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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DECAF Cross-device characterization of tokamak disruptions indicated by abnormalities in plasma vertical position and current

Abnormal (deviating from target) variations in the plasma vertical position Z and current I p (such as vertical displacements, transient I p 'spikes' and quenches) constitute common elements of a disruption, a phenomenon that is to be mitigated, or ultimately avoided in future reactor-relevant tokamaks. While those abnormalities are generally recognized cross-shot and cross-device, details in terms of appearance (or not) and order of those abnormalities in disruption event chains is bound with the plasma state at the time of the chain initiation. Detection of those abnormalities is thus indicative not only of the onset of the plasma collapse itself, but also of the disruption driving cause that is promoted at the particular plasma state. Here, occurrence of disruptions, explored via detection of a Ip quench, and analysis of disruption event chains constituted by Ip and Z abnormalities, is reported for in total 7 full years of operation of 3 devices (KSTAR, MAST-U and NSTX-U) using the DECAFTM code expanded tools and capabilities. It is shown that the disruption occurrence depends not only on details of the plasma state, but also on (device-dependent) technical elements of the shot exit scenario. A year-to-year change in main disruption causes and a reduction of the disruptivity rate, bound with device and operation upgrades, are reported. Particular trigger instances of disruption event chains (and the full chains, when applicable) are shown to occupy different parts of the operation space diagrams, in accordance with prior expectation. Plasma elongation is identified as an important factor influencing details of the chains and its role will be further explored.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Plasma Facing Component Characterization and Correlation With Plasma Conditions in Lithium Tokamak Experiment-β

Lithium coatings in the Lithium Tokamak eXperiment (LTX) led to flat temperature profiles. The flat temperature profiles were observed along with a hot, low density edge, implying a broad, collisionless scrape-off layer (SOL). Additionally, in vacuo X-ray photoelectron spectroscopy (XPS) measurements established that lithium coatings evaporatively deposited onto high-Z plasma facing components (PFCs) became oxidized while retaining the ability to achieve good plasma performance long after lithium was applied to the PFCs. Longstanding theory predicted flat temperature profiles with low recycling walls, which was presumed to be due to hydrogen binding with elemental lithium to form lithium hydride. The presence of oxidized lithium, however, raised questions regarding the exact mechanism of hydrogen retention in LTX. To investigate these questions, the upgraded facility LTX- β includes a new sample exposure probe (SEP) for more detailed in vacuo analysis of PFC samples. The SEP is equipped with a vacuum suitcase capable of transporting samples representative of the LTX- β outer midplane PFCs to a stand-alone XPS system while maintaining pressures lower than the LTX- β base vacuum to limit the contamination between sample exposure and analysis. The low-energy resolution XPS system used in past experiments could only enable the determination of elemental percentages on the PFC sample surfaces. Because the new XPS system has higher energy resolution, it is more direct to assign chemical compounds to the measured binding energies. This capability has been confirmed by comparing XPS data from PFC test samples with measurements using a commercial high-resolution XPS system. Quartz crystal microbalances (QCMs) were used to quantify the thickness of the deposited lithium on the LTX- β PFCs. This article describes the application of the SEP to characterize the PFC surfaces using XPS and their relationship to plasma conditions.

Maan, Anurag↗
NASA NTRS2002

Investigation of Friction Stir Welding and Laser Engineered Net Shaping of Metal Matrix Composite Materials

The improvement in weld quality by the friction stir welding (FSW) process invented by TWI of Cambridge, England, patented in 1991, has prompted investigation of this process for advanced structural materials including Al metal matrix composite (Al-MMC) materials. Such materials can have high specific stiffness and other potential beneficial properties for the extreme environments in space. Developments of discontinuous reinforced Al-MMCs have found potential space applications and the future for such applications is quite promising. The space industry has recognized advantages of the FSW process over conventional welding processes such as the absence of a melt zone, reduced distortion, elimination of the need for shielding gases, and ease of automation. The process has been well proven for aluminum alloys, and work is being carried out for ferrous materials, magnesium alloys and copper alloys. Development work in the FSW welding process for joining of Al-MMCs is relatively recent and some of this and related work can be found in referenced research publications. NASA engineers have undertaken to spear head this research development work for FSW process investigation of Al-MMCs. Some of the reported related work has pointed out the difficulty in fusion welding of particulate reinforced MMCs where liquid Al will react with SiC to precipitate aluminum carbide (Al4C3). Advantages of no such reaction and no need for joint preparation for the FSW process is anticipated in the welding of Al-MMCs. The FSW process has been best described as a combination of extrusion and forging of metals. This is carried out as the pin tool rotates and is slowly plunged into the bond line of the joint as the pin tool's shoulder is in intimate contact with the work piece. The material is friction-stirred into a quality weld.

Ravinder M. Diwan↗
DOE OSTI2022

A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The Trajectory of Additively Manufactured Titanium Alloys with Superior Mechanical Properties and Engineered Microstructures

Additive manufacturing (AM) plays a crucial role in the manufacturing and development of advanced materials including titanium alloys for engineering applications. During the last two decades, a great deal of effort has been devoted to print titanium parts with desired properties. However, due to presence of non-equilibrium/metastable phases, anisotropic microstructure, and various porosities in the printed titanium alloys, achieving an excellent combination of mechanical properties has been challenging. Here this review paper aims to provide a comprehensive overview of multiple post-process and in-process approaches to achieve enhanced strength-ductility combinations by microstructure engineering. Approaches such as addition of alloying elements/nucleants, multi-step post heat treatment, in-situ heat treatment, forced inter-pass cooling, in situ peening/rolling, hybridizing microstructure, high-intensity acoustic vibration, thermo-hydrogen refinement of microstructure, deliberately introducing lack of fusion defects with subsequent hot isostatic pressing are discussed in detail. Finally, we conclude by highlighting the challenges associated with each method and potential areas of improvement that can pave the way to develop reliable components with enhanced performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Plasma Focused Ion Beam Milling of High-Aspect-Ratio Holes in Diamond

Plasma focused ion beam (PFIB) technology has a great potential for applications requiring rapid micro-machining of high-aspect-ratio features. Here, we use 30-keV Ar, Xe, and O 2 ion beams to study PFIB milling of high-aspect-ratio circular holes in polycrystalline diamond. Our results show that Xe and O 2 ion beams have the highest milling efficiency for low-aspect-ratio and high-aspect-ratio hole milling, respectively. Each ion beam species produces holes with its characteristic shape and wall surface morphology. In conclusion, based on these results, we demonstrate a “hybrid” hole milled in a two-step process with Xe and O 2 ion beams with the geometry and wall morphology attractive for the attachment of a fuel fill tube to the inertial confinement fusion capsule.

ICF targets↗
DOE OSTI2022

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

42 ENGINEERING↗
DOE OSTI2024

Artificial correlation heating in PIC simulations

The Particle-in-Cell (PIC) method, a cornerstone in plasma modeling, is widely employed for its ability to simulate kinetic phenomena in device-scale domains. Part of what makes this possible is that computational macroparticles represent many physical particles. It converges under certain constraints, including a grid spacing that resolves the Debye length and a time step small enough to respect the Courant–Friedrichs–Lewy condition and plasma frequency stability limit. Here, we introduce a new constraint necessary to avoid Artificial Correlation Heating (ACH). This requires that the macroparticle coupling strength be smaller than one, Γ ω < 1, where Γ ω ≡ Γω 2/3 ⁠, Γ = Z 2 e 2 /(4πε 0 ak B T) is the physical coupling strength, and w is the macroparticle weight. This is particularly relevant to 3D simulations of dense plasmas, which are becoming common with modern computing power. If this condition is violated, the finite macroparticle weight artificially enhances the coupling strength and causes the plasma to heat until the macroparticle coupling strength is near unity, depending on the grid resolution. A comprehensive model of ACH is developed that incorporates electron density, temperature, macroparticle weight, and grid resolution. It is then tested using PIC simulations, delineating the boundaries of the method's applicability and offering a predictive framework for ACH. Moreover, the research explores a runaway heating process induced by ACH in the presence of ionization, which can lead to numerical instability. A conclusion of this study is that the onset of ACH can impose a more stringent constraint on the macroparticle weight and average number of macroparticles per cell than what is typically expected, particularly in 3D simulations of dense plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Projective Representations, Bogomolov Multiplier, and Their Applications in Physics

We present a pedagogical review of projective representations of finite groups and their physical applications in quantum many-body systems. Some of our physical results are new. We begin with a self-contained introduction to projective representations, highlighting the role of group cohomology, representation theory, and classification of irreducible projective representations. We then focus on a special subset of cohomology classes, known as the Bogomolov multiplier, which consists of cocycles that are symmetric on commuting pairs but remain nontrivial in group cohomology. Such cocycles have important physical implications: they characterize (1+1)D SPT phases that cannot be detected by string order parameters and give rise, upon gauging, to distinct gapped phases with completely broken non-invertible Rep(G) symmetry. We construct explicit lattice models for these phases and demonstrate how they are distinguished by the fusion rules of local order parameters. We show that a pair of completely broken Rep(G) SSB phases host nontrivial interface modes at their domain walls. As an example, we construct a lattice model where the ground state degeneracy on a ring increases from 32 without interfaces to 56 with interfaces.

Bogomolov multiplier↗
DOE OSTI2021

A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

We present our recent development of an integrated mesoscale digital twin (DT) framework for relating processing conditions, microstructures, and mechanical responses of additively manufactured (AM) metals. In particular, focusing on the laser powder bed fusion technique, we describe how individual modeling and simulation capabilities are coupled to investigate and control AM microstructural features at multiple length and time scales. We review our prior case studies that demonstrate the integrated modeling schemes, in which high-fidelity melt pool dynamics simulations provide accurate local thermal profiles and histories to subsequent AM microstructure simulations. We also report our new mechanical response modeling results for predicted AM microstructures. In addition, we illustrate how our DT framework has been validated through modeling–experiment integration, as well as how it has been practically utilized to guide and analyze AM experiments. Finally, we share our perspectives on future directions of further development of the DT framework for more efficient, accurate predictions and wider ranges of applications.

36 MATERIALS SCIENCE↗
NASA NTRS2004

The Vasimr Engine: Project Status and Recent Accomplishments

The development of the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) was initiated in the late 1970s to address a critical requirement for fast, high-power interplanetary space transportation. While not being a fusion rocket, it nevertheless borrows heavily from that technology and takes advantage of the natural topology of open-ended magnetic systems. In addition to its high power density and high exhaust velocity, VASIMR is capable of "constant power throttling" a feature, which allows in-flight mission-optimization of thrust and specific impulse to enhance performance and reduce trip time. A NASA-led, research team, involving industry, academia and government facilities is pursuing the development of this concept in the United States. The technology can be validated, in the near term, in venues such as the International Space Station, where it can also serve as both a drag compensation device and a plasma contactor for the orbital facility. Other near-Earth applications in the commercial and scientific satellite sectors are also envisioned. This presentation covers the evolution of the VASIMR concept to its present status, as well as recent accomplishments in our understanding of the physics. Approaches and collaborative programs addressing the major technical challenges will also be presented.

ChangDiaz, Franklin R.↗
DOE OSTI2022

Modelling of edge plasma dynamics with active wall boundary conditions

A self-consistent 2D model is presented for transport in boundary plasma and plasma-facing material walls. Plasma dynamics in the domain is represented by a 2D collisional plasma fluid model in the edge-plasma code UEDGE, and transport of hydrogen and heat in the wall is represented by a system of reaction–diffusion equations in the 1D wall code FACE. To account for variation of parameters along the wall, in the coupled model multiple instances of the FACE code run in parallel. Here, the coupled model provides a tool for investigating a range of dynamic plasma–material interactions phenomena in 2D. For demonstration of its capability, one application of particular interest is the role of active wall in tokamak strike point sweeping proposed for mitigation of divertor heat loads. In the present study, the coupled calculations are applied to investigation of the impact of heat and hydrogen transport in the material wall on the divertor plasma and target heat load during sweeping of the target strike point for parameters of a high-power tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Plasma and trap-based techniques for science with antimatter

Positrons (i.e., antielectrons) find use in a wide variety of applications, and antiprotons are required for the formation and study of antihydrogen. Available sources of these antiparticles are relatively weak. To optimize their use, most applications require that the antiparticles be accumulated into carefully prepared plasmas. We present an overview of the techniques that have been developed to efficiently accumulate low energy antiparticles and create, in particular, tailored antiparticle plasmas. Techniques are also described to create tailored antiparticle beams. Many of these techniques are based on methods first developed by the nonneutral plasma community using electron plasmas for increased data rate. They have enabled the creation and trapping of antihydrogen, have been critical to studies of positron and positronium interactions with matter, including advanced techniques to characterize materials and material surfaces, and have led to the creation and study of the positronium molecule. Rather than attempting to be comprehensive, we focus on techniques that have proven most useful, applications where there has been significant, recent progress, and areas that hold promise for future advances. Examples of the latter include the ever more precise comparisons of the properties of antihydrogen and hydrogen, tests of gravity using antihydrogen and positronium atoms, and efforts to create and study phases of the many-electron, many-positron system.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Three-dimensional feedback processes in current-driven metal

Using three-dimensional (3D) magnetohydrodynamic simulations, we study how a pit on a metal surface evolves when driven by intense electrical current density j. Redistribution of j around the pit initiates a feedback loop: j both reacts to and alters the electrical conductivity σ, through Joule heating and hydrodynamic expansion, so that j and σ are constantly in flux. Thus, the pit transforms into larger striation and filament structures predicted by the electrothermal instability theory. Both structures are important in applications of current-driven metal: Here, the striation constitutes a density perturbation that can seed the magneto-Rayleigh-Taylor instability, while the filament provides a more rapid path to plasma formation, through 3D j redistribution. Simulations predict distinctive self-emission patterns, thus allowing for experimental observation and comparison.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

Fabrication of imaging X-ray optics

The design, fabrication, and performance of optics for X-ray astronomy and laboratory applications are described and illustrated with diagrams, drawings, graphs, photographs, and sample images. Particular attention is given to the Wolter I telescope developed for spectroscopic observation of 8-30-A cosmic X-ray sources from a rocketborne X-ray Objective Grating Spectrometer; this instrument employs three nested paraboloid-hyperboloid mirrors of 5083 Al alloy, figured by diamond turning and covered with a thin coating of acrylic lacquer prior to deposition of a 40-nm-thick layer of Sn. In calibration tests at NASA Marshall, the FWHM of the line-spread function at 1.33 nm was found to be 240 microns, corresponding to 21 arcsec. Also presented are the results of reflectivity measurements on C and W multilayers sputtered on Si and fusion glass substrates.

Catura, R. C.↗
NASA NTRS1992

Energy for lunar resource exploitation

Humanity stands at the threshold of exploiting the known lunar resources that have opened up with the access to space. America's role in the future exploitation of space, and specifically of lunar resources, may well determine the level of achievement in technology development and global economic competition. Space activities during the coming decades will significantly influence the events on Earth. The 'shifting of history's tectonic plates' is a process that will be hastened by the increasingly insistent demands for higher living standards of the exponentially growing global population. Key to the achievement of a peaceful world in the 21st century, will be the development of a mix of energy resources at a societally acceptable and affordable cost within a realistic planning horizon. This must be the theme for the globally applicable energy sources that are compatible with the Earth's ecology. It is in this context that lunar resources development should be a primary goal for science missions to the Moon, and for establishing an expanding human presence. The economic viability and commercial business potential of mining, extracting, manufacturing, and transporting lunar resource based materials to Earth, Earth orbits, and to undertake macroengineering projects on the Moon remains to be demonstrated. These extensive activities will be supportive of the realization of the potential of space energy sources for use on Earth. These may include generating electricity for use on Earth based on beaming power from Earth orbits and from the Moon to the Earth, and for the production of helium 3 as a fuel for advanced fusion reactors.

Glaser, Peter E.↗
DOE OSTI2026

Quantifying Microstructure Variability in Laser Powder Bed Fusion 316 L Stainless Steel Microstructures with Spatial Statistics

Here, we have explored data-driven methods for material microstructure quantification that improve sensitivity to microstructural changes compared to traditional approaches. The methods integrate multiple microstructural properties, including grain morphology, crystallographic orientation, and material phase information. The simpler method employs maps of the Euclidean distance transformation metric to evaluate the morphology of grain boundary networks. The more intensive approach employs generalized spherical harmonic mapping for crystallographic orientations, per-pixel phase information, and a variational auto-encoder for dimensionality reduction and results in a multidimensional clustering of by microstructure similarity. Applied to an experimental dataset of additively manufactured steel, both methods detected slight variations in samples produced under nominally identical processing conditions. Both methods were able to distinguish between samples from multiple (nominally identical) builds, while the generalized spherical harmonics-based method could additionally cluster data samples rotated at two orientations on the build plate. The improved sensitivity of the methods, demonstrated through comparison with traditional microstructure characterization techniques, offers advantages for microstructure quantification and comparisons in advanced manufacturing applications.

SS316L↗
DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗