apps can be found in Ref. In contrast to a fully fledged MC code, nuclear data mini-apps do not feature particle tracking; instead, the cross section lookup process is considered in isolation, a simplification that allows for easier implementation and evaluation of various lookup schemes and techniques. GIDI+, as described on its public repository1, is ...a collection of C++ libraries for accessing evaluated and processed nuclear data stored in the Generalized Nuclear Database Structure (GNDS). In addition to reading GNDS files, GIDI+ has functions to sum and collapse multi-group data as needed by deterministic transport codes, and to sample GNDS data as needed by Monte Carlo transport codes. Certain modes of Mercury, a LLNL-developed MC radiation transport code, utilize GIDI+ for cross section lookups. Specifically, Mercury uses the MCGIDI library contained within GIDI+ to perform lookups on GPUs. A mini-app exercising MCGIDI’s cross section lookup capabilities would prove useful for optimization, which in turn could improve the performance of client codes such as Mercury. Such a mini-app could also be used to assess the performance of MCGIDI compared to other nuclear data mini-apps. In this document, we introduce a nuclear data mini-app built with the MCGIDI library. The MCGIDI mini-app (MCGIDI-MA) was developed to closely resemble the methodology present in XSBench, a nuclear data mini-app developed at Argonne National Laboratory. The remainder of this section provides an overview on XSBench. Section 2 describes MCGIDI-MA and its usage. Section 3 contains performance results of MCGIDI-MA on LLNL’s Lassen and Quartz compute platforms, as well as comparisons to XSBench performance where appropriate. In Section 4, we present a summary of our findings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Metrics and Methods for Radiation Detection Algorithm Characterization for Nuclear/Radiological Source Search

This report presents a series of recommendations for data to train and evaluate radiation detection algorithms and performance metrics to evaluate these algorithms. These recommendations were formed through a community consensus approach through the Detection Radiation Algorithms Group (DRAG), a multi-institution collaboration spanning eight Department of Energy laboratories and John Hopkins Applied Physics Laboratory. This report includes recommendations on background data variability, and metrics to quantify variability, sources and shielding configurations to include in data collection campaigns and detector response variability. In addition, this report describes several anomaly detection and identification algorithms and recommends metrics to report their performance. Finally, this report ends with a discussion on machine learning algorithms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗