Inertial Confinement Fusion Experiments Research Articles

Collective stimulated Brillouin scattering modes of two crossing laser beams with shared scattered wave

In inertial confinement fusion (ICF), overlapping of laser beams is common. Owing to the effective high laser intensity of the overlapped beams, the collective mode of stimulated Brillouin scattering (SBS) with a shared scattered light wave is potentially important. In this work, an exact analytic solution for the convective gain coefficient of the collective SBS modes with shared scattered wave is presented for two overlapped beams based on a linear kinetic model. The effects of the crossing angle, polarization states, and finite beam overlapping volume of the two laser beams on the shared light modes are analyzed for cases with zero and nonzero wavelength difference between the two beams. It is found that all these factors have a significant influence on the shared light modes of SBS. Furthermore, the out-of-plane modes, in which the wavevectors of daughter waves lie in different planes from the two overlapped beams, are found to be important for certain polarization states and especially for obtuse crossing angles. In particular, adjusting the polarization directions of the two beams to be orthogonal to each other or tuning the wavelength difference to a sufficiently large value (of the order of nanometers) are found to be effective methods to suppress the shared light modes of SBS. This work will be helpful for comprehending and suppressing collective SBS with shared scattered waves in ICF experiments.

Considerations for the modeling of the laser ablation region of ICF targets with Lagrangian simulations

Recently, much effort has been dedicated to the improvement of models and modeling choices utilized in radiation hydrodynamic simulations of direct drive inertial confinement fusion experiments in an effort to improve their predictive capability. In this paper, we consider the choice in mesh for the simulation of the laser ablation of a direct-drive-like target and compare Lagrangian simulations with various mesh zoning choices with Eulerian simulations with fixed resolution in the laser energy deposition region. Using these simulations, we demonstrate how errors in ablation pressure, laser deposition rate, shock speed, and density profile arise from insufficient zoning following from the conservation of mass of Lagrangian zones. These considerations place stringent requirements on the initial t = 0 zoning in the solid density shell for simulations aiming at resolving the ablation and laser absorption region. However, with sufficiently fine zoning in the t = 0 shell, agreement with Eulerian simulations and analytic scaling laws can be recovered.

Density evolution after shock release from laser-driven polystyrene (CH) targets in inertial confinement fusion

The evolution of the plasma density in the rarefaction wave formed after a laser-driven shock is released from a CH foil was measured using optical interferometry. It was found that the plasma density profile is very sensitive to the conditions at the back surface of the foil before the shock release. Dedicated experiments demonstrated that radiation preheat by coronal x rays caused early expansion of the back surface and faster expansion of the rarefaction wave. Radiation-hydrodynamics simulations with accurate modeling of radiation preheat from the plasma corona are in good agreement with the experimental results. The early expansion of material interfaces due to coronal x-ray preheat must be evaluated in designing and interpreting laser-driven inertial confinement fusion experiments.

Analyzing and relieving the thermal issues caused by fabrication details of a deuterium cryogenic target

In inertial confinement fusion experiments, fuel quality is determined mainly by the thermal environment of the capsule in the layering procedure. Owing to the absence of a radial thermal gradient, formed deuterium–deuterium (DD) ice shells in the capsule are thermally instable. To obtain a solid DD layer with good quality and long lifetime, stringent demands must be placed on the thermal performance of cryogenic targets. In DD cryogenic target preparation, two issues arise, even after the capsule’s temperature uniformity has been improved by the use of thick aluminized films. The first is the inconsistent ice shape, which is related to the capsule’s thermal field. In this article, some typical fabrication details are investigated, including adhesive penetration during assembly, the presence of the fill tube, the optical properties of the hohlraum and film surfaces, the jacket–hohlraum connection, deviations in capsule location, and asymmetrical contact at the arm–jacket interfaces. Detailed comparisons of the thermal effects of these factors provide guidance for target optimization. The second issue is the instability of seeding crystals in the fill tube due to unsteadiness of the direction of the thermal gradient in the fill tube assembly. An additional thermal controller is proposed, analyzed, and optimized to provide robust controllability of tube temperature. The analysis results and optimization methods presented in this article should not only help in dealing with thermal issues associated with DD cryogenic targets, but also provide important references for engineering design of other cryogenic targets.

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

A sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

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. 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.

Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning

Building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While simulation codes are used to model ICF implosions, incomplete physics and the need for approximations deteriorate their predictive capability. Identification of relationships between controllable design inputs and measurable outcomes can help guide the future design of experiments and development of simulation codes, which can potentially improve the accuracy of the computational models used to simulate ICF implosions. In this paper, we leverage developments in machine learning (ML) and methods for ML feature importance/sensitivity analysis to identify complex relationships in ways that are difficult to process using expert judgment alone. We present work using random forest (RF) regression for prediction of yield, velocity, and other experimental outcomes given a suite of design parameters, along with an assessment of important relationships and uncertainties in the prediction model. We show that RF models are capable of learning and predicting on ICF experimental data with high accuracy, and we extract feature importance metrics that provide insight into the physical significance of different controllable design inputs for various ICF design configurations. These results can be used to augment expert intuition and simulation results for optimal design of future ICF experiments.

Development of a deuterium-ice extruder for inertial confinement fusion experiments on the Z Facility.

A deuterium-ice extruder has been developed for inertial confinement fusion experiments on the Sandia National Laboratories Z Facility. The screw-driven extruder is filled via desublimation, where a slow flow of deuterium gas enters the extruder cavity and freezes to the walls without entering the liquid phase. Ice generated in this manner is optically clear, demonstrating its high uniformity. When the extruder cavity is filled with ice, the screw is driven downward, closing off the gas-fill line. With the ice cavity isolated, further screw rotation compresses the deuterium through a nozzle, extruding a fiber. Fiber diameters ranging from 200 to 500 µm have been extruded to lengths of 1.5 feet before hitting the vacuum chamber floor. The fiber straightness improves with the nozzle length-to-diameter aspect ratio. Deuterium-ice fibers can persist in high vacuum for more than 10min before breaking free from the nozzle. The peripheral infrastructure required for Z experimental operations is under development. An in-vacuum stepper-motor-based drive system will allow remote operation, and a translating cathode will ensure proper placement of the fiber in the powerflow hardware.

Detrimental effects and mitigation of the joint feature in double shell implosion simulations

Double shell capsules provide an attractive option in inertial confinement fusion experiments due to their potential for achieving a low-convergence, robust burn. However, these designs suffer from symmetry degradation and accompanying reduced fuel confinement due to the currently necessary joint between the two hemispheres of the outer shell. The gap widens as a result of the excess ablation pressure produced by x rays that penetrate the joint during the drive phase, and this perturbation grows and imprints onto the inner shell during the collision. xRAGE Eulerian radiation-hydrodynamic simulations predict significant reductions in deuterium–tritium fusion yields compared to joint-less simulations when the depth of the outer joint is increased, whereas the performance is less sensitive to the depth of the inner gap. Here we examine the technique of plating the insides of the outer gap with a high-Z material to mitigate the impact of this feature. Gold-plating in quantities comparable to or exceeding the “missing” outer shell mass shows promise toward restoring both implosion symmetry and yield closer to the joint-less levels, and synthetic diagnostics suggest that high-energy x-ray radiographs can capture this shape retention of the inner and outer shells in experiments.

Understanding the effects of neutron scattering for neutron-yield-isotropy measurements at the NIF.

Neutron-yield diagnostics at the NIF have been upgraded to include 48 detectors placed around the NIF target chamber to assess the DT-neutron-yield isotropy for inertial confinement fusion experiments. Real-time neutron-activation detectors are used to understand yield asymmetries due to Doppler shifts in the neutron energy attributed to hotspot motion, variations in the fuel and ablator areal densities, and other physics effects. In order to isolate target physics effects, we must understand the contribution due to neutron scattering associated with the different hardware configurations used for each experiment. We present results from several calibration experiments that demonstrate the ability to achieve our goal of 1% or better precision in determining the yield isotropy.

Reducing direct drive preheat with dopants

Preheat in laser-driven experiments can have negative impacts on inertial confinement fusion (ICF) and hydrodynamic experiments. While many groups employ the use of dopants to reduce or block preheat, direct quantification has not previously been explored. We developed a planar platform and a series of ablator targets to measure the electron and x-ray spectra generated by laser-plasma interactions with a direct drive using OMEGA-60. By comparing both thin ablators (75m) and thick ablators (270 m) that were either pure CH, 3% Si doped or 3% I doped, we were able to measure differences in electron and x-ray spectra. In addition, we observed the preheat growth of tracer layers and observed reductions in the growth with different materials. We find that iodine or a thin gold layer is the best at tamping the direct-drive preheat at OMEGA, but that the growth is still significant.

Application of an energy-dependent instrument response function to analysis of nTOF data from cryogenic DT experiments

Neutron time-of-flight (nTOF) detectors are used to diagnose the conditions present in inertial confinement fusion (ICF) experiments and basic laboratory physics experiments performed on an ICF platform. The instrument response function (IRF) of these detectors is constructed by convolution of two components: an x-ray IRF and a neutron interaction response. The shape of the neutron interaction response varies with incident neutron energy, changing the shape of the total IRF. Analyses of nTOF data that span a broad range of energies must account for this energy-dependence in order to accurately infer plasma parameters and nuclear properties in ICF experiments. This work briefly reviews a matrix multiplication approach to convolution, which allows for an energy-dependent change in the shape of the IRF. This method is applied to synthetic data resembling symmetric cryogenic DT implosions to examine the effect of the energy-dependent IRF on the inferred areal density. The results of forward fits that infer ion temperatures and areal densities from nTOF data collected during cryogenic DT experiments on OMEGA are also discussed.

Fuel convergence sensitivity in indirect drive implosions

In inertial confinement fusion experiments at the National Ignition Facility, a spherical shell of deuterium–tritium fuel is imploded in an attempt to reach the conditions needed for fusion, self-heating, and eventual ignition. Since theory and simulations indicate that ignition efficacy in 1D improves with increasing imploded fuel convergence ratio, it is useful to understand the sensitivity of the scale-invariant fuel convergence on all measurable or inferable 1D parameters. In this paper, we develop a simple isobaric and isentropic compression scaling model incorporating sensitivity to the in-flight adiabat inferred from shock strengths, to measured implosion velocity, and to known initial ablator and fuel aspect ratio and mass ratio. The model is first benchmarked to 1D implosion simulations spanning a variety of relevant implosion designs. We then use the model to compare compressibility trends across all existing indirect-drive layered implosion data from the facility spanning three ablators [CH, carbon (C), and Be], for which in-flight fuel adiabats varied from 1.6 to 5 by varying the number of drive shocks from 2 to 4, peak implosion velocities varied by 1.4×, capsule radii by 50%, and initial fuel aspect ratios by 1.4×. We find that the strength of the first shock is the dominant contributor setting the maximum fuel convergence. We also observe additional sensitivities to successive shock strengths and fuel aspect ratios that improve the agreement between the expected and measured compression for carbon and Be designs with adiabats above 3. A principal finding is that the adiabat 2.5 C-shell designs exhibit less convergence than CH-shell designs of similar inferred in-flight adiabat.

Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data

The design space for inertial confinement fusion (ICF) experiments is vast, and experiments are extremely expensive. Researchers rely heavily on computer simulations to explore the design space in search of high-performing implosions. However, ICF multiphysics codes must make simplifying assumptions, and thus deviate from experimental measurements for complex implosions. For more effective design and investigation, simulations require input from past experimental data to better predict future performance. In this work, we describe a cognitive simulation method for combining simulation and experimental data into a common, predictive model. This method leverages a machine learning technique called “transfer learning,” the process of taking a model trained to solve one task, and partially retraining it on a sparse dataset to solve a different, but related task. In the context of ICF design, neural network models are trained on large simulation databases and partially retrained on experimental data, producing models that are far more accurate than simulations alone. We demonstrate improved model performance for a range of ICF experiments at the National Ignition Facility and predict the outcome of recent experiments with less than 10% error for several key observables. We discuss how the methods might be used to carry out a data-driven experimental campaign to optimize performance, illustrating the key product—models that become increasingly accurate as data are acquired.

Mitigation of mode-one asymmetry in laser-direct-drive inertial confinement fusion implosions

Nonuniformities present in the laser illumination and target in laser-driven inertial confinement fusion experiments lead to an asymmetric compression of the target, resulting in an inefficient conversion of shell kinetic energy to thermal energy of the hot-spot plasma. In this paper, the effects of asymmetric compression of cryogenic deuterium tritium laser-direct-drive implosions are examined using a suite of nuclear and x-ray diagnostics on the OMEGA laser. The neutron-averaged hot-spot velocity (u→hs) and apparent ion temperature (Ti) asymmetry are determined from neutron time-of-flight measurements of the primary deuterium tritium fusion neutron energy spectrum, while the areal density (ρR) of the compressed fuel surrounding the hot spot is inferred from measurements of the scattered neutron energy spectrum. The low-mode perturbations of the hot-spot shape are characterized from x-ray self-emission images recorded along three quasi-orthogonal lines of sight. Implosions with significant mode-1 laser-drive asymmetries show large hot-spot velocities (>100 km/s) in a direction consistent with the hot-spot elongation observed in x-ray images, measured Ti asymmetry, and ρR asymmetry. Laser-drive corrections have been applied through shifting the initial target location in order to mitigate the observed asymmetry. With the asymmetry corrected, a more-symmetric hot spot is observed with reduced u→hs, Ti asymmetry, ρR asymmetry, and a 30% increase in the fusion yield.

Measurement of L-shell emission from mid-Z targets under non-LTE conditions using Transmission Grating Spectrometer and DANTE power diagnostics.

In this work, we present the measurement of L-band emission from buried Sc/V targets in experiments performed at the OMEGA laser facility. The goal of these experiments was to study non-local thermodynamic equilibrium plasmas and benchmark atomic physics codes. The L-band emission was measured simultaneously by the time resolved DANTE power diagnostic and the recently fielded time integrated Soreq-Transmission Grating Spectrometer (TGS) diagnostic. The TGS measurement was used to support the spectral reconstruction process needed for the unfolding of the DANTE data. The Soreq-TGS diagnostic allows for broadband spectral measurement in the 120 eV-2000 eV spectral band, covering L- and M-shell emission of mid- and high-Z elements, with spectral resolution λ/Δλ = 8-30 and accuracy better than 25%. The Soreq-TGS diagnostic is compatible with ten-inch-manipulator platforms and can be used for a wide variety of high energy density physics, laboratory astrophysics, and inertial confinement fusion experiments.

Spectral sensor error analysis for measuring x-ray radiation drive using the DANTE diagnostic toward inertial confinement fusion experiments.

DANTE is a diagnostic used to measure the x-radiation drive produced by heating a high-Z cavity ("hohlraum") with high-powered laser beams. It records the spectrally and temporally resolved radiation flux at x-ray energies between 50 eV and 20 keV. Each sensor configuration on DANTE is composed of filters, mirrors, and x-ray diodes to define 18 different x-ray channels whose output is voltage as a function of time. The absolute flux is then determined from the photometric calibration of the sensor configuration and a spectral reconstructing algorithm. The reconstruction of the spectra vs time from the measured voltages and known response of each channel has presented challenges. We demonstrate a novel approach here for quantifying the error on the determined flux based on the channel sensor configuration and most commonly used reconstruction algorithm. In general, we find that the integrated spectral flux from a hohlraum can robustly be reconstructed (within ∼14%) using a traditional unfold approach with as few as ten channels due to the underlying assumption of a largely Planckian spectral intensity distribution.

Neural network for 3D inertial confinement fusion shell reconstruction from single radiographs.

In inertial confinement fusion (ICF), x-ray radiography is a critical diagnostic for measuring implosion dynamics, which contain rich three-dimensional (3D) information. Traditional methods for reconstructing 3D volumes from 2D radiographs, such as filtered backprojection, require radiographs from at least two different angles or lines of sight (LOS). In ICF experiments, the space for diagnostics is limited, and cameras that can operate on fast timescales are expensive to implement, limiting the number of projections that can be acquired. To improve the imaging quality as a result of this limitation, convolutional neural networks (CNNs) have recently been shown to be capable of producing 3D models from visible light images or medical x-ray images rendered by volumetric computed tomography. We propose a CNN to reconstruct 3D ICF spherical shells from single radiographs. We also examine the sensitivity of the 3D reconstruction to different illumination models using preprocessing techniques such as pseudo-flatfielding. To resolve the issue of the lack of 3D supervision, we show that training the CNN utilizing synthetic radiographs produced by known simulation methods allows for reconstruction of experimental data as long as the experimental data are similar to the synthetic data. We also show that the CNN allows for 3D reconstruction of shells that possess low mode asymmetries. Further comparisons of the 3D reconstructions with direct multiple LOS measurements are justified.

The Scattered Light Time-history Diagnostic suite at the National Ignition Facility

The Scattered Light Time-history Diagnostic (SLTD) is being implemented at the National Ignition Facility (NIF) to greatly expand the angular coverage of absolute scattered-light measurements for direct- and indirect-drive inertial confinement fusion (ICF) experiments. The SLTD array will ultimately consist of 15 units mounted at a variety of polar and azimuthal angles on the NIF target chamber, complementing the existing NIF backscatter suite. Each SLTD unit collects and diffuses scattered light onto a set of three optical fibers, which transport the light to filtered photodiodes to measure scattered light in different wavelength bands: stimulated Brillouin scattering (350 nm-352nm), stimulated Raman scattering (430 nm-760nm), and ω/2 (695 nm-745nm). SLTD measures scattered light with a time resolution of ∼1ns and a signal-to-noise ratio of up to 500. Currently, six units are operational and recording data. Measurements of the angular dependence of scattered light will strongly constrain models of laser energy coupling in ICF experiments and allow for a more robust inference of the total laser energy coupled to implosions.

Thresholds of absolute two-plasmon-decay and stimulated Raman scattering instabilities driven by multiple broadband lasers

Thresholds for the absolute stimulated Raman scattering (SRS) and two-plasma decay (TPD) instabilities driven by multiple broadband laser beams are evaluated using 3D simulations at conditions relevant to inertial confinement fusion experiments. Multibeam TPD and SRS backscatter are found to be easier to mitigate with bandwidth than the corresponding single-beam instabilities. A relative bandwidth of 1% increases the threshold for absolute SRS backscatter by a factor of 4 at conditions relevant to ongoing National Ignition Facility experiments and should be sufficient to keep all of the absolute instabilities below threshold in experiments with similar conditions.