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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Laser polarization effects on crossed-beam energy transfer in inertial confinement fusion

Crossed-beam energy transfer (CBET) is a consequential process in inertial confinement fusion (ICF) experiments. CBET depends on the polarization state of the interacting lasers and can, in turn, alter their polarization. Here, we derive analytical expressions for two-beam CBET with linearly and circularly polarized light, and present simulations of CBET that include polarization effects for ICF conditions relevant to experiments on the National Ignition Facility. The results show that CBET mixes the polarization of the beams as they propagate through the target and leads to azimuthal power imbalances between beams within a given cone (i.e., at the same polar angle in the target chamber). These variations are shown to correlate with variations in measured backscatter between beams of a same quadruplet. Using circularly polarized, instead of linearly polarized, light produces similar overall levels of CBET within a cone of beams but tends to reduce the azimuthal variations. This is expected to slightly improve irradiation symmetry and reduce the risk of backscatter from stimulated Brillouin scattering. Circular polarization may therefore be beneficial for the next generation of laser fusion drivers.

Physics - Plasma physics↗
DOE OSTI2023

Ray-based cross-beam energy transfer modeling for broadband lasers

Broadband lasers have the potential to mitigate cross-beam energy transfer (CBET) in direct-drive inertial confinement fusion (ICF) experiments. Furthermore, a quantitative assessment of the bandwidth required for CBET mitigation necessitates the development of broadband ray-based CBET models that can be implemented in the radiation-hydrodynamic codes that are used to design ICF experiments. Two different approaches to broadband ray-based CBET modeling (discrete and fixed spectrum) are developed and compared to wave-based calculations. Both approaches give good agreement with wave-based calculations in ICF-relevant configurations. Full-scale 3D calculations show that the bandwidth required for adequate CBET mitigation increases with increasing scale and drive intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Effect of laser preheat in magnetized liner inertial fusion at OMEGA

Integrated magnetized liner inertial fusion (MagLIF) experiments on the OMEGA laser system are modeled to investigate the effects of laser preheat on implosion performance. In both simulations and experiments, preheating the fuel with a laser enhances the neutron yield, with the maximum yield occurring at an optimal preheat laser energy. Increasing the preheat energy past the optimal value reduces the neutron yield. In simulations, the rate of the drop in neutron yield depends on the inclusion of the Nernst effect. The Nernst effect advects the magnetic field away from the center of the fuel region during the preheat stage of MagLIF on OMEGA and weakens magnetic-flux compression. If the Nernst effect is not included, the simulated drop in yield past the optimal preheat laser energy is more gradual as opposed to the sharper drop seen in experiments. Simulations are able to model trend in measured ion temperatures seen in experiments. Here, a mix model is used to show that including mix from the wall in the simulated fuel region further degrades the yield and lowers the optimal preheat laser energy. Simulations with mix predict that increasing the initial axial magnetic field may still enhance yield performance in integrated implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Kinetic-ballooning-bifurcation in tokamak pedestals across shaping and aspect-ratio

We use a new gyrokinetic threshold model to predict a bifurcation in tokamak pedestal width-height scalings that depends strongly on plasma shaping and aspect-ratio. The bifurcation arises from the first and second stability properties of kinetic-ballooning-modes that yields wide and narrow pedestal branches, expanding the space of accessible pedestal widths and heights. The wide branch offers potential for edge-localized-mode-free pedestals with high core pressure. For negative triangularity, low-aspect-ratio configurations are predicted to give steeper pedestals than conventional-aspect-ratio. Both wide and narrow branches have been attained in tokamak experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

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–352 nm), stimulated Raman scattering (430 nm–760 nm), and ω/2 (695 nm–745 nm). SLTD measures scattered light with a time resolution of ~1 ns 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.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Impact of areal-density asymmetries on the loss of confinement and ignition threshold in inertial confinement fusion capsules

In inertial confinement fusion implosion experiments, variations in the shell areal density reduce the shell’s inertia to confine the core pressure. Distorted capsules with large areal-density modulations decompress faster than uniform capsules in the disassembly phase. A simple 3-D analytic hot-spot model is derived to include the effects of low-mode areal-density modulations in the ignition criterion. The generalized 3-D ignition criterion for low modes is shown to depend on both the harmonic mean and the arithmetic mean of the areal density. Here, the “thin spots” in the shell are shown to dominate the loss of confinement as reflected by the harmonic mean definition of areal densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Disruption prevention using rotating resonant magnetic perturbation on J-TEXT

Major plasma disruption is one of the most critical issues to be solved for tokamak fusion reactors. Experiments to prevent mode locking and subsequent disruptions have been carried out on the J-TEXT tokamak using rotating resonant magnetic perturbations (RMPs). The tearing modes, which are locked and lead to disruptions without the application of RMPs, can be accelerated by rotating RMPs to the RMP frequency. As a result, mode locking and subsequent disruptions are delayed or prevented. The effects of RMP amplitude and frequency on disruption prevention have been investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Fixed Source Sensitivity Calculations for Inertial Confinement Fusion Applications

A numerical code library was developed for the radiation transport code MCNP6.3 to calculate generalized response sensitivity coefficients for fixed source neutron transport problems with applications to inertial confinement fusion (ICF) experiments. The new MCNP6.3 dependency is used to generate a novel time convolution response that represents a neutron time-of-flight (nToF) signal. The traditional suite of macroscopic cross-section sensitivities and constrained fixed source probability distribution sensitivities are available for both the standard and the new response tallies in this library. However, novel sensitivity coefficients for the constrained hyperparameters of analytic fixed source probability distributions are emphasized in this work for their connection to ICF neutron transport models. Particularly, advanced Monte Carlo methods are developed for calculating the sensitivity of a nToF signal to perturbations in an ICF plasma’s ion temperature and burn history as well as perturbations in the target liner mass density and the shape parameters of the nToF detector’s impulse response function. Together, these capabilities form an advanced suite of computational tools that can be used to analyze and extract information from any ICF experimental platform.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

On the initiation and evolution of dielectric breakdown in auto-magnetizing liner experiments

Auto-magnetizing (AutoMag) liners are cylindrical tubes composed of discrete metallic helices encapsulated in insulating material; when driven with a ~2 MA, ~100-ns prepulse on the 20 MA, 100-ns rise time Z accelerator, AutoMag targets produced >150 T internal axial magnetic fields. Once the current rise rate of the pulsed power driver reaches sufficient magnitude, the induced electric fields in the liner cause dielectric breakdown of the insulator material and, with sufficient current, the cylindrical target radially implodes. The dielectric breakdown process of the insulating material in AutoMag liners has been studied in experiments on the 500–900 kA, ~100-ns rise time Mykonos accelerator. Multi-frame gated imaging enabled the first time-resolved observations of photoemission from dynamically evolving plasma distributions during the breakdown process in AutoMag targets. Using magnetohydrodynamic simulations, we calculate the induced electric field distribution and provide a detailed comparison to the experimental data. We find that breakdown in AutoMag targets does not primarily depend on the induced electric field in the gaps between conductive helices as previously thought. Finally, to better control the dielectric breakdown time, a 12–32 mJ, 170 ps ultraviolet (λ = 266 nm) laser was implemented to irradiate the outer surface of AutoMag targets to promote breakdown in a controlled manner at a lower internal axial field. Here, the laser had an observable effect on the time of breakdown and subsequent plasma evolution, indicating that pulsed UV lasers can be used to control breakdown timing in AutoMag.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Analysis of streaked images of x-ray self-emission in laser-driven spherical implosions

Imaging of x-ray self-emission provides a powerful in situ measurement of the spatial and temporal evolution of high-energy-density plasmas. However, interpretation of these measurements requires detailed understanding of the data-generating process. This work presents a case study in the interpretation of x-ray self-emission data for the specific application of streaked one-dimensional slit imaging of spherical laser-driven implosions. A comprehensive generative model of the streaked slit-imaging diagnostic is developed including detailed treatments of the radiation transfer, photometrics, and photostatistics associated with the measurement. The model is used to generate realistic synthetic streaked images and to analyze experimental streaked images to extract important physical quantities of interest. An example analysis of streaked images from implosion experiments on the OMEGA laser is presented, where the model developed in this work is used to constrain the trajectory and peak velocity of the implosion using Bayesian inference.

Bayesian inference↗
DOE OSTI2022

Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation

Significant variety is observed in spherical crystal x-ray imager (SCXI) data for the stagnated fuel–liner system created in Magnetized Liner Inertial Fusion (MagLIF) experiments conducted at the Sandia National Laboratories Z-facility. As a result, image analysis tasks involving, e.g., region-of-interest selection (i.e. segmentation), background subtraction and image registration have generally required tedious manual treatment leading to increased risk of irreproducibility, lack of uncertainty quantification and smaller-scale studies using only a fraction of available data. We present a convolutional neural network (CNN)-based pipeline to automate much of the image processing workflow. This tool enabled batch preprocessing of an ensemble of N scans = 139 SCXI images across N exp = 67 different experiments for subsequent study. The pipeline begins by segmenting images into the stagnated fuel and background using a CNN trained on synthetic images generated from a geometric model of a physical three-dimensional plasma. The resulting segmentation allows for a rules-based registration. Our approach flexibly handles rarely occurring artifacts through minimal user input and avoids the need for extensive hand labelling and augmentation of our experimental dataset that would be needed to train an end-to-end pipeline. Here we also fit background pixels using low-degree polynomials, and perform a statistical assessment of the background and noise properties over the entire image database. Our results provide a guide for choices made in statistical inference models using stagnation image data and can be applied in the generation of synthetic datasets with realistic choices of noise statistics and background models used for machine learning tasks in MagLIF data analysis. We anticipate that the method may be readily extended to automate other MagLIF stagnation imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Multi-camera imaging to characterize jet and liner uniformity on the Plasma Liner Experiment (PLX)

At Plasma Liner Experiment, a set of 36 coaxial plasma guns are deployed quasi-uniformly over a 9 ft diameter spherical chamber and are used to form a high-Z spherically compressive plasma liner. Simulations indicate that for the concept to ultimately achieve optimal target density and temperature, a high degree of timing uniformity is required between all guns. Therefore, to aid in quantifying and correcting gun-to-gun nonuniformities, a key diagnostic will consist of up to six fisheye-view CCD cameras positioned inside the main chamber such that each has all plasma guns within its view. The individual cameras can be triggered at different times to determine each plasma jet’s muzzle velocity and structure for different operating conditions. This camera array is currently under development, and the implementation needs and challenges for this camera array are discussed here. Additionally, we detail the analysis methodology for determining jet-to-jet uniformity deviations and how we can correct them, thereby improving overall liner uniformity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Quantitative assessment of fitting errors associated with streak camera noise in Thomson scattering data analysis

Thomson scattering measurements in high energy density experiments are often recorded using optical streak cameras. In the low-signal regime, noise introduced by the streak camera can become an important and sometimes the dominant source of measurement uncertainty. In this paper, we present a formal method of accounting for the presence of streak camera noise in our measurements. We present a phenomenological description of the noise generation mechanisms and present a statistical model that may be used to construct the covariance matrix associated with a given measurement. This model is benchmarked against simulations of streak camera images. We demonstrate how this covariance may then be used to weight fitting of the data and provide quantitative assessments of the uncertainty in the fitting parameters determined by the best fit to the data and build confidence in the ability to make statistically significant measurements in the low-signal regime, where spatial correlations in the noise become apparent. These methods will have general applicability to other measurements made using optical streak cameras.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Such experiments are carried out at facilities such as the National Ignition Facility (NIF) in Livermore, California, where high powered lasers are used to compress a DT fuel-containing target to the necessary high temperature, high pressure conditions. These experiments are limited in number, which creates a heavy dependence on high fidelity predictive physics simulations and analysis performed “pre shot,” or before the experiment occurs. Many of these simulations in higher dimensions (2D and 3D) are computationally expensive, so finding optimal simulation-based designs presents its own challenges. In this work, we present our multi-fidelity Bayesian optimization with Gaussian processes (GPs) for ICF double shell targets, where a 1D surrogate model is used to help find a 2D surrogate model, enabling us to find optimal targets in the higher fidelity (2D), while saving computational cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing the hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High-density carbon capsules made for ICF experiments at the National Ignition Facility are precision polished to achieve surface smoothness on the order of a few nanometers as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with the goal of elevating the efficiency of this process. Our approach is to use MEMS (micro-electromechanical systems)–based sensors to capture the fine vibration signals generated during the polishing process and combine them with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, in this work, we describe the multiple fronts we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used to ensure the progress of the run as well as a means for faster optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2020

View factor estimation of hot spot velocities in inertial confinement fusion implosions at the National Ignition Facility

nertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) suffer from asymmetries in thex-ray drive that degrade capsule performance compared to expectations for a symmetric one-dimensional implosion.Mode 1, or pole-to-pole, drive asymmetry can reduce confinement and implosion efficiency, driving a bulk motion ofthe hot spot that is detectable with neutron diagnostics. Understanding and removing sources of mode 1 asymmetry inICF implosions is important for improving performance, and the three-dimensional nature of the problem makes high-resolution radiation-hydrodynamic modeling extremely computationally expensive. This work describes a reducedorder view factor model that calculates the drive asymmetry induced by beam-to-beam variations in laser delivery andhohlraum diagnostic windows along the equator. Capsule response is estimated by coupling to a Green’s function thatrelates final hot spot velocity to the applied time-varying mode 1 asymmetry. The model makes several predictionsabout the impact of mode 1 drivers such as laser delivery and target misalignment, and achieves good agreementin both magnitude and vector direction for several shots in three families of high-performance platforms. However,notable discrepancies suggest other potential sources of mode 1 asymmetry not captured by the model are also at play

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Modeling of a spatially resolved ion temperature diagnostic for inertial confinement fusion

Here, the performance of modern laser-driven inertial confinement fusion (ICF) experiments is degraded by contamination of the deuterium–tritium (DT) fuel with high-Z material during compression. Simulations suggest that this mix can be described by the ion temperature distribution of the implosion, given that such contaminants deviate in temperature from the surrounding DT plasma. However, existing neutron time-of-flight (nTOF) diagnostics only measure the spatially integrated ion temperature. This paper describes the techniques and forward modeling used to develop a novel diagnostic imaging system to measure the spatially resolved ion temperature of an ICF implosion for the first time. The technique combines methods in neutron imaging and nTOF diagnostics to measure the ion temperature along one spatial dimension at yields currently achievable on the OMEGA laser. A detailed forward model of the source and imaging system was developed to guide instrument design. The model leverages neutron imaging reconstruction algorithms, radiation hydrodynamics and Monte Carlo simulations, optical ray tracing, and more. The results of the forward model agree with the data collected on OMEGA using the completed diagnostic. The analysis of the experimental data is still ongoing and will be discussed in a separate publication.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗