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DOE OSTI2024

Isotopic Analysis using FRAM [Slides]

FRAM is an isotopic analysis code nominally designed for plutonium and uranium. It stands for Fixed-energy Response-function Analysis with Multiple efficiencies. It has self-calibration using several gamma-ray peaks and can analyze gamma ray data from 30keV to >1MeV of HPGe, CdTe, or LaBr3 detector. The key difference between the MGA family of codes (from LLNL) and FRAM is the use of user-editable analysis parameters in the latter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C$_3$F$_8$ dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. The PICO Collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C$_3$F$_8$ from calibration data taken with 5 distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 keV to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov-Chain Monte-Carlo (MCMC) routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 keV and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be $\geq 50\, \%$ for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be $\geq 50\, \%$ for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated data sets are used to calculate a p-value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

The Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections*

In this work, we describe the survey design, calibration, commissioning, and emission-line detection algorithms for the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the redshifts of over a million Lyα emitting galaxies between 1.88 < z < 3.52, in a 540 deg 2 area encompassing a comoving volume of 10.9 Gpc 3 . No preselection of targets is involved; instead the HETDEX measurements are accomplished via a spectroscopic survey using a suite of wide-field integral field units distributed over the focal plane of the telescope. This survey measures the Hubble expansion parameter and angular diameter distance, with a final expected accuracy of better than 1%. Additionally, we detail the project's observational strategy, reduction pipeline, source detection, and catalog generation, and present initial results for science verification in the Cosmological Evolution Survey, Extended Groth Strip, and Great Observatories Origins Deep Survey North fields. We demonstrate that our data reach the required specifications in throughput, astrometric accuracy, flux limit, and object detection, with the end products being a catalog of emission-line sources, their object classifications, and flux-calibrated spectra.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗

DOE OSTI2022

IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗

DOE OSTI2022

Stellar Abundance Maps of the Milky Way Disk

To understand the formation of the Milky Way's prominent bar it is important to know whether stars in the bar differ in the chemical element composition of their birth material as compared to disk stars. This requires stellar abundance measurements for large samples across the Milky Way's body. Such samples, e.g., luminous red giant stars observed by the Sloan Digital Sky Survey's APOGEE survey, will inevitably span a range of stellar parameters; as a consequence, both modeling imperfections and stellar evolution may preclude consistent and precise estimates of their chemical composition at a level of purported bar signatures, which has left current analyses of a chemically distinct bar inconclusive. Here, we develop a new self-calibration approach to eliminate both modeling and astrophysical abundance systematics among red giant branch (RGB) stars of different luminosities (and hence surface gravity $\mathrm{log} g$). We apply our method to 48,853 luminous APOGEE Data Release 16 RGB stars to construct spatial abundance maps of 20 chemical elements near the Milky Way's mid-plane, covering galactocentric radii of 0 kpc < R GC < 20 kpc. Our results indicate that there are no abundance variations whose geometry matches that of the bar, and that the mean abundance gradients vary smoothly and monotonically with galactocentric radius. We confirm that the high-α disk is chemically homogeneous, without spatial gradients. Furthermore, we present the most precise [Fe/H] versus R GC gradient to date with a slope of – 0.057 ±0.001 dex kpc –1 out to approximately 15 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Introduction to and comparison of deep learning and optimization approaches to analytical wake modeling of a tilted wind turbine

This paper introduces innovative optimization and deep learning techniques to enhance the prediction of complex wake dynamics in the downstream wind velocity of tilted wind turbines. Traditional methods for calibrating the Bastankhah wake model often lead to increased errors in wind velocity distribution due to overfitting of the local wake characteristics. To address this issue, we propose an additional global optimization step to reduce errors in wind velocity predictions with respect to various wake parameters. Despite this improvement, the Bastankhah model's axisymmetric Gaussian wake shape limits its accuracy for complex wake structures. Therefore, we also propose a deep learning approach, which demonstrates promising results by accurately modeling complex wake shapes across a broader range of tilt angles with minimal computational cost. The deep learning approach achieves near-identical predictions to high-fidelity large-eddy simulations, representing a promising advancement in wake modeling.

17 WIND ENERGY↗

DOE OSTI2021

Raster Thomson scattering in large-scale laser plasmas produced at high repetition rate

We present optical Thomson scattering measurements of electron density and temperature in a large-scale (~2 cm) exploding laser plasma produced by irradiating a solid target with a high energy (5-10 J) laser pulse at high repetition rate (1 Hz). The Thomson scattering diagnostic matches this high repetition rate. Unlike previous work performed in single shots at much higher energies, the instrument allows point measurements anywhere inside the plasma by automatically translating the scattering volume using motorized stages as the experiment is repeated at 1 Hz. Measured densities around 4×10 16 cm -3 and temperatures around 7 eV result in a scattering parameter near unity, depending on the distance from the target. The measured spectra show the transition from collective scattering close to the target to non-collective scattering at larger distances. Densities obtained by fitting the weakly collective spectra agree to within 10% with an irradiance calibration performed via Raman scattering in nitrogen.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?

Variation in the electrical conductivity (EC) of water can reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. Broader application of open source (OS) EC sensors could provide an inexpensive method to measure water quality. While studies show that other water quality parameters can be robustly measured with sensors, a similar effort is needed to evaluate the performance of OS EC sensors. To address this need, we evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. We found a significant difference between OS sensor mean accuracy (3.08%) and all other sensors combined (9.23%). Our study also found that EC sensor precision decreased across all sensor configurations with increasing calibration standard EC. There was also a significant difference between OS sensor mean precision (2.85 μS/cm) and the mean precision of all other sensors combined (9.12 μS/cm). Cable length did not affect OS sensor precision. Furthermore, our results suggest that future research should include evaluating how performance is impacted by combining OS sensors with commercial data loggers as this study found significantly decreased performance in OS/commercial-hybrid sensor configurations. To increase confidence in the reliability of OS sensor data, more studies such as ours are needed to further quantify OS sensor performance in terms of accuracy and precision across different settings and OS sensor and data collection platform configurations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Constraints on Neutrino Oscillation Parameters from Neutrinos and Antineutrinos with Machine Learning

NOvA is a two detector, long baseline neutrino oscillation experiment measuring the oscillations of muon neutrinos from the \numi neutrino beam over a baseline of \SI{810}{km}. The experiment uses four oscillation channels, $\numu \rightarrow \numu$, $\numubar \rightarrow \numubar$, $\numu \rightarrow \nue$, and $\numubar \rightarrow \nuebar$, with a peak neutrino energy of \SI{1.8}{GeV}. This dissertation describes the analysis of these channels using a dataset of $13.6\times10^{20}$ protons on target neutrino beam mode and $12.5\times10^{20}$ protons on target antineutrino beam mode. The analysis makes use of improvements in the treatment of systematic uncertainties and machine learning techniques to reconstruct neutrino interactions. A technique for decorrelating systematic errors using principle component analysis was utilized to reduce and optimize neutrino cross section and beam related uncertainties. The improved machine learning algorithms make use of convolutional ne ural net works for neutrino event classification, particle classification, and instance segmentation. The selection of neutrino signal events utilizing the neutrino event classifier shows an efficiency of 63\% for the selection of electron neutrinos in neutrino beam mode and 75\% for electron antineutrinos in antineutrino beam mode. Using this algorithm, 82 appearing electron neutrino candidates and 33 appearing electron antineutrino candidates were observed with expected backgrounds of 26.8 and 14.0 respectively. In addition, 211 surviving muon neutrino candidates and 105 muon antineutrino candidates were identified with a purity of more than 96\% using the same neutrino event classifier. Fitting these data to the three flavor neutrino oscillation model, using constraints on \thetaonetwo, \thetaonethree, and \dmsqonetwo from solar and reactor neutrino experiments, the oscillation parameters are measured to be $\sintwothree = 0.57^{+0.04}_{-0.03}$, $\dmsqthreetwo = \SI[parse-numbers= false]{+ 2.41\pm0.07 \times 10^{-3}}{eV^2}$, and $\dcp=0.82^{+0.27}_{-0.87}\pi$ with a preference for the normal neutrino mass hierarchy. Leading systematic uncertainties for these measurements come from detector calibration and neutrino interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗

DOE OSTI2023

New Absolute Cavity Pyrgeometer equation by application of Kirchhoff's law and adding a convection term

An equation for the Absolute Cavity Pyrgeometer (ACP) is derived from application of Kirchhoff's law and the addition of a convection term to account for the thermopile being open to the environment, unlike a domed radiometer. The equation is then used to investigate four methods to characterise key instrumental parameters using laboratory and field measurements. The first uses solar irradiance to estimate the thermopile responsivity, the second uses a minimisation method that solves for the thermopile responsivity and transmission of the cavity, and the third and fourth revisit the Reda et al. (2012) linear least squares calibration technique. Data were collected between January and November 2020, when the ACP96 and two IRIS radiometers monitoring terrestrial irradiances were available. The results indicate good agreement with IRIS irradiances using the new equation. The analysis also indicates that while the thermopile responsivity, concentrator transmission and emissivity of an ACP can be determined independently, as an open instrument, the impact of the convection term is minor in steady-state conditions but significant when the base of the instrument is being subjected to rapid artificial cooling or heating. Using laboratory characterisation of the transmission and emissivity, together with use of an estimated solar calibration of the thermopile, generated mean differences of less than 1.5 Wm -2 to the two IRIS radiometers. A minimisation method using each IRIS radiometer as the reference also provided similar results, and the derived thermopile responsivity was within 0.3 µV W -1 m 2 of the solar-calibration-derived infrared responsivity estimate of 10.5 µV W -1 m 2 estimated using a nominal solar calibration and provide irradiances within ±2 % of the terrestrial irradiance measured by the reference pyrgeometers traceable to the International System of Units (SI). The calibration method using linear least squares regression introduced by Reda et al. (2012) that relies on rapid cooling of the ACP base but utilising the new equation was found to produce consistent results but was dependent on the assumed temperature of the air above the thermopile. This study demonstrates the potential of the ACP as another independent reference radiometer for terrestrial irradiance once the magnitude of the convection coefficient and any potential variations in it have been resolved.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

ReNew100: Reliable Power System Operation with 100% Renewable Generation

The ReNew100 project has developed and demonstrated an operator support system (OSS) to operate power systems with 100% renewable power generation from inverter-based resources (IBRs) like wind and solar that significantly reduces the risk of widespread power outages in a simulated operational environment at Technology Readiness Level (TRL) 6. The OSS achieves resilient operation for power systems under changing operation modes including varying combinations of conventional and renewable generation, including cases with 100% renewable generation from wind and solar IBRs. The OSS continuously monitors the N-1 security of the power system, which refers to the ability of the power systems to survive single outages of power system elements, like the loss of a generator or a power line, without causing widespread power outages beyond those expected and planned for. If the OSS identifies that the system is not N-1 secure, an automatic Controller Parameter Optimization (CoPO) developed within Renew100 is activated to optimize the N-1 security of the system by tuning controller parameters within different assets like batteries, wind, and solar plants. The core innovation of ReNew100 is the development of this CoPO as well as the demonstration of the OSS for a real-time simulation of the Hawai'i Island power system. Moreover, Renew100 has developed new model calibration techniques for dynamic power system models and demonstrated them for Hawai'i Island.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [U. Chicago (main)] (ORCID:00090002189↗

DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

Zheng, Jake [Chicago U.] (ORCID:0009000218901379)↗

DOE OSTI2021

Selective Biosorption of Valuable Rare Earth Elements Among Co-Occurring Lanthanides

To meet the increasing demand for rare earth elements (REEs) essential for low carbon-intensity energy technologies, new methods are needed for selective REE extraction from unconventional resources. Only a few REEs have significant economic value, but isolation of target rare earths from co-occurring lanthanides is challenging due to their similar chemical behavior. We present a novel approach to enhance separation of specific REEs from lanthanide mixtures. Escherichia coli cells engineered with lanthanide binding tags (LBTs) were immobilized in nonadsorbing, permeable polyethylene glycol diacrylate beads and packed into continuous flow, fixed-bed columns. Breakthrough of 15 rare earths in the +3 oxidation state resulted in notable differences in adsorption selectivity, with greatest separation between europium (Eu) and lanthanum (La) due to competitive displacement. REE adsorption onto fixed-bed columns was predicted by coupling a surface complexation model to a calibrated one-dimensional dual porosity transport model that accounts for interbead advective and intrabead diffusive transport. A tradeoff between high-abundance, low-affinity native carboxyl sites and low-abundance, high-affinity engineered LBT sites dictates process recovery efficiency and selectivity. Key chemical and operational parameters are identified to maximize selective extraction of high-value lanthanides, achieving a threefold enhancement of Eu recovery relative to La in a mixed REE solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Estimating the Ages of FGK Dwarf Stars through the Use of GALEX FUV Magnitudes

Stellar age cannot be directly measured, yet age determinations are fundamental to understanding the evolution of stars, planets, and galaxies. The work presented here builds upon the idea of a stellar-activity age. We utilized far-ultraviolet (FUV) photometry acquired by the Galaxy Evolution Explorer (GALEX) space telescope as an indicator of chromospheric activity to infer ages of late-F, G, and K type dwarf stars. We derived a purely empirical correlation between FUV magnitudes and stellar age in conjunction with (B − V) color. Our attention is restricted to Sun-like stars with color range 0.55⩽(B−V)⩽0.71 and absolute magnitude range 4.3 ≤ M {sub V} ≤ 5.3. The correlation is defined in terms of a FUV-excess parameter Q(FUV−B,B−V). We related stellar age, τ, to Q through the relation log{sub e}(τ)=log{sub e}(a)+bQ, where a and b are fit parameters and functions of (B − V). This correlation is functional up to 6 Gyr for FGK dwarfs. With such a correlation, one only needs Johnson (B − V) and FUV measurements to estimate the stellar age for Population i dwarf stars of solar-like temperature and metallicity. Such a calibration has utility in population studies of FGK dwarfs for further understanding of the chemical evolution of the Milky Way. As an illustration of one such application, we have constructed activity and FUV–age distributions for a sample of thin and thick disk stars, as distinguished by their chemical abundances. Considerable overlap is found between the activity distribution and age range of the two populations. We discuss the possibility that some high-[α/Fe] thick disk stars were formed as a result of the accretion of dwarf galaxies as recently as 4 Gyr ago.

79 ASTRONOMY AND ASTROPHYSICS↗