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At least 199 records · Page 11

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DOE OSTI2025

Normalizing flows for high-dimensional detector simulations

Whenever invertible generative networks are needed for LHC physics, normalizing flows show excellent performance. In this work, we investigate their performance for fast calorimeter shower simulations with increasing phase space dimension. We use fast and expressive coupling spline transformations applied to the CaloChallenge datasets. In addition to the base flow architecture we also employ a VAE to compress the dimensionality and train a generative network in the latent space. We evaluate our networks on several metrics, including high-level features, classifiers, and generation timing. Our findings demonstrate that invertible neural networks have competitive performance when compared to autoregressive flows, while being substantially faster during generation.

Ernst, Florian↗

DOE OSTI2020

Normal modes in thermal AdS via the Selberg zeta function

The heat kernel and quasinormal mode methods of computing 1-loop partition functions of spin s s fields on hyperbolic quotient spacetimes \mathbb{H}^{3}/\mathbb{Z} ℍ 3 / ℤ are related via the Selberg zeta function. We extend that analysis to thermal \text{AdS}_{2n+1} AdS 2 n + 1 backgrounds, with quotient structure \mathbb{H}^{2n+1}/\mathbb{Z} ℍ 2 n + 1 / ℤ . Specifically, we demonstrate the zeros of the Selberg function encode the normal mode frequencies of spin fields upon removal of non-square-integrable modes. With this information we construct the 1-loop partition functions for symmetric transverse traceless tensors in terms of the Selberg zeta function and find exact agreement with the heat kernel method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Global normal spectral irradiance in Albuquerque: a one-year open dataset for PV research

This report describes the creation process and final content of a spectral irradiance dataset for Albuquerque NM. The spectral irradiance measurements were made using a dual-axis tracker; therefore, they represent global normal irradiance. The dataset combines spectroradiometer and weather measurements from a two-year period into a continuous calendar year. The data files are accompanied by extensive metadata as well as example calculations and graphs to demonstrate the potential uses of this database.

14 SOLAR ENERGY↗

DOE OSTI2023

Rheology of dense fiber suspensions: Origin of yield stress, shear thinning, and normal stress differences

We use high-fidelity computational model of fiber suspension to investigate suspension rheology. We investigate the interplay between the hydrodynamic, noncontact attractive and repulsive, and interfiber contact interactions. The shear-thinning viscosity and finite yield stress obtained from the Immerse Boundary Method simulations align quantitatively with experimental findings from the literature. The study demonstrates that attractive interactions lead to both yield stress and shear thinning behavior in rigid fiber suspensions. This discovery holds significance as it contributes to the ongoing debate on the source of yield stress in fiber suspensions. The proposed model is used to quantify normal stresses in addition to shear thinning and yield stress.

Ardekani, Arezoo↗

DOE OSTI2025

High Purity Germanium Detector Normalization

The presentation summarizes a project completed by our group a couple years ago comparing two detectors and attempting to normalize the results using a mathematical equation and how those results impacted our current operations.

Drumm, Natalie Daphne [Sandia National Laboratorie↗

DOE OSTI2021

Heavy Ion Minibeam Therapy: Side Effects in Normal Brain

The purpose of this work was to investigate whether minibeam therapy with heavy ions might offer improvements of the therapeutic ratio for the treatment of human brain cancers. To assess neurotoxicity, we irradiated normal juvenile rats using 120 MeV lithium-7 ions at an absorbed integral dose of 20 Gy. Beams were configured either as a solid parallel circular beam or as an array of planar parallel minibeams having 300-micron width and 1-mm center-to-center spacing within a circular array. We followed animals for 6 months after treatment and utilized behavioral testing and immunohistochemical studies to investigate the resulting cognitive impairment and chronic pathologic changes. We found both solid-beam therapy and minibeam therapy to result in cognitive impairment compared with sham controls, with no apparent reduction in neurotoxicity using heavy ion minibeams instead of solid beams under the conditions of this study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Estimating Field-Level Perennial Bioenergy Grass Biomass Yields Using the Normalized Difference Red-Edge Index and Linear Regression Analysis for Central Virginia, USA

We investigated the indicative power of the normalized difference red-edge index (NDRE) for estimating field-level perennial bioenergy grass biomass yields utilizing Sentinel-2 imagery and a linear regression model as a rapid, cost-effective method for biomass yield estimations for bioenergy. We used 2019 data from three study sites containing mature perennial bioenergy grass stands in central Virginia, USA. Of the simulated daily NDRE values based on the temporally weighted averaging of two temporal neighbors, we found the strongest index–yield correlation on 11 August (R = 0.85). We estimated the perennial bioenergy grass biomass yields for (1) all sites using the data pooled from the three sites (all-site estimation) and (2) each site using the data pooled from the other two sites (cross-site estimation). The estimated field-level perennial bioenergy grass biomass yields strongly correlated with the recorded yields (average R2 = 0.76), with a root mean square error (RMSE) of 1.5 Mg/ha and a mean absolute error (MAE) of 1.2 Mg/ha for the all-site estimation. For the cross-site estimation, the site with diverse perennial grass types had the weakest correlation (R2 = 0.44) of the sites, indicating a difficulty in accounting for heterogeneous index–yield relationships in a single model. In addition to identifying a strong indicative power of the NDRE for estimating the overall perennial bioenergy grass biomass yields at a field level, the findings from this study call for an analysis across multiple perennial grasses and a comparison using multiple sites to understand (1) if the indicative power of the index shifts from the biomass of the specific perennial bioenergy grass type to the overall biomass during the growing season and (2) the level of perennial bioenergy grass heterogeneity that may hinder the remotely sensed biomass yield estimation using a single model.

09 BIOMASS FUELS↗

DOE OSTI2025

Simulation Results of a Thermal Power Dispatch System from a Generic Pressurized Water Reactor in Normal and Abnormal Operating Conditions

Amid economic pressures in the U.S. electricity market, nuclear utilities are exploring new revenue streams, including hydrogen production. A generic pressurized water reactor simulator was modified to incorporate a novel design for a TPD system coupled to a hydrogen production plant. Standard malfunctions were included in the simulation design, including steam line breaks at various system locations and flow interruptions in the hydrogen plant due to multiple faults, reflecting anticipated operational challenges. It is imperative that the TPD system operation has a minimal effect on the reactor power, primary coolant system, and turbine system operation and performance. Due to the specific design and application of this TPD system, with the proposed turbine control system changes, the overall impact on the existing plant systems is low. Normal TPD operating scenarios resulted in minor effects on the existing plant systems: reactor power changes by at most 0.2%, and gross generator output changes by 20.5 MWe from 100 MWt of TPD. The most severe malfunction analyzed in this work is a full TPD steam line break downstream of the extraction location, which results in an increase in reactor power of about 0.5%. The gross generator output decreases by 36 MWe, a total decrease of 60 MWe from the full power steady state (FPSS) condition. These results indicate that an industrial hydrogen production plant could be coupled thermally to a nuclear power plant with limited effects on the existing system operation and safety.

08 HYDROGEN↗

DOE OSTI2024

Improving Cathode Testing with a High-Gradient Cryogenic Normal Conducting RF Photogun

Future electron accelerator applications such as X-ray free electron lasers and colliders are dependent on significantly increasing beam brightness. With the observation that linac beam manipulation’s best preservation of max brightness is at the cathode, we are incentivized to create an environment where we can study how to achieve the highest possible photogun brightness. In order to do so, we intend to extract beams from high-brightness photocathodes with the highest achievable accelerating gradients we can manage in a klystron-powered radiofrequency (RF) photogun. We utilize here cryogenic normal conducting cavities to achieve ultra-high gradients via limitation of breakdown rates (BDR). The low temperatures should also reduce cathode emittance by reducing the mean transverse energy (MTE) of electrons near the photoemission threshold. To this end, we have designed and produced a new CrYogenic Brightness-Optimized Radiofrequency Gun (CYBORG) for use in a new beamline at UCLA. We will introduce the enabling RF and photoemission physics as a primer for the new regime of high field low temperature cathodes we intend to enter. We further report the current status of the beamline commissioning, including the cooling of the photogun to 100 K, and producing 0.5 MW of RF feed power, which corresponds to cathode accelerating fields in the range of 80–90 MV/m. We further plan iterative improvements to both to 77 K and 1 MW corresponding to our ultimate goal >120 MV/m. Our discussion will include future beamline tests and the consideration of the initial realization of an ultra-high-gradient photoinjector concept.

Lawler, Gerard Emile (ORCID:0000000160113435)↗

DOE OSTI2020

The Young and Nearby Normal Type Ia Supernova 2018gv: UV-optical Observations and the Earliest Spectropolarimetry

The nondetection of companion stars in SN Ia progenitor systems lends support to the notion of double-degenerate systems and explosions triggered by the merging of two white dwarfs. This very asymmetric process should lead to a conspicuous polarimetric signature. By contrast, observations consistently find very low continuum polarization as the signatures from the explosion process largely dominate over the pre-explosion configuration within several days. Critical information about the interaction of the ejecta with a companion and any circumstellar matter is encoded in the early polarization spectra. In this study, we obtain spectropolarimetry of SN 2018gv with the ESO Very Large Telescope at -13.6 days relative to the B-band maximum light, or ~5 days after the estimated explosion—the earliest spectropolarimetric observations to date of any SN Ia. These early observations still show a low continuum polarization (lesssim0.2%) and moderate line polarization (0.30% ± 0.04% for the prominent Si ii λ6355 feature and 0.85% ± 0.04% for the high-velocity Ca component). The high degree of spherical symmetry implied by the low-line and continuum polarization at this early epoch is consistent with explosion models of delayed detonations and is inconsistent with the merger-induced explosion scenario. Finally, the dense UV and optical photometry and optical spectroscopy within the first ~100 days after the maximum light indicate that SN 2018gv is a normal SN Ia with similar spectrophotometric behavior to SN 2011fe.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Solar Energetic Particle Acceleration at a Spherical Shock with the Shock Normal Angle $θ$ $B_n$ Evolving in Space and Time

We present a 2D kinematic model to study the acceleration of solar energetic particles (SEPs) at a shock driven by a coronal mass ejection. The shock is assumed to be spherical about an origin that is offset from the center of the Sun. This leads to a spatial and temporal evolution of the angle between the magnetic field and the shock-normal direction (θ Bn ) as it propagates through the Parker spiral magnetic field from the lower corona to 1 au. We find that the high-energy SEP intensity varies significantly along the shock front due to the evolution of θ Bn . Generally, the west flank of the shock preferentially accelerates particles to high energies compared to the east flank and shock nose. This can be understood in terms of the rate of acceleration, which is higher at the west flank. Double power-law energy spectra are reproduced in our model as a consequence of the local acceleration and transport effects. These results will help us to better understand the evolution of SEP acceleration and provide new insights into large SEP events observed by multiple spacecraft, especially those close to the Sun, such as Parker Solar Probe and Solar Orbiter.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗

DOE OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance and normalized difference vegetation index, Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) – operated by the Terrestrial Ecosystem Science & Technology group https://www.bnl.gov/envsci/testgroup/ at Brookhaven National Laboratory. This package includes data from 19 flights flown over the NGEE-Arctic, Kougarok Mile Marker (MM) 80, Kougarok Fire Complex (KFC) and Teller MM 27 sites in July 2022. Derived image products include point cloud, ortho-mosaiced multispectral image, a digital surface model (DSM) using the structure from motion (SfM) technique, and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance, canopy height model, normalized difference vegetation index, Seward Peninsula, Alaska, 2021

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) - operated by the Terrestrial Ecosystem Science Technology group at Brookhaven National Laboratory. This package includes data from 10 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska, in August 2021. Derived image products include point cloud, ortho-mosaiced multispectral image, ortho-mosaiced RGB image, a digital surface model (DSM) using the structure from motion (SfM) technique, a canopy height model (CHM), and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Response of CR-39 nuclear track detectors to protons with non-normal incidence

This paper presents data from experiments with protons at non-normal incidence to CR-39 nuclear track detectors, analyzing the properties of detection efficiency, proton track diameter, track contrast, and track eccentricity. Understanding the CR-39 response to protons incident at an angle is important for designing charged particle detectors for inertial confinement fusion (ICF) applications. This study considers protons with incident energies less than 3 MeV. In this regime, an incident angle of 10° has no effect on CR-39 detection efficiency, and >85% detection efficiency is preserved up through 25° in the range of 1.0 MeV–2.1 MeV. For ICF applications, incident angles above 30° are deemed impractical for detector design due to significant drops in proton detection at all energies. We observe significant reductions in detection efficiency compared to theoretical predictions, particularly at low energies where proton tracks are etched away. The proton track diameter measured by the scan system is observed to decrease with higher incident angles. The track diameters are analyzed with two fitting models, and it is shown that the diameter–energy relation can be fit with the existing models at angles up to 30°. The optical contrast of the tracks tends to increase with the angle, meaning that the tracks are fainter, and a larger increase is observed for higher energies. Eccentricity, a measure of how elongated proton tracks are, increases with the incident angle and drops after the critical angle. The lowest energy tracks remain nearly circular even at higher angles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

The Spallation Neutron Source Normal Conducting Linac RF System Design for the Proton Power Upgrade Project

The Proton Power Upgrade (PPU) project at the Spallation Neutron Source will double the available proton beam power from 1.4 to 2.8 MW by increasing the beam energy from 1.0 to 1.3 GeV and the beam current from 26 to 38 mA. The increase in beam current resulted in the need to redesign the existing normal conducting linac (NCL) RF Systems. High-power testing of the existing NCL RF Systems configured to accelerate PPU-level beam provided the data used to make the final design decisions. This paper describes the development and execution of those in-situ tests and the subsequent results.

Moss, John↗

DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

DNI↗

DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗