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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science

Nuclear fusion holds the promise of an endless source of energy. Several research experiments across the world and joint modeling and simulation efforts between the nuclear physics and high performance computing communities are actively preparing the operation of the International Thermonuclear Experimental Reactor (ITER). Both experimental reactors and their simulated counterparts generate data that must be analyzed quickly and in a resilient way to support decision making for the configuration of subsequent runs or prevent a catastrophic failure. However, the cost if the traditional techniques used to improve the resilience of analysis workflows, i.e., replicating datasets and computational tasks, becomes prohibitive with explosion of the volume of data produced by modern instruments and simulations. Therefore, we advocate in this paper for an alternate approach based on data reduction and data streaming. The rationale is that by allowing for a reasonable, controlled, and guaranteed loss of accuracy it becomes possible to transfer smaller amounts of data, shorten the execution time of analysis workflows, and lower the cost of replication to increase resilience. We develop our research and development roadmap towards resilient near real-time analysis workflows in fusion energy science and present early results showing that data streaming and data reduction is a promising way to speed up the execution and improve the resilience of analysis workflows.

Suter, Fred↗
DOE OSTI2024

Mid-Range Science Objectives for the Event Horizon Telescope

The first images of the black holes in Sagittarius A* and M87* have created a wide range of new scientific opportunities in gravitational physics, compact objects, and relativistic astrophysics. We discuss here the scientific opportunities that arise from the rich data sets that have already been obtained and the new data sets that will be obtained, exploiting a wide range of technical advances, including observational agility, receiver upgrades, and the addition of new stations. This document provides a 5-year framework for Event Horizon Telescope (EHT) science structured around four fundamental questions that are used to prioritize the analysis of existing data, guide technical upgrades, and determine the optimal use of future observational opportunities with EHT, ALMA, and multi-wavelength facilities. Through enhancements over this period, the EHT will create the first movie of M87* connecting black hole and jet physics, provide detailed studies of the structure and dynamics of Sgr A*, characterize the magnetospheres of both systems through polarimetric imaging, and explore the spacetime properties of black holes with greater precision and range.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dimuon production in the MicroBooNE detector

This analysis studies the production of the rare signal with two muons (dimuon) in the finalstate at µB using the Booster Neutrino Beam (BNB) as source of neutrino interactions. Themain background source for the dimuon signal are pions. Differentiating muons and pions hasbeen challenging at µB because the tracks left by these particles are almost identical. Thisanalysis faces this problem using a supervised classifier algorithm called boosted decisiontree (BDT). A Monte Carlo simulation (MC) enhanced dimuon signal sample was producedto train a BDT capable of recognizing this signal. A set of variables that show somediscrimination characteristics was used to perform the training. A MC neutrino interactionsimulation sample was used to estimate the background. Estimations of dimuon productionin real data samples were made for different cases. Additionally, an analysis of the systematicuncertainties, fake data studies, and BDT performance checks were obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Statistics and sensitivity of axion wind detection with the homogeneous precession domain of superfluid helium-3

The homogeneous precession domain (HPD) of superfluid He 3 has recently been identified as a detection medium which might provide sensitivity to the axion-nucleon coupling g a N N competitive with, or surpassing, existing experimental proposals. In this work, we make a detailed study of the statistical and dynamical properties of the HPD system in order to make realistic projections for a full-fledged experimental program. We include the effects of clock error and measurement error in a concrete readout scheme using superconducting qubits and quantum metrology. This work also provides a more general framework to describe the statistics associated with the axion gradient coupling through the treatment of a transient resonance with a nonstationary background in a time-series analysis. Incorporating an optimal data-taking and analysis strategy, we project a sensitivity approaching g a N N ∼ 10 − 12 GeV − 1 across a decade in axion mass. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Enhancing Modeling and Simulation for Effective Protection Strategies

This report was created by Sandia National Laboratories (SNL) to document the principles and methodology of performance data collection and integration with modeling and simulation tools to better facilitate the performance evaluation of physical protection systems (PPS). Results and conclusions from the use of modeling and simulation tools are only as good as the data employed by the tools when conducting analysis. Acquiring the performance testing data necessary to ensure effective evaluation can be a complex and sometimes daunting process. It is the desire of the organization to provide guidance that eases the burdens associated with pursuit of these objectives. This document draws heavily upon longstanding principles of systems engineering that have been developed and employed by SNL in the discipline of security since the 1970s. The scope of this document is constrained to the testing of system components and integration of data that is applicable within the context of PPS performance analysis using two tools that have been developed by SNL, PathTrace© and Scribe3D©. For guidance related to testing and evaluation more broadly, the manuals and reports referenced by this document can be consulted.

42 ENGINEERING↗
DOE OSTI2025

Discovering $\mu$Hz gravitational waves and ultra-light dark matter with binary resonances

In the presence of a weak gravitational wave (GW) background, astrophysical binary systems act as high-quality resonators, with efficient transfer of energy and momentum between the orbit and a harmonic GW leading to potentially detectable orbital perturbations. In this work, we develop and apply a novel modeling and analysis framework that describes the imprints of GWs on binary systems in a fully time-resolved manner to study the sensitivity of lunar laser ranging, satellite laser ranging, and pulsar timing to both resonant and nonresonant GW backgrounds. We demonstrate that optimal data collection, modeling, and analysis lead to projected sensitivities which are orders of magnitude better than previously appreciated possible, opening up a new possibility for probing the physics-rich but notoriously challenging to access $\mu\mathrm{Hz}$ frequency GWs. We also discuss improved prospects for the detection of the stochastic fluctuations of ultra-light dark matter, which may analogously perturb the binary orbits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Software For Advanced Large-scale Analysis Of Magnetic Confinement For Numerical Design, Engineering & Research (salamander)

As magnetic confinement fusion energy gains traction internationally to enable abundant energy production, designing components for fusion systems is a pressing challenge. During the planned lifetime of a fusion device, components evolve in extreme environments and must withstand large, repeated thermal loads and bombardment by 14 MeV neutrons, plasma ions, and neutral particles (deuterium, tritium, and helium), corrosive conditions, etc. All these physical processes take place simultaneously, interact in intricate ways, and impose important constraints that can affect performance. Experimental data is rare and costly to obtain, making design particularly challenging. Predictive computational frameworks must be an integral part of an accelerated and cost-effective design process by modeling fusion system performance in simulated environments. To better understand component degradation and operational impacts on their performance, the Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER) is designed as an open-source, fully integrated, multiphysics, multiscale, NQA-1 compliant framework facilitating 3D, high-fidelity fusion system modeling. To that end, SALAMANDER is a MOOSE-based framework, and therefore leverages MOOSE upstream libraries such as PETSc and libMesh to deliver sophisticated finite element, finite volume, and nonlinear solver technology for fusion energy simulations. SALAMANDER couples MOOSE physics module capabilities—such as thermal hydraulics, heat conduction, Navier-Stokes, and thermomechanics—with tritium transport via TMAP8, neutronics via Cardinal, and nascent particle-in-cell capabilities. Direct simulation Monte Carlo methods will be used to address neutral transport near the walls. By coupling all these physics in an integrated application, SALAMANDER will enable high-fidelity modeling of irradiation levels and plasma exposure conditions of plasma facing components and their impact on heat and tritium distributions, as well as the resulting mechanical constraints experienced by the plasma facing components and performance of blanket systems. Furthermore, SALAMANDER will be particularly suited for engineering studies thanks to the stochastic tool module readily available in MOOSE, allowing for extended uncertainty quantification and risk analysis studies. It is also able to use computer-aided design (CAD) meshes to model complex geometries, which is indispensable for fusion systems. SALAMANDER therefore supports design, safety, engineering, and research projects for magnetic confinement fusion systems

Simon, Pierre-Clement [Idaho National Laboratory (↗
DOE OSTI2025

Identification of low-momentum muons in the CMS detector using multivariate techniques in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV

“Soft” muons with a transverse momentum below 10 GeV are featured in many processes studied by the CMS experiment, such as decays of heavy-flavor hadrons or rare tau lepton decays. Maximizing the selection efficiency for these muons, while simultaneously suppressing backgrounds from long-lived light-flavor hadron decays, is therefore important for the success of the CMS physics program. Multivariate techniques have been shown to deliver better muon identification performance than traditional selection techniques. To take full advantage of the large data set currently being collected during Run 3 of the CERN LHC, a new multivariate classifier based on a gradient-boosted decision tree has been developed. It offers a significantly improved separation of signal and background muons compared to a similar classifier used for the analysis of the Run 2 data. The performance of the new classifier is evaluated on a data set collected with the CMS detector in 2022 and 2023, corresponding to an integrated luminosity of 62 fb -1 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Calibration of the DUNE Far Detector Using Cosmic-ray Muon Events

The Deep Underground Neutrino Experiment (DUNE) aims to set new limits on parameters associated with neutrino oscillations, neutrino astrophysics, and beyond the Standard Model (SM) searches such as nucleon decay. DUNE will quantify the magnitude of CP violation in the lepton sector, and determine the neutrino mass ordering. These benefit highly from the large target mass and excellent imaging, tracking, and particle identification capabilities of Liquid Argon Time Projection Chambers (LArTPCs). Detector calibration is essential to make precise physics measurements. For instance, accurate energy reconstruction is necessary for measuring many of the aforementioned quantities with the precision required for discovering new physics and fully exploiting the capabilities of the detector. Cosmic muons are a freely available natural source of calorimetric data and can be used for calibrating various detector parameters. This thesis provides an analysis of simulated cosmic-ray muon events generated with the Muon Simulation Underground (MUSUN) generator in the DUNE horizontal drift (HD) far detector (FD). The study focuses on analysing the energy and angular distribution of various classes of muon events, as well as characterising the different particles produced by cosmic muon interactions. The analysis of π0 → 2γ events within the cosmic-ray muon sample is presented in this thesis with a detailed study of reconstructing electromagnetic showers. The π0 mass is reconstructed within the DUNE FD, yielding a value of (136 ± 7) MeV/c2. Additionally, the thesis introduces methods for dE/dx calibration using simulated and reconstructed muon tracks. A calibration constant Ccal = (5.469 ± 0.003) × 10−3 ADC × tick/e is obtained through a model-dependent calibration process, where 1 tick corresponds to 500 ns of sampling time of an ADC. Furthermore, a calibration technique is presented, demonstrating precise translation from dQ/dx to dE/dx. This calibration method is applied to stopping muons, charged pions, and protons in the DUNE FD, addressing the measurement of energy loss in the detector volume. These are important calibrations of the DUNE FD and will contribute to achieving the exciting physics goals of the experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A New Measurement of the Neutron Electric Form Factor with the Super Bigbite Spectrometer Apparatus

Protons and neutrons, collectively known as nucleons, make up the nuclei at the core of atoms which form our world. The nucleon has been under intensive study for over 100 years, and yet we still do not fully understand the internal dynamics which govern properties like its spin or its mass-which contributes to almost all of the visible mass in the universe. These dynamics are governed by quantum chromodynamics(QCD), the predictions of which are experimentally tested at high energy accelerator facilities such as Jefferson Lab. TheGEN-II experiment (E12-09-016) is one such experiment. GEN-II is part of the Super Bigbite Spectrometer (SBS) experimental form factor pro gramme taking place in Hall A at Jefferson Lab, which aims to make precision measurements of the nucleon electromagnetic form factors(EMFFs)at record high values of squared four momentum transfer ¿2. EMFFs describe the electric and magnetic moment distributions within the nucleon. They can be measured through elastic electron scattering off the nucleon, and describe the recoil response of the target nucleon at a given energy scale. GEN-II is a double polarized semi-exclusive beam target asymmetry (BTA) experiment, seeking to measure the electric form factor of the neutron,¿¿ ¿,at three new values of squared four-momentum transfer¿2 =2.92,6.74and9.82GeV². The latter two points being at record high ¿2. The form factor is determined through measuring the BTA of quasielliptical scattering of a neutron from a polarized nuclear target. The experiment utilized the CEBAF accelerator to produce longitudinally polarized electrons up to ~85% polarization, which were scattered off neutrons within a novel polarized helium-3 (³He) target. This new polarized ³He target was employed by building on the technology of its precursors which existed in similar preceding experiments. This target was designed to operate at the high luminosities typical of Hall A, and reached a record breaking combination of polarization and beam intensity known as figure of merit, three times larger than those predecessors. The SBS collaboration designed and constructed two brand new high acceptance spectrometers for these experiments, an electron arm named Bigbite (BB) and a hadron arm named Super Bigbite. Both spectrometers featured a large acceptance EM dipole magnet, and complementary detector systems. The electron arm contained gaseous electronmultipliers(GEMs) which were used for high precision tracking of the scattered electrons, a heavy gas cherenkov (GRINCH) which was used for PID between electrons and pions, a plastic i ii scintillator timing hodoscope to provide high resolution timing of the start of events, and a pair of EM calorimeters (BBCal) which provided energy measurements of detected particles, and provided the experimental trigger. The hadron arm also contained a system of GEMs which will be utilized for future SBS experiments, and a hadron calorimeter designed to provide position, timing and energy measurements of the recoiling nucleon. The calibration of all detector subsystems, beam and target data is discussed, with a focus on novel timing calibrations to the hodoscope and hadron calorimeter. An analysis of selecting quasielliptical events and suppressing background contributions from a number of sources which contaminate the final event sample is given. The largest irreducible backgrounds are found to be from misidentified protons, timing accidentals and inelastic events. The physical asymmetry is measured and used to extract a value for the form factor ratio ¿¿ ¿/¿¿ ¿. High precision ¿2 data for ¿¿ ¿ is used to then extract ¿¿ ¿. This work finds at ¿2 = 2.92 GeV2 that ¿¿ ¿ = 0.0129+0.0019 -0.0020. This result is in statistical agreement with existing fits to world data, and predictions from the constituent quark model and Dyson–Schwinger equations, in this region of ¿2.

Penman, Gary [Univ. of Glasgow, Scotland (United K↗
DOE OSTI2024

Measuring Neutron Polarisation in Deuteron Photo-disintegration with the CLAS Start Counter [Thesis]

Deuteron photo-disintegration (γd → γp) is a reaction that represents the simplest case in which nuclear and hadron physics models can be tested. Despite this, associated polarization analyses are limited in terms of angular coverage and energy ranges, especially in observables related to the recoil neutron. This is largely due to a lack in dedicated polarimetry equipment, and represents a roadblock in global progress to understand high-energy phenomena such as hexaquarks, and quark-gluon degrees of freedom. To address this problem, this PhD thesis pioneers a new methodology for the parasitic measurement of nucleon polarization using kinematic reconstruction of (spin-dependent) nucleon-nucleus scattering of reaction products, prior to their detection in large acceptance particle detector apparatus. Following this novel approach, which requires no dedicated polarimeter, a determination of the double polarization observable, $C^n_{x'}$, from deuteron photo-disintegration is presented, using Jefferson Lab’s CLAS detector. The analysis utilizes the (n,p) charge exchange reaction in CLAS’s "start counter" (plastic scintillator) to determine the final state neutron polarizations. The results present the first ever data for this observable above 0.7 GeV (photon beam energy) and significantly extend the angular range of the world data set. This new data is largely statistically consistent with the previous measurement of $C^n_{x'}$ by Bashkanov et al . in the overlapping energy range of 0.4-0.7 GeV. It is planned for the statistical accuracy of the presented result to be increased by the inclusion of additional data. The analysis herein serves as a key proof of concept for future applications, including a recommended similar analysis to be implemented with data from the more modern CLAS12 detector. This paves the way for a plethora of additional analyses using existing data sets that would provide crucial new constraints for hadron and nuclear physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Modeling and Energy Analysis of Refrigeration Systems in Supermarkets: A Case Study

Refrigeration systems are the single largest consumer of electricity in supermarkets, accounting for approximately 40–60% of total store electricity use. As supermarkets face increasing pressures to improve efficiency and reduce operational costs, understanding the energy performance of refrigeration systems in supermarkets has become essential. In this paper, we investigate the energy performance and patterns of the refrigeration system using field measurements in one supermarket. The compressor coefficient of performance (COP) averaged 4.5 during nighttime steady-state operation, providing a practical efficiency benchmark. We develop simple physical-based load models for the display cases in the supermarket, where the refrigeration system uses R404A. The results show the display case models achieve a good agreement with measured data, validating its utility for energy estimation during unoccupied hours. Finally, the analysis reveals several challenges of data collection systems for refrigeration systems in the supermarket industry as well.

Chen, Yimin [ORNL] (ORCID:0000000338181655)↗
DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Machine learning neutrino-nucleus cross sections

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries—can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Unique & challenging aspects of plutonium metal standards exchange program for actinide measurements

The Los Alamos National Laboratory exchange program is the only program of its kind for the distribution of plutonium (Pu) standards materials with a range of impurity contents to multiple laboratories for destructive measurements of elemental concentration. This paper discusses statistical methods used to address challenges in Pu metal exchange data by way of two case studies. Challenges include how to evaluate a data set when a large fraction of the values are minimum detection limits (MDLs), and how to determine potential outliers with limited in-formation on the true spread of the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

User Guide: A Curated Dataset of Regional Meteor Events with Simultaneous Optical and Infrasound Observations

This user guide supports a curated dataset of 71 meteor events recorded between 2006 and 2011 in Southwestern Ontario, Canada. Each event was simultaneously observed by ground-based optical cameras and an infrasound array, providing a rare opportunity to examine meteor trajectories and acoustic signals from the same atmospheric entry events. The dataset includes raw and processed optical data, meteor trajectories, photometric light curves, infrasound waveforms, and atmospheric specifications relevant for acoustic modeling. The archive is structured to support reproducible research in meteor physics, atmospheric acoustics, and shock wave analysis. It is organized following transparent file naming conventions and structured folders to facilitate scientific reuse, comparison, and integration across research domains. The dataset is freely available on Zenodo, doi: 10.5281/zenodo.15868512.

54 ENVIRONMENTAL SCIENCES↗