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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Using 100G Network Technology in Support of Petascale Science

NASA in collaboration with a number of partners conducted a set of individual experiments and demonstrations during SC 10 that collectively were titled "Using 100G Network Technology in Support of Petascale Science". The partners included the iCAIR, Internet2, LAC, MAX, National LambdaRail (NLR), NOAA and SCinet Research Sandbox (SRS) as well as the vendors Ciena, Cisco, ColorChip, cPacket, Extreme Networks, Fusion-io, HP and Panduit who most generously allowed some of their leading edge 40G/100G optical transport, Ethernet switch and Internet Protocol router equipment and file server technologies to be involved. The experiments and demonstrations featured different vendor-provided 40G/100G network technology solutions for full-duplex 40G and 100G LAN data flows across SRS-deployed single-node fiber-pairs among the Exhibit Booths of NASA, the National Center for Data lining, NOAA and the SCinet Network Operations Center, as well as between the NASA Exhibit Booth in New Orleans and the Starlight Communications Exchange facility in Chicago across special SC 10- only 80- and 100-Gbps wide area network links provisioned respectively by the NLR and Internet2, then on to GSFC across a 40-Gbps link. provisioned by the Mid-Atlantic Crossroads. The networks and vendor equipment were load-stressed by sets of NASA/GSFC High End Computer Network Team-built, relatively inexpensive, net-test-workstations that are capable of demonstrating greater than 100Gbps uni-directional nuttcp-enabled memory-to-memory data transfers, greater than 80-Gbps aggregate--bidirectional memory-to-memory data transfers, and near 40-Gbps uni-directional disk-to-disk file copying. This paper will summarize the background context, key accomplishments and some significances of these experiments and demonstrations.

Gary, James P.↗
DOE OSTI2021

Concept Design and Analysis of the Magnet System of the Sustained High Power Density Tokamak Facility

A recent National Academy study recommended a next-step sustained high power density (SHPD) facility for the United States that can be a bridge to a compact fusion pilot plant. A design has been initiated to investigate a possible SHPD non-deuterium-tritium device that builds upon recent low aspect ratio tokamak studies. Here, a 1.2-m device with a 2.4 aspect ratio has been chosen to evaluate physics performance goals within a double-null plasma machine arrangement centered on three component features: high current density toroidal field (TF) and central ohmic heating/poloidal field (PF) coils, liquid metal divertor/first wall systems, and the integration of a limited set of outboard dual-coolant lead lithium test blankets that can be maintained within a vertical maintenance approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Fusion of Experiments and Simulations for Real-Time Identification of Pipeline Defects

In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.

deep learning↗
DOE OSTI2025

Fusion of Experiments and Simulations for Real-Time Identification of Pipeline Defects

In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.

deep learning↗
DOE OSTI2024

Voltage waveform tailoring for high aspect ratio plasma etching of SiO 2 using Ar/CF 4 /O 2 mixtures: Consequences of low fundamental frequency biases

The use of non-sinusoidal waveforms in low pressure capacitively coupled plasmas intended for microelectronics fabrication has the goal of customizing ion and electron energy and angular distributions to the wafer. One such non-sinusoidal waveform uses the sum of consecutive harmonics of a fundamental sinusoidal frequency, f 0 , having a variable phase offset between the fundamental and even harmonics. In this paper, we discuss results from a computational investigation of the relation between ion energy and DC self-bias when varying the fundamental frequency f 0 for capacitively coupled plasmas sustained in Ar/CF 4 /O 2 and how those trends translate to a high aspect ratio etching of trenches in SiO 2 . The fundamental frequency, f 0 , was varied from 1 to 10 MHz and the relative phase from 0° to 180°. Two distinct regimes were identified. Average ion energy onto the wafer is strongly correlated with the DC self-bias at high f 0 , with there being a maximum at φ = 0° and minimum at φ = 180°. In the low frequency regime, this correlation is weak. Average ion energy onto the wafer is instead dominated by dynamic transients in the applied voltage waveforms, with a maximum at φ = 180° and minimum at φ = 0°. The trends in ion energy translate to etch properties. In both, the high and low frequency regimes, higher ion energies translate to higher etch rates and generally preferable final features, though behaving differently with phase angle.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Spatial channeling in toroidal plasmas: overview and new results

Energy and momentum transfer by eigenmodes in tokamaks and stellarators, which arises when eigenmodes are destabilized by superthermal ions in a region that does not coincide with the damping region, is considered. This phenomenon, named spatial channeling, may play an important role in toroidal plasmas. Furthermore, it may aect plasma energy connement, plasma rotation, heating of the electron and ion components, and features of eigenmodes. The work contains both an overview and new results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A data integration framework of additive manufacturing based on FAIR principles

Abstract Laser-powder bed fusion (L-PBF) is a popular additive manufacturing (AM) process with rich data sets coming from both in situ and ex situ sources. Data derived from multiple measurement modalities in an AM process capture unique features but often have different encoding methods; the challenge of data registration is not directly intuitive. In this work, we address the challenge of data registration between multiple modalities. Large data spaces must be organized in a machine-compatible method to maximize scientific output. FAIR (findable, accessible, interoperable, and reusable) principles are required to overcome challenges associated with data at various scales. FAIRified data enables a standardized format allowing for opportunities to generate automated extraction methods and scalability. We establish a framework that captures and integrates data from a L-PBF study such as radiography and high-speed camera video, linking these data sets cohesively allowing for future exploration. Graphical abstract

36 MATERIALS SCIENCE↗
NASA NTRS2013

Mid-Infrared Study of Samples from Multiple Stones from the Sutters Mill Meteorite

The Sutter's Mill meteorite fell in N. California on April 22, 2012 and numerous pieces have been recovered and studied. We present Fourier transform infrared (FTIR) spectra of fragments from several stones of the meteorite. Methods and analysis: Infrared spectra of the samples were recorded with a Nicolet iN10 MX FTIR microscope in the mid-IR range (4000-675/cm; spectral resolution 4/cm). All samples were deposited on a clean glass slide, crushed with a stainless steel roller tool, and placed directly on the focal plane of the microscope. IR spectra were collected by averaging 128 scans. Results: Preliminary IR spectra of the non-fusion crust samples show mineral compositions that are dominated by phyllosilicates, carbonates, or mixtures of both [2]. The carbonates display a dominant, broad band centered at 1433/cm, with additional bands at 2515/cm, 1797/cm, 882/cm, and 715/cm). Features associated with phyllosilicates include a symmetric Si-O stretching mode band centered at 1011/cm and several O-H stretching mode bands. The O-H shows up in two forms (1) a broadband centered at 3415/cm that is probably largely due to adsorbed H2O and (2) a much weaker, narrower feature centered near 3680/cm due to structural -OH. Features observed in the 2985-2855/cm range suggest the presence of aliphatic -CH3 and -CH2- groups. The relative intensities of the bands in this range are somewhat unusual. Typically, the asymmetric aliphatic CH stretching bands are stronger than the symmetric stretching bands, but in this case the reverse is true. This unusual pattern is well matched by the aliphatic features seen in the spectrum of a terrestrial calcite (CaCO3) standard. This observation, and the fact that the strength of the carbonate and aliphatic bands seem to correlate, suggest the organics are associated with the carbonates. Conclusions: IR spectra of samples from the Sutter's Mill meteorite show absorption features associated with carbonates, phyllosilicates, and organics. Both the unusual band profile of the aliphatic C-H stretching mode bands and their correlation with the strength of the carbonate bands suggests the organics and the carbonates are associated in some manner.

Sutter's mill↗
DOE OSTI2024

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Diagnosing up-scattered deuterium–tritium fusion neutrons produced in burning plasmas at the National Ignition Facility (invited)

In the push to higher performance fusion plasmas, two critical quantities to diagnose are α-heat deposition that can improve and impurities mixed into the plasma that can limit performance. In high-density, highly collisional inertial confinement fusion burning plasmas, there is a significant probability that deuterium–tritium (DT) fusion products, 14.1 MeV neutrons and 3.5 MeV α-particles, will collide with and deposit energy onto (“up-scatter”) surrounding deuterium and tritium fuel ions. These up-scattered D and T ions can then undergo fusion while in-flight and produce an up-scattered neutron (15–30 MeV). These reaction-in-flight (RIF) neutrons can then be uniquely identified in the measured neutron energy spectrum. Further, the magnitude, shape, and relative size of this spectral feature can inform models of stopping-power in the DT plasma and hence is directly proportional to α-heat deposition. In addition, the RIF spectrum can be related to mix into the burning fuel, particularly relevant for high-Z shell and other emerging National Ignition Facility platforms. The neutron time-of-flight diagnostic upgrades needed to obtain this small signal, ~10 –5 times the primary DT neutron peak, will be discussed. Results from several gain > 1 implosions will be shown and compared to previous RIF spectra. Finally, comparisons of experimental data to a simplified computational model will be made.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

USE OF TWO-PISTON SPLAT QUENCHING TO INVESTIGATE & CHARACTERIZE THE IMPACT OF COMPOSITIONAL VARIATIONS ON RAPID SOLIDIFICATION MICROSTRUCTURES & SUB-MICROSCALE FEATURES IN STAINLESS STEEL ALLOY.

The objective of this dissertation was to use two-piston splat quenching (SQ) to investigate the impact of compositional modifications on the solidification and microstructure of rapidly solidified austenitic stainless steels (SS) and to demonstrate the ability of SQ to quickly and effectively simulate rapid solidification conditions similar to those found in powder bed fusion (PBF) additive techniques. PBF techniques like laser powder bed fusion (LPBF) are being implemented across a breadth of research and industrial applications to create parts with complex geometries and performance capabilities while pushing the current limits of processing conditions and understanding of material systems. In this work, SQ was used to experimentally produce rapid solidification in 20+ unique austenitic SS compositions with systematic variations of the chrome and nickel equivalency ratio (Cr/Nieq) through targeted compositional modifications. From the targeted change of Cr, Ni, and Mo concentrations in rapidly solidified SS alloys, the ferrite solidification mode was found to be the primary solidification mode at significantly lower Cr/Nieq than previously predicted for RS. Also, decreasing concentrations of Fe at a constant Cr/Nieq ratio (i.e., different Fe isopleths), or increased Mo concentrations at a constant Cr/Nieq ratio were found to suppress the ferrite to austenite massive transformation when compared to alloys with lower concentrations at the same Cr/Nieq. Using an established empirical relationship between cell size and cooling rate, the SQ technique was estimated to produce cooling rates between 106 and 108 K/s. Thermal gradients were extracted from 2-D heat transfer simulations of the SQ solidification event and used with these cooling rates to produce solidification rate estimates for SQ which were between 0.4-1.6m/s. The primary solidification mode was observed to be the determining factor in which elements segregated to the cell boundaries during RS, for which Cr and Mo were the main elements to segregate during primary austenite solidification and Ni during primary ferrite solidification. Finally, the solidification rates and conditions produced by SQ experiments resulted in similar microstructures, features, and microsegregation to what was found in LPBF samples of the same feedstock.

Hasenbusch, Zachary↗
DOE OSTI2025

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗
DOE OSTI2021

Lower hybrid current drive in a tokamak for correlated passes through resonance

Standard quasilinear descriptions are based on the constant magnetic field form of the quasilinear operator so improperly treat the trapped electron modifications associated with tokamak geometry. Moreover, successive poloidal transits of the Landau resonance during lower hybrid current drive in a tokamak are well correlated, and these geometrical details must be properly retained to account for the presence of trapped electrons that do not contribute to the driven current. The recently derived quasilinear operator in tokamak geometry accounts for these features and finds that the quasilinear diffusivity is proportional to a delta function with a transit or bounce averaged argument (rather than a local Landau resonance condition). The new quasilinear operator is combined with the Cordey ( Nucl. Fusion , vol. 16, 1976, pp. 499–507) eigenfunctions to properly derive a rather simple and compact analytic expression for the trapped electron modifications to the driven lower hybrid current and the efficiency of the current drive.

Physics↗
DOE OSTI2022

Lower hybrid current drive in a tokamak for correlated passes through resonance

Standard quasilinear descriptions are based on the constant magnetic field form of the quasilinear operator so improperly treat the trapped electron modifications associated with tokamak geometry. Moreover, successive poloidal transits of the Landau resonance during lower hybrid current drive in a tokamak are well correlated, and these geometrical details must be properly retained to account for the presence of trapped electrons that do not contribute to the driven current. The recently derived quasilinear operator in tokamak geometry accounts for these features and finds that the quasilinear diffusivity is proportional to a delta function with a transit or bounce averaged argument (rather than a local Landau resonance condition). The new quasilinear operator is combined with the Cordey (Nucl. Fusion, vol. 16, 1976, pp. 499–507) eigenfunctions to properly derive a rather simple and compact analytic expression for the trapped electron modifications to the driven lower hybrid current and the efficiency of the current drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Minimizing separatrix crossings through isoprominence

Abstract A simple property of magnetic fields that minimizes bouncing to passing type transitions of guiding center orbits is defined and discussed. This property, called isoprominence, is explored through the framework of a near-axis expansion. It is shown that isoprominent magnetic fields for a toroidal configuration exist to all orders in a formal expansion about a magnetic axis. Some key geometric features of these fields are described.

confinement↗
DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Spectral Data Fusion From Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) Analyzers for Improved Detection of Cerium in a Simulated Dispersal Accident

Here, this work implements a mid-level data fusion methodology on spectral data from handheld X-ray fluorescence and laser-induced breakdown spectroscopy analyzers to quantify plutonium surrogate (CeO 2 ) contamination in soil samples for the first time. Spectral data from each analyzer were used independently to train supervised machine learning regressions to predict Ce concentration. Fused features from both data sets were then used to train the same models, comparing prediction performance by evaluating model precision and sensitivity. Fusing principal component scores from the two sensors yielded an order of magnitude improvement in precision and sensitivity of predictions made with an artificial neural network, compared to predictions made by models trained on independent sensor data. As a result, a boosted ensemble trained on the fused spectral features yielded an ideal predictor with root-mean-squared error on the order of 10 –6 and calculated limit of detection order 10 –5 wt %.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗