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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Implementing a microphysics model in hydrodynamic simulations to study the initial plasma formation in dielectric ablator materials for direct-drive implosions

A microphysics model to describe the photoionization and impact ionization processes in dielectric ablator materials like plastic has been implemented into the 1-D hydrodynamic code LILAC for planar and spherical targets. Currently, the initial plasma formation during the early stages of a laser drive are modeled in an ad hoc manner, until the formation of a critical surface. Implementation of the physics-based models predict higher values of electron density, electron temperature, and pressure than the ad hoc model. Moreover, the numerical predictions are consistent with previous experimental observations of the shinethrough mechanism in plastic ablators. For planar targets, a decompression of the rear end of the target was observed, that is similar to recent experiments. An application of this model is to understand the laser-imprint mechanism that is caused by nonuniform laser irradiation due to single beam speckle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

NNSA SSAP Article VT 101320

Computer simulations of the experiments are being performed using the Los Alamos National Laboratories’ FLAG magnetohydrodynamics code by graduate student Seth Kreher, and Lawrence Livermore National Laboratory’s Ares by graduate students Robert Masti and Matthew Carrier.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Post-Shot Report for OMEGA Double Cylinders (CylDRT 22B)

The direct-drive double cylinder experimental platform is a high-energy-density (HED) science platform designed to image an imploding cylindrical target. The target consists of a directly-driven outer cylinder and a shock-and-collision driven inner cylinder. The purpose of this platform is to study hydrodynamic instability growth on the inner cylinder, the outer surface of which is classically Rayleigh-Taylor unstable during the acceleration phase. We present results from recent experiments at the OMEGA laser facility. These experiments were designed as a proof-of-principle for the platform, using the same cylinder exterior dimensions and direct-drive beam configuration as previous single cylinder experiments. In these experiments, three sets of targets were fielded: no machined perturbations (smooth), a sinusoidal mode-10 perturbation on the outer surface of the inner cylinder, and a mode-20 perturbation on the outer surface of the inner cylinder. The primary diagnostic was a gated x-ray framing camera which imaged the backlit inner cylinder on-axis for sixteen frames over a time window of 1 ns for each shot. A second side-lit radiograph captured one image per shot, diagnosing axial uniformity. In this report we include an overview of the results from both the backlighter and the sidelighter diagnostics. We discuss at length the experimental analysis process. Finally, we present the results of the smooth target implosion trajectory and compare them to post-shot simulations. We see favorable agreement between simulation and experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

The data-driven future of high-energy-density physics

High-energy-density physics is the field of physics concerned with studying matter at extremely high temperatures and densities. Such conditions produce highly nonlinear plasmas, in which several phenomena that can normally be treated independently of one another become strongly coupled. The study of these plasmas is important for our understanding of astrophysics, nuclear fusion and fundamental physics—however, the nonlinearities and strong couplings present in these extreme physical systems makes them very difficult to understand theoretically or to optimize experimentally. Here we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proved far too nonlinear for human researchers. Furthermore, from a fundamental perspective, our understanding can be improved by the way in which machine learning models can rapidly discover complex interactions in large datasets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to approximately daily), thus moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we suggest proposals for the community in terms of research design, training, best practice and support for synthetic diagnostics and data analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Thermodynamic assessment of the quaternary WTaCrV refractory high entropy alloy as a means to guide experimental approaches

The deployment of fusion energy poses challenges for materials in plasma facing components to withstand high temperatures and thermal gradients, particle implantation and neutron damage. The current material of choice is tungsten, although property degradation limits its consideration in future fusion reactors. Hence, materials with better resistance to harsh environments need to be developed for fusion energy to become a reality. High entropy alloys are being explored as potential candidates with some compositions showing good radiation resistance to defect cluster formation. One of these materials is the WTaCrV system, although only one composition has been tested under ion irradiation. In this work, we study the thermodynamic properties of the entire quaternary alloy composition range. Coupling first principles calculations, cluster expansion approaches, and Monte Carlo methods, we access the free energy functionals, short-range ordering as a function of temperature, and atomic configurations that can be compared to experimental observations. We use this data to inform experiments into compositions with higher propensity to form solid solutions, instead of phase separating. With this formalism we have developed thermodynamic database (TDB) files that can be used to plot quaternary phase diagrams.

Cluster Expansion↗
DOE OSTI2020

Hydro-scaling of direct-drive cylindrical implosions at the OMEGA and the National Ignition Facility

Deceleration-phase Rayleigh–Taylor instability (RTI) growth during inertial confinement fusion capsule implosions significantly affects the performance as it mixes cold ablator material into the fuel. Precise measurements of such instability growth are essential for both validating the existing simulation codes and improving our predictive capability. RTI measurements on the inner surface of a spherical shell are limited and are often inferred indirectly at limited convergence. In contrast, cylindrical implosions allow for direct diagnostic access to the converging interface by imaging down the cylinder axis while retaining the effects of convergence. We have performed direct-drive cylindrical implosion experiments at both the OMEGA and the NIF laser facilities using scaled targets. RTI growth is demonstrated to be scale-invariant between the cylindrical targets at OMEGA and similar targets at the NIF, which are scaled up by a factor of three in the radial dimension. Single-mode (m = 0) instability growth factors of ~14 are measured at a convergence ratio (CR) ~ 2.5 with nearly identical mode growth at both scales. The measurements are in agreement with xRAGE radiation-hydrodynamics simulations. In addition, we have developed the Bayesian-inference-engine method to account for the variations in the target alignment, magnification, and the parallax effect in the measurement, allowing a more precise comparison between the experimental data and the simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A Workflow to Optimize Fast Neutron Irradiation in A Thermal Neutron Spectrum Test Reactor Leveraging Open-Source Tools

The Advanced Test Reactor (ATR) located at Idaho National Laboratory (INL) is one of the key nuclear engineering research and testing facilities within the US Department of Energy (DOE). The ATR is one of few high-power research reactors in the world with different application including accelerated testing of nuclear fuel, materials irradiation in a very high neutron flux environment, and medical radioisotope production [1]. Also, the ATR offers opportunities for testing fast spectrum fission and fusion reactor materials. The key challenges in this area are in further detailing and optimizing a fast spectrum environment within a thermal test reactor. This challenge involves researching, developing, and testing novel concepts for the multiplying of neutron populations into ever higher energy spectra in high flux test reactors like ATR. The main objective of this work is to investigate candidate materials for establishing a fast neutron experiment irradiation in thermal neutron spectrum test reactors which can be accomplished by filtering thermal and epithermal neutrons and boosting fast neutrons at designated irradiation positions. However, adding these filters will render the neutron spectrum and the criticality of the system. The selection of the thickness and material layers should be accomplished by developing an optimization design algorithm that is applicable for ATR to enhance the fast neutron spectrum irradiation utilizing high-fidelity Monte Carlo methods along with advanced machine learning capabilities. This paper presents workflow for design optimization to enhance fast neutron irradiation in the ATR. The workflow leverages open-source tools to develop an algorithm that is viable to ATR and can be leveraged in other reactors. The following sections discuss the development of the experiment design optimization workflow and its application to ATR irradiation positions.

42 - ENGINEERING↗
DOE OSTI2022

Design and experimental demonstration of feedback adaptive RMP ELM controller toward complete long pulse ELM suppression on KSTAR

Operation of a fusion power plant requires robust edge localized mode (ELM) suppression simultaneously with high plasma performance. In this study, we describe a novel feedback adaptive resonant magnetic perturbation (RMP) ELM controller designed to address this problem by achieving optimized ELM suppression through the advanced application of 3D RMPs. From real-time $D_α$ data, the controller is achievable robust ELM suppression while simultaneously minimizing the applied RMP in order to enhance plasma performance. In real time, the instantaneous ELM-frequency is analyzed with an adaptive feedback algorithm to determine amplitudes and phases of RMP coil currents that will maximize plasma performance while maintaining ELM suppression. When applied through the KSTAR plasma control system in several experiments using $textiti{n}$ = 1 RMPs, robust ELM suppression is achieved and sustained in feedback while reducing the RMP strength to ~65% of its initial value. Minimization of the RMP strength in this manner not only allows for operation of longer discharges due to a decrease in flux consumption but also allows for a strong recovery of up to ~60% of $β_N$ throughout the ELM-free period.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Overview of results from the 2023 DIII-D negative triangularity campaign

Negative triangularity (NT) is a potentially transformative configuration for tokamak-based fusion energy with its high-performance core, edge localized mode (ELM)-free edge, and low-field-side divertors that could readily scale to an integrated reactor solution. Previous NT work on the TCV and DIII-D tokamaks motivated the installation of graphite-tile armor on the low-field-side lower outer wall of DIII-D. A dedicated multiple-week experimental campaign was conducted to qualify the NT scenario for future reactors. During the DIII-D NT campaign, high confinement ($H_\mathrm{98y,2}\gtrsim$ 1), high current ($q_\mathrm{95} \lt$ 3), and high normalized pressure plasmas ($\beta_\mathrm{N} \gt$ 2.5) were simultaneously attained in strongly NT-shaped discharges with average triangularity $\delta_\mathrm{avg}$ = −0.5 that were stably controlled. Experiments covered a wide range of DIII-D operational space (plasma current, toroidal field, electron density and pressure) and did not trigger an ELM in a single discharge as long as sufficiently strong NT was maintained; in contrast, to other high-performance ELM-suppression scenarios that have narrower operating windows. These strong NT plasmas had a lower outer divertor X-point shape and maintained a non-ELMing edge with an electron temperature pedestal, exceeding that of typical L-mode plasmas. Also, the following was achieved during the campaign: high normalized density ($n_\mathrm{e}$/$n_\mathrm{GW}$ of at least 1.7), particle confinement comparable to energy confinement with $Z_\mathrm{eff}\sim2$ , a detached divertor without impurity seeding, and a mantle radiation scenario using extrinsic impurities. These results are promising for a NT fusion pilot plant but further questions on confinement extrapolation and core-edge integration remain, which motivate future NT studies on DIII-D and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Scaling Subspace-Driven Approaches Using Information Fusion

In this work, we seek to exploit the deep structure of multi-modal data to robustly exploit the group subspace distribution of the information using the Convolutional Neural Networks (CNNs) formalism. Upon unfolding the set of subspaces constituting each data modality, and learning their corresponding encoders, an optimized integration of the generated inherent information is carried out to yield a characterization of various classes. Referred to as deep Multimodal Robust Group Subspace Clustering (DRoGSuRe), this approach is compared against the independently developed state-of-the-art approach named Deep Multimodal Subspace Clustering (DMSC). Experiments on different multimodal datasets show that our approach is competitive and more robust in the presence of noise.

Ghanem, Sally↗
DOE OSTI2024

Preliminary Assessment of Additively Manufactured Cooling Channel Performance for Helium-Cooled Blanket Concepts

Sufficient cooling of the blanket first wall remains a critical challenge for the design and deployment of fusion power plants. Helium has been targeted as a potential blanket coolant due to its inertness and low neutron interactivity, among other advantages. However, the low thermal mass of helium creates a need for heat transfer enhancements in coolant channels to provide adequate cooling to the blanket’s first wall. Toward this end, a series of ribbed flow channels of various rib cross sections and configurations has been produced via additive manufacturing (AM) to study the efficacy of AM for first wall heat transfer enhancement and the optimization of heat transfer geometries. Helium cooling performance is studied in AM test articles at 4 MPa operating pressure, Reynolds numbers up to 197 000, and outer surface heat fluxes up to 42 kW/m 2 in the recently commissioned helium flow loop experiment (HFLE). Preliminary results of this study are presented herein. Heat transfer performance of nominally smooth (i.e., featureless) AM channels is quantified via measured Nusselt numbers and friction factors and compared to off-the-shelf smooth pipe experiments. Results are compared to existing correlations and used to discuss the effects of the AM processes on thermal-hydraulic performance. It is seen that the inherent roughness of the AM channels leads to an increase in both heat transfer coefficient and pressure drop when compared to the conventional pipe. In conclusion, recommendations are made for future studies based on these findings and additional considerations for the deployment of AM blanket cooling components.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pair plasma instability in homogeneous magnetic guide fields

Pair plasmas, collections of both matter and antimatter particles of equal mass, represent a paradigm for the study of basic plasma science, and many open questions exist regarding these unique systems. They are found in many astrophysical settings, such as gamma-ray bursts, and have recently also been produced in carefully designed laboratory experiments. A central research topic in plasma physics is instability; however, unlike their more common ion–electron siblings, pair plasmas are generally thought to be stable to cross field pressure gradients in homogeneous magnetic fields. It is shown here by means of kinetic full-f simulations that, when a pressure gradient is first established, the Gradient-driven Drift Coupling mode is destabilized and becomes turbulent. Force balance is eventually achieved by a combination of flattened pressure profiles due to turbulent transport and establishment of a magnetic field gradient, saturating the growth. During the unstable phase, key physics can be captured by a δf gyrokinetic description, where it is shown analytically and numerically that parallel particle motion results in a coupling of all electromagnetic field components. A fluid model derived therefrom accurately predicts linear eigenmodes and is used to resolve global profile effects. For laser-based electron–positron plasma experiments, prompt instability is predicted with growth times much shorter than plasma lifetimes. Similarly, growth rates are calculated for the planned APEX experiment as well as gamma-ray burst scenarios, suggesting that the instability may contribute to the early evolution of these systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Predicting tungsten erosion and leakage properties for the new V-shaped small angle slot divertor in DIII-D

Impurity transport modeling of the new tungsten (W)-coated, V-shaped small angle slot (SAS) divertor in the DIII-D tokamak was conducted using the SOLPS-ITER plasma edge code package and the DIVIMP impurity tracking code. The inboard baffle of the current SAS divertor will be shifted closer to the outboard baffle, creating a V-corner at the slot vertex. In addition, the outboard baffle will be coated with 10–15 μm of W for experiments studying high-Z sourcing and leakage in a closed divertor. Modeling of the 'SAS-VW' divertor predicts that these changes to the inner baffle will reduce W gross erosion by 40× relative to the existing SAS divertor when the outer strike point (OSP) is at the V-corner and the ion B × ∇B drift is towards the divertor, driven primarily by significant cooling near the slot vertex. Most W erosion in SAS-VW is expected to occur near the slot entrance, which may pose a higher risk to core contamination than W eroded deeper in the slot. Furthermore, adding a new sheath-based prompt redeposition model increases the sensitivity of redeposition estimates to near-target plasma conditions and may provide more accurate predictions of net erosion. Moving the OSP outboard from the slot vertex ~4 cm onto the W-coated region yields a 40× increase in the gross erosion rate and a 50% decrease in the core leakage fraction. Thus slight variations in strike point location may counteract the potential benefits of the tightly-baffled V slot on minimizing erosion. This impurity transport modeling provides useful guidance for future experiments on the SAS-VW divertor focused on high-Z erosion/redeposition, scrape-off layer transport, and core leakage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

FY19 FES Theory Performance Target (Final Report)

Understanding the relevant turbulent transport mechanisms at the edge of a high-performance tokamak is essential for predicting and optimizing the H-mode pedestal structure in future burning plasma devices. Global electromagnetic gyrokinetic simulations will be performed based on representative experimental pedestal scenarios in order to clarify which instabilities are most important for each of the particle and heat transport channels. Edge transport modeling will be performed in order to estimate and bound the particle and heat sources—e.g., the ionization density source and the atomic energy loss channels due to ionization, charge exchange, and radiation. Comparisons will be made with data from the DIII-D, JET, C-Mod and NSTX or MAST experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The Motional Stark Effect Diagnostic for NSTX-U

This report describes the development of the motional Stark Effect diagnostic for NSTX. The MSE concept relies upon observation of the Balmer-alpha (n=3 to n=2) emission from a neutral hydrogen beam traversing a plasma. As a beam at high velocity, $\vec{ν}$, passes through the magnetic field in the plasma, $\vec{B}$, it experiences in its reference frame a Lorentz electric field, $\vec{E}$ = $\vec{ν}$ x $\vec{B}$. This electric field causes the spectral emission to be split and polarized as described by the Stark effect. The transition is separated into a set of lines in which the line spacing is linearly proportional to the electric field magnitude, and the line polarization is dependent on the electric field direction. Traditionally, MSE has used polarimetry to determine the polarization angle of the light, and related that to the magnetic field pitch angle in the plasma. The MSE diagnostic was developed under high magnetic field ($>$ 1~T) conditions, and the lower fields of recent high-beta experiments such as NSTX posed challenges to the technique. At low magnetic fields Doppler broadening effects mask the Stark effect. With the use of a narrow bandwidth filter MSE measurements at very low magnetic fields have been obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Deep Multimodal Networks for M-type Star Classification with Paired Spectrum and Photometric Image

Abstract Traditional stellar classification methods include spectral and photometric classification separately. Although satisfactory results can be achieved, the accuracy could be improved. In this paper, we pioneer a novel approach to deeply fuse the spectra and photometric images of the sources in an advanced multimodal network to enhance the model’s discriminatory ability. We use Transformer as the fusion module and apply a spectrum–image contrastive loss function to enhance the consistency of the spectrum and photometric image of the same source in two different feature spaces. We perform M-type stellar subtype classification on two data sets with high and low signal-to-noise ratio (S/N) spectra and corresponding photometric images, and the F1-score achieves 95.65% and 90.84%, respectively. In our experiments, we prove that our model effectively utilizes the information from photometric images and is more accurate than advanced spectrum and photometric image classifiers. Our contributions can be summarized as follows: (1) We propose an innovative idea for stellar classification that allows the model to simultaneously consider information from spectra and photometric images. (2) We discover the challenge of fusing low-S/N spectra and photometric images in the Transformer and provide a solution. (3) The effectiveness of Transformer for spectral classification is discussed for the first time and will inspire more Transformer-based spectral classification models.

Astronomy & Astrophysics↗
DOE OSTI2026

Validation of an integrated modeling framework for investigating 3D plasma responses in tokamak plasmas

As contemporary experimental tokamaks are pushed toward reactor-relevant operation, they provide essential testbeds for demonstrating and exploring ELM control strategies for deployment in future fusion pilot plants. Accurate predictions of full plasma responses are essential to guide and optimize these demonstrations. This paper introduces and validates an integrated modeling framework over a historical range of DIII-D operational space. The integrated modeling framework uses only scalar plasma parameters and optional reference boundary to self-consistently and flexibly scan through tokamak operational space and estimate the corresponding ELM-suppression relevant plasma response over 3D coil phase space. The framework generates tightly converged equilibria that satisfy a target set of plasma parameters (I p , β N , l i ), with kinetic profiles constrained by an EPED(NN)-computed pedestal and empirical core model. The plasma response of these modeled equilibria is calculated with GPEC. Validated against 55 distinct DIII-D equilibria, the framework consistently reproduces experimentally constrained equilibrium pressure, q, and other representative profiles using the time-varying information from only evolving scalar plasma parameters; plasma response validation is performed for the n=3 perturbation. In particular, the plasma response of a DIII-D discharge scanning q 95 in search of ELM suppression windows is quantitatively reproduced. By accurately reproducing experimental equilibria and plasma responses across wide parameter variation, the framework supports potential for synthetic parameter scans in key operational, stability, and plasma response dimensions to investigate RMP ELM-suppression experiments and inform predictive RMP scenario optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗