Search NASA⌕ Search

SEARCH · Search NASA

Results for “Benchmark data”

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.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Dragonfly Entry Aerosciences Measurements (DrEAM) Suite Science Objectives

NASA Ames and Langley are partnering with DLR to propose a comprehensive instrumentation suite known as the Dragonfly Entry Aerosciences Measurements (DrEAM). DrEAM will provide key aerothermodynamic data and performance analysis for Dragonfly’s forebody and backshell Thermal Protection System (TPS), and also includes a DLR-provided Data Acquisition System (DAS). Titan's atmosphere predominantly consists of nitrogen (~ 98% by mole) with small amounts of methane (~ 2% by mole). CN is a strong radiator and is found in nonequilibrium concentrations for Titan entry, the modeling of which has proven to be a difficult task. The DrEAM instrumentation suite will significantly advance the state-of-the-art not only by documenting the environment and performance of Dragonfly’s entry system but also by making key measurements in Titan’s atmosphere for the first time, thus providing new benchmark data applicable to entry science more generally.

Aaron Brandis↗
NASA NTRSDate not supplied

The LuNaMaps Project: Advancing Capabilities for Developing and Validating Digital Elevation Models of Rocky Surfaces from Orbital Data

Both navigation and surface science can benefit from the ability to generate high resolution and accurate maps of the surface of the Moon and other solar system bodies. The primary way these maps are generated is through the use of orbital imagery and ranging data. Traditionally, the process of using orbital imagery and ranging data is tedious and labor-intensive. Additionally, once maps have been built, there has generally been limited effort in developing standards by which to verify the accuracy and quality of the generated maps. The Lunar Navigation Maps (LuNaMaps) project is a NASA Game Changing Development (GCD) project which over the last 4 years has aimed to address these issues both for the Moon and for other rocky solar system bodies. This has been accomplished through development of new and existing capabilities including: a suite of methods and tools to combine all sources of orbital imagery; a benchmark data set as well as basic requirements for high-fidelity simulations of precision landing functions; tools to synthetically enhance map products with lander-scale features for use in the development and testing of hazard detection systems; methods and tools to evaluate the accuracy of developed digital elevation maps (DEMs) and their quality for use in terrain relative navigation scenarios; and tools to realistically render image and lidar data. In this work, we provide an overview of the capabilities developed through LuNaMaps, demonstrating its use for processing existing lunar data, and describing how it can be applied to other use cases. We additionally provide preliminary results showing the application of the developed tools and processes to the generation of elevation maps of the Lunar Surface Proving Grounds (LSPG) lunar analog at Astrobotic’s Mojave testing facility using “orbital imagery” captured by a drone. In this terrestrial demonstration, we have the benefit of being able to compare the results to a ground truth model of the LSPG. We finally describe plans to use the newly created maps in a terrestrial terrain relative navigation demonstration over the LSPG in early 2025.

optical navigation↗
DOE OSTI2025

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic predictions. This challenge intensifies across regions characterized by diverse hydro-climatological and geographical conditions, such as in the conterminous US (CONUS) where a single precipitation product struggles to consistently replicate observed hydrographs, particularly peak flow dynamics. To enhance streamflow predictions, we utilize a VIC-RAPID hydrologic modeling framework driven by multiple commonly used meteorological forcing data sets, such as Daymet, PRISM, ST4, AORC, and their hybrids and create multiple sets of 40-year (1980–2019) hourly, daily, and monthly streamflow reanalysis, Dayflow Version 2, for 2.7 million river reaches across the CONUS. Most forcings lead to skillful streamflow performance, except for ST4 in the mountainous west, where severe radar blockage adversely affects the accuracy. The evaluation using over 6,000 hourly stream gauges shows that hourly AORC and ST4 lead to improved annual peak flow performance over Daymet—driven streamflow (Dayflow V1), particularly in smaller basins, highlighting the value of high temporal resolution forcings in hydrologic predictions. Compared with other benchmark data sets like National Water Model V3.0, AORC-driven VIC-RAPID exhibits improved regional streamflow performance, with comparable peak flow representation. We envision that multi-forcing streamflow reanalysis data can inform regions in need of forcing data enhancement, diagnose hydrologic model performance, and benefit diverse water resource applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

GCSS Cirrus Parcel Model Comparison Project

The Cirrus Parcel Model Comparison Project, a project of GCSS Working Group on Cirrus Cloud Systems (WG2), involves the systematic comparison of current models of ice crystal nucleation and growth for specified, typical, cirrus cloud environments. The goal of this project is to document and understand the factors resulting in significant inter-model differences. The intent is to foment research leading to model improvement and validation. In Phase 1 of the project reported here, simulated cirrus cloud microphysical properties are compared for situations of "warm" (-40 C) and "cold" (-60 C) cirrus subject to updrafts of 4, 20 and 100 cm/s, respectively. Five models participated. These models employ explicit microphysical schemes wherein the size distribution of each class of particles (aerosols and ice crystals) is resolved into bins. Simulations are made including both homogeneous and heterogeneous ice nucleation mechanisms. A single initial aerosol population of sulfuric acid particles is prescribed for all simulations. To isolate the treatment of the homogeneous freezing (of haze drops) nucleation process, the heterogeneous nucleation mechanism is disabled for a second parallel set of simulations. Qualitative agreement is found for the homogeneous-nucleation-only simulations, e.g., the number density of nucleated ice crystals increases with the strength of the prescribed updraft. However, non-negligible quantitative differences are found. Detailed analysis reveals that the homogeneous nucleation formulation, aerosol size, ice crystal growth rate (particularly the deposition coefficient), and water vapor uptake rate are critical components that lead to differences in predicted microphysics. Systematic bias exists between results based on a modified classical theory approach and models using an effective freezing temperature approach to the treatment of nucleation. Each approach is constrained by critical freezing data from laboratory studies, but each includes assumptions that can only be justified by further laboratory data. Consequently, it is not yet clear if the two approaches can be made consistent. Large haze particles may deviate considerably from equilibrium size in moderate to strong updrafts (20-100 cm/s) at -60 C when the commonly invoked equilibrium assumption is lifted. The resulting difference in particle-size-dependent solution concentration of haze particles may significantly affect the ice nucleation rate during the initial nucleation interval. The uptake rate for water vapor excess by ice crystals is another key component regulating the total number of nucleated ice crystals. This rate, the product of ice number concentration and ice crystal diffusional growth rate, which is sensitive to the deposition coefficient when ice particles are small, partially controls the peak nucleation rate achieved in an air parcel and the duration of the active nucleation time period. The effects of heterogeneous nucleation are most pronounced in weak updraft situations. Vapor competition by the nucleated (heterogeneous) ice crystals limits the achieved ice supersaturation and thus suppresses the contribution of homogeneous nucleation. Correspondingly, ice crystal number density is markedly reduced. Definitive laboratory and atmospheric benchmark data are needed for the heterogeneous nucleation process. Inter-model differences are correspondingly greater than in the case of the homogeneous nucleation process acting alone.

Lin, Ruei-Fong↗
NASA NTRS2001

Cirrus Parcel Model Comparison Project: The Critical Components to Simulate Cirrus Initiation Explicitly - Phase 1

The Cirrus Parcel Model Comparison Project, a project of the GCSS (GEWEX Cloud System Studies) Working Group on Cirrus Cloud Systems, involves the systematic comparison of current models of ice crystal nucleation and growth for specified, typical, cirrus cloud environments. In Phase I of the project reported here, simulated cirrus cloud microphysical properties are compared for situations of "warm" (40 C) and "cold" (-60 C) cirrus, both subject to updrafts of 4, 20 and 100 centimeters per second. Five models participated. The various models employ explicit microphysical schemes wherein the size distribution of each class of particles (aerosols and ice crystals) is resolved into bins or treated separately. Simulations are made including both the homogeneous and heterogeneous ice nucleation mechanisms. A single initial aerosol population of sulfuric acid particles is prescribed for all simulations. To isolate the treatment of the homogeneous freezing (of haze droplets) nucleation process, the heterogeneous nucleation mechanism is disabled for a second parallel set of simulations. Qualitative agreement is found for the homogeneous-nucleation- only simulations, e.g., the number density of nucleated ice crystals increases with the strength of the prescribed updraft. However, significant quantitative differences are found. Detailed analysis reveals that the homogeneous nucleation rate, haze particle solution concentration, and water vapor uptake rate by ice crystal growth (particularly as controlled by the deposition coefficient) are critical components that lead to differences in predicted microphysics. Systematic bias exists between results based on a modified classical theory approach and models using an effective freezing temperature approach to the treatment of nucleation. Each approach is constrained by critical freezing data from laboratory studies, but each includes assumptions that can only be justified by further laboratory research. Consequently, it is not yet clear if the two approaches can be made consistent. Large haze particles may deviate considerably from equilibrium size in moderate to strong updrafts (20-100 centimeters per second) at -60 C when the commonly invoked equilibrium assumption is lifted. The resulting difference in particle-size- dependent solution concentration of haze particles may significantly affect the ice particle formation rate during the initial nucleation interval. The uptake rate for water vapor excess by ice crystals is another key component regulating the total number of nucleated ice crystals. This rate, the product of particle number concentration and ice crystal diffusional growth rate, which is particularly sensitive to the deposition coefficient when ice particles are small, modulates the peak particle formation rate achieved in an air parcel and the duration of the active nucleation time period. The effects of heterogeneous nucleation are most pronounced in weak updraft situations. Vapor competition by the heterogeneously nucleated ice crystals may limit the achieved ice supersaturation and thus suppresses the contribution of homogeneous nucleation. Correspondingly, ice crystal number density is markedly reduced. Definitive laboratory and atmospheric benchmark data are needed for the heterogeneous nucleation process. Inter-model differences are correspondingly greater than in the case of the homogeneous nucleation process acting alone.

Lin, Ruei-Fong↗
DOE OSTI2024

Microstructure effects on high velocity microparticle impacts of copper

Constitutive models can fail to predict high-rate deformation behavior due to their inability to account for microstructural effects. In part, this is because of a dearth of experimental benchmarking data in the high strain-rate, low pressure regime, since many high-rate experiments also probe a region of strong shockwaves, at which point microstructure effects no longer play a primary role. This work uses laser-induced particle impact testing to quantitatively study high velocity impacts of small, rigid alumina microspheres on flat copper substrates with varying amounts of initial cold work in the weak shock regime, but at very high strain rates up to ~10 7 s –1 . Through paired experiments and numerical simulations, this work shows that the initial microstructure condition can have significant influence on dynamical mechanical properties in this range. Specifically, prior work hardening of the copper substrate leads to increased rebounding of the microparticles (i.e., less plastic dissipation in the impact) as well as smaller craters. Each of these experimental measurables can be converted into a strength measure, i.e., the dynamic yield strength or dynamic hardness, respectively, neither of which is well predicted consistently by existing constitutive laws. The general trend of hardening can be captured by such models by incorporating an existing “pre-strain,” suggesting that future calibration of the materials parameters may yield a good fit over a broader range of conditions. Our results emphasize the importance of reporting the microstructural condition in dynamic studies, as well as the necessity of accounting for these factors when formulating and optimizing constitutive models.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Benchmark microgravity experiments and computations for 3D dendritic-array stability in directional solidification

In this study, we present a comprehensive quantitative analysis of stability bands for dendritic arrays during directional solidification of a transparent succinonitrile-0.46 wt % camphor alloy, spanning a broad range of pulling velocities. Taking advantage of the microgravity environment aboard the International Space Station where most convection effects are suppressed, we obtain unique measurements that quantify the stable primary spacing range of spatially extended three-dimensional dendritic array structures under purely diffusive growth conditions. Through carefully designed velocity jump experiments and detailed examination of sub-grain boundary dynamics, we characterize key instabilities, including elimination and tertiary branching, shedding new light on the mechanisms governing dynamic dendritic spacing selection in extended 3D arrays. Phase field simulations are performed to characterize the stability limits of dendritic array structures for quantitative comparison with the flight experiments. Although the simulations capture general trends, significant deviations are noted at the upper stability boundary, indicating the influence of additional, unexplored factors. These findings contribute to a deeper understanding of dendritic growth dynamics and offer valuable benchmark data that could aid in refining predictive models and improving control of dendritic microstructures in metallurgical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

China's plug-in hybrid electric vehicle transition: An operational carbon perspective

Assessing the emissions of plug-in hybrid electric vehicle (PHEV) operations is crucial for accelerating the carbon–neutral transition in the passenger car sector. This study is the first to adopt a bottom-up model to measure the real-world energy use and carbon dioxide emissions of China’s top twenty selling PHEV models across different regions from 2020 to 2022. The results indicate that (1) the actual electricity intensity of the best-selling PHEV models (20.2–38.2 kWh/100 km) was 30–40 % higher than the New European Driving Cycle values, and the actual gasoline intensity (4.7–23.5 L/100 km) was 3–6 times greater than the New European Driving Cycle values. (2) The overall energy use of the best-selling models varied among different regions, and the energy use from 2020 to 2022 in Southern China was double that Northern China and the Yangtze River Middle Reach. (3) The top-selling models emitted 4.7 megatons of carbon dioxide nationwide from 2020 to 2022, with 1.9 megatons released by electricity consumption and 2.8 megatons released by gasoline combustion. Furthermore, targeted policy implications for expediting the carbon–neutral transition within the passenger car sector are proposed. In essence, this study explores and compares benchmark data at both the national and regional levels, along with performance metrics associated with PHEV operations. The main objective is to aid nationwide decarbonization efforts, focusing on carbon reduction and promoting the rapid transition of road transportation toward a net-zero carbon future.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗
DOE OSTI2024

Community standards and future opportunities for synthetic communities in plant–microbiota research

Harnessing beneficial microorganisms is seen as a promising approach to enhance sustainable agriculture production. Synthetic communities (SynComs) are increasingly being used to study relevant microbial activities and interactions with the plant host. Yet, the lack of community standards limits the efficiency and progress in this important area of research. Here, to address this gap, we recommend three actions: (1) defining reference SynComs; (2) establishing community standards, protocols and benchmark data for constructing and using SynComs; and (3) creating an infrastructure for sharing strains and data. We also outline opportunities to develop SynCom research through technical advances, linking to field studies, and filling taxonomic blind spots to move towards fully representative SynComs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Energy dataset of Frontier supercomputer for waste heat recovery

The Hewlett Packard Enterprise–Cray EX Frontier is the world’s first and fastest exascale supercomputer, hosted at the Oak Ridge Leadership Computing Facility in Tennessee, United States. Frontier is a significant electricity consumer, drawing 8–30 MW; this massive energy demand produces significant waste heat, requiring extensive cooling measures. Although harnessing this waste heat for campus heating is a sustainability goal at Oak Ridge National Laboratory (ORNL), the 30 °C–38 °C waste heat temperature poses compatibility issues with standard HVAC systems. Heat pump systems, prevalent in residential settings and some industries, can efficiently upgrade low-quality heat to usable energy for buildings. Thus, heat pump technology powered by renewable electricity offers an efficient, cost-effective solution for substantial waste heat recovery. However, a major challenge is the absence of benchmark data on high-performance computing (HPC) heat generation and waste heat profiles. This paper reports power demand and waste heat measurements from an ORNL HPC data centre, aiming to guide future research on optimizing waste heat recovery in large-scale data centres, especially those of HPC calibre.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Vibrational and electronic properties of Np 2 O 5 from experimental spectroscopy and first principles calculations

High-valence actinide oxides are critical to understanding the behavior of 5f-electrons, yet their structural and electronic properties remain poorly understood due to challenges in synthesis and handling. We report the first Raman spectroscopic study of single-crystalline Np 2 O 5 and the first scanning tunneling spectroscopy (STS) measurement on any neptunium-containing material. Hydrothermally synthesized crystals were structurally verified by X-ray diffraction. Raman spectra revealed sharply resolved vibrational features, including previously unreported low-frequency modes. STS measurements revealed a band gap of 1.5 eV. Density functional theory (DFT) enables vibrational mode assignments, reveals neptunium-dominated low-frequency phonons, oxygen-dominated high-frequency modes, and predicts an indirect band gap of 1.68 eV. This predicted value is in excellent agreement with the experimentally measured STS gap. This combined Raman, DFT, and STS approach provides a robust framework for correlating lattice dynamics and electronic structure in actinide materials, providing benchmark data for Np 2 O 5 , and opening new avenues for probing structure–property relationships in complex f-electron materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Planar shock-induced bubble collapse and jetting in water captured via X-ray phase contrast imaging

Shock wave–bubble interactions in water manifest rich dynamics driven by a combination of strong pressure and density mismatches. They have a wide variety of applications, including the injection of pharmaceuticals, and through scaling, enable the exploration of various aspects of high-energy-density systems such as inertial confinement fusion. In this work, the interaction between a micrometric nitrogen bubble and a planar shock wave, characterized by a Mach number of M = 1.24 and a peak pressure of p max = 0.57 , is experimentally recorded using ultra-high-speed x-ray phase contrast imaging. Highly resolved radiographs provide access to all phase discontinuities along the beam path, offering quantities such as the time-varying bubble size, the speed of a jet produced during the bubble collapse, and the time evolution of the shock wave front, which are critical benchmark data for numerical scheme validation. This study addresses the lack of well-characterized, repeatable, and high spatiotemporal resolution experiments at negative Atwood numbers by providing shock–bubble visualization and corresponding numerical simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Implementation of compound refractive lenses for large field-of-view x-ray phase-contrast imaging during hypervelocity impact experiments

Synchrotron x-ray phase-contrast imaging (XPCI) offers time-resolved visualization of dynamic compression phenomena, but its intrinsically small field-of-view (FOV) limits the time that key features remain in frame. A novel approach to enlarge the FOV is achieved by positioning a two-dimensional parabolic compound refractive lens (CRL) upstream of the sample to deliberately defocus the white beam. Ray-tracing simulations and XPCI measurements show that this CRL configuration can expand the beam by ∼50% vertically and ∼15% horizontally based on the full width at half-maximum of the beam. Implementing the CRL, however, attenuates the photon flux and lowers signal-to-noise ratio (SNR). Task-based analysis using a calibration grid (30 μm dots) showed that both setups fail to consistently meet the Rose criterion (SNR ≥ 5) for features of this size in single-bunch imaging. Extrapolating the measured SNR Rose values suggests that the minimum consistently detectable feature lies closer to 30–40 μm for the standard XPCI setup and above 40 μm for CRL-XPCI. Despite this limitation, the CRL configuration nearly doubles the illuminated area, enabling simultaneous tracking of front and rear observations of boron carbide targets subjected to rod and sphere impacts at 1.0–2.6 km/s. Image tracking algorithms and photonic Doppler velocimetry were used to measure penetration and rear-surface velocity histories. Together, these measurements capture crack fronts, penetration, and material breakout, offering new benchmark data for validating high-strain-rate constitutive models of ceramic materials.

Ceramic materials↗
DOE OSTI2026

Plasma decay of nanosecond pulsed laser-produced Ar and Ar–H 2 O sparks at atmospheric pressure

Time-resolved diagnostics were applied to investigate free-electron properties in nanosecond laser-produced discharges generated in atmospheric pressure Ar and in Ar–3%H 2 O. The discharges were generated using 23 ns, 1064 nm laser pulses. Broadband plasma imaging and laser Thomson scattering were combined with optical emission spectroscopy, with particular emphasis on the Stark broadening of the H α and H β lines. The plasma exhibited a bright emission that persists for up to 30–40 µs after breakdown. Plasma emission was then followed by a very weak glow emission that persisted for up to 19 ms after breakdown. Peak electron number density of ∼2 × 10 17 cm −3 and electron temperature of ∼7 eV were measured. An excellent agreement between both techniques was obtained regarding absolute electron number densities. The inferred free-electron temporal decay dynamics are consistent with processes dominated by hydrodynamic expansion and two- and three-body electron–ion recombination. These results provide benchmark data for modeling nanosecond laser discharges and demonstrate the reliability of combining Thomson scattering with Stark broadening in atmospheric laser sparks.

Thomson scattering↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Radioisotope production at the Spallation Neutron Source: Design concept of experimental target station

Completion of the Proton Power Upgrade Project for the Spallation Neutron Source (SNS) accelerator at Oak Ridge National Laboratory opens an opportunity to utilize reserve beam power of more than 100 kW for applications beyond neutron production. One of these applications is the production of critical radionuclides. To demonstrate the feasibility of using the reserve beam power to produce radioisotope at SNS, a design concept of a small-scale experimental target station in the Linac Dump area has been developed. This experimental facility will provide isotope yield benchmarking data using protons in the GeV range. It will also enable additional research and development in isotope handling and radiochemical separation. The target station consists of a target module enclosed in a vessel and concrete shielding. Particle transport calculations and thermo-mechanical simulations are used to determine beam parameters, decay time, isotope yield, shielding dimensions, and target design parameters. Calculations verified that the irradiated capsule can be handled manually using hands-off tools and transported to a hot cell in a shielded container for post-irradiation characterizations.

Lee, Yong Joong [ORNL] (ORCID:0000000298381723)↗