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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dispersion relation and instability for an anisotropic nonuniform flowing plasma

A generalized formula for wave instability is developed for an anisotropic nonuniform plasma with finite flows and temperatures. Six-moment fluid equations are solved to give the analytic expression for wave instability in arbitrarily nonuniform plasmas. The analytic formula explicitly states the dependence of wave instability on the nonuniformities of number density, flow velocity, and anisotropic or isotropic pressure. The accuracy of the formalism is verified by a numerical calculation of implicit dispersion relations in complex Fourier space. The analysis shows that nonuniformity plays a critical role in plasma instability, while the flow velocity and anisotropic pressures determine the growth rate of the instability. Lastly, the instability diagram and associated instability criterion for anisotropy-driven instability are introduced as applications of the formalism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Asynchronous and Load-Balanced Union-Find for Distributed and Parallel Scientific Data Visualization and Analysis

We present a novel distributed union-find algorithm that features asynchronous parallelism and k-d tree based load balancing for scalable visualization and analysis of scientific data. Applications of union-find include level set extraction and critical point tracking, but distributed union-find can suffer from high synchronization costs and imbalanced workloads across parallel processes. In this study, we prove that global synchronizations in existing distributed union-find can be eliminated without changing final results, allowing overlapped communications and computations for scalable processing. We also use a k-d tree decomposition to redistribute inputs, in order to improve workload balancing. We benchmark the scalability of our algorithm with up to 1,024 processes using both synthetic and application data. Here, we demonstrate the use of our algorithm in critical point tracking and super-level set extraction with high-speed imaging experiments and fusion plasma simulations, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Electromagnetic Field Simulation Utilizing VERTEX

The understanding of electromagnetic fields is essential for many core applications at Oak Ridge National Laboratory (ORNL). Electromagnetic fields play an important role in particle accelerators, antennas, electric motors, power grids, and are principal part of nuclear fusion. We develop a numerical solver called able to treat the Maxwell system utilizing ORNL's VERTEX framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

DOE Final Report on Virginia Tech’s contribution to “Tokamak Disruption Simulation”

This work was performed by Virginia Tech in collaboration with multiple institutions led by Los Alamos National Laboratory as a part of the Tokamak Disruption Simulation SciDAC (Scientific Discovery through Advanced Computing) project supported jointly by the Department of Energy Office of Science and Ad- vanced Scientific Computing Research. This report summarizes Virginia Tech’s contributions to the Sci- DAC project. Virginia Tech researchers (presently University of Washington researchers) focused on the fundamental role of plasma-material interaction on transport, which could then have macroscopic effects on simulations of tokamak disruptions. The plasma sheath, which regulates plasma particle and energy fluxes to the wall, is an essential component in the study of plasma-material interaction (PMI). Understanding sheath theory by accounting for finite sheath thickness and transport in the vicinity of the sheath entrance can sig- nificantly modify typical assumptions that are made in the Bohm speed analysis, where the Bohm speed provides the lower bound of the plasma exit flow speed. Our work provides a modified Bohm speed formu- lation that accounts for the critical role of transport and for applications that are away from the asymptotic limits that are typically assumed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Strategies for Fabricating Molybdenum Structures Using Laser Powder Bed Fusion

Advances in manufacturing techniques are viewed as enabling technologies for development of high performance nuclear fuel forms that couple high uranium density with improvements to key properties such as thermal conductivity unattainable through conventional fabrication routes. Additive manufacturing (AM) enables the fabrication of complex fuel geometries that are difficult or impossible to achieve using conventional manufacturing methods. Melting-based AM processes, such as laser powder bed fusion (LPBF), provide high geometric resolution (>200 µm depending on the feature) across a variety of metal alloys, including those suitable for high-temperature fuel cladding applications, such as Nb, W, and Mo. Molybdenum is particularly attractive due to its high thermal conductivity, low thermal expansion, and excellent mechanical stability at elevated temperatures. However, its high melting temperature and brittle nature at low temperatures pose significant challenges during LPBF processing. Rapid solidification inherent to LPBF induces high residual stresses, often leading to post-solidification cracking, which limits the manufacturability of Mo components via this method.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Parallel Algebraic Multigrid for Fusion and Higher-Order PDEs

Multigrid methods play a key role in large-scale scientific simulation because they are among the fastest and most scalable approaches for solving the underlying sparse linear systems of equations that arise from a wide array of Partial Differential Equation (PDE) discretizations. Algebraic multigrid (AMG) is a special type of multigrid method that depends only on the description of the linear system, giving it better portability and broader applicability than geometric multigrid, as it requires no explicit knowledge of the problem geometry. Even though these methods are widely used today, there are still applications where further development is needed. In this report, we focus on PDEs with higher-order terms (e.g., fourth order), concentrating on a PDE that arises in tokamak edge plasma simulations (a tokamak is a machine that confines a plasma using magnetic fields and is believed to be the leading plasma confinement concept for future fusion power plants). General multigrid relaxes a linear system on coarser grids and reverses this process with interpolation, but standard AMG methods struggle with the aforementioned higher-order PDEs. We investigate cyclic coarsening and interpolation heuristics, as well as new iterative approximation methods of refining the solution at each grid to improve the existing multigrid approach. To this end, we ensure that these techniques are transferable to a parallelized setting with LLNL’s supercomputers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Applicability of alkali beam emission spectroscopy on NSTX-U

Understanding fast pedestal dynamics and turbulent transport in the edge and scrape-off layer (SOL) plasma of spherical tokamaks is crucial for the design and operation of future fusion reactors. The alkali beam emission spectroscopy diagnostic technique offers a means to measure the absolute electron density radial profile and fluctuation amplitude in these regions. Here, in this study, we demonstrate that injecting a sodium neutral beam radially into the plasma and analyzing the light emission from its 3p–3s atomic transition using near-orthogonal viewing angles allows for accurate measurement of the electron density profile and fluctuations in the National Spherical Torus Experiment (NSTX) Upgrade spherical tokamak. Our findings indicate a peak signal-to-noise ratio of 118 in the pedestal and 12 in the SOL under typical NSTX plasma conditions. The spatial resolution for the electron density profile is estimated to be between 2 and 8 mm, while for fluctuation measurements, it ranges from 12 to 15 mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Understanding NBI heating and fueling in LTX-β tokamak

My work on the contract DE-SC=0023274 (July, 2022 - July, 2025) was focused on understanding the plasma fueling by NBI. On Dec. 1998 with Sergei Krasheninnikov (UCSD, San Diego, CA) we initiated the Li Wall Fusion (LiWFusion) as a new concept of magnetic fusion [1]. The new 1 2 plasma 3 4 5 6 2.1 Overview of rate coefficients, mean-free paths λH0 , and diffusions coefficients 6 2. GSV code for ⟨σv⟩ analysis of NBI fueling concept was a reaction of the lack of luck of tokamak fusion with QDT = 1 on TFTR and JET. We recognized the edge plasma cooling by recycling to be the route reason of the tokamak problems on the way to burning plasma. LiWFusion relies on plasma pumping by a lithium layer on the inner walls of the plasma chamber, combined with the plasma heating and fueling by the Neutral Beam Injection (NBI). These two innovations eliminate the route problem of the tokmak fusion. The concept became theoretically mature in 2006. In 2012, the technology of continuously Flowing Liquid Lithium (24/7-FLiLi) was invented by me for the future implementations of the LWFusion concept. At the same time, my every presentation on LiWFusion to International Symposium on Lithium Applications since 2010 was objected by some person with words “Everybody since the 1970s knows that plasma fueling by NBI is impossible”. I dropped the name of the author of this objection and ignored his views. My work on the current grant on NBI fueling of LTX-β not only clarified the issue but resolved it in an astonishing way. The NBI fueling was fully understood (thus humiliating the current dogmatic fusion community). The new future of LTX-β dedicated for decades to Li in tokamaks, as well as of the entire magnetic fusion program was envisioned, in sharp contrast with the fallure of OFES in the post-TFTR era of 21st century.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Ab initio study of tungsten-based alloys under fusion power-plant conditions

Tungsten (W) is considered a leading candidate for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, primarily associated with intergranular failure and bulk plasticity, limiting its applications. In recent years, several families of tungsten-based alloys have been explored to overcome the aforementioned limitations of pure tungsten. These include tungsten-based high-entropy alloys (W-HEAs) and tungsten-based Self-passivating Metal Alloys with Reduced Thermo-oxidation or “SMART alloys” (W-SAs). Given their proximity to the plasma, it is crucial to understand how the exposure of these candidate plasma-facing materials (PFMs) to the neutron fluxes expected in fusion reactors impacts their material behavior over time. In this work, we present a computational approach that combines inventory codes and first-principles DFT electronic structure calculations to understand the behavior of transmuting tungsten-based PFMs. In particular, we calculate the changes in the chemical composition, production uncertainties, the elastic and ductility properties, and the density of states for five tungsten-based PFMs when exposed to EU-DEMO fusion first wall conditions for ten years.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Laser melting modes in metal powder bed fusion additive manufacturing

In laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures and hence the properties of the build. To date, no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. Here, we distinguish process-based definitions of different melting modes from those based on postmortem evidence. The latter are mainly derived from the transverse cross-sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. Further, we highlight the significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Evaluating the potential of disaggregated memory systems for HPC applications

Summary Disaggregated memory is a promising approach that addresses the limitations of traditional memory architectures by enabling memory to be decoupled from compute nodes and shared across a data center. Cloud platforms have deployed such systems to improve overall system memory utilization, but performance can vary across workloads. High‐performance computing (HPC) is crucial in scientific and engineering applications, where HPC machines also face the issue of underutilized memory. As a result, improving system memory utilization while understanding workload performance is essential for HPC operators. Therefore, learning the potential of a disaggregated memory system before deployment is a critical step. This paper proposes a methodology for exploring the design space of a disaggregated memory system. It incorporates key metrics that affect performance on disaggregated memory systems: memory capacity, local and remote memory access ratio, injection bandwidth, and bisection bandwidth, providing an intuitive approach to guide machine configurations based on technology trends and workload characteristics. We apply our methodology to analyze thirteen diverse workloads, including AI training, data analysis, genomics, protein, fusion, atomic nuclei, and traditional HPC bookends. Our methodology demonstrates the ability to comprehend the potential and pitfalls of a disaggregated memory system and provides motivation for machine configurations. Our results show that eleven of our thirteen applications can leverage injection bandwidth disaggregated memory without affecting performance, while one pays a rack bisection bandwidth penalty and two pay the system‐wide bisection bandwidth penalty. In addition, we also show that intra‐rack memory disaggregation would meet the application's memory requirement and provide enough remote memory bandwidth.

Ding, Nan↗
DOE OSTI2026

Evaluating Lithium-Lead Mixtures for Increased Tritium Breeding in Fusion Energy Blanket Systems: Exploring the Impact of Composition and Temperature

This project investigates hypo- and hyper-eutectic liquid lithium-lead (PbLi) mixtures as a coolant in fusion blanket systems, with a focus on testing the compatibility of compositions with better tritium breeding ratios (TBR). The 12-month study concentrates on static corrosion experiments, comparing silicon carbide (SiC) corrosion rates in Li-rich and eutectic Li-Pb mixtures, and examining interactions between Mo and PbLi. The research seeks to determine the maximum operating temperatures for this material combination, acknowledging the balance between Li-Pb melting temperature and achievable TBR to unlock new opportunities for blanket design. This work lays the groundwork for future collaboration between Kyoto Fusioneering and Oak Ridge National Laboratory (ORNL). Findings could enhance the TBR of fusion blanket designs, and impact fusion energy development by confirming material compatibility between different Li-Pb mixtures with SiC and Mo at higher temperatures, including at temperatures relevant for very high-temperature blankets (1,000 °C), which could enable higher electricity conversion efficiencies and commercial applications using process heat.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Differentiable lagrangian shock hydrodynamics with application to stable shock acceleration of density interfaces

We develop a gradient based optimization approach for the equations of compressible, Lagrangian hydrodynamics and demonstrate how it can be employed to automatically uncover strategies to control hydrodynamic instabilities arising from shock acceleration of density interfaces. Strategies for controlling the Richtmyer-Meshkov instability (RMI) are of great benefit for inertial confinement fusion (ICF) where shock interactions with many small imperfections in the density interface lead to instabilities which rapidly grow over time. These instabilities lead to mixing which, in the case of laser driven ICF, quenches the runaway fusion process ruining the potential for positive energy return. Here, we demonstrate that control of these instabilities can be achieved by optimization of initial conditions with ( > 100) parameters. Optimizing over a large parameter space like this is not possible with gradient-free optimization strategies. This requires computation of the gradient of the outputs of a numerical solution to the equations of Lagrangian hydrodynamics with respect to the inputs. We show that the efficient computation of these gradients is made possible via a judicious application of (i) adjoint methods, the exact formal representation of sensitivities involving partial differential equations, and (ii) automatic differentiation (AD), the algorithmic calculation of derivatives of functions. Careful regularization of multiple operators including artificial viscosity and timestep control is required. We perform design optimization of > 100 parameter energy field driving the Richtmyer Meshkov instability showing significant suppression while simultaneously enhancing the acceleration of the interface relative to a nominal baseline case.

Hydrophysics↗
DOE OSTI2025

Pointing stabilization of a 1 Hz high-power laser via machine learning

Abstract High-power lasers are vital for particle acceleration, imaging, fusion and materials processing, requiring precise control and high-energy delivery. Laser plasma accelerators (LPAs) demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders. Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs. We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam. By preemptively adjusting a correction mirror, this approach overcomes traditional feedback limits. Demonstrated on the BELLA petawatt laser operating at the terawatt level (30 mJ amplification), our method achieved root mean square pointing stabilization of 0.34 and 0.59 $\unicode{x3bc} \mathrm{rad}$ in the x and y directions, reducing jitter by 65% and 47%, respectively. This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems, paving the way for full-energy petawatt lasers and transformative advances across science, industry and security.

Amodio, Alessio↗
DOE OSTI2023

Siderocalin fusion proteins enable a new 86 Y/ 90 Y theranostic approach

The mammalian protein siderocalin binds bacterial siderophores and their iron complexes through cation-π and electrostatic interactions, but also displays high affinity for hydroxypyridinone complexes of trivalent lanthanides and actinides. In order to circumvent synthetic challenges, the use of siderocalin-antibody fusion proteins is explored herein as an alternative targeting approach for precision delivery of trivalent radiometals. We demonstrate the viability of this approach in vivo, using the theranostic pair 90 Y (β − , t 1/2 = 64 h)/ 86 Y (β + , t 1/2 = 14.7 h) in a SKOV-3 xenograft mouse model. Ligand radiolabeling with octadentate hydroxypyridinonate 3,4,3-LI(1,2-HOPO) and subsequent protein binding were achieved at room temperature. The results reported here suggest that the rapid non-covalent binding interaction between siderocalin fusion proteins and the negatively charged Y(III)-3,4,3-LI(1,2-HOPO) complexes could enable purification-free, cold-kit labeling strategies for the application of therapeutically relevant radiometals in the clinic.

Cosby, Alexia G.↗
DOE OSTI2024

Simulations and models for the Richtmyer–Meshkov instability with broadband perturbations

The Richtmyer–Meshkov instability (RMI) is shock driven and affects many phenomena from inertial fusion to supernova explosions. The behavior of single-modes in the RMI has been studied extensively but less is known with the broadband perturbations that occur in applications. Here, we describe extensive numerical simulations and modeling of the RMI with broadband perturbations with an initial power spectrum of the form P ∝ km, where k is the wavenumber. The hydrodynamic condition is the same as in the θ-Group Collaboration [Thornber et al., “Late-time growth rate, mixing, and anisotropy in the multimode narrowband Richtmyer–Meshkov instability: The θ-group collaboration,” Phys. Fluids 29, 105107 (2017)] with a Mach ∼1.86 shock and gamma-law = 5/3 fluids with Atwood number A = −0.5. The bubble amplitude hB is found to grow in two stages. Initially, hB undergoes a phase-inversion and grows linearly in time (t) at a rate consistent with a linear theory. Asymptotically, hB grows as a power law ∼tθ when k|hB| > O(1), where k is the average wavenumber for the initial spectrum. The RMI behavior in simulations and modeling agree over a wide range of exponent m, spectral width, initial amplitude, and time. The agreement is quantified objectively using statistical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Microscale thermophoresis as a powerful tool for screening glycosyltransferases involved in cell wall biosynthesis

Background: Identification and characterization of key enzymes associated with cell wall biosynthesis and modification is fundamental to gain insights into cell wall dynamics. However, it is a challenge that activity assays of glycosyltransferases are very low throughput and acceptor substrates are generally not available. Results: We optimized and validated microscale thermophoresis (MST) to achieve high throughput screening for glycosyltransferase substrates. MST is a powerful method for the quantitative analysis of protein-ligand interactions with low sample consumption. The technique is based on the motion of molecules along local temperature gradients, measured by fluorescence changes. We expressed glycosyltransferases as YFP-fusion proteins in tobacco and optimized the MST method to allow the determination of substrate binding affinity without purification of the target protein from the cell lysate. The application of this MST method to the β-1,4-galactosyltransferase AtGALS1 validated the capability to screen both nucleotide-sugar donor substrates and acceptor substrates. We also expanded the application to members of glycosyltransferase family GT61 in sorghum for substrate screening and function prediction. Conclusions: This method is rapid and sensitive to allow determination of both donor and acceptor substrates of glycosyltransferases. MST enables high throughput screening of glycosyltransferases for likely substrates, which will narrow down their in vivo function and help to select candidates for further studies. Additionally, this method gives insight into biochemical mechanism of glycosyltransferase function.

59 BASIC BIOLOGICAL SCIENCES↗