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At least 595 records · Page 33

Line identification of boron and nitrogen emissions in EUV and VUV wavelength ranges in the impurity powder dropping experiments of LHD and its application to spectroscopic diagnostics

An impurity powder dropper was installed in the 21st campaign of the Large Helical Device experiment (Oct. 2019–Feb. 2020) under a collaboration between the National Institute for Fusion Science and the Princeton Plasma Physics Laboratory for the purposes of real-time wall conditioning and edge plasma control. In order to assess the effective injection of the impurity powders, spectroscopic diagnostics were applied to observe line emission from the injected impurity. Therefore, extreme-ultraviolet (EUV) and vacuum-ultraviolet (VUV) emission spectra were analyzed to summarize observable impurity lines with B and BN powder injection. Emission lines released from B and N ions were identified in the EUV wavelength range of 5–300 Å measured using two grazing incidence flat-field EUV spectrometers and in the VUV wavelength range of 300–2400 Å measured using three normal incidence 20 cm VUV spectrometers. BI–BV and NIII–NVII emission lines were identified in the discharges with the B and BN powder injection, respectively. Useful B and N emission lines which have large intensities and are isolated from other lines were successfully identified as follows: BI (1825.89, 1826.40) Å (blended), BII 1362.46 Å, BIII (677.00, 677.14, 677.16) Å (blended), BIV 60.31 Å, BV 48.59 Å, NIII (989.79, 991.51, 991.58) Å (blended), NIV 765.15 Å, NV (209.27, 209.31) Å (blended), NVI 1896.80 Å, and NVII 24.78 Å. Applications of the line identifications to the advanced spectroscopic diagnostics were demonstrated, such as the vertical profile measurements for the BV and NVII lines using a space-resolved EUV spectrometer and the ion temperature measurement for the BII line using a normal incidence 3 m VUV spectrometer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review

In the past decade, different sensing mechanisms and algorithms have been developed to detect or estimate indoor occupancy. One of the most recent advancements is using networked sensor nodes to create a more comprehensive occupancy detection system where multiple sensors can identify human presence within more expansive areas while delivering enhanced accuracy compared to a system that relies on stand-alone sensor nodes. The present work reviews the studies from 2012 to 2022 that use networked sensor nodes to detect indoor occupancy, focusing on PIR-based sensors. Methods are compared based on pivotal ADPs that play a significant role in selecting an occupancy detection system for applications such as Health and Safety or occupant comfort. These parameters include accuracy, information requirement, maximum sensor failure and minimum observation rate, and feasible detection area. We briefly describe the overview of occupancy detection criteria used by each study and introduce a metric called “sensor node deployment density” through our analysis. This metric captures the strength of network-level data filtering and fusion algorithms found in the literature. It is hinged on the fact that a robust occupancy estimation algorithm requires a minimal number of nodes to estimate occupancy. This review only focuses on the occupancy estimation models for networked sensor nodes. It thus provides a standardized insight into networked nodes’ occupancy sensing pipelines, which employ data fusion strategies, network-level machine learning algorithms, and occupancy estimation algorithms. This review thus helps determine the suitability of the reviewed methods to a standard set of application areas by analyzing their gaps.

Emad-Ud-Din, Muhammad (ORCID:0000000279515538)↗

Investigation of Various Transformer Topologies for HF Isolation Applications

High-frequency (HF) transformers are an essential part of many power electronic devices. The performance and behavior of HF transformers can greatly affect the efficiency and performance of all systems, particularly, from a parasitic parameter point of view. In this article, HF transformers' parasitic parameters, such as leakage inductances and parasitic capacitances, are analyzed using a novel analytical method, finite element method (FEM), and experimental measurements of different structures and winding arrangements. Also, the magnetic field, electric field, electric displacement field, and electric potential distribution within the transformers are simulated and analyzed. Four different HF transformers with E and U cores with different windings are designed and analyzed. Investigation outcomes help to classify structures according to the trade-off between leakage inductances and series parasitic capacitances. This information can later be used for the optimal selection and design of transformers as a function of their operating frequency for any power rating and voltage level. Moreover, 3-D FEM and experimental results validate the proposed methodology to be used for designing HF transformers in high-voltage/power applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

Required toroidal confinement for fusion and omnigeneity

Deuterium–tritium (DT) burning requires a long energy confinement times compared to collision times, so the particle distribution functions must approximate local Maxwellians. Non-equilibrium thermodynamics is applicable, which gives relations among transport, entropy production, the collision frequency, and the deviation from a Maxwellian. The distribution functions are given by the Fokker–Planck equation, which is an advection–diffusion equation. A large hyperbolic operator, the Vlasov operator with the particle trajectories as its characteristics, equals a small diffusive operator, the collision operator. The collisionless particle trajectories would be chaotic in stellarators without careful optimization. This would lead to rapid entropy production and transport—far beyond what is consistent with a self-sustaining DT burn. Omnigeneity is the weakest general condition that is consistent with a sufficiently small entropy production associated with the thermal particle trajectories. Omnigeneity requires that the contours of constant magnetic field strength be unbounded in at least one of the two angular coordinates in magnetic surfaces and that there be a symmetry in the field-strength wells along the field lines. Even in omnigenous plasmas, fluctuations due to microturbulence can produce chaotic particle trajectories and the gyro-Bohm transport is seen in many stellarator and tokamak experiments. The higher the plasma temperature above 10 keV, the smaller the transport must be compared to gyro-Bohm for a self-sustaining DT burn. The hot alphas of DT fusion heat the electrons. When the ion–electron equilibration time is long compared to the ion energy confinement time, a self-sustaining DT burn is not possible, which sets a limit on the electron temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On a fully-implicit VMS-stabilized FE formulation for low Mach number compressible resistive MHD with application to MCF

This study presents the development and evaluation of a fully-implicit variational multiscale (VMS) stabilized unstructured finite element (FE) formulation for compressible magnetohydrodynamics (MHD) model, at low Mach number regime. The model describes the dynamics of a compressible conducting fluid in the low Mach number limit in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics phenomena. The specific applications that motivate this study are macroscopic simulations of the longer time-scale stability and disruptions of magnetic confinement fusion (MCF) devices, specifically the ITER tokamak. The discussion considers the development of the VMS FE representation, the structure of the stabilizing terms that deal with significant convective flows, the stabilization of the nearly incompressible response of the fluid flow, and the stabilization of the constraint that enforces the solenoidal involution on the magnetic field. The nonlinear discretized system is solved with scalable preconditioned Newton–Krylov iterative methods, which employs a multiphysics block preconditioning method based on approximate block factorizations and Schur complements. The study presents an evaluation of the VMS method on a 2D cartesian tearing mode instability, and illustrates the scalability of the solvers on MCF relevant problems. A set of results are also presented for longer time-scale stability and disruptions for the ITER tokamak. These include a vertical displacement event (VDE), and a (1,1) internal kink mode. Here, the formulation is demonstrated to be scalable and also reasonably robust with respect to the Lundquist number scaling.

42 ENGINEERING↗

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗

Magnetic field impact on the laser heating in MagLIF

Prior to implosion in Magnetized Liner Inertial Fusion (MagLIF), the fuel is heated to temperatures on the order of several hundred eV with a multi-kJ, multi-ns laser pulse. In this paper, we present two laser heated plasma experiments, relevant to the MagLIF preheat stage, performed at Z with beryllium liners filled with deuterium and a trace amount of argon. In one experiment, there is no magnetic field and, in the other, the liner and fuel are magnetized with an 8.5 T axial magnetic field. The recorded time integrated, spatially resolved spectra of the Ar K-shell emission are sensitive to electron temperature T e . Individual analysis of the spatially resolved spectra produces electron temperature distributions T e (z) that are resolved along the axis of laser propagation. In the experiment with magnetic field, the plasma reaches higher temperatures and the heated region extends deeper within the liner than in the unmagnetized case. Radiation magnetohydrodynamics simulations of the experiments are presented and post-processed. A comparison of the results from experimental and simulated data reveals that the simulations underpredict T e in both cases but the differences are larger in the case with magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development of observation-based global multilayer soil moisture products for 1970 to 2016

Abstract. Soil moisture (SM) datasets are critical to understanding the global water, energy, and biogeochemical cycles and benefit extensive societal applications. However, individual sources of SM data (e.g., in situ and satellite observations, reanalysis, offline land surface model simulations, Earth system model – ESM – simulations) have source-specific limitations and biases related to the spatiotemporal continuity, resolutions, and modeling and retrieval assumptions. Here, we developed seven global, gap-free, long-term (1970–2016), multilayer (0–10, 10–30, 30–50, and 50–100 cm) SM products at monthly 0.5∘ resolution (available at https://doi.org/10.6084/m9.figshare.13661312.v1; Wang and Mao, 2021) by synthesizing a wide range of SM datasets using three statistical methods (unweighted averaging, optimal linear combination, and emergent constraint). The merged products outperformed their source datasets when evaluated with in situ observations (mean bias from −0.044 to 0.033 m3 m−3, root mean square errors from 0.076 to 0.104 m3 m−3, Pearson correlations from 0.35 to 0.67) and multiple gridded datasets that did not enter merging because of insufficient spatial, temporal, or soil layer coverage. Three of the new SM products, which were produced by applying any of the three merging methods to the source datasets excluding the ESMs, had lower bias and root mean square errors and higher correlations than the ESM-dependent merged products. The ESM-independent products also showed a better ability to capture historical large-scale drought events than the ESM-dependent products. The merged products generally showed reasonable temporal homogeneity and physically plausible global sensitivities to observed meteorological factors, except that the ESM-dependent products underestimated the low-frequency temporal variability in SM and overestimated the high-frequency variability for the 50–100 cm depth. Based on these evaluation results, the three ESM-independent products were finally recommended for future applications because of their better performances than the ESM-dependent ones. Despite uncertainties in the raw SM datasets and fusion methods, these hybrid products create added value over existing SM datasets because of the performance improvement and harmonized spatial, temporal, and vertical coverages, and they provide a new foundation for scientific investigation and resource management.

54 ENVIRONMENTAL SCIENCES↗

Study of Mechanical Properties, Microstructure, and Residual Stresses of AISI 304/304L Stainless Steel Submerged Arc Weld for Spent Fuel Dry Storage Systems

The confinement boundaries of spent nuclear fuel (SNF) canisters are typically fusion welded. Welded microstructures, strain hardening, and residual stresses combined with a chemically aggressive, chloride-rich environment led to concerns that the welded canister may be susceptible to chloride-induced stress corrosion cracking (CISCC). A comprehensive understanding of the modification of stainless steel (SS) metallurgical and mechanical properties by fusion welding could accelerate the predictive analysis of CISCC susceptibility. This paper describes a submerged arc welding (SAW) procedure that was developed and qualified on 12.7 mm (0.5 in.) thick AISI 304/304L SS to produce joints in a way similar to actual SNF canister manufacturing. This procedure has the potential to reduce the production cost and weld CISCC susceptibility by using fewer welding passes and lower heat input than current industrial applications. Global and local mechanical behaviors and properties, as well as residual stress distributions on the welded joint, were studied. The results indicate that hardness values in the fusion zone (FZ) and heat-affected zone (HAZ) are slightly higher than that of the base metal. Strain localization was presented in the HAZ before the tensile stress reached its maximum value, and then it shifted to the FZ. The specimen finally broke in the FZ. High tensile residual stresses exhibited in the FZ and the nearby HAZ suggest the highest CISCC-susceptible spots. The maximum tensile residual stresses were along the welding direction, indicating that if cracks occur, they would be perpendicular to the welding direction. This study involved developing and qualifying a SAW procedure for SNF canister production. The new procedure yielded cost savings (SAW working efficiency increased by about 80%), improved mechanical properties, and presented moderate residual stresses. Analysis revealed that the welded joint’s low-stress and high-stress damage assessments may be affected by shifts in the strain localization spot under loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hydrodynamic conditions in laser irradiated buried layer experiments

The calculation of open shell ionization level and radiative properties of materials in Non-Local Thermal Equilibrium (NLTE) is currently still a major challenge for any atomic model. The predictions of various NLTE atomic codes at these conditions still differ significantly. In recent years, a new buried layer platform was developed at the Lawrence Livermore National Laboratory and the Laboratory for Laser Energetics. This platform is used to measure ionization distribution and emission of open L-shell, mid-Z ions and open M-shell, high-Z ions at NLTE conditions that are relevant in many laser plasma applications. These experiments offer a unique chance for benchmarking the atomic models. In order to perform these experiments, a uniform well characterized plasma source is required. In this work, we present one-dimensional (1D) and two-dimensional simulations of the experimental platform. These simulations were used for both the design and the analysis of the experiments. The simulations demonstrate the different phases of hydrodynamic evolution of the target and identify the time windows in which uniform conditions can be achieved. A 1D expansion of the target was found to be adequate to describe the target's evolution for most of the experiment duration. The fast 1D simulations were compared with recent experimental results from the Omega laser facility. The sensitivity of the results to several modeling parameters such as the electron flux limiter and laser resonant absorption is reported.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LaserNetUS Collaboration Network—University of Rochester (Final Report)

LaserNetUS Collaborative Network established in 2018 is a network of high-power laser facilities supported by the Department of Energy (DOE) Office of Fusion Energy Sciences (FES) and operating effectively as a user facility. Its mission is to advance and promote intense laser science and applications by providing scientists and students with broad access to unique facilities and enabling technologies, advancing the frontiers of laser-science research, and fostering collaboration among researchers and networks from around the world. Users who submit proposals through an annual call are selected by an external and independent proposal review panel (PRP) not involving personnel from any of the facilities. Besides the Omega Laser Facility at the University of Rochester’s Laboratory for Laser Energetics (UR/LLE), the network during this project period includes high-intensity laser facilities from six other universities and three national laboratories, namely, the Colorado State University (CSU), the University of Michigan (UM), the University of Nebraska at Lincoln (UNL), The Ohio State University (OSU), Université du Québec, the University of Texas at Austin (UT Austin), Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory (SLAC) and Lawrence Livermore National Laboratory (LLNL), respectively. The network facilities span a wide range in laser pulse energy, pulse duration, repetition rate, and experimental diagnostic equipment enabling innovative research in a variety of exciting areas. Details of the LaserNetUS facilities, organization and committees, events, and accomplishments can be found at the network website (https://lasernetus.org/). A very important role that the LaserNetUS fulfills is the training of students and young scientists who will be key for the future development of laser-plasma science and high-power laser technology itself. The network provides these students not only with access to the most advanced instrumentation and laser facilities, but also the opportunities to interact and collaborate with students from other institutions and with a large group of experienced scientists. As the largest university-based laser users’ facility in the world, the Omega Laser Facility at the UR/LLE has served the high-energy-density physics (HEDP) and inertial fusion science community for nearly 40 years. The multi-beam multi-kJ OMEGA EP Laser System brings unique capabilities to the LaserNetUS network. The combination of high intensity and high energy in short- and long-pulse operation together with solid or gas-jet targets and externally applied magnetic fields provides users a wide domain of experimental conditions. This award provides a total of eight shot days on OMEGA EP for LaserNetUS users. During the award period of performance (June 2019–November 2021), seven teams have fully utilized the eight shot days for their unique science experiments on OMEGA EP with a total of 83 target shots. These experiments involve 13 graduate students, two undergraduate students and six postdoctoral researchers. Results have been widely disseminated at international conferences including LaserNetUS annual meeting (~20 presentations including three invited), and in peer-reviewed journal publications (three published with several manuscripts in preparation).

36 MATERIALS SCIENCE↗

Saturn-ring proton backlighters for the National Ignition Facility

Proton radiography is a well-established technique for measuring electromagnetic fields in high-energy-density plasmas. Fusion reactions producing monoenergetic particles, such as D 3 He, are commonly used as a source, produced by a capsule implosion. Using smaller capsules for radiography applications is advantageous as the source size decreases, but on the National Ignition Facility (NIF), this can introduce complications from increasing blow-by light, since the phase plate focal spot size is much larger than the capsules. In this article, we report a demonstration of backlighter targets where a “Saturn” ring is placed around the capsule to block this light. The nuclear performance of the backlighters is unperturbed by the addition of a ring. We also test a ring with an equatorial cutout, which severely affects the proton emission and is not viable for radiography applications. These results demonstrate the general viability of Saturn ring backlighter targets for use on the NIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparison of CNN-Based Image Classification Approaches for Implementation of Low-Cost Multispectral Arcing Detection

Camera-based sensing has benefited in recent years from developments in machine learning data processing methods, as well as improved data collection options such as Unmanned Aerial Vehicles (UAV) mounted sensors. However, cost considerations, both for the initial purchase of sensors as well as updates, maintenance, or potential replacement if damaged, can limit adoption of more expensive sensing options for some applications. To evaluate more affordable options with less expensive, more available, and more easily replaceable hardware, we examine the use of machine learning-based image classification with custom datasets, utilizing deep learning based-image classification and the use of ensemble models for sensor fusion. Utilizing the same models for each camera to reduce technical overhead, we showed that for a very representative training dataset, camera-based detection can be successful for detection of electrical arcing. We also use multiple validation datasets, based on conditions expected to be of varying difficulty, to evaluate custom data. These results show that ensemble models of different data sources can mitigate risks from gaps in training data, though the system will be less redundant for those cases unless other precautions are taken. We found that with good quality custom datasets, data fusion models can be utilized without specialization in design to the specific cameras utilized, allowing for less specialized, more accessible equipment to be utilized as multispectral camera components. This approach can provide an alternative to expensive sensing equipment for applications in which lower-cost or more easily replaceable sensing equipment is desirable.

convolutional neural networks↗

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

Abstract Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.

60 APPLIED LIFE SCIENCES↗

Activation Analysis for the Inboard Region of FNSF Using SERPENT

This study describes an application of the SERPENT 2 code with the TENDL-2017 nuclear data library and the latest available model features of the Fusion Energy System Studies–Fusion Nuclear Science Facility (FNSF), to evaluate the activation of components after shutdown at 1, 10, and 100 years, assuming a plant lifetime of 8.5 full-power years. The primary parameters evaluated include the specific activity, decay heat, and waste disposal rating (WDR). The specific activity and decay heat are calculated with SERPENT 2 using a 360-deg model of the FNSF, while the WDR is calculated and classified based on the waste disposal limits established by the U.S. Nuclear Regulatory Commission under 10 CFR 61.55 as well as by using the Fetter approach. A python-based script developed for a previous high-level waste classification and analysis study was implemented and adapted to this research to calculate the WDR by comparing nuclide concentrations to the values established in 10 CFR 61.55 to generate a waste classification for each component surveyed. As only three short-lived isotopes have limitations for classifications beyond Class A, of which only 63Ni is present in appreciable quantities, there is a limit to the amount that short-lived isotopes contribute to the most significant waste analyzed here. In most cases, a handful of long-lived isotopes can be problematic, such as 59Ni and 94Nb, for example, which are solely responsible for multiple Class C classifications. The results herein reported heavily depend on the specific materials and mass/volume fractions in the specific model used in this study, which has changed and evolved since the inception of the FNSF concept and past studies. Furthermore, the more significant contributions of this study may be the development of a modeling and simulation toolkit and a strategy to perform these calculations, so to help evaluate and optimize future fusion facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transport of an intense proton beam from a cone-structured target through plastic foam with unique proton source modeling

Laser-accelerated proton beams are applicable to several research areas within high-energy density science, including warm dense matter generation, proton radiography, and inertial confinement fusion, which all involve transport of the beam through matter. Here, we report on experimental measurements of intense proton beam transport through plastic foam blocks. The intense proton beam was accelerated by the 10 ps, 700 $\textit{J}$ OMEGA EP laser irradiating a curved foil target, and focused by an attached hollow cone. The protons then entered the foam block of density 0.38 g/cm 3 and thickness 0.55 or 1.00 mm. At the rear of the foam block, a Cu layer revealed the cross section of the intense beam via proton- and hot electron-induced Cu-K α emission. Images of x-ray emission show a bright spot on the rear Cu film indicative of a forward-directed beam without major breakup. 2D fluid-PIC simulations of the transport were conducted using a unique multi-injection source model incorporating energy-dependent beam divergence. Along with postprocessed calculations of the Cu – $K_α$ emission profile, simulations showed that protons retain their ballistic transport through the foam and are able to heat the foam up to several keV in temperature. The total experimental emission profile for the 1.0 mm foam agrees qualitatively with the simulated profile, suggesting that the protons indeed retain their beamlike qualities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Additive Manufacturing of Tool Steels

This article provides a brief overview of additive manufacturing (AM) of tool steels via various AM technologies such as laser powder bed fusion, electron powder bed fusion, blown powder directed energy deposition, and binder jet AM. The discussion includes process overview and covers the mechanism, advantages, and applications of each of these techniques.

Nandwana, Peeyush↗