ARCS White Beam Vanadium Normalization Data for SNS Cycle 2022B
Neutron scattering Data from a Vanadium cylinder. Acquired on the ARCS spectrometer in white beam mode to normalize the detector efficiencies. During Cycle 2022B
MATERIALS SCIENCE↗
SEARCH · Engineering Papers
Results for “Normalization”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
ARCS White Beam Vanadium Normalization Data for SNS Cycle 2022B (May 15 - Jun., 14, 2022)
A data set used to normalize the detector response of the ARCS instrument see ARCS_226797.md in the data set for more details.
36 MATERIALS SCIENCE↗
ARCS White Beam Vanadium Normalization Data for SNS Cycle 2024B
A data set used to normalize the detector response of the ARCS instrument see ARCS_269548.md in the data set for more details.
36 MATERIALS SCIENCE↗
ARCS White Beam Vanadium Normalization Data for SNS Cycle 2025B
A data set used to normalize the detector response of the ARCS instrument see ARCS_322552.md in the data set for more details.
36 MATERIALS SCIENCE↗
Dose-Rate Effects of Protons and Light Ions for DNA Damage Induction, Survival and Transformation in Apparently Normal Primary Human Fibroblasts
In this work, we report on effects of low-dose exposures of accelerated protons delivered at high-dose rate (HDR) or a simulated solar-particle event (SPE) like low-dose rate (LDR) on immediate DNA damage induction and processing, survival and in vitro transformation of low passage NFF28 apparently normal primary human fibroblasts. Cultures were exposed to 50, 100 and 1,000 MeV monoenergetic protons in the Bragg entrance/plateau region and cesium-137 γ rays at 20 Gy/h (HDR) or 1 Gy/h (LDR). DNA double-strand breaks (DSB) and clustered DNA damages (containing oxypurines and abasic sites) were measured using transverse alternating gel electrophoresis (TAFE) and immunocytochemical detection/scoring of colocalized γ-H2AX pS139/53BP1 foci, with their induction being linear energy transfer (LET) dependent and dose-rate sparing observed for the different damage classes. Relative biological effectiveness (RBE) values for cell survival after proton irradiation at both dose-rates ranged from 0.61–0.73. Transformation RBE values were dose-rate dependent, ranging from ~1.8–3.1 and ~0.6–1.0 at low doses (≤30 cGy) for HDR and LDR irradiations, respectively. However peak transformation frequencies were significantly higher (1.3–7.3-fold) for higher doses of 0.5–1 Gy delivered at SPE-like LDR. Cell survival and transformation frequencies measured after low-dose 500 MeV/n He-4, 290 MeV/n C-12 and 600 MeV/n Si-28 ion irradiations also showed an inverse dose-rate effect for transformation at SPE-like LDR. This work demonstrates the existence of inverse dose-rate effects for proton and light-ion-induced postirradiation cell survival and in vitro transformation for space mission-relevant doses and dose rates.
59 BASIC BIOLOGICAL SCIENCES↗
Progress on the normal conducting magnets for the Electron-Ion Collider
The electron-ion collider (EIC) at Brookhaven National Laboratory (BNL) is designed to deliver a peak luminosity of 1e+34 1/cm2 1/sec. The EIC will take advantage of the existing Relativistic Heavy Ion Collider (RHIC) facility. Two additional rings will be installed: an electron storage ring (ESR) and a rapid cycling electron synchrotron ring (RCS).This paper presents an update on the normal conducting magnet designs required for both the ESR and RCS rings. The ESR will store polarized electron beams up to 18 GeV and utilizes a triplet of dipole magnets to increase the emittance at 5 GeV and generate excess bending to create additional radiation damping to allow a larger beam-beam tune shift. The RCS will accelerate single bunches of spin-polarized electrons at various energies from 5 GeV to 18 GeV, with a ramp rate of 100 ms and 1 Hz repetition rate. Both rings require dipole, quadrupole and sextupole magnets with different specifications.
43 PARTICLE ACCELERATORS↗
MENT-Flow: maximum-entropy phase space tomography using normalizing flows
Generative models can be trained to reproduce low-dimensional projections of high-dimensional phase space distributions. Normalizing flows are generative models that parameterize invertible transformations, allowing exact probability density evaluation and sampling. Consequently, flows are unbiased entropy estimators and could be used to solve the high-dimensional maximum-entropy tomography (MENT) problem. In this work, we evaluate a flow-based MENT solver (MENT-Flow) against exact maximum-entropy solutions and Minerbo's iterative MENT algorithm in two dimensions.
Hoover, Austin↗
Efficient continuous-wave normal conducting accelerator for industrial applications
A normal conducting, high power, high efficiency copper linear accelerator prototype is being developed for industrial applications. The system will be powered by low-cost high-efficiency magnetron RF sources and will use a gridded thermionic cathode electron gun. Leveraging the significant accelerator expertise at JLab and industry partners, these technologies will be combined to deliver high-power (>100 kW) electron beams with energies of 1 MeV or higher that are cost-effective to produce and operate. The design is modular such that energy and power can be increased by adding additional sections as required. The status of the design, prototype fabrication and plans for a beam demonstration at JLab are described.
Accelerator Physics↗
Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka
Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome (“epigenetic aging”) can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka (Oryzias latipes). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.
60 APPLIED LIFE SCIENCES↗
Ephemeral Learning - Augmenting Triggers with Online-Trained Normalizing Flows
The large data rates at the LHC require an online trigger system to select relevant collisions. Rather than compressing individual events, we propose to compress an entire data set at once. We use a normalizing flow as a deep generative model to learn the probability density of the data online. The events are then represented by the generative neural network and can be inspected offline for anomalies or used for other analysis purposes. We demonstrate our new approach for a toy model and a correlation-enhanced bump hunt.
97 MATHEMATICS AND COMPUTING↗
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↗
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↗
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↗
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↗
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↗
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↗
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↗
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↗