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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 OSTI2025

Content-aware foveated camera for multi-target tracking

Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing a single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.

Zang, Zihan [Univ. of California, Los Angeles, CA ↗
DOE OSTI2024

Nonlinear control of the minimum safety factor in tokamaks by optimal allocation of spatially moving electron cyclotron current drive

The minimum value of the safety factor profile is related to the magnetohydrodynamic (MHD) stability of the plasma confined in a tokamak. Therefore, active control of the minimum safety factor may mitigate MHD instabilities that can degrade or even terminate plasma confinement. Typically, in most tokamak scenarios, the minimum safety factor evolves spatially with time, i.e., the location at which the safety factor achieves the minimum value changes with time. In addition to the inherent nonlinearities in the minimum safety factor evolution, its spatial variation makes the control design challenging. In particular, complexity in control design may arise from the need for time-dependent nonlinear models that account for spatial variation of the minimum safety factor. Furthermore, the minimum safety factor may drift to locations where the actuator authority is low. The problem of minimum safety factor control with target location tracking and moving electron cyclotron current drive (ECCD) is addressed in this work. A nonlinear time-dependent model that incorporates the spatial variation of the minimum safety factor is presented. A nonlinear controller based on optimal feedback linearization is developed to track a target minimum safety factor. The proposed controller treats the ECCD position as a controllable variable. In other words, the controller prescribes the ECCD position (in addition to the non-inductive powers) in real time based on an optimal criterion that is defined a priori. This work also presents the steps necessary to integrate the minimum safety factor controller with a total energy controller to achieve multiple control objectives simultaneously. In conclusion, the proposed integrated control algorithm is tested using nonlinear simulations in the Control Oriented Transport SIMulator (COTSIM) for a DIII-D tokamak scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The Satellite Image Simulation Toolkit

The Satellite Image Simulation Toolkit (SatIST) is a python software package designed to generate diverse and realistic satellite imaging scenarios. It serves as a toolkit for simulating data that supports the development and testing of algorithms used in satellite detection, calibration, and characterization. SIST provides a suite of simulation tools that allow users to replicate various satellite observation conditions, including sidereal and target tracking. By enabling the creation of scenarios that mimic real-world satellite operations, SIST facilitates advancements in satellite image data processing and the study of satellite behavior under different observational parameters.

Perloff, AlexxS [Lawrence Livermore National Labor↗
DOE OSTI2025

Strategies for the in-orbit gain tracking using the modulated X-ray sources for the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission

Accurate and precise correction of the gain drift is the key to achieve the required energy resolution of the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission (XRISM). Therefore, Resolve is equipped with highly configurable X-ray sources called the modulated X-ray source (MXS). The pulsed nature allows us to separate calibration and astrophysical X-rays by time interval selections. However, undesirable characteristics of the MXS, such as the afterglow X-rays, restrict the allowed configuration range. Moreover, the nonlinear and discontinuous behaviors of the calibration line count rate make the determination of the optimal setting highly complex. The MXS count rate model has been established using measurements in the spacecraft thermal vacuum test with the flight detector and MXS. A trade-off study using the model enables us to choose a few settings for the continuous use of the MXS optimized for different ranges of target gain tracking intervals. An alternative approach, where the MXS is used only intermittently, has also been developed and implemented. This new mode enables us to reconstruct the drift without having most of the undesirable effects in science data. This also forms the basis of the gain tracking under the current Resolve configuration with the closed gate valve.

Astronomy and AstroPhysics↗
DOE OSTI2024

Optimal control of the electron temperature profile in DIII-D using machine learning surrogate models

The viability of the tokamak as a potential fusion reactor depends on the ability to keep the plasma in a stable regime while achieving temperatures, densities, and confinement times that are as high as possible. Tokamak scenario development attempts to find plasma regimes that achieve all of these conditions and are accessible with a given set of hardware constraints. This requires the ability to control plasma properties such as the normalized beta, the internal inductance, safety factor, rotation, etc. One property that has received less attention than some of the others, but is no less critical to achieving high performance, is the electron temperature (T e ) profile. In this work, Linear Quadratic Integral (LQI) control is used to develop a controller for the electron temperature profile in DIII-D. The controller is based on a linearized model derived from the transport equation that describes the evolution of the electron temperature, and includes contributions from the neural network surrogate models NubeamNet and MMMnet. Furthermore, the controller is tested in simulation using COTSIM, and is proven capable of tracking a target T e profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

MOD-Amp System Design Spring: Spring 2026 – Georgetown University, SYSM–5620

High-energy lasers (HELs) play an important role in both national defense and scientific research. In defense applications, HELs are used for target detection, tracking, and engagement. In research environments, they support studies of extreme physical conditions relevant to fusion energy and plasma science. These systems depend on the amplification of light through stimulated emission of radiation, allowing optical energy to be increased to the levels required for operation. This amplification occurs when light passes through an energized gain medium that receives energy from an external optical or electrical source. To achieve the desired output, laser systems often use multiple amplification stages, including high-gain preamplifiers and lower-gain power or booster amplifiers. At Lawrence Livermore National Laboratory (LLNL) and other national laboratories, many large-aperture laser amplifier systems are aging and rely on system-specific hardware, obsolete technologies, and incomplete documentation. These legacy systems create challenges for maintenance, supportability, and long-term operation. Their lack of standardization also increases the difficulty of sustaining reliable performance over time. As this infrastructure continues to age, the likelihood of unplanned downtime grows, which can negatively affect both national security missions and scientific research programs that depend on dependable HEL capabilities. The purpose of this document is to demonstrate the application of systems engineering fundamentals and design thinking through the development of a laser amplifier case study. The proposed system concept is intended as an academic exercise and not as a finalized engineering design. As a result, the development presented in this document is incomplete and may contain technical assumptions or errors that would require further investigation before any real-world implementation.

42 ENGINEERING↗
DOE OSTI2026

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗
DOE OSTI2026

Performance of the Particle-Identification Silicon-Telescope Array coupled with the VAMOS++ magnetic spectrometer

The Particle-Identification Silicon-Telescope Array (PISTA) is a new detection system designed for high-resolution studies of fission process induced by multi-nucleon transfer in inverse kinematics. It is specifically optimized for experiments with the VAMOS++ magnetic spectrometer at GANIL (Grand Accélérateur National d’Ions Lourds). The array comprises eight trapezoidal ΔE-E silicon telescopes arranged in a lamp shade configuration. Each telescope integrates two single-sided stripped silicon detectors, enabling target-like recoil identification, energy loss measurements, and trajectory reconstruction. Positioned in close proximity to the target, PISTA’s compact geometry achieves high-efficiency tracking of target-like recoils produced in multi-nucleon transfer reactions at Coulomb barrier energies. The spatial segmentation of the array allows precise determination of the mass and charge of the target-like nucleus, and excitation energy of fissioning systems. This work presents the particle identification and excitation energy reconstruction performances for the interactions of 238 U beam with 12 C target. An excitation energy resolution of 800 keV (FWHM) was determined together with mass resolution of 1.1% (FWHM). The combination of PISTA and VAMOS++ magnetic spectrometer enables unprecedented investigations of the fission process as a function of the excitation energy of the fissioning nucleus, particularly for exotic systems produced in transfer-induced reactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Measurement of the Neutron Elastic Electromagnetic Form Factor Ratio at Large Momentum Transfer

Exploring nucleon structure is vital both for understanding its origin and existence as well as for the advancement of the sciences. It helps us answer key questions such as how quark and gluon dynamics create 99% of the nucleon mass. Electron- nucleon scattering has been widely used for precision studies of the nucleon and nuclear structure since the Nobel Prize winning investigations by Robert Hofstadter and collaborators in the 1950s. These studies provide information about the spatial charge and current densities of the nucleon in terms of the electromagnetic form factors. The form factors are functions of four momentum transfer squared (Q2). Extending the electromagnetic form factor measurements to higher Q2 plays a critical role in furthering the understanding of nucleon structure. This motivated the Super BigBite Spectrometer (SBS) program at Jefferson Lab. The open nature of the spectrometers and the direct line of sight from the target to the tracking detector locations in experimental setups such as SBS creates high levels of background at the detectors. This necessitates the use of tracking detectors with high rate capability and good position resolution. Gas Electron Multiplier (GEM) detectors are an excellent choice for tracking detectors in such experiments. Understanding the performance of the GEM detectors is important not just for SBS experiments but also for future high-luminosity experiments. This thesis reports the exploratory results from the measurement of the neutron elastic electromagnetic form factor ratio (Gn E/Gn M) at high momentum transfer. A longitudinally polarized electron beam was scattered off a polarized 3He target, used as an effective polarized neutron target. In this experiment, the polarized 3He target achieved a world record polarization weighted luminosity at a beam current of 45 µA. Double spin asymmetry of the scattered neutron events is used to extract the neutron form factor ratio. Measurements were taken at Q2 = 3.0, 6.8, 9.8 (GeV/c)2. The lowest Q2 measurement is in good agreement with the existing world data, and the higher-Q2 measurements extend the Q2 reach well beyond the existing world data and are expected to remain unmatched for a long time.

Gamage, Vimukthi Haththotuwa [Univ. of Virginia, C↗
DOE OSTI2025

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗
DOE OSTI2024

Forest Carbon Storage in the Western United States: Distribution, Drivers, and Trends

Abstract Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Environmental Sciences & Ecology↗
DOE OSTI2025

Searching for Neutrino Tridents in the NOvA Near Detector

This dissertation presents a search for neutrino trident production in the NOvA near detector through the coherent ``dimuon" channel: $\nu_\mu +\hspace{1pt}\text{X} \rightarrow \nu_\mu + \mu^- + \mu^+ +\hspace{1pt}\text{X}$. Trident production is a rare, purely electroweak process with sensitivity to physics beyond the Standard Model. The theoretical background, motivation for studying the process, and previous experimental measurements are reviewed. The analysis uses data collected by the NOvA near detector (ND) from Fermilab's Neutrinos at the Main Injector (NuMI) beam between November 2014 and February 2024, corresponding to an exposure of $25.5\times 10^{20}$ protons on target. The ND is a segmented tracking calorimeter located 800~m from the beam target, receiving neutrinos with a mean energy of 2~GeV. A multi-pass background reduction strategy is implemented, including the development of a novel dimuon-specific tracking technique. Trident candidates are identified using a boost ed decision tree classifier trained on simulated signal and background events. Limited background Monte Carlo statistics necessitate the use of functional fits to sideband data, which are extrapolated to estimate backgrounds in the signal region. The unblinded data contain 9 trident-like events, with an estimated background of 5.66 $\pm$ 5.15 events. This yields a best fit estimate of 3.34 tridents compared to the Standard Model prediction of 4.66. A profiled Feldman-Cousins method is used to determine a 90\% confidence interval of [0,9.1] on the number of signal events, corresponding to an upper limit of 1.95$\times$ the Standard Model prediction. This result represents the lowest energy search for trident events to date, and the first experimental contribution to the process in 27 years.

Bowles, Reed Scott [Indiana U.]↗
DOE OSTI2025

Status and prospects for inertial fusion energy via lasers

Fusion energy is the ultimate clean and limitless energy source, but its development requires overcoming many scientific and technological challenges. For the first time in the 60-year long history of fusion research, ignition and target gain above unity (G>1) were demonstrated in the laboratory at the National Ignition Facility at the Lawrence Livermore National Laboratory in 2022. Turning laser fusion into an energy source requires that the results from single shot experiments be replicated at much higher repetition rates of many shots per second to produce high average power at relatively low cost. Furthermore, this requires the development of new laser technologies, mass production of suitable targets, accurate injection and tracking systems and new materials for the reactor chamber components and final optics. Ultra broadband and deep UV light are laser advances that can dramatically improve the laser energy coupling to the target thereby reducing the laser energy and power requirements.

Fusion energy↗
DOE OSTI2025

Correcting beam space charge effects in Active-Target Time Projection Chamber

By providing a large gaseous volume for nuclear interactions while simultaneously recording the tracks of resulting reaction products, an active target serves as both a thick target and a detector. Once a reaction occurs, the emitted charged fragments strip electrons from the target gas along their path as they transverse the detector. Collection of these stripped electrons allow for detection of the product tracks. As beam intensity increases, the resulting ionization in the active target can significantly distort this collection of electrons. If left uncorrected, the resulting measurements could be wrong. In this paper, we investigate the impact of the space charge produced by heavy radioactive beams within the Active Target - Time Projection Chamber at Michigan State University. The beams are injected parallel to the electric field of the time projection chamber which is operated without a magnetic field for this experiment. Furthermore, we analyze the rate dependence of the space charge effects and demonstrate that they can be modeled and effectively corrected.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Using Eye Tracking to Elucidate the Mechanisms Underlying Stimulation-Enhanced Visual Target Detection

Transcranial direct current stimulation (tDCS) is a noninvasive form of brain stimulation that involves passing a weak electrical current between electrodes on the scalp to modulate underlying neural tissue. TDCS has been shown to modulate cognition in a variety of domains, including memory, attention, and visual processing. Prior work from our laboratory has shown positive effects of tDCS on learning to detect target objects hidden in complex naturalistic visual scenes and learn rules for categorizing images, though the mechanism for these benefits remains unknown. One possibility is that tDCS optimizes visual search by modulating visual attention or via the reduction in search errors. One method of quantifying visual attention is to use eye tracking to record search patterns to determine if and how visual search is adjusted under verum stimulation conditions. Eye tracking data allows classification of errors into error types, including sampling errors (failing to look in the relevant region), recognition errors (looking at the critical portion of a scene, but failing to recognize it as such as evidenced by visual fixation), and decision-making errors (fixating on the relevant portion of a scene, but making the wrong determination). Our results indicate that the benefit tDCS confers on visual search for targets stems from the reduction in decision-making errors when targets are present (Cohen’s d = 0.86). Also reported is a replication of previous findings showing a tDCS-dependent improvement in learning this task, learning score (Cohen’s d = 0.88); d’ (Cohen’s d = 1.00). This provides support for moving tDCS into the application space by pairing it with analysts who are concerned with the type of search error that is corrected via stimulation.

attention↗
DOE OSTI2025

Direct Reactions and Spectroscopy with Hydrogen Targets at the RIBF

The implementation of MINOS, a liquid-hydrogen target and vertex-tracking system, at the Radioactive Isotope Beam Factory (RIBF) of the RIKEN Nishina Center has led to numerous nuclear physics discoveries. In experiments involving rare-isotope beams at intermediate energies, MINOS was integrated with the DALI2 + γ-ray spectrometer and other auxiliary devices. These were positioned in front of both the ZeroDegree Spectrometer and the SAMURAI magnetic spectrometers for the identification of ejectiles following quasi-free scattering direct reactions. Notable outcomes include the first spectroscopy of unstable doubly magic nucleus, investigations into multi-neutron decays, and the study of shell evolution along isotopic chains. These studies have significantly advanced our understanding of nuclear structure, as well as the mechanism of direct reactions with fast beams. Simultaneously, these direct reactions enabled raising new physics questions and paved the way for next-generation experimental setups to address them. Through the combination of particle- and γ-spectroscopy with a broad range of nuclear reactions, new frontiers will be established in our understanding of nuclear structure and reaction mechanisms. Here, we review the past ten years of studies on direct reactions and spectroscopy of exotic nuclei with liquid-hydrogen targets at the RIBF and define a vision for the future.

Bertulani, Carlos A [East Texas A & M Univ., Comme↗
DOE OSTI2025

Experimental demonstration of real-time electron temperature profile control in DIII-D

Future tokamak reactor operation will require the ability to maintain a given plasma scenario for extended periods of time. This will necessitate the capability to react to changes in the plasma state and return the plasma to the target scenario; the principal method to achieve this is through feedback control. Thus, it is necessary to develop and test feedback controllers for the plasma profiles that define a target scenario. In this work, a feedback controller for the electron temperature (Te) profile is tested experimentally in DIII-D. This experiment relied on the ability to ascertain the electron temperature profile in real time, which was achieved using an observer algorithm. The observer relies on both diagnostic data and a predictive model of the electron temperature profile evolution; this predictive model includes contributions from neural network surrogate models. Because of these dependencies, a number of capabilities needed to be added to the real-time PCS for DIII-D in order to support the Te profile control experiment. The neural network surrogates needed to be integrated into the PCS to be called in real time. An observer algorithm for the Te profile needed to be added and connected to the Thomson scattering system to allow access to the current state of the profile in real time. When tested, the observer was shown to produce Te profiles that are consistent with the shape of the Thomson scattering data while rejecting much of the noise in the diagnostic data. Finally, the controller itself was tested in real time. This experiment showed that the controller is capable of tracking the electron temperature target at locations across the spatial profile.

Morosohk, Shira [Oak Ridge Associated Universities↗
DOE OSTI2024

Underwater Target Detection Software Demonstration on the RivGen Turbine

This repository contains data and processing scripts necessary to train the object detection models utilized in the underwater target detection software demonstration on the RivGen turbine project and to produce performance metrics (precision, recall, mAP50, mAP50-95). - Contents - Data consist of "images" and "labels". Each image has an associated label, both share the same time string in its file name (e.g., 2024_05_25_09_01_57.98.jpg and 2024_05_25_09_01_57.98.txt). Time strings have the format %yyyy_%mm_%dd_%HH_%MM_%SS.%3f. Images and labels were curated from 2021 and 2024 smolt outmigration periods at the project site in Igiugig, AK. Images are monochrome 8-bit images of objects (smolt, debris, and other) passing through the field of view of the deployed cameras during various operational stages of the RivGen turbine. Labels are text files indicating the class and bounding polygon of each object in an image. The provided labels use the "YOLO" label format. - Requirements - Python3.8+ is required to install and run the train and validation script. The README.md provides instruction for installing the requirements from the requirements.py file. - Instructions - The "example_train.py" file ingests the provided data, trains a model, and produces model performance metrics at completion. NOTE: model performance metrics will vary from run to run as a consequence of the random selection of training and validation data.

16 TIDAL AND WAVE POWER↗