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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Demonstration of object location, classification, and characterization by developed deep learning dust ablation trail analysis code package using plasma jets

Based on deep learning, a Dust Ablation Trail Analysis (DATA) code package is developed to detect dust ablation trails in tokamaks, which is intended to analyze a large amount data of tokamak dusts. To validate and benchmark the DATA code package, 2440 plasma jet images are exploited for the training and test of the deep learning DATA code package, since plasma jets resemble the shape and size of dust ablation clouds in tokamaks. After being trained by 1920 plasma jet images, the DATA code package is able to locate 100% plasma jets, classify plasma jets with the accuracy of >99.9%, and output image skeleton information for classified plasma jets. The DATA code package trained by the plasma jet images is also used to analyze the dust ablation trails captured in the Experimental Advanced Superconducting (EAST) tokamak with the satisfactory performance, further verifying its applicability in the fusion dust ablation investigation. Based on its excellent performance presented here, it is demonstrated that our DATA code package is able to automatically identify and analyze dust ablation trails in tokamaks, which can be used for further detailed investigations, such as the three-dimensional reconstruction of dusts and their ablation trails.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Curious cross-field transport effects in multi-ion, magnetized plasma

In contrast to single-ion plasma, multiple-ion-species plasma exhibits new, curious, and large transport effects. On short timescales, where ions exchange momentum, magnetized multi-ion plasma behaves as a most unusual substance, compressible across field lines in number density but incompressible in charge density. It takes 40 times longer for electrons to participate. In this ion–ion cross-field transport regime, we identified the charge-incompressibility heat pump effect, transferring heat both spatially and between species. Curiously, the direction of impurity transport strongly depends on plasma magnetization, characterized by the ratio of light ion gyrofrequency to the collision frequency between light and heavy ion species. The expulsion of heavy ion impurities from a hotspot occurs sufficiently quickly to be observable on MagLIF, so long as plasma becomes sufficiently collisionally magnetized under implosion. Even more curious, multi-ion transport changes its nature in partially ionized plasma, where ions occupy different charge states. In this regime, we identify a partial-ionization deconfinement effect. The combination of cross-field transport, ionization, and recombination leads to a net ion charge moving across magnetic field lines on the ion–ion transport timescale as opposed to the electron–ion transport timescale. Cross-field transport effects in multi-ion plasma are important in a number of applications, including nuclear fusion and plasma mass filters.

Mlodik, M. E. (ORCID:0000000343003941)↗
DOE OSTI2026

Key metrics of progress in the NIF ignition implosions and future challenges on the path to higher yields

Successful demonstration of an implosion that meets the physics metrics for ignition on the National Ignition Facility (NIF) in August 2021 and demonstration of target energy gain G > 1 in December 2022 represented the culmination of more than a decade of research on the NIF. An in-depth analysis of the key ignition metrics achieved on the NIF over the past decade shows sustained progress toward identifying and mitigating degradation effects. Ignition implosions on the NIF have progressed from early experiments whose compressed fuel conditions were degraded by a factor of 10–20 below the ignition threshold with yields of only 1%–2% of the laser energy, to current experiments that significantly exceed the ignition threshold and in the best experiments achieve yields greater than twice the laser energy. It is very likely that NIF can get more than 20 MJ of yield and possibly 50–70 MJ yields when fully optimized at an ultraviolet laser energy of 2.6 MJ following the completion of the NIF Extended Yield Capability Project. Achieving these higher yields will also require improvements to capsules at larger size and possibly with alternate materials, as well as an improved understanding of hohlraum and capsule physics. Now that NIF has achieved ignition, the design of a Next Generation High Energy Density Facility that could achieve the National Nuclear Security Administration long-term goal of substantially higher yields than the NIF can proceed with a more confident physics base. We evaluate these opportunities including possible applications for inertial fusion energy and likely challenges to achieving this level of performance over the next decade.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Explicit structure-preserving geometric particle-in-cell algorithm in curvilinear orthogonal coordinate systems and its applications to whole-device 6D kinetic simulations of tokamak physics

Explicit structure-preserving geometric particle-in-cell (PIC) algorithm in curvilinear orthogonal coordinate systems is developed. The work reported represents a further development of the structure-preserving geometric PIC algorithm achieving the goal of practical applications in magnetic fusion research. The algorithm is constructed by discretizing the field theory for the system of charged particles and electromagnetic field using Whitney forms, discrete exterior calculus, and explicit non-canonical symplectic integration. In addition to the truncated infinitely dimensional symplectic structure, the algorithm preserves exactly many important physical symmetries and conservation laws, such as local energy conservation, gauge symmetry and the corresponding local charge conservation. As a result, the algorithm possesses the long-term accuracy and fidelity required for first-principles-based simulations of the multiscale tokamak physics. The algorithm has been implemented in the SymPIC code, which is designed for high-efficiency massively-parallel PIC simulations in modern clusters. The code has been applied to carry out whole-device 6D kinetic simulation studies of tokamak physics. A self-consistent kinetic steady state for fusion plasma in the tokamak geometry is numerically found with a predominately diagonal and anisotropic pressure tensor. The state also admits a steady-state sub-sonic ion flow in the range of 10 km s -1 , agreeing with experimental observations and analytical calculations Kinetic ballooning instability in the self-consistent kinetic steady state is simulated. It is shown that high-n ballooning modes have larger growth rates than low-n global modes, and in the nonlinear phase the modes saturate approximately in 5 ion transit times at the 2% level by the E × B flow generated by the instability. These results are consistent with early and recent electromagnetic gyrokinetic simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Containers for Massive Ensemble of I/O Bound Hierarchical Coupled Simulations

We present our experience using containers to scale up a massive ensemble of coupled I/O bound workloads on the NERSC Cori supercomputer. We describe the design of a hierarchical simulation structure using the Integrated Plasma Simulator (IPS) that enables the flexible execution of coupled simulations at the system, node, and core level using the same coupling abstraction and API. The hierarchical design allows for the node-level execution to be efficiently executed using containers while not impacting the structure of the simulation at the system level. We demonstrate the viability of the approach by presenting experimental results from applications in coupled fusion plasma simulations that illustrate the performance impact of using containers to deploy the node-level workloads, in conjunction with the user mountable XFS file systems to ameliorate the load on the Lustre parallel file system. We also present results from production runs showing the ability of the ensemble simulations to scale to hundreds of Cori Haswell nodes, with little or no overhead.

Elwasif, Wael↗
DOE OSTI2026

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit

Turbulence plays a crucial role in multiphysics applications, including aerodynamics, fusion, and combustion. Accurately capturing turbulence's multiscale characteristics is essential for reliable predictions of multiphysics interactions, but remains a grand challenge even for exascale supercomputers and advanced deep learning models. The extreme-resolution data required to represent turbulence, ranging from billions to trillions of grid points, pose prohibitive computational costs for models based on architectures like vision transformers. To address this challenge, we introduce a multiscale hierarchical Turbulence Transformer that reduces sequence length from billions to a few millions and a novel RingX sequence parallelism approach that enables scalable long-context learning. We perform scaling and science runs on the Frontier supercomputer. Our approach demonstrates excellent performance up to 1.1 EFLOPS on 32,768 AMD GPUs, with a scaling efficiency of 94\%. To our knowledge, this is the first AI model for turbulence that can capture small-scale eddies down to the dissipative range in three-dimensional turbulence at high Reynolds numbers.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗
DOE OSTI2024

Visualization at exascale: Making it all work with VTK-m

The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for software development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs for GPUs and GPU-centric computing often deviate from those that worked well on previous generations of high-performance computers that relied on traditional CPUs. Fortunately, VTK-m provides scientific visualization algorithms for GPUs and other accelerators. VTK-m also provides a framework that simplifies the implementation of new algorithms and adds a porting layer to work across multiple processor types. This paper describes the main challenges encountered when making scientific visualization available at exascale. Here, we document the surprises and obstacles faced when moving from pre-exascale platforms to the final exascale designs and the performance on those systems including scaling studies on Frontier, an exascale machine with over 37,000 AMD GPUs. We also report on the integration of VTK-m with other exascale software technologies. Finally, we show how VTK-m helps scientific discovery for applications such as fusion and particle acceleration that leverage an exascale supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science

We have trained a fully convolutional spatio-temporal model for fast and accurate representation learning in the challenging exemplar application area of fusion energy plasma science. The onset of major disruptions is a critically important fusion energy science issue that must be resolved for advanced tokamak plasmas such as the $25B burning plasma international thermonuclear experimental reactor (ITER) experiment. While a variety of statistical methods have been used to address the problem of tokamak disruption prediction and control, recent approaches based on deep learning have proven particularly compelling. In the present paper, we introduce further improvements to the fusion recurrent neural network (FRNN) software suite, which delivered cross-machine disruption predictions with unprecedented accuracy using a large database of experimental signals from two major tokamaks. Up to now, FRNN was based on the long short-term memory (LSTM) variant of recurrent neural networks to leverage the temporal information in the data. Here, we implement and apply the "temporal convolutional neural network (TCN)" architecture to the time-dependent input signals. Furthermore, this allows highly optimized convolution operations to carry the majority of the computational load of training, thus enabling a reduction in training time, and the effective use of high-performance computing resources for hyperparameter tuning. At the same time, the TCN-based architecture achieves better predictive performance when compared with the LSTM architecture for various tasks for a representative fusion database.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Towards High-Repetition-Rate Fast Neutron Sources Using Novel Enabling Technologies

High-flux, high-repetition-rate neutron sources are of interest in studying neutron-induced damage processes in materials relevant to fusion, ultimately guiding designs for future fusion reactors. Existing and upcoming petawatt laser systems show great potential to fulfill this need. Here, we present a platform for producing laser-driven neutron beams based on a high-repetition-rate cryogenic liquid jet target and an adaptable stacked lithium and beryllium converter. Selected ion and neutron diagnostics enable monitoring of the key parameters of both beams. A first single-shot proof-of-principle experiment successfully implemented the presented platform at the Texas Petawatt Laser facility, achieving efficient generation of a forward-directed neutron beam. This work lays the foundation for future high-repetition-rate experiments towards pulsed, high-flux, fast neutron sources for radiation-induced effect studies relevant for fusion science and applications that require neutron beams with short pulse duration.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Characterization of Properties of Laser Powder Bed Fusion 3D-Printed Inconel 718 for Centrifugal Turbomachinery Applications

Here, this paper presents the results of a comprehensive effort to characterize the properties of Inconel 718 produced by a form of laser powder bed fusion (LPBF) additive manufacturing (AM) or 3D-printing, subsequently subjected to hot isostatic pressing (HIP) and heat treatment according to standards F3055-14a and AMS 5663, respectively. Material property data, while broadly available for traditional Inconel 718 presentations (e.g. forgings or castings), is currently lacking for the 3D-printed material. It is expected that while limited in size, the experimental data sets presented provide sufficient information to glean the capability of LPBF Inconel 718. These include: 1) Chemical composition, electron backscatter diffraction (EBSD), and x-ray energy dispersive spectroscopy (XEDS) characterization of 3D-printed material structure; 2) Tensile properties — 0.2% yield stress, ultimate stress, modulus of elasticity, and elongation to failure — based on 108 samples, as functions of temperature and sample print orientation; 3) Creep rupture data including the Larson-Miller parameter, based on 21 samples; and 4) High cycle fatigue data based on 21 samples as a function of temperature. Results are compared to available standards and/or data for forged, cast, and other AM Inconel 718. A key observation of this study, based on the EBSD results, is that while the material appears to approach full recrystallization following heat treatment, there is a detectable fraction of the material that does not fully recrystallize, resulting in a material with mechanical properties (e.g. yield stress, creep rupture) measurably lower than those of forgings, but higher than those of castings.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

A review on charged-particle transport modeling for laser direct-drive fusion

Inertial confinement fusion (ICF) with the laser-indirect-drive scheme has recently made a tremendous breakthrough recently after decades of intensive research effort. Taking this success to the next step, the ICF community is coming to a general consensus that laser direct-drive (LDD) fusion might be the viable way for enabling inertial fusion energy (IFE) and high-gain targets for other applications. Designing and understanding LDD fusion targets heavily rely on radiation-hydrodynamic code simulations, in which charged-particle transport plays an essential role in modeling laser-target energy coupling and bootstrap heating of fusion-produced α-particles. To better simulate charged-particle transport in LDD targets, over the past four decades the plasma physics community has advanced transport calculations from simple plasma physics models to sophisticated computations based on first-principles methods. In this review, we give an overview of the current status of charged-particle transport modeling for LDD fusion, including what challenges we still face and the possible paths moving forward to advance transport modeling for ICF simulations. We hope this review will provide a summary of exciting challenges to stimulate young minds to enter the field, facilitate further progress in understanding warm-dense matter physics, and ultimately bridge toward the success of reliable LDD fusion designs for IFE and other high-gain ICF applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Validation of theory-based models for the control of plasma currents in W7-X divertor plasmas

A theory-based model for the control of plasma currents for steady-state operation in W7-X is proposed and intended for model-based plasma control. The conceptual outline implies the strength of physics-based models: it offer approaches applicable to future conditions of fusion devices or next-step machines. The application at extrapolated settings is related to the validity range of the theory model. Therefore, the predictive power of theory-based control models could be larger than for data-driven approaches and limitations can be predicted from the validity range for the prediction of bootstrap currents in W7-X. The model predicts the L/R response when density or heating power is changed. The model is based on neoclassical bootstrap current calculations and validated for different discharge conditions. While the model was found to be broadly applicable for conducted electron-cyclotron-heated discharges in W7-X, limits were found for cases when the polarization of the electron cyclotron heating was changed from X2 to O2-heating. The validity assessment attempts to quantify the potential of the derived model for model-based control in the operational space (density, heating power) of W7-X.

neoclassical modelling↗
DOE OSTI2025

Electrochemical loading enhances deuterium fusion rates in a metal target

Nuclear fusion research for energy applications aims to create conditions that release more energy than required to initiate the fusion process1. To generate meaningful amounts of energy, fuels such as deuterium need to be spatially confined to increase the collision probability of particles2, 3–4. We therefore set out to investigate whether electrochemically loading a metal lattice with deuterium fuel could increase the probability of nuclear fusion events. Here we report a benchtop fusion reactor that enabled us to bombard a palladium metal target with deuterium ions. These deuterium ions undergo deuterium–deuterium fusion reactions within the palladium metal. We showed that the in situ electrochemical loading of deuterium into the palladium target resulted in a 15(2)% increase in deuterium–deuterium fusion rates. This experiment shows how the electrochemical loading of a metal target at the electronvolt energy scale can affect nuclear reactions at the megaelectronvolt energy scale.

Chen, Kuo-Yi↗
DOE OSTI2022

Observation of spatter-induced stochastic lack-of-fusion in laser powder bed fusion using in situ process monitoring

Material produced via additive manufacturing (AM) continues to exhibit variable mechanical properties despite apparent optimization of processing parameters, inhibiting qualification efforts and limiting use in critical applications. Stochastic lack-of-fusion flaws may help explain this variability, but the origin of these seemingly random defects has to this point remained unclear. In this work, we show that spatter particles, material ejected from the laser melt pool, are directly responsible for generating stochastic lack-of-fusion in laser-based powder bed fusion components through the application of spatial statistics. Herein a statistically significant, causal relationship between spatter particles and stochastic lack-of-fusion is established, and the spatial and morphological relationships between spatter and internal flaws are investigated. The occurrence of spatter-induced lack-of-fusion in relation to the inert gas flow and laser trajectory direction is also investigated, and recommendations for mitigating the occurrence of spatter are evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dense hydrogen layers for high performance MagLIF

We report that Magnetized Liner Inertial Fusion (MagLIF) experiments driven by the Z machine produce >10 13 deuterium-deuterium fusion reactions. Simulations indicate high yields and gains (1000) with increased current and deuterium-tritium layers for burn propagation. Such a coating also isolates the metal liner from the gaseous fuel, which should reduce mixing of liner material into the fuel. However, the vapor density at the triple point is only 0.3 kg/m3, which is not high enough for MagLIF operation. We present two solutions to this problem. First, a fuel wetted low-density plastic foam can be used to form a layer on the inside of the liner. The desired vapor density can be obtained by controlling the temperature. This does however introduce carbon into the layer which will enhance radiation losses. Simulations indicate that this wetted foam layer can significantly contribute to the fusion yield when the foam density is less than 35 kg/m 3 . Second, we show that a pure frozen fuel layer can first be formed on the inside of the liner and then low temperature gaseous fuel can be introduced just before the implosion without melting a significant amount of the ice layer. This approach is the most promising for MagLIF to produce high yield and gain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Progress with applications of three-ion ICRF scenarios for fusion research: A review

The viability of magnetic confinement fusion as an energy source depends on achieving the high ion temperatures required for D-T fusion. Among the available techniques, plasma heating with waves in the ion cyclotron range of frequencies (ICRF) is a prominent method for bulk ion heating in fusion plasmas. Furthermore, a detailed understanding of the non-linear physics of alpha heating and the complex impact of MeV-range fast ions on plasma dynamics becomes progressively more important. This paper provides a comprehensive overview of recent developments with the three-ion ICRF scenarios on Alcator C-Mod, ASDEX Upgrade and JET tokamaks. The results demonstrate the flexibility of these novel scenarios for heating bulk ions in D-T ≈ 50%-50% plasmas and efficient generation of MeV-range fast ions in multi-ion species plasmas. In conclusion, several key results relevant for ITER and future fusion reactors are highlighted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Physics and applications of dusty plasmas: The Perspectives 2023

Dusty plasmas are electrically quasi-neutral media that, along with electrons, ions, neutral gas, radiation, and electric and/or magnetic fields, also contain solid or liquid particles with sizes ranging from a few nanometers to a few micrometers. These media can be found in many natural environments as well as in various laboratory setups and industrial applications. As a separate branch of plasma physics, the field of dusty plasma physics was born in the beginning of 1990s at the intersection of the interests of the communities investigating astrophysical and technological plasmas. An additional boost to the development of the field was given by the discovery of plasma crystals leading to a series of microgravity experiments of which the purpose was to investigate generic phenomena in condensed matter physics using strongly coupled complex (dusty) plasmas as model systems. Finally, the field has gained an increasing amount of attention due to its inevitable connection to the development of novel applications ranging from the synthesis of functional nanoparticles to nuclear fusion and from particle sensing and diagnostics to nano-contamination control. The purpose of the present perspectives paper is to identify promising new developments and research directions for the field. As such, dusty plasmas are considered in their entire variety: from classical low-pressure noble-gas dusty discharges to atmospheric pressure plasmas with aerosols and from rarefied astrophysical plasmas to dense plasmas in nuclear fusion devices. Both fundamental and application aspects are covered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗