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At least 1,459 records · Page 81

Characterization of the hardened single line of sight camera at the National Ignition Facility

The hardened single line of sight camera has been recently characterized in preparation for its deployment on the National Ignition Facility. The latest creation based on the pulse-dilation technology leads to many new features and improvements over the previous-generation cameras to provide better quality measurements of inertial confinement fusion experiments, including during high neutron yield implosions. Here, we present the characterization data that illustrate the main performance features of this instrument, such as extended dynamic range and adjustable internal magnification, leading to improved spatial resolution.

Trosseille, C. (ORCID:0000000289430482)↗

Static characterization of a highly optimized streak tube design incorporating a steering slot anode and an aberration-corrected Einzel lens

The BHx streak tube, under development at the Laboratory for Laser Energetics, incorporates a series of novel electron-optics elements to enable high fidelity measurements for high-energy-density physics experiments. The system is engineered to support a 25-mm active photocathode region compatible with sub-picosecond temporal resolution and with 70% internal photoelectron throughput. It exhibits negligible geometric distortion on a flat output screen, making it well suited for variety of measurements, such as ultrafast x-ray spectroscopy. Here, this paper presents characterization data from a prototype unit tested with an ultraviolet laser in a static deflection (non-swept) mode and shows good agreement with the predictions from numerical modeling, including focusing performance and geometric distortion measurements. Key design elements have been demonstrated and de-risked, laying the foundation for dynamic deflection testing. The anticipated improvements in data fidelity are expected to impact the fields as diverse as inertial confinement fusion, laboratory astrophysics, and materials science.

High energy density physics↗

Prediction of laser beam spatial profiles in a high-energy laser facility by use of deep learning

We adapt the significant advances achieved recently in the field of generative artificial intelligence/machine-learning to laser performance modeling in multipass, high-energy laser systems with application to high-shot-rate facilities relevant to inertial fusion energy. Advantages of neural-network architectures include rapid prediction capability, data-driven processing, and the possibility to implement such architectures within future low-latency, low-power consumption photonic networks. Four models were investigated that differed in their generator loss functions and utilized the U-Net encoder/decoder architecture with either a reconstruction loss alone or combined with an adversarial network loss. We achieved inference times of 1.3 ms for a 256 × 256 pixel near-field beam with errors in predicted energy of the order of 1% over most of the energy range. It is shown that prediction errors are significantly reduced by ensemble averaging the models with different weight initializations. These results suggest that including the temporal dimension in such models may provide accurate, real-time spatiotemporal predictions of laser performance in high-shot-rate laser systems.

47 OTHER INSTRUMENTATION↗

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗

Neural Networks for Nuclear Reactions in MAESTROeX

We demonstrate the use of neural networks to accelerate the reaction steps in the MAESTROeX stellar hydrodynamics code. A traditional MAESTROeX simulation uses a stiff ODE integrator for the reactions; here, we employ a ResNet architecture and describe details relating to the architecture, training, and validation of our networks. Our customized approach includes options for the form of the loss functions, a demonstration that the use of parallel neural networks leads to increased accuracy, and a description of a perturbational approach in the training step that robustifies the model. We test our approach on millimeter-scale flames using a single-step, 3-isotope network describing the first stages of carbon fusion occurring in Type Ia supernovae. We train the neural networks using simulation data from a standard MAESTROeX simulation, and show that the resulting model can be effectively applied to different flame configurations. This work lays the groundwork for more complex networks, and iterative time-integration strategies that can leverage the efficiency of the neural networks.

79 ASTRONOMY AND ASTROPHYSICS↗

Numerical studies and metric development for validation of magnetohydrodynamic models on the HIT-SI experiment

We present application of three scalar metrics derived from the Biorthogonal Decomposition (BD) technique to evaluate the level of agreement between macroscopic plasma dynamics in different data sets. BD decomposes large data sets, as produced by distributed diagnostic arrays, into principal mode structures without assumptions on spatial or temporal structure. These metrics have been applied to validation of the Hall-MHD model using experimental data from the Helicity Injected Torus with Steady Inductive helicity injection experiment. Each metric provides a measure of correlation between mode structures extracted from experimental data and simulations for an array of 192 surface-mounted magnetic probes. Numerical validation studies have been performed using the NIMROD code, where the injectors are modeled as boundary conditions on the flux conserver, and the PSI-TET code, where the entire plasma volume is treated. Initial results from a comprehensive validation study of high performance operation with different injector frequencies are presented, illustrating application of the BD method. Using a simplified (constant, uniform density and temperature) Hall-MHD model, simulation results agree with experimental observation for two of the three defined metrics when the injectors are driven with a frequency of 14.5 kHz.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Forward fitting of experimental data from a NE213 neutron detector installed with the magnetic proton recoil upgraded spectrometer at JET

In this paper, we present the results obtained from the data analysis of neutron spectra measured with a NE213 liquid scintillator at JET. We calculated the neutron response matrix of the instrument combining MCNPX simulations, a generic proton light output function measured with another detector and the fit of data from ohmic pulses. For the analysis, we selected a set of pulses with neutral beam injection heating (NBI) only and we applied a forward fitting procedure of modeled spectral components to extract the fraction of thermal neutron emission. The results showed the same trend of the ones obtained with the dedicated spectrometer TOFOR, even though the values from the NE213 analysis were systematically higher. This discrepancy is probably due to the different lines of sight of the two spectrometers (tangential for the NE213, vertical for TOFOR). The uncertainties on the thermal fraction estimates were from 4 to 7 times higher than the ones from the TOFOR analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MSSM Electroweak Baryogenesis and LHC Data

Electroweak baryogenesis is an attractive scenario for the generation of the baryon asymmetry of the universe as its realization depends on the presence at the weak scale of new particles which may be searched for at high energy colliders. In the MSSM it may only be realized in the presence of light stops, and with moderate or small mixing between the left- and right-handed components. Consistency with the observed Higgs mass around 125 GeV demands the heavier stop mass to be much larger than the weak scale. Moreover the lighter stop leads to an increase of the gluon-gluon fusion Higgs production cross section which seems to be in contradiction with indications from current LHC data. We show that this tension may be considerably relaxed in the presence of a light neutralino with a mass lower than about 60 GeV, satisfying all present experimental constraints. In such a case the Higgs may have a significant invisible decay width and the stop decays through a three or four body decay channel, including a bottom quark and the lightest neutralino in the final state. All these properties make this scenario testable at a high luminosity LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Directly Observing Micelle Fusion and Growth in Solution by Liquid-Cell Transmission Electron Microscopy

Amphiphilic small molecules and polymers form commonplace nanoscale macromolecular compartments and bilayers, and as such are truly essential components in all cells and in many cellular processes. The nature of these architectures, including their formation, phase changes, and stimuli-response behaviors, is necessary for the most basic functions of life, and over the past half-century, these natural micellar structures have inspired a vast diversity of industrial products, from biomedicines to detergents, lubricants, and coatings. The importance of these materials and their ubiquity have made them the subject of intense investigation regarding their nanoscale dynamics with increasing interest in obtaining sufficient temporal and spatial resolution to directly observe nanoscale processes. However, the vast majority of experimental methods involve either bulk-averaging techniques including light, neutron, and X-ray scattering, or are static in nature including even the most advanced cryogenic transmission electron microscopy techniques. Here, we employ in situ liquid-cell transmission electron microscopy (LCTEM) to directly observe the evolution of individual amphiphilic block copolymer micellar nanoparticles in solution, in real time with nanometer spatial resolution. These observations, made on a proof-of-concept bioconjugate polymer amphiphile, revealed growth and evolution occurring by unimer addition processes and by particle-particle collision-and-fusion events. In conclusion, the experimental approach, combining direct LCTEM observation, quantitative analysis of LCTEM data, and correlated in silico simulations, provides a unique view of solvated soft matter nanoassemblies as they morph and evolve in time and space, enabling us to capture these phenomena in solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of temperature-velocity distribution on fusion neutron peak shape

Doppler broadening of the 14 MeV DT and 2.45 MeV DD fusion neutron lines has long been our best measure of temperature in a burning plasma. At the National Ignition Facility (NIF), yields are high enough and our neutron spectrometers accurate enough that we see finer details of the peak shape. For example, we can measure the shift of the peak due to the bulk motion of the plasma, and we see indications of non-thermal broadening, skew, and kurtosis of the peak caused by the variations of temperature and fluid velocity during burn. We can also distinguish spectral differences among several lines of sight. Finally, this paper will review the theory of fusion neutron line shape, show examples of non-Gaussian line shapes and directional variations in NIF data, and describe detailed spectral shapes we see in radiation-hydrodynamics simulations of implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Combined neutron and x-ray imaging at the National Ignition Facility (invited)

X-ray and neutrons are commonly used to image Inertial Confinement Fusion implosions, providing key diagnostic information on the fuel assembly of burning DT fuel. The x-ray and neutron data provided are complementary as the production of neutrons and x-rays occur from different physical processes, but typically these two images are collected from different views with no opportunity for co-registration of the two images. Neutrons are produced where the DT fusion fuel is burning; X-rays are produced in regions corresponding to high temperatures. Processes such as mix of ablator material into the hotspot can result in increased x-ray production and decreased neutron production but can only be confidently observed if the two images are collected along the same line of sight and co-registered. To allow direct comparison of x-ray and neutron data, a Combined Neutron X-ray Imaging system has been tested at Omega and installed at the National Ignition Facility to collect an x-ray image along the currently installed neutron imaging line-of-sight. Here, this system is described, and initial results are presented along with prospects for definitive coregistration of the images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Enabling co-simulation of tokamak plant models and plasma control systems

A system for connecting the Plasma Control System and a model of the tokamak Plant in closed loop co-simulation for plasma control development has been in routine use at DIII-D for more than 20 years and at other fusion labs that use variants of the DIII-D PCS for approximately the last decade. Here, co-simulation refers to the simultaneous execution of two independent codes with the exchange of data - Plant actuator commands and tokamak diagnostic data - between them during execution. Interest in this type of PCS-Plant simulation technology has also been growing recently at other fusion facilities. In fact, use of such closed loop control simulations is assumed to play an even larger role in the development of both the ITER Plasma Control System (PCS) and the experimental operation of the ITER device, where they will be used to support verification/validation of the PCS and also for ITER pulse schedule development and validation. We describe the key use cases that motivate the co-simulation capability and the features that must be provided by the Plasma Control System to support it. These features could be provided by the PCS itself or by a model of the PCS. If the PCS itself is chosen to provide them, there are requirements imposed on its architecture. If a PCS model is chosen, there are requirements imposed on the initial implementation of this simulation as well as long-term consequences for its continued development and maintenance. We describe these issues for each use case and discuss the relative merits of the two choices. Several examples are given illustrating uses of the co-simulation method to address problems of plasma control during the operation of DIII-D and of other devices that use the DIII-D PCS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nominal Device Support for ATCA Shelf Manager

The ATCA standard specifies a mandatory Shelf Manager (ShM) unit which is a key element for the system operation. It includes the Intelligent Platform Management Controller (IPMC) which monitors the system health, retrieves inventory information and controls the Field Replaceable Units (FRUs). These elements enable the intelligent health monitoring, providing high-availability and safety operation, ensuring the correct system operation. For critical systems like ones of tokamak ITER these features are mandatory to support the long pulse operation. The Nominal Device Support (NDS) was designed and developed for the ITER CODAC Core System (CCS), which will be the responsible for plant Instrumentation and Control (I and C), supervising and monitoring on ITER. It generalizes the Enhanced Physics and Industrial Control System (EPICS) device support interface for Data Acquisition (DAQ) and timing devices. However the support for health management features and ATCA ShM are not yet provided. This paper presents the implementation and test of a NDS for the ATCA ShM, using the ITER Fast Plant System Controller (FPSC) prototype environment. This prototype is fully compatible with the ITER CCS and uses the EPICS Channel Access (CA) protocol as the interface with the Plant Operation Network (PON). The implemented solution running in an EPICS Input / Output Controller (IOC) provides Process Variables (PV) to the PON network with the system information. These PVs can be used for control and monitoring by all CA clients, such as EPICS user interface clients and alarm systems. The results are presented, demonstrating the fully integration and the usability of this solution. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Origins and Scaling of Hot-Electron Preheat in Ignition-Scale Direct-Drive Inertial Confinement Fusion Experiments

Planar laser-plasma interaction (LPI) experiments at the National Ignition Facility (NIF) have allowed access for the rst time to regimes of electron density scale length (~500 to 700 μm), electron temperature (~3 to 5 keV), and laser intensity (6 to 16 x 10 14 W/cm 2 ) that are relevant to direct-drive inertial confinement fusion ignition. Unlike in shorter-scale-length plasmas on OMEGA, scattered-light data on the NIF show that the near-quarter-critical LPI physics is dominated by stimulated Raman scattering (SRS) rather than by two-plasmon decay (TPD). This difference in regime is explained based on absolute SRS and TPD threshold considerations. SRS sidescatter tangential to density contours and other SRS mechanisms are observed. The fraction of laser energy converted to hot electrons is ~0.7% to 2.9%, consistent with observed levels of SRS. The intensity threshold for hot-electron production is assessed, and the use of a Si ablator slightly increases this threshold from ~4 x 10 14 to ~6 x 10 14 W/cm 2 . These results have significant implications for mitigation of LPI hot-electron preheat in direct-drive ignition designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tomographic Reconstruction of the Neutron Time-Energy Spectrum from a Dense Plasma Focus

A dense plasma focus (DPF) nuclear fusion device is an attractive pulsed neutron source in many applications, due to its relatively large neutron yield, produced in a short time duration. In order to design a DPF that generates neutrons within a specified time profile, or generates a neutron energy spectrum with specific properties, it is necessary to be able to characterize and model the results of the fusion process releasing the neutrons. The time-energy spectrum of fusion neutrons is an ideal quantity to use to validate multiphysics codes that simulate the pinch and fusion processes, because it is a quantity that requires the physics of each of the stages leading up to and ending in the fusion reaction to be simulated correctly. In particular, since DPF fusion neutrons are not monoenergetic -- and there can often be several fusion pinches creating neutrons -- a computer simulation matching high quality neutron spectrum measurements provides great confidence in the fidelity of the simulation. In order to make such a comparison, it is first necessary to have quality measurements from which to infer the spectrum. In this work we pose neutron spectroscopy as the classical tomographic inverse problem from neutron time of flight data at multiple distances, but enhanced by using an additional measurement of the time profile of the fusion pinch near its source and by using detector pairs set up in a geometry that allows for scatter background subtraction. The detector pairs enhance the quality of the time of flight measurements, and the additional constraint posed by the measured time profile allows for reconstructions discretized as finely as the time measurements and in energy as finely as 100 keV, without the problem being underdetermined. We present results from a Deuterium-fueled DPF at the U.S. Department of Energy's Nevada National Security Site and show that we can infer the time-energy spectrum from our measurements for both single and multi-pinch fusion reactions with equal fidelity.

Catenacci, Jared↗

Machine Learning for Rapid Biomarker Discovery via Image-Omic Fusion

In this project we proposed to accelerate biomarker discovery and improve disease prediction by combining image and omic data using a single, unified modelling approach. We hypothesized that much richer information could be derived from both the image and omic data when they are analyzed together. Using imaging mass spectrometry (IMS) data collected from mice we fused image and omic data to increase the resolution of the IMS data. Using human data provided to us by Oregon Health and Science University, we developed an initial modeling framework that can increase the accuracy of both imaging and MS datasets.

59 BASIC BIOLOGICAL SCIENCES↗

The equation of state and ionization equilibrium of dense aluminum plasma with conductivity verification

The equation of state, ionization equilibrium, and conductivity are the most important parameters for investigation of dense plasma. The equation of state is calculated with the non-ideal effects taken into consideration. The electron chemical potential and pressure, which are commonly used thermodynamic quantities, are calculated by the non-ideal free energy and compared with results of a semi-empirical equation of state based on Thomas-Fermi-Kirzhnits model. The lowering of ionization potential, which is a crucial factor in the calculation of non-ideal Saha equation, is settled according to the non-ideal free energy. The full coupled non-ideal Saha equation is applied to describe the ionization equilibrium of dense plasma. The conductivity calculated by the Lee-More-Desjarlais model combined with non-ideal Saha equation is compared with experimental data. It provides a possible approach to verify the accuracy of the equation of state and ionization equilibrium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST toreduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗