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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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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Discovery of 15 A-F Main Sequence Pulsating Star Candidates

Delta Scuti stars, spanning spectral types A to F with masses between 1.5 and 2.5 solar masses, exhibit a complex mix of radial and non-radial pressure modes. This study focuses on 15 Delta Scuti, Gamma Doradus, and Hybrid candidate stars using TESS satellite photometry data with a time series of exposures ranging from 20 to 600 seconds across different sky regions. Employing the prewhitening technique via fast Fourier transforms, significant frequencies are extracted from light curves. Three approximation methods are used to estimate critical stellar parameters such as density, radius, and mass. This research also verifies the variability of these stars, which are currently not classified as variable in databases like SIMBAD.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

SCORE (Synthesis of COnsists as Rolling Energy microgrids) (Final Technical Report)

The SCORE toolset is an open source, web-based application to assess the impact of new powering technologies on railroad performance, specifically technologies capable of both putting power into the rail (motive force) and taking power from the rail (regeneration). SCORE’s primary goal is generate trade studies to analyze different powering and train make-up options to minimize energy usage and greenhouse gas generation. At the core of generating these trade spaces is calculating the optimal powering policy for the train given the makeup of the train, the route, and time constraints. This paper presents details on the algorithms used in SCORE to compute this powering policies that is fast and accurate, discusses its implementation in an Energy-Longitudinal Train Dynamics (E-LTD) model, compares it to naïve approaches, and demonstrates its use across a variety of train/route pairs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Materials for Energy Management across the Electromagnetic Spectrum (MEMES) (LDRD Report)

Electrification of the United States has been a major driver of economic growth, powering industrialization, modern manufacturing, and the digital economy. Today, further economic and environmental benefits can be realized by improving the energy efficiency of the technologies we have come to rely on. This project focused on enhancing the energy efficiency of two cornerstone technologies of modern society: electronic displays and building climatization. While these two technologies operate in different parts of the electromagnetic spectrum (the visible and infrared, respectively), they share a common potential technological solution: electrically-driven displays that change reflectivity. In this work, we developed the first multipixel multicolor reflective display that achieves multi-colorization with fast-changing structural color. In the course of this demonstration, we quantified the structural changes that occur across different time and length scales and resolved device sealing issues, enabling operation of these devices over months (as opposed to days previously). We furthermore developed two reflectivity changing devices in the infrared and demonstrated how these technologies can be used to reduce climatization demands for both smart window and smart wall technologies. Implementing such a device in a scaled down mock room resulted in 10 degree Celsius change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Postirradiation Examination of WIRE-21 Experiment Irradiated in the High Flux Isotope Reactor

Westinghouse Electric Company is developing wireless sensors to monitor the centerline temperature and internal pressure of commercial light-water reactor fuel rods during irradiation. Oak Ridge National Laboratory and Westinghouse Electric Company developed the Wireless Instrumented RB Experiment 2021 (WIRE-21) to test wireless temperature and pressure sensor technologies in a removable beryllium position in the High Flux Isotope Reactor. The experiment was irradiated for a total of 75 days, at temperatures ranging from approximately 150°C to 400°C, resulting in a peak fast (energy > 0.1 MeV) neutron fluence of about 3 × 10 21 n/cm 2 . The temperature was intentionally cycled multiple times to compare the response of the wireless temperature sensor to collocated thermocouples. Similarly, the pressure sensor was actuated in multiple steps to compare the response of the wireless measurement to excore pressure transducers (Petrie et al., 2023). After irradiation, the experiment was disassembled in the Irradiated Fuels Examination Laboratory (IFEL) hot cell at Oak Ridge National Laboratory with the intent to recover sensor and dosimetry components, document the as-irradiated condition of the hardware, and investigate possible causes of the sensor behavior observed during irradiation. The postirradiation examination successfully recovered and preserved key WIRE-21 components. After the housing was removed using a milling machine, the internal experiment sections were examined. All eight fiber-optic sensors were recovered, cut, and stored. The silicon carbide thermometry, temperature sensor, pressure sensor, lower spacer, and selected pressure and temperature cable sections were also removed and stored. The metal bellows of the pressure sensor was found to be plastically deformed, indicating that it had been properly pressurized during irradiation and generally behaved as expected. X-ray diffraction analysis of a section of one of the irradiated inductor cores within the pressure sensor was performed and confirmed the presence of phase-pure alpha ferrite (i.e., no unexpected phase transformations). Inductance testing was performed on the irradiated pressure sensor cores using an unirradiated test coil, and DC resistance measurements of the transceiver coils were also performed. The measurements with irradiated inductor cores assembled inside unirradiated coils showed slightly reduced inductance compared to measurements made with unirradiated cores, but the difference was not sufficient to explain the more significant reductions in inductance that were observed in-pile. Therefore, it is suspected that degradation of the inductor coils (specifically the wire wrapping) is responsible for the reduced inductance observed in-pile.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Dynamics of iodine geminate recombination in supercritical xenon solvent: Caging effect

Understanding the dynamics of chemical reactions in solutions is vital, as their rates and kinetics are significantly affected by the solvent environment. Supercritical solvents offer extensive applications in chemical reactions by enabling the manipulation of the solution environment. Here, in this study, we investigate the geminate recombination of iodine in a supercritical xenon solvent by using ReaxFF-based molecular dynamics simulations. Our findings reveal that the highest iodine recombination rate occurs near supercritical conditions, while lower-pressure conditions lead to reduced collision rates and unstable recombination, and higher-pressure conditions hinder iodine diffusion, resulting in a lower recombination rate. Our analysis shows that the xenon local density at the time of recombination is at least 2.5 times higher than the global density, confirming the presence of xenon clusters surrounding the Iodine atoms. This observation is further supported by coordination number analysis, which confirms an elevated xenon local density during recombination. In addition, the correlation between the total energy of xenon atoms within a cluster and recombined iodine atoms underscores the kinetic energy transfer process, validating the occurrence of geminate recombination. The excess kinetic energy from the recombining iodine atoms is transferred to the surrounding xenon atoms. Our examination of geminate recombination demonstrates that iodine atoms confined within xenon clusters—whether through manual insertion of atoms or the fast dissociation of an iodine molecule within xenon clusters—are more likely to recombine as primary geminate recombination. However, extending the iodine molecule dissociation time allows iodine atoms to diffuse out of the cluster, and the recombination to shift toward secondary geminate recombination.

Cage effect↗
DOE OSTI2024

Fast spark-detection system for GEM detectors

The sPHENIX experiment is currently under commissioning at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Lab (BNL). The Time Projection Chamber (TPC) serves as a tracking detector for the experiment. The sPHENIX TPC uses a stack of four Gas Electron Multipliers (GEMs) as a gain stage in a reduced ion back-flow configuration. To mitigate the damaging effects of sparks in the GEMs, an online spark monitoring system was created. Once the system detects a spark in a GEM stack, the voltages across the GEMs in that stack can be lowered to prevent further sparking without affecting the gain and efficiency of the other modules. Spark signals are coupled out of the GEM stack by a pick-off capacitor attached to the bottom of the bottom GEM. Custom PCBs convert the oscillatory spark signal into a mono-polar pulse that is then digitized. The software then saves the waveform in a server and uses experimentally derived thresholds to determine how to react. As a result, the system has so far proven to be effective at improving the stability of the TPC and preventing damaging events while collecting cosmic ray data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗
DOE OSTI2026

Time Matters: A Survival Analysis of Public Electric Vehicle Charging Infrastructure Utilization

The rapid adoption of plug-in electric vehicles (PEVs) places significant demands on public charging infrastructure, making it critical to understand and optimize charger utilization. This study provides one of the most comprehensive analyses of charging behavior to date by applying a survival analysis to a dataset of nearly 16 million level 2 (L2) and direct current (DC) fast charger sessions across the United States from 2017 to 2022. Using Kaplan-Meier curves and log rank tests, our analysis reveals statistically significant and distinct duration patterns influenced by charger type, time of day, and day of the week. We find that L2 charging sessions exhibit high variability tied to venue type, whereas DC sessions are more uniform, typically lasting 30-45 min. This study introduces the operational efficiency score (OES), a metric for standardizing the performance evaluation of charging stations. Our findings offer actionable insights for optimizing charger deployment, developing dynamic pricing strategies to reduce vehicle dwell time, and improving load management for grid operators, ultimately enhancing the efficiency and availability of public charging infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

High-heat transfer lithium-ion batteries: A new era in battery thermal management

Despite advances in lithium-ion battery technology, critical challenges remain that must be addressed to accelerate electric vehicle (EV) adoption and global energy transformation. Significantly improved battery thermal management (BTM) is key to overcoming these challenges. BTM approaches focus on increasing heat transfer coefficients via air, liquid, or refrigerant cooling, but less attention is given to reducing the battery's thermal resistance, a major bottleneck for heat transfer. This work introduces a novel approach to reduce battery thermal resistance by integrating in-plane heat transfer with optimized cell geometry, minimized thermal resistances, and reduced interfacial resistances, representing a departure from previous methods. The standard prismatic can cell incorporating this technology is referred to as the high heat transfer (HHT) battery. An equivalent resistance battery thermal model is developed for speed and accuracy, validated against experimental data in the literature, demonstrating strong correlation and ensuring reliable predictions for real-world performance. Thermal performance metrics of the conventional and HHT batteries are compared using a parametric study with air, liquid, and refrigerant boundary conditions across a range of aspect ratios. The HHT battery shows a heat removal rate up to 20 times higher than a conventional battery. These findings suggest that HHT technology could be transformative for EV battery performance, enabling fast charging, mitigating thermal runaway, extending battery life, reducing cold-weather power loss, increasing reliability, lowering costs, and enabling higher energy density, all critical for EV adoption and energy transformation. Future work will focus on prototyping and real-world testing to refine these findings for commercial-scale applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Simulation of Li-pellet triggered ELMs in EAST with an impurity model implemented under BOUT++ framework

A simple impurity model has been developed under the BOUT++ framework to investigate the Li-pellet triggered edge localized mode (ELM) in EAST configuration. The present impurity model decouples the ion pressure enhancement effect (IPEE) (which affects radial E X B flow shear and gyro-viscosity of deuterium ions and is implicitly included in our previous work) to make the simulation of Li pellet injection more physically reasonable. In addition, the present impurity model also includes the impurity equilibrium effect (IEE) (which induces modifications on vorticity and gyro-viscosity). The simulation results show that without IPEE a turbulent ELM induced by Li pellet is triggered by multiple peeling-ballooning modes (PBMs) rather than by a single dominant mode, and the simultaneous growth of multiple modes is conducive to reducing the time for pedestal entering the energy loss state. When a turbulent ELM occurs, the nonlinearly dominant modes undergo a secondary fast growth during fast crash phase. The finding explains the secondary increase of D α emission observed in the DIII-D Li injection experiments. During the evolution of a turbulent ELM, the continuous pedestal collapse dominates the pedestal energy loss in turbulent transport phase; however, in saturation phase, the stabilizing effects on PBMs (n ≠ 0) by n = 0 mode and radial E X B flow shear within the steepest gradient region are more prominent. It is also found that with IEE and without IPEE, the size threshold of ELM triggering and the magnitude of ELM sizes both show a good agreement with EAST and DIII-D experimental observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Laser-driven ion and electron acceleration from near-critical density gas targets: Towards high-repetition rate operation in the 1 PW, sub-100 fs laser interaction regime

Ion acceleration from gaseous targets driven by relativistic-intensity lasers was demonstrated as early as the late 1990s, yet most of the experiments conducted to date have involved picosecond-duration, Nd:glass lasers operating at low repetition rate. Here, we present measurements on the interaction of ultraintense ( ≈ 10 20 W cm − 2 , 1 PW ) , ultrashort ( ≈ 70 fs ) Ti:Sa laser pulses with near-critical ( ≈ 10 20 cm − 3 ) helium gas jets, a debris-free targetry with the potential for future compatibility with high ( ≈ 1 Hz ) repetition rate operation. We provide evidence of α particles being forward accelerated up to ≈ 2.7 − MeV energy with a total flux of ≈ 10 11 sr − 1 as integrated over > 0.1 − MeV energies and detected within a 0.5 − mrad solid angle. We also report on on-axis emission of relativistic electrons with an exponentially decaying spectrum characterized by a ≈ 10 − MeV slope, i.e., five times larger than the standard ponderomotive scaling. The total charge of these electrons with energy above 2 MeV is estimated to be of ≈ 1 nC , corresponding to ≈ 0.1 % of the laser drive energy. In addition, we observe the formation of a plasma channel, extending longitudinally across the gas density maximum and expanding radially with time. These results are well captured by large-scale particle-in-cell simulations, which reveal that the detected fast ions most likely originate from reflection off the rapidly expanding channel walls. The latter process is predicted to yield ion energies in the MeV range, which compare well with the measurements. Finally, direct laser acceleration is shown to be the dominant mechanism behind the observed electron energization. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Refining Fast Simulation Using Machine Learning

A growing reliance on the fast Monte Carlo (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. FastSim is roughly 10 times faster than equivalent GEANT4-based full simulation (FullSim). However, reduced accuracy of the FastSim affects some analysis variables and collections. To improve its accuracy, FastSim is refined using regression-based neural networks trained with ML. The status of FastSim refinement is presented. The results show improved agreement with the FullSim output and an improvement in correlations among output observables and external parameters.

Güngördü, Acelya Deniz↗
DOE OSTI2024

Optically multiplexed neutron time-of-flight technique for inertial confinement fusion

Neutron time-of-flight (nTOF) detectors are crucial in diagnosing the performance of inertial confinement fusion (ICF) experiments, which implode targets of deuterium–tritium fuel to achieve thermonuclear conditions. These detectors utilize the fusion neutron energy spectrum to extract key measurements, including the hotspot ion temperature and fuel areal density. Previous work [Danly et al., Rev. Sci. Instrum. 94, 043502 (2023)] has demonstrated adding 1D spatial resolution to an nTOF-like detector using a neutron aperture and streak camera to measure the ion temperature profile of an ICF implosion. By contrast, the study presented herein explores modifying the 1D detector to use a fast photomultiplier tube (PMT) to validate the design of a 2D spatially resolved instrument based on reconstruction from 1D profiles. The modification would collect time-of-flight traces from separate scintillators in an imaging array with one PMT using optical fibers of varying lengths to time-multiplex the signals. This technique has been demonstrated in ride-along experiments on the OMEGA laser with 20 fiber-coupled scintillator channels connected to a Photek PMT210. Results provide constraints on the fiber lengths and PMT gating requirements to promote pulse fidelity throughout all channels. Calibration of the detector to fixed nTOFs can provide a preliminary estimate of the instrument response function (IRF), although measurement of the IRF is currently under way. These results suggest that nTOF signals can potentially be time-multiplexed with fibers so long as the design is strategic to mitigate signal-to-noise reduction, modal dispersion, and charge build-up in the PMT, which has implications beyond ion temperature imaging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Sub-microsecond Transformers for Jet Tagging on FPGAs

We present the first sub-microsecond transformer implementation on an FPGA achieving competitive performance for state-of-the-art high-energy physics benchmarks. Transformers have shown exceptional performance on multiple tasks in modern machine learning applications, including jet tagging at the CERN Large Hadron Collider (LHC). However, their computational complexity prohibits use in real-time applications, such as the hardware trigger system of the collider experiments up until now. In this work, we demonstrate the first application of transformers for jet tagging on FPGAs, achieving $\mathcal{O}(100)$ nanosecond latency with superior performance compared to alternative baseline models. We leverage high-granularity quantization and distributed arithmetic optimization to fit the entire transformer model on a single FPGA, achieving the required throughput and latency. Furthermore, we add multi-head attention and linear attention support to hls4ml, making our work accessible to the broader fast machine learning community. This work advances the next-generation trigger systems for the High Luminosity LHC, enabling the use of transformers for real-time applications in high-energy physics and beyond.

Laatu, Lauri [Imperial Coll., London]↗
DOE OSTI2025

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part I: Model Formulation

Here, this paper formulates a new particle-in-cell method for the Vlasov–Maxwell system. Under the Lorenz gauge condition, Maxwell’s equations for the electromagnetic fields can be written as a collection of scalar and vector wave equations. The use of potentials for the fields motivates the adoption of a Hamiltonian formulation for particles that employs the generalized (conjugate) momentum. A notable advantage offered by the Hamiltonian formulation is the elimination of time derivatives in the Lorenz gauge formulation that are required by the standard Newton–Lorentz treatment of the particles. This allows the fields to retain the full time-accuracy guaranteed by the field solver. The resulting updates for particles require only knowledge of the fields and their spatial derivatives. An analytical method for constructing these spatial derivatives is presented that exploits the underlying integral solution used in the field solver for the wave equations. Moreover, these derivatives are demonstrated to converge at the same rate as the fields in both time and space. The Method of Lines Transpose field solver we consider in this work is globally first-order accurate in time and high-order accurate in space (e.g., fourth- and fifth-order) and belongs to a larger class of methods which are unconditionally stable, can address geometry, and leverage $\mathcal {O}(N)$ fast summation methods for efficiency. We demonstrate the method on several well-established benchmark problems on bounded domains, including a plasma sheath as well as a relativistic particle beam. The efficacy of the proposed formulation is established by comparing with a second-order accurate finite-difference time-domain method that employs a leapfrog time advance for particles and a charge conserving map suitable for bounded domains. The new method shows mesh-independent numerical heating properties even in cases where the plasma Debye length is smaller than the grid spacing. This is an important feature of the new method for problems defined on bounded domains, because it permits the use of coarser grids in space in the representation of the fields. Such a capability has significant implications for the simulation of plasmas in bounded domains with complex geometry, where the ratio between the largest and smallest cells can vary significantly. The use of high-order spatial approximations in the new method also means that fewer grid points are required in order to achieve a fixed accuracy. Our results also suggest that the new method can be used with fewer simulation particles per cell compared to the benchmark explicit method, which permits further computational savings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗
DOE OSTI2025

Effect of energetic ions on edge-localized modes in tokamak plasmas

The most efficient and promising operational regime for the International Thermonuclear Experimental Reactor tokamak is the high-confinement mode. In this regime, however, periodic relaxations of the plasma edge can occur. These edge-localized modes pose a threat to the integrity of the fusion device. Here we reveal the strong impact of energetic ions on the spatio-temporal structure of edge-localized modes in tokamaks using nonlinear hybrid kinetic–magnetohydrodynamic simulations. A resonant interaction between the fast ions at the plasma edge and the electromagnetic perturbations from the edge-localized mode leads to an energy and momentum exchange. Energetic ions modify, for example, the amplitude, frequency spectrum and crash timing of edge-localized modes. The simulations reproduce some observations that feature abrupt and large edge-localized mode crashes. The results indicate that, in the International Thermonuclear Experimental Reactor, a strong interaction between the fusion-born alpha particles and ions from neutral beam injection, a main heating and fast particle source, is expected with predicted edge-localized mode perturbations. This work advances the understanding of the physics underlying edge-localized mode crashes in the presence of energetic particles and highlights the importance of including energetic ion kinetic effects in the optimization of edge-localized mode control techniques and regimes that are free of such modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗