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At least 307 records · Page 17

The physics of gain relevant to inertial fusion energy target designs

In inertial confinement fusion, pellets of deuterium tritium fuel are compressed and heated to the conditions where they undergo fusion and release energy. The target gain (ratio of energy released from the fusion reactions to the energy in the drive source) is a key parameter in determining the power flow and economics of an inertial fusion energy (IFE) power plant. In this study, the physics of gain is explored for laser-direct-drive targets with driver energy at the megajoule scale. This analysis is performed with the assumption of next-generation laser technologies that are expected to increase convergent drive pressures to over 200 Mbar. This is possible with the addition of bandwidth to the laser spectrum and by employing focal-spot zooming. Simple physics arguments are used to derive scaling laws that describe target gain as a function of laser energy, adiabat, ablation pressure, and implosion velocity. Scaling laws are found for the unablated mass, ablation pressure, areal density, implosion velocity, and in-flight aspect ratio. Furthermore, those scaling laws are then used to explore the design space for IFE targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

FY20 LLNL Experimental Programs at Omega

In Fiscal Year 2020 (FY20), Lawrence Livermore National Laboratory’s (LLNL’s) High-Energy-Density Physics (HED) and Indirect Drive Inertial Confinement Fusion (ICF-ID) programs conducted numerous campaigns on the OMEGA and OMEGA-EP (EP) laser systems. This was the 22ndyear of National Lab collaborative experiments at OMEGA since the Nova Laser at LLNL shut down in 1999, building upon prior collaborations. In FY20overall,these LLNL programs led 375target shots, with 166shots using just the OMEGA laser system and209 shots using just the EP laser system. Approximately 34% of the total number of shots (35OMEGA shots and 93EP shots) supported the Indirect Drive Inertial Confinement Fusion Campaign. The remaining 66% (131OMEGA-only shots and 116EP-only shots) were dedicated to experiments for High-Energy-Density Physics.Highlights of the various HED and ICF-ID campaigns are summarized in the following reports.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Review of pulsed power-driven high energy density physics research on Z at Sandia

Pulsed power accelerators compress electrical energy in space and time to provide versatile experimental platforms for high energy density and inertial confinement fusion science. The 80-TW “Z” pulsed power facility at Sandia National Laboratories is the largest pulsed power device in the world today. Z discharges up to 22 MJ of energy stored in its capacitor banks into a current pulse that rises in 100 ns and peaks at a current as high as 30 MA in low-inductance cylindrical targets. Considerable progress has been made over the past 15 years in the use of pulsed power as a precision scientific tool. This paper reviews developments at Sandia in inertial confinement fusion, dynamic materials science, x-ray radiation science, and pulsed power engineering, with an emphasis on progress since a previous review of research on Z in Physics of Plasmas in 2005.

Sinars, D. B. (ORCID:0000000155473532)↗

Deep learning for NLTE spectral opacities

Computer simulations of high energy density science experiments are computationally challenging, consisting of multiple physics calculations including radiation transport, hydrodynamics, atomic physics, nuclear reactions, laser–plasma interactions, and more. To simulate inertial confinement fusion (ICF) experiments at high fidelity, each of these physics calculations should be as detailed as possible. However, this quickly becomes too computationally expensive even for modern supercomputers, and thus many simplifying assumptions are made to reduce the required computational time. Much of the research has focused on acceleration techniques for the various packages in multiphysics codes. In this work, we explore a novel method for accelerating physics packages via machine learning. The non-local thermodynamic equilibrium (NLTE) package is one of the most expensive calculations in the simulations of indirect drive inertial confinement fusion, taking several tens of percent of the total wall clock time. We explore the use of machine learning to accelerate this package, by essentially replacing the physics calculation with a deep neural network that has been trained to emulate the physics code. Overall, we demonstrate the feasibility of this approach on a simple problem and perform a side-by-side comparison of the physics calculation and the neural network inline in an ICF Hohlraum simulation. We show that the neural network achieves a 10× speed up in NLTE computational time while achieving good agreement with the physics code for several quantities of interest.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Imaging velocity interferometer system for any reflector (VISAR) diagnostics for high energy density sciences

Two variants of optical imaging velocimetry, specifically the one-dimensional streaked line-imaging and the two-dimensional time-resolved area-imaging versions of the Velocity Interferometer System for Any Reflector (VISAR), have become important diagnostics in high energy density sciences, including inertial confinement fusion and dynamic compression of condensed matter. Here, we give a brief review of the historical development of these techniques, then describe the current implementations at major high energy density (HED) facilities worldwide, including the OMEGA Laser Facility and the National Ignition Facility. We illustrate the versatility and power of these techniques by reviewing diverse applications of imaging VISARs for gas-gun and laser-driven dynamic compression experiments for materials science, shock physics, condensed matter physics, chemical physics, plasma physics, planetary science and astronomy, as well as a broad range of HED experiments and laser-driven inertial confinement fusion research.

47 OTHER INSTRUMENTATION↗

Neural network surrogate models for equations of state

Equation of state (EOS) data provide necessary information for accurate multiphysics modeling, which is necessary for fields such as inertial confinement fusion. Here, we suggest a neural network surrogate model of energy and entropy and use thermodynamic relationships to derive other necessary thermodynamic EOS quantities. We incorporate phase information into the model by training a phase classifier and using phase-specific regression models, which improves the modal prediction accuracy. Our model predicts energy values to 1% relative error and entropy to 3.5% relative error in a log-transformed space. Although sound speed predictions require further improvement, the derived pressure values are accurate within 10% relative error. Our results suggest that neural network models can effectively model EOS for inertial confinement fusion simulation applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Diagnosing Thermonuclear Burn in Fusion Implosions using Ultra-Fast Gas Cherenkov Detectors [Slides]

This presentations addresses these questions. What is fusion and what is ignition? How does LASER driven Inertial Confinement Fusion work? What can we measure and what does it tell us about fusion? How do Gas Cherenkov detectors work and what do they tell us? What are our plans for the future? In brief, the take away messages for this presentation are as follows: DT fusion reaction history provides crucial physics for ICF; gamma reaction history diagnostics are ready to resolve burn width on ignition shots; and GCDs have a lot of potential solving some of the questions related to fusion science.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Antimatter propulsion, status and prospects

The use of advanced propulsion techniques must be considered if the currently envisioned launch date of the manned Mars mission were delayed until 2020 or later. Within the next thirty years, technological advances may allow such methods as beaming power to the ship, inertial-confinement fusion, or mass-conversion of antiprotons to become feasible. A propulsion system with an ISP of around 5000 s would allow the currently envisioned mission module to fly to Mars in 3 months and would require about one million pounds to be assembled in Earth orbit. Of the possible methods to achieve this, the antiproton mass-conversion reaction offers the highest potential, the greatest problems, and the most fascination. Increasing the production rates of antiprotons is a high priority task at facilities around the world. The application of antiprotons to propulsion requires the coupling of the energy released in the mass-conversion reaction to thrust-producing mechanisms. Recent proposals entail using the antiprotons to produce inertial confinement fusion or to produce negative muons which can catalyze fusion. By increasing the energy released per antiproton, the effective cost, (dollars/joule) can be reduced. These proposals and other areas of research can be investigated now. These short term results will be important in assessing the long range feasibility of an antiproton powered engine.

Howe, Steven D.↗

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗

Hollow-cathode chemical vapor deposition of thick, low-stress diamond-like carbon films

A radio-frequency (RF), hollow-cathode plasma source with confining magnetic field is described for the chemical vapor deposition of thick ( > 10 µm), amorphous diamond-like carbon ablator films for inertial confinement fusion applications. Plasma is characterized by optical emission spectroscopy, while properties of the resultant films are measured by a combination of profilometry, Rutherford backscattering spectrometry, elastic recoil detection analysis, X-ray diffraction, Raman spectroscopy, and atomic force microscopy. The dependence of the deposition rate, film density, elemental composition, self-bias and residual stress is reported as a function of RF power. Higher density films were found when using Ar plasma, than N 2 or H 2 plasma. The coatings produced are x-ray amorphous, exhibit low compressive stress ( ~ 100 MPa), high density ( < 1.7 g/cm 3 ), hydrogen content of ~ 30 at.%, and a low average roughness of 0.75 nm. Finally, applications of these films as tunable-density ablators for inertial confinement fusion experiments are discussed.

36 MATERIALS SCIENCE↗

Thermal transport in warm dense matter revealed by refraction-enhanced x-ray radiography with a deep-neural-network analysis

Abstract Transport properties of high energy density matter affect the evolution of many systems, ranging from the geodynamo in the Earth’s core, to hydrodynamic instability growth in inertial confinement fusion capsules. Large uncertainties of these properties are present in the warm dense matter regime where both plasma models and condensed matter models become invalid. To overcome this limit, we devise an experimental platform based on x-ray differential heating and time-resolved refraction-enhanced radiography coupled to a deep neural network. We retrieve the first measurement of thermal conductivity of CH and Be in the warm dense matter regime and compare our measurement with the most commonly adopted models. The discrepancies observed are related to the estimation of a correction term from electron-electron collisions. The results necessitate improvement of transport models in the warm dense matter regime and could impact the understanding of the implosion performance for inertial confinement fusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A novel photomultiplier tube neutron time-of-flight detector

A traditional neutron time-of-flight (nTOF) detector used in inertial confinement fusion consists of a scintillator coupled with a photomultiplier tube (PMT). The instrument response function (IRF) of such a detector is dominated by the scintillator-light decay. At DT neutron yields larger than 1013 a novel detector consisting of a microchannel-plate photomultiplier tube in a housing without a scintillator (PMT nTOF) can be used to measure DT yield, ion temperature, and neutron velocity. Most of the neutron signal in PMT nTOF is produced from neutron interaction with a PMT window. The direct interaction of neutrons with MCP has negligible contribution. The elimination of the scintillator removes the scintillator decay from the instrument response function and makes the IRF of the PMT nTOF faster, which makes the ion temperature and neutron velocity measurements more accurate. Three PMT nTOFs were deployed on the OMEGA Laser System for the first time to diagnose inertial confinement fusion plasma. Here, the design details, characteristics, and calibration results of these detectors in DT implosions on OMEGA are presented. Recommendations on the use of different PMTs for specific applications are provided.

47 OTHER INSTRUMENTATION↗

Investigating the impact of intermediate-mode perturbations on diagnosing plasma conditions in DT cryogenic implosions via synthetic x-ray Thomson scattering

The pursuit of inertial confinement fusion ignition target designs requires precise experimental validation of the conditions within imploding capsules, in particular the density and temperature of the compressed shell. Previous work has identified x-ray Thomson scattering (XRTS) as a viable diagnostic tool for inferring the in-flight compressed deuterium-tritium shell conditions during capsule implosions (Poole et al 2022 Phys. Plasmas 29 072703). However, this study focused on one-dimensional simulations, which do not account for the growth of hydrodynamic instabilities. In this work, two-dimensional DRACO simulations incorporating intermediate-mode perturbations up to Legendre mode l = 50 were used to generate synthetic XRTS spectra with the SPECT3D code. The analysis employed Markov-Chain Monte Carlo techniques to infer plasma conditions from these spectra. The results demonstrate that the XRTS diagnostic platform can effectively discern the in-flight compressed shell conditions for targets with varying adiabats, even in the presence of intermediate-mode perturbations. This work underscores the potential of XRTS for realistic inertial confinement fusion experiments, providing a robust method for probing the complex dynamics of fusion implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inverse Bremsstrahlung Absorption

Inverse bremsstrahlung absorption was measured based on transmission through a finite-length plasma that was thoroughly characterized using spatially resolved Thomson scattering. Expected absorption was then calculated using the diagnosed plasma conditions while varying the absorption model components. To match data, it is necessary to account for: (1) the Langdon effect; (2) laser-frequency (rather than plasma-frequency) dependence in the Coulomb logarithm, as is typical of bremsstrahlung theories but not transport theories; and (3) a correction due to ion screening. Radiation-hydrodynamic simulations of inertial confinement fusion implosions have to date used a Coulomb logarithm from the transport literature and no screening correction. Here, we anticipate that updating the model for collisional absorption will substantially revise our understanding of laser-target coupling for such implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Self-consistent theory of the Darrieus–Landau and Rayleigh–Taylor instabilities with self-generated magnetic fields

The Rayleigh–Taylor (RT) and Darrieus–Landau (DL) instabilities are studied in an inertial confinement fusion context within the framework of small critical-to-shell density ratio D R and weak acceleration regime, i.e., large Froude number Fr. The quasi-isobaric analysis in Sanz et al. is completed with the inclusion of non-isobaric and self-generated magnetic-field effects. The analysis is restricted to perturbation wavelengths k~1 larger than the conduction length scale at the ablation front, yet its validity ranges from wavelengths shorter and larger than the conduction layer width (distance between the ablation front and the critical surface). The use of a sharp boundary model leads to a single analytical expression of the dispersion relation encompassing both instabilities. The two new effects come into play by modifying the perturbed mass and momentum fluxes at the ablation front. The momentum flux (perturbed pressure at the spike) is the predominant stabilizing mechanism in the RT instability (overpressure) and the driving mechanism in the DL instability (underpressure). The non-isobaric effects notably modify the scaling laws in the DL limit, leading to an underpressure scaling as ~k –11/15 rather than ~k –2/5 obtained in the quasi-isobaric model. The magnetic fields are generated due to misalignment between pressure and density gradients (Biermann battery effect). They affect the hydrodynamics by bending the heat flux lines. Within the framework of this paper, they enhance ablation, resulting in a stabilizing effect that peaks for perturbation wavelengths comparable to the conduction layer width. Here, the combination of parameters D R Fr 2/3 defines the region of predominance of each instability in the dispersion relation. It is proven that the DL region falls outside of the parameter range in inertial confinement fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparison of tungsten versus molybdenum for double shell capsules using machine learning design optimization

Double shell targets are an alternative ignition platform for inertial confinement fusion. One design consideration for double shell targets is the choice of inner shell material to help trap radiation emitted by the hot fuel to aid ignition. Materials such as molybdenum and tungsten are of interest for the inner shell layer of the targets. While molybdenum has a lower density that could inhibit instability growth and allow for radiography and code benchmarking, tungsten has a higher density that could provide more compression and confinement. These tradeoffs have been explored using optimized designs for each material. Our previous work [Vazirani et al., “Coupling 1D xRAGE simulations with machine learning for graded inner shell design optimization in double shell capsules,” Phys. Plasmas 28, 122709 (2021); Vazirani et al., “Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules,” Phys. Plasmas 30, 062704 (2023); and Vazirani et al., “Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design,” Stat. Anal. Data Min. 17, e11698 (2024)] resulted in a multi-fidelity Bayesian optimization framework to find yield-optimized double shell target geometries. By leveraging simulations of varying fidelities (one-dimensional and two-dimensional) to inform one another, the multi-fidelity optimization was able to optimize a design in the highest fidelity with significantly fewer simulations than would be used in a systematic parameter scan. In this work, we apply the multi-fidelity Bayesian optimization to explore the optimized designs of double shell targets with molybdenum and tungsten inner shells as well as the physics producing the high performing implosions. A physics exploration of all the simulations used in this study shows trends in designs that contribute to high yields, ion temperatures, and fuel areal densities. Comparison of molybdenum and tungsten simulations shows that they can produce similar implosion conditions with different geometries, which would be important to study in experiments. Graded density layers produce varying performances with the two materials but continue to be of interest for future studies along with studies of doped inner shell materials and applied surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fundamental factors affecting thermonuclear ignition

Recent inertial confinement fusion experiments on the National Ignition Facility (NIF) have improved performance and interpretability. These results help us address hydrodynamic efficiency, pusher adiabat, tamping, and hot-spot confinement as they pertain to criteria for ignition. Here, we present requirements for propagating burn that are stringent compared to existing literature. The effects of the pusher adiabat on the energy partition for the cold and hot DT are addressed, as well as the persistent discrepancy between the observed and simulated neutron down scattering ratio. The required energy for achieving ignition on NIF and paths forward to optimize or increase the capsule yields for given laser energy are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Observation of Hydrodynamic Flows in Imploding Fusion Plasmas on the National Ignition Facility [plus supplemental information]

Inertial confinement fusion implosions designed to have minimal fluid motion at peak compression often show significant linear flows in the laboratory, attributable per simulations to percent-level imbalances in the laser drive illumination symmetry. In this work, we present experimental results which intentionally varied the mode 1 drive imbalance by up to 4% to test hydrodynamic predictions of flows and the resultant imploded core asymmetries and performance, as measured by a combination of DT neutron spectroscopy and high-resolution x-ray core imaging. Neutron yields decrease by up to 50%, and anisotropic neutron Doppler broadening increases by 20%, in agreement with simulations. Furthermore, a tracer jet from the capsule fill-tube perturbation that is entrained by the hot-spot flow confirms the average flow speeds deduced from neutron spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗