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DOE OSTI2025

XRISM Constraints on Unidentified X-Ray Emission Lines, Including the 3.5 keV Line, in the Stacked Spectrum of 10 Galaxy Clusters

We stack 3.75 Ms of early XRISM Resolve observations of 10 galaxy clusters to search for unidentified spectral lines in the E = 2.5–15 keV band (rest frame), including the E = 3.5 keV line reported in earlier low spectral resolution studies of cluster samples. Such an emission line may originate from the decay of the sterile neutrino, a warm dark matter (DM) candidate. No unidentified lines are detected in our stacked cluster spectrum, with the 3σ upper limit on the m s ∼ 7.1 keV DM particle decay rate (which corresponds to an E = 3.55 keV emission line) of Γ ∼ 1.0 × 10 −27 s −1 . This upper limit is 3–4 times lower than the one derived by Hitomi Collaboration from the Perseus observation but still 5 times higher than the XMM-Newton detection reported by E. Bulbul et al. in the stacked cluster sample. XRISM Resolve, with its high spectral resolution but small field of view, may reach the sensitivity needed to test the XMM-Newton cluster sample detection by combining several years worth of future cluster observations.

Astronomy and AstroPhysics↗

DOE OSTI2024

Kernelized approaches to streaming compression of scientific data

In this paper three algorithms are developed for the streaming compression of scientific data. The algorithms presented are reliant on the theory of vector-valued reproducing kernel Hilbert spaces and operator valued kernel. Further, the scientific data is modeled as a snapshot of time dependent vector field F(x, t) over a manifold M and the recovery of the data is framed as a learning problem. These processes are then appropriately modified and ana lyzed for the streaming scenario in which data is generated without the ability to revisit past entries.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors. This evaluation is performed using ground truth data, obtained by measuring the lane positions and transforming them into pixel coordinates. The performance of each method is assessed using the statistical R2 score, indicating the correlation between the detected lane lines and the ground truth. The results show that the U-Net camera-based method exhibits limitations in accurately detecting and aligning the lane lines, particularly in challenging scenarios. However, the radar-based lane detection method demonstrates a strong correlation with the ground truth which implies that the use of this sensor may improve current reliability issues from conventional camera lane detection approach. Furthermore, the study highlights the limitations of the U-Net model for camera lane detection, especially in scenarios with sun glare. This study shows that infrastructure-based radar retro-reflectors can improve autonomous vehicle lane detection reliability. The integration of different sensor modalities and the development of advanced computer vision algorithms are crucial for improving the accuracy, reliability, and energy efficiency of lane detection systems. Addressing these challenges contributes to the advancement of autonomous vehicles and the realization of safer and more efficient transportation systems.

Brown, Nicolas E.↗

DOE OSTI2025

TDCOSMO - XVII. New time delays in 22 lensed quasars from optical monitoring with the ESO-VST 2.6m and MPG 2.2m telescopes

We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σ depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag – similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.Key words: methods: data analysis / surveys / distance scale

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

An Advanced Cyber-Physical System Security Testbed for Substation Automation

A Cyber-Physical System (CPS) testbed serves as a powerful platform for testing and validating cyber intrusion detection and mitigation strategies in substations. This study presents the design and development of a CPS testbed that can effectively assess the real-time dynamics of a substation. Cyber attacks exploiting IEC 61850-based SV and GOOSE protocols are demonstrated using the testbed, along with an analysis on attack detection. Realistic timing measurements are obtained, and the time frames for deploying detection and mitigation strategies are evaluated.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Intrinsic alignment demographics for next-generation lensing: Revealing galaxy property trends with DESI Y1 direct measurements

We present direct measurements of the intrinsic alignments (IA) of over 2 million spectroscopic galaxies using DESI Data Release 1 and imaging from four lensing surveys: DES, HSC, KiDS, and SDSS. In this uniquely data-rich regime, we take initial steps towards a more tailored IA modelling approach by building a library of IA measurements across colour, luminosity, stellar mass, and redshift. We map the dependence between galaxy type -- in terms of rest-frame colour, strength of the 4000 Angstrom break, and specific star formation rate -- and IA amplitude; the bluest galaxies have an alignment consistent with zero, across low ($0.05

Siegel, J. [Princeton U.]↗

DOE OSTI2025

HAMscope: a snapshot Hyperspectral Autofluorescence Miniscope for real-time molecular imaging

We introduce HAMscope, a compact, snapshot hyperspectral autofluorescence miniscope that enables real-time, label-free molecular imaging in a wide range of biological systems. By integrating a thin polymer diffuser into a widefield miniscope, HAMscope spectrally encodes each frame and employs a probabilistic deep learning framework to reconstruct 30-channel hyperspectral stacks (452-703 nm) or directly infer molecular composition maps from single images. A scalable multi-pass U-Net architecture with transformer-based attention and per pixel uncertainty estimation enables high spatio-spectral fidelity (mean absolute error ∼0.0048) at video rates. While initially demonstrated in plant systems, including lignin, chlorophyll, and suberin imaging in intact poplar and cork tissues, the platform is readily adaptable to other applications such as neural activity mapping, metabolic profiling, and histopathology. We show that the system generalizes to out-of-distribution tissue types and supports direct molecular mapping without the need for spectral unmixing. HAMscope establishes a general framework for compact, uncertainty-aware spectral imaging that combines minimal optics with advanced deep learning, offering broad utility for real-time biochemical imaging across neuroscience, environmental monitoring, and biomedicine.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Transmission electron microscopy of ion irradiated ODS MA956 samples

Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).

Prabhakaran, Ramprashad↗

DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗

DOE OSTI2025

Transcriptomics outputs and phylogenetic trees used for pathway discovery of diterpenoid alkaloids in Delphinium and Aconitum

Transcriptome assemblies, open reading frames in nucleotide and peptide sequences, clustered transcriptomes and corresponding amino acid files, and expression matrices in TPM and raw counts for RNA-seq datasets from Delphinium grandiflorum, Aconitum plicatum, Aconitum lycoctonum, Aconitum carmichaelii, Aconitum japonicum, Aconitum kusnezoffii, and Aconitum vilmorinianum. Also included are phylogenetic trees for terpene synthases and cytochromes P450 mined from these assemblies.

biosynthesis↗

DOE OSTI2026

A Fast, Accurate Prediction for System-Wide Damage Due to Dynamic Wind Loading

The complex relationship between photovoltaic (PV) hardware configurations, overall system dynamics, and turbulent aerodynamic phenomena generates highly unsteady, non-uniform loads that can lead to damaging instabilities. These effects may result in glass breakage, cell cracking, and structural failures in frames and mounting systems, even under moderate wind conditions. Addressing industry concerns about premature system failures in field conditions deemed survivable, our research aims to develop a fast and accurate predictive model for system damage. This model integrates configurable hardware choices with advanced simulation tools to represent the overall system-specific dynamics effectively. Using this model, we predict responses under varying weather conditions and hardware setups, translating these predictions into pre-trained surrogate models capable of accurately identifying failure risks and rapidly testing new system hardening measures. In this presentation, we will showcase preliminary results in capturing system dynamics through our customizable library of PV hardware configurations. Additionally, we will highlight how these new tools build upon PVade's established wind load modeling capabilities and foster the development of advanced AI/ML surrogates for improving system robustness.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

ACE Science Workshop Report

We summarize the Fermilab Accelerator Complex Evolution (ACE) Science Workshop, held on June 14-15, 2023. The workshop presented the strategy for the ACE program in two phases: ACE Main Injector Ramp and Target (MIRT) upgrade and ACE Booster Replacement (BR) upgrade. Four plenary sessions covered the primary experimental physics thrusts: Muon Collider, Neutrinos, Charged Lepton Flavor Violation, and Dark Sectors. Additional physics and technology ideas were presented from the community that could expand or augment the ACE science program. Given the physics framing, a parallel session at the workshop was dedicated to discussing priorities for accelerator R&D. Finally, physics discussion sessions concluded the workshop where experts from the different experimental physics thrusts were brought together to begin understanding the synergies between the different physics drivers and technologies. In December of 2023, the P5 report was released setting the physics priorities for the field in the next decade and beyond, and identified ACE as an important component of the future US accelerator-based program. Given the presentations and discussions at the ACE Science Workshop and the findings of the P5 report, we lay out the topics for study to determine the physics priorities and design goals of the Fermilab ACE project in the near-term.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Special Considerations for the Removal and Disposal of Micro-Reactor Experiments

Idaho National Laboratory (INL) is preparing to host several microreactor experiments through 2030 and beyond. Two new test beds currently under development will operate as microreactor or nuclear system experiment user facilities. Test bed experiments will be performed in series, with each nuclear experiment installed, operated, and removed before installation of the subsequent experiment. The necessarily brief transition period between experiments introduces unique equipment removal and radioactive waste disposal challenges. This paper evaluates equipment removal and radioactive waste management topics associated with tight sequencing of nuclear experiments and presents some of the solutions and approaches currently planned to meet these special considerations for one such experiment, the Molten Chloride Reactor Experiment (MCRE), slated for operation at INL’s Laboratory for Operation and Testing in the United States (LOTUS). The MCRE project is a collaboration between Southern Company Services, TerraPower, and INL, among others, to provide integral nuclear data that will advance molten salt fast reactor technology. MCRE will be the first critical fast-spectrum circulating fuel system ever operated and the first experiment operated in the LOTUS test bed. The experiment will nominally operate at zero power with planned low power excursions as part of operational planning for MCRE has been to minimize at-power operations to limit fission product formation while still achieving experimental objectives. After the experiment is complete, MCRE will be allowed to radioactively decay for a short period (nominally 90 days) prior to system defueling, flushing, removal, and disposal of all MCRE equipment, readying the test bed for the next nuclear experiment. Equipment removal and radioactive waste disposal have been integral to MCRE project planning since the Cooperative Research and Development Agreement was formalized in 2021. Due to requirements for future use of the test bed, the MCRE system, of necessity, must be removed in a much shorter time frame than typical for historic reactor decommissioning projects at INL. This results in minimal time for radioactive decay, resulting in not only elevated radiation dose rates but also the presence of short-to-medium-lived isotopes not typically encountered in the reactor decommissioning and radioactive waste management space. Additional unique constraints placed on the project include lack of intrinsic remote-operations capabilities in the test bed, space constraints in the test bed once MCRE has been installed, and contamination minimization requirements to return the test bed to as-found conditions to enable future use. This paper discusses planned solutions to these challenges. Approaches for implementing remote or semi-remote technologies in a non-hot cell environment with limited space availability are discussed. The paper also summarizes the systems engineering approach for concept development and design of equipment removal systems, which are being implemented concurrent with the MCRE design phase, providing feedback to system designers to incorporate features enabling efficient and safe equipment removal approaches. The timing of this paper at a relatively early phase of the project is meant to highlight the importance of early planning for nuclear system decommissioning while reactor design is ongoing to allow design feedback on componentry driven from decommissioning system needs. As new, innovative nuclear reactor technologies enter the nuclear market sector, reactor experiments are crucial for providing new integral nuclear data that establish safe operational margins for technology advancement. Microreactor experiments at INL will require safe, effective, and timely decommissioning approaches, which in turn require nuclear systems designed to expedite decommissioning. In addition to the advancement of nuclear reactor technologies, these nuclear experiments provide an opportunity to demonstrate, deploy, and test new removal and disposal capabilities to support the next generation of nuclear reactor technology.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems: Preprint

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the Pennsylvania-New Jersey-Maryland Interconnection (PJM), in a competitive electricity market. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure and vulnerable communication networks to a multitude of cybersecurity threats. These evolving threats not only endanger grid operations but also have the potential to trigger cascading disruptions across the broader grid network and influence regulation markets. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events and provide a comprehensive situation awareness to grid operators. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a fully active BESS topology using the slow regulation signal (Reg A) coming from the PJM market. Our simulation results reveal that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's instability and economic loss during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗

DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials: Preprint

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. The benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite materials↗

DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials

composite materials↗

DOE OSTI2024

YOU-ONLY-LOOK-ONCE (YOLO) FOR RADIO FREQUENCY SIGNAL CLASSIFICATION

We propose a method that uses deep learning (DL) to identify and frame various signals that are present in an environment. This DL framework is based on the You Only Look Once (YOLO) object detection pipeline Our work demonstrates a specific application of high performance computing and computer vision to the field of telecommunications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Angular Distribution of Dimuons from Drell-Yan Production in p+Fe Interactions at 120 GeV Beam Energy

In the E906/SeaQuest Fermilab experiment, we report a measurement of the angular distributions by measuring the angular parameters $\lambda$, $\mu$, and $\nu$ of Drell-Yan dimuons produced using a 120 GeV proton beam incident on an iron target. The angular distribution in the naive Drell-Yan model does not show any $\cos2\phi$ dependency, where $\phi$ denotes the azimuthal angle of dimuons in the Collins-Soper frame. However, pion-induced Drell-Yan experiments, such as NA10 and E615, have observed a significant dependence on $\cos2\phi$. The Boer–Mulders function, a transverse momentum-dependent distribution function, represents the correlation between the transverse spin and the transverse momentum of the quark. A non-zero Boer-Mulders function or an improved higher-order Drell-Yan model considering QCD effects can produce a $\cos 2\phi$ modulation in the Drell-Yan angular distribution. To measure the angular distributions, we have used an event mixing method to construct the combin atorial background, which was then subtracted from the data to isolate the Drell-Yan signal. Following this, we corrected the detector, trigger, and reconstruction efficiencies using a doubly-iterative Bayesian Unfolding method. This iterative unfolding technique improves the response matrix based on the results of the previous unfolding step, ensuring robust convergence without exaggeration of uncertainties. The angular distributions of the dimuons were measured over the invariant mass range $5.0 < M_{\mu^+ \mu^-} < 8.0$ $GeV/c^2$, with dimuon transverse momentum $P_T < 2$ GeV/c and Feynman-x $-0.18 < x_F < 0.9$. The measured angular distributions are then compared with the QCD calculations for $p + \text{Fe}$ interactions, and proton-induced angular distribution measurements from other experiments. We have observed weak $\cos 2\phi$ modulations as a function of $P_T$. For $P_T > 1.0 \, \text{GeV}/c$, the predicted NNLO perturbative QCD value of $\nu$ is larger than what we have me asured at E906/SeaQuest. Moreover, we have not observed a strong dependence of $\nu$ on the kinematic variables, such as dimuon mass $M_{\mu^+ \mu^-}$ and Bjorken-$x$. The spin alignment of the virtual photon, $\lambda$, measured from the SeaQuest Drell-Yan $p+\text{Fe}$ data, is found to be strongly dependent on $P_T$, decreasing as $P_T$ increases. $\lambda$ also holds to the upper bound condition $\lambda < 1.0$ within the statistical uncertainty, showing a trend similar to that predicted by NNLO perturbative QCD. However, for $1.0 < P_T < 2.0 \, \text{GeV}/c$, the extracted $\lambda$ value from SeaQuest is smaller than that predicted by perturbative QCD at NNLO.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗