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At least 505 records · Page 28

Hot-spot model for inertial confinement fusion implosions with an applied magnetic field

Imposing a magnetic field on inertial confinement fusion implosions magnetizes the electrons in the compressed fuel; this suppresses thermal losses, which increases temperature and fusion yield. Indirect-drive experiments at the National Ignition Facility with 12 and 26 T applied magnetic fields demonstrate up to 40% increase in temperature, 3× increase in fusion yield, and indicate that magnetization alters the radial temperature profile [Moody et al., Phys. Rev. Lett. 129, 195002 (2022); Lahmann et al., APS DPP (2022)]. In this work, we develop a semi-analytic hot-spot model, which accounts for the two-dimensional (2D) Braginskii anisotropic heat flow due to an applied axial magnetic field. First, we show that hot-spot magnetization alters the radial temperature profile, increasing the central peakedness, which is most pronounced for moderately magnetized implosions (with 8–14 T applied field), compared to both unmagnetized (with no applied field) and highly magnetized (with 26 T or higher applied field) implosions. This model explains the trend in the experimental data, which finds a similarly altered temperature profile in the 12 T experiment. Next, we derive the hot-spot model for gas-filled (Symcap) implosions, accounting for the effects of magnetization on the thermal conduction and in changing the radial temperature (and density) profiles. Using this model, we compute predicted central temperature amplification and yield enhancement scaling with the applied magnetic field. The central temperature fits the experimental data accurately, and the discrepancy in the yield suggests a systematic (independent of applied field) degradation, such as mix, and additional degradation in the reference unmagnetized shot, such as reduced laser drive, increased implosion asymmetry, or the magnetic field suppressing ablator mixing into the hot-spot.

Alpha particles↗

Flexible, integrated modeling of tokamak stability, transport, equilibrium, and pedestal physics

The STEP (Stability, Transport, Equilibrium, and Pedestal) integrated-modeling tool has been developed in OMFIT to predict stable, tokamak equilibria self-consistently with core-transport and pedestal calculations. STEP couples theory-based codes to integrate a variety of physics, including magnetohydrodynamic stability, transport, equilibrium, pedestal formation, and current-drive, heating, and fueling. The input/output of each code is interfaced with a centralized ITER-Integrated Modelling & Analysis Suite data structure, allowing codes to be run in any order and enabling open-loop, feedback, and optimization workflows. This paradigm simplifies the integration of new codes, making STEP highly extensible. STEP has been verified against a published benchmark of six different integrated models. Core-pedestal calculations with STEP have been successfully validated against individual DIII-D H-mode discharges and across more than 500 discharges of the H98,y2 database, with a mean error in confinement time from experiment less than 19%. STEP has also reproduced results in less conventional DIII-D scenarios, including negative-central-shear and negative-triangularity plasmas. Predictive STEP modeling has been used to assess performance in several tokamak reactors. Simulations of a high-field, large-aspect-ratio reactor show significantly lower fusion power than predicted by a zero-dimensional study, demonstrating the limitations of scaling-law extrapolations. STEP predictions have found promising scenarios for an EXhaust and Confinement Integration Tokamak Experiment, including a high-pressure, 80%-bootstrap-fraction plasma. ITER modeling with STEP has shown that pellet fueling enhances fusion gain in both the baseline and advanced-inductive scenarios. Finally, STEP predictions for the SPARC baseline scenario are in good agreement with published results from the physics basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of interpretive modelling of fusion performance in JET DTE2 discharges with TRANSP

In the paper we present an overview of interpretive modelling of a database of JET-ILW 2021 D-T discharges using the TRANSP code. The main aim is to assess our capability of computationally reproducing the fusion performance of various D-T plasma scenarios using different external heating and D-T mixtures, and to understand the performance driving mechanisms. We find that interpretive simulations confirm a general power-law relationship between increasing external heating power and fusion output, which is supported by absolutely calibrated neutron yield measurements. A comparison of measured and computed D-T neutron rates shows that the calculations' discrepancy depends on the absolute neutron yield. The calculations are found to agree well with measurements for higher performing discharges with external heating power above ~20 MW, while low-neutron shots display an average discrepancy of around +40% compared to measured neutron yields. A similar trend is found for the ratio between thermal and beam-target fusion, where larger discrepancies are seen in shots with dominant beam-driven performance. We compare the observations to studies of JET-ILW D discharges, to find that on average the fusion performance is well modelled over a range of heating power, although an increased unsystematic deviation for lower-performing shots is observed. The ratio between thermal and beam-induced D-T fusion is found to be increasing weakly with growing external heating power, with a maximum value of ≳1 achieved in a baseline scenario experiment. An evaluation of the fusion power computational uncertainty shows a strong dependence on the plasma scenario type and fusion drive characteristics, varying between ±25% and 35%. D-T fusion alpha simulations show that the ratio between volume-integrated electron and ion heating from alphas is ≲10 for the majority of analysed discharges. Alphas are computed to contribute between ~15% and 40% to the total electron heating in the core of highest performing D-T discharges. An alternative workflow to TRANSP was employed to model JET D-T plasmas with the highest fusion yield and dominant non-thermal fusion component because of the use of fundamental radio-frequency heating of a large minority in the scenario, which is calculated to have provided ~10% to the total fusion power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Aerodynamic Data Fusion Toward the Digital Twin Paradigm

This paper considers the fusion of two aerodynamic data sets originating from differing types of physical or computer experiments. This paper specifically addresses the fusion of 1) noisy and in-complete fields from wind-tunnel measurements and 2) deterministic but biased fields from numerical simulations. These two data sources are fused in order to estimate the true field that best matches measured quantities that serve as the ground truth. For example, two sources of pressure fields about an aircraft are fused based on measured forces and moments from a wind-tunnel experiment. A fundamental challenge in this problem is that the true field is unknown and cannot be estimated with 100% certainty. A Bayesian framework is employed to infer the true fields conditioned on measured quantities of interest; essentially a statistical correction to the data is performed. The fused data may then be used to construct more accurate surrogate models suitable for early stages of aerospace design. An extension of the proper orthogonal decomposition with constraints is also introduced to solve the same problem. In this work, both methods are demonstrated on fusing the pressure distributions for flow past the RAE2822 airfoil and the Common Research Model wing at transonic conditions. Comparison of both methods reveals that the Bayesian method is more robust when data are scarce and capable of also accounting for uncertainties in the data. Furthermore, given adequate data, the proper-orthogonal-decomposition-based and Bayesian approaches lead to surprisingly similar results.

42 ENGINEERING↗

A multi-MeV alpha particle source via proton-boron fusion driven by a 10-GW tabletop laser

Nuclear fusion between protons and boron-11 nuclei has undergone a revival of interest thanks to the rapid progress in pulsed laser technology. Potential applications of such reaction range from controlled nuclear fusion to radiobiology and cancer therapy. A laser-driven fusion approach consists in the interaction of high-power, high-intensity pulses with H- and B-rich targets. We report on an experiment exploiting proton-boron fusion in CN-BN targets to obtain high-energy alpha particle beams (up to 5 MeV) using a very compact approach and a tabletop laser system with a peak power of ~10 GW, which can operate at high-repetition rate (up to 1 kHz). The secondary resonance in the cross section of proton-boron fusion (~150 keV in the center-of-mass frame) is exploited using a laser-based approach. The generated alpha particles are characterized in terms of energy, flux, and angular distribution using solid-state nuclear-track detectors, demonstrating a flux of ~10 5 particles per second at 10 Hz, and ~10 6 per second at 1 kHz. Hydrodynamic and particle-in-cell numerical simulations support our experimental findings. Potential impact of our approach on future spread of ultra-compact, multi-MeV alpha particle sources driven by moderate intensity (10 16 -10 17 W/cm 2 ) laser pulses is anticipated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Propagation of radio frequency waves through turbulent plasmas

The practical and economic viability of tokamak fusion reactors depends, in a significant way, on the efficiency of radio frequency (RF) waves to deliver energy and momentum to the plasma in the core of the reactor. The RF electromagnetic waves, excited by antenna structures placed near the wall of a tokamak, have to propagate through the turbulent edge plasma along their path to the core of the fusion device. In present day experiments, the radial width of the edge region and scrape-off layer is of the order of a few centimeters. In ITER, and in future fusion reactors, this width will be of the order of tens of centimeters. Any effects on RF waves due to plasma turbulence have to be properly understood in order to optimize the delivery of RF energy and momentum into the core. This paper is on a multi-pronged, theoretical and computational, approach that is being pursued to quantify the effect of edge plasma turbulence on the propagation of RF waves. The theoretical and analytical models are based on solutions of the Faraday-Ampere equation in a magnetized plasma and on the Kirchhoff tangent plane approximation. An effective medium approach has been developed so as to approximate the permittivity of a turbulent plasma by analytical expressions. The computations are being carried out with a newly developed code ScaRF that is based on the finite difference finite domain technique for solving Maxwell's equations. The plasma permittivity can be assigned as desired. The code is being used to validate the analytical and theoretical models and to evaluate their limitations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhanced plasma performance in C-2W advanced beam-driven field-reversed configuration experiments

TAE Technologies’ fifth-generation fusion device, C-2W (also called ‘Norman’), is the world’s largest compact-toroid device and has made significant progress in field-reversed configuration (FRC) plasma performance. C-2W produces record breaking, macroscopically stable, high-temperature advanced beam-driven FRC plasmas, dominated by injected fast particles and sustained in steady state, which is primarily limited by neutral-beam (NB) pulse duration. The NB power supply system has recently been upgraded to extend the pulse length from 30 ms to 40 ms, which allows for a longer plasma lifetime and thus better characterization and further enhancement of FRC performance. An active plasma control system is routinely used in C-2W to produce consistent FRC performance as well as for reliable machine operations using magnet coils, edge-biasing electrodes, gas injection and tunable-energy NBs. Google’s machine learning framework for experimental optimization has also been routinely used to enhance plasma performance. D

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Two-photon absorption laser induced fluorescence measurements of absolute neutral deuterium density, temperature, and bulk flow in Proto-MPEX

Neutral particle control is critical for fusion fueling and confinement. Neutral diagnostics for fusion-relevant plasmas are commonly restricted to line-integrated or ex situ methods. A non-perturbative, two-photon absorption laser induced fluorescence (TALIF) diagnostic is implemented on the Prototype Material Plasma Exposure eXperiment (Proto-MPEX) to probe neutral atomic deuterium in a fusion-relevant plasma at 1 cm intervals along the radius of the vacuum vessel. The diagnostic is situated ~20 m from the vacuum vessel, and a signal is collected along the laser injection axis, requiring only one line-of-sight. TALIF measurements are absolutely calibrated using xenon and krypton. Absolute atomic densities derived from xenon calibration are compared to absolute atomic densities derived from krypton calibration. In this work, preliminary measurements of absolute atomic deuterium density, temperature, and local bulk flow dependence on radial location and input power in Proto-MPEX are presented. Neutral atomic deuterium velocity distribution functions are measured throughout a one-second plasma pulse with a time resolution of 250 ms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Wind Tunnel Data Fusion and Immersive Visualization: A Case Study

This case study describes the process of fusing the data from several wind tunnel experiments into a single coherent visualization. Each experiment was conducted independently and was designed to explore different flow features around airplane landing gear. In the past, it would have been very difficult to correlate results from the different experiments. However, with a single 3-D visualization representing the fusion of the three experiments, significant insight into the composite flowfield was observed that would have been extremely difficult to obtain by studying its component parts. The results are even more compelling when viewed in an immersive environment.

Severance, Kurt↗

Suprathermal electron transport studies in radio-frequency-heated tokamak plasmas

This contribution reports on the study of suprathermal electron radial transport enhancement in the presence of electron-heating radio-frequency waves, such as electron-cyclotron waves or lower-hybrid waves. Since suprathermal electrons emit hard X-rays from Bremsstrahlung, experimental data from hard X-ray measurements are used to follow their dynamics. In particular, electron-cyclotron power modulation experiments performed in TCV show that this transport depends on the total electron-cyclotron power. These results are corroborated by experimentally constrained Fokker-Planck simulations [J. Cazabonne et al, Plasma Phys. Control. Fusion 65, 104001 (2023)]. Similar experiments have been performed in WEST with lower-hybrid waves, and are reported for the first time. Preliminary analyses show potential evidence of suprathermal electron transport, but no clear dependence on wave power nor photon energy at this stage.

Cazabonne, Jean [CEA, IRFM, Saint Paul Lez Durance↗

Normalizing flows for likelihood-free inference with fusion simulations

Fluid-based scrape-off layer transport codes, such as UEDGE, are heavily utilized in tokamak analysis and design, but typically require user-specified anomalous transport coefficients to match experiments. Determining the uniqueness of these parameters and the uncertainties in them to match experiments can provide valuable insights to fusion scientists. Here, we leverage recent work in the area of likelihood-free inference (‘simulation-based inference’) to train a neural network, which enables accurate statistical inference of the anomalous transport coefficients given experimental plasma profile input. UEDGE is treated as a black-box simulator and runs multiple times with anomalous transport coefficients sampled from priors, and the neural network is trained on these simulations to emulate the posterior. The neural network is trained as a normalizing flow model for density estimation, allowing it to accurately represent complicated, high-dimensional distribution functions. With a fixed simulation budget, we compare a single-round procedure to a multi-round approach that guides the training simulations toward a specific target observation. Finally, we discuss the future possibilities for use of amortized models, which train on a wide range of simulations and enable fast statistical inference for results during experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Absolute Neutron Rate Measurement and Non-Thermal/Thermonuclear Fusion Differentiation

The goal of fusion energy is to produce significantly more energy from fusion reactions than is input into the device. One of the products of fusion reactions is neutrons, which, due to their lack of charge, provide a unique view into the parameters of the device. Lawrence Livermore National Laboratory (LLNL) in collaboration with the University of California, Berkeley (UCB) have designed, assembled, and fielded a robust and portable neutron detection system known as PANDA (Portable and Adaptable Neutron Diagnostics for ARPA-E). This detector suite consists of three LaBr activation detectors that are calibrated to give a total neutron yield on shot, and twenty-four scintillators coupled to photo-multiplier tubes (SPMT). The SPMTs can be configured to attain spatial, temporal and/or energy information from fusion neutrons. The system was designed to be portable and is compartmentalized so that individual components can be used at different fusion facilities. During the duration of this work, part of the system was installed at the FuZE facility, a part of Zap Energy. Another component was installed that the CESZAR facility at the University of California, San Diego (UCSD) to support experiments by Magneto-Inertial Fusion Technologies, Inc. (MIFTI). The diagnostics were successful at both locations and the LLNL/UCB team supported the data analysis by creating and running analysis scripts and Monte-Carlo calculations. At Zap Energy the diagnostics demonstrated that the fusion from the FuZE device is thermonuclear in nature, a result that resulted in an invited talk at the American Physical Society Division of Plasma Physics and an invited paper. Additionally, temporal and spatial data was taken using the SPMTs to understand the duration and length of fusion production. At UCSD the neutron yield from the diagnostics was used to show improvements to fusion yields on their gas puff Z-pinch when using a gas shell surrounding the fuel. The success in this diagnostic has led to continued work at both Zap Energy and MIFTI, as well as follow on funding and interest at other fusion energy companies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Neutron irradiation & thermomechanical experiment (NITE) - design

For the reliable long-term operation of fusion power plants, it is crucial to understand and predict the lifetime of materials in use. These materials include all structural and functional materials utilized at the first wall, blanket, magnets, and shielding. The key challenge is, that the harsh environment including high heat fluxes, high thermal stress and stress cycling, neutron irradiation, and sputtering on such materials should not be viewed separately. Currently, the synergistic loads cannot be evaluated experimentally because of the lack of adequate facilities. The purpose of that work is to design a synergetic Neutron Irradiation and Thermomechanical Experiment (NITE) for fusion materials. This design will leverage the existing Advanced-Test-Reactor (ATR), a fission reactor at the Idaho National Laboratory. We also acknowledge that with existing fission reactors the exact fusion condition cannot be created, and the limitations are critically discussed. The combination of neutron irradiation with a high heat flux is the focus. This is realized with an irradiation capsule design that includes a TRISO fueled region inside the capsule to enable a steady-state heat flux on one side of the specimen. In conclusion, the experimental design modeling showed that steady-state heat fluxes of 2.4 MW/m 2 with a thermal gradient of above 250°C can be achieved in a 5 mm thick specimen.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Lighting a Star on Earth—Again and Again

At Lawrence Livermore National Laboratory’s (LLNL) National Ignition Facility (NIF), scientists are learning what it takes to keep a fusion reaction burning. Their latest experiments, presented this week at the American Physical Society’s Division of Plasma Physics annual meeting, build on a series of successful ignition shots to reveal how capsule design and laser precision can sustain record-setting performance. At NIF, researchers are consistently producing plasmas dominated by self-heating from fusion reactions, achieving target gain greater than two — meaning the fusion output energy exceeds twice the energy used to initiate the reaction. Using the world’s most energetic laser to create these conditions, LLNL scientists can explore the detailed physics of ignition and burn that underpin the Laboratory’s stockpile modernization mission. “It’s a bit like lighting a campfire with a match and a single breath,” said LLNL physicist David Schlossberg, who is co-leading the work. “If you have too little fuel, it burns out quickly; too much, and it won’t light at all. We’ve found the balance between capsule mass and drive strength that starts the burn and keeps it going efficiently.” NIF is the only laboratory in the world to have achieved fusion ignition, a historic breakthrough first realized in December 2022. Since then, the facility has repeated ignition ten times, most recently in October 2025, demonstrating the robustness of the experimental platform and the reproducibility of ignition physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Instabilities and Mixing in Inertial Confinement Fusion

By imploding fuel of hydrogen isotopes, inertial confinement fusion (ICF) aims to create conditions that mimic those in the Sun's core. This is fluid dynamics in an extreme regime, with the ultimate goal of making nuclear fusion a viable clean energy source. The fuel must be reliably and symmetrically compressed to temperatures exceeding 100 million degrees Celsius. After the best part of a century of research, the foremost fusion milestone was reached in 2021, when ICF became the first technology to achieve an igniting fusion fuel (thermonuclear instability), and then in 2022 scientific energy breakeven was attained. A key trade-off of the ICF platform is that greater fuel compression leads to higher burn efficiency, but at the expense of amplified Rayleigh–Taylor and Richtmyer–Meshkov instabilities and kinetic-energy-wasting asymmetries. In extreme cases, these three-dimensional instabilities can completely break up the implosion. Even in the highest-yielding 2022 scientific breakeven experiment, high-atomic-number (high-Z) contaminants were unintentionally injected into the fuel. Here we review the pivotal role that fluid dynamics plays in the construction of a stable implosion and the decades of improved understanding and isolated experiments that have contributed to fusion ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗