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DOE OSTI2019

Tensile properties, strain rate sensitivity, and activation volume of additively manufactured 316L stainless steels [Tensile properties of 316L stainless steels made by laser powder-bed-fusion additive manufacturing]

The tensile properties of additively manufactured (AM) metals and alloys are among the most important variables that impact the potential applications of these materials. Here we examine and report on the tensile properties of AM 316L stainless steels fabricated by the laser powder-bed-fusion (L-PBF) technique, via twelve sets of optimized laser processing parameters that produce materials with density >98.8 ± 0.10%. A heterogeneous microstructure is observed in all L-PBF samples, including microscopic features such as dislocations, cellular walls, elemental segregations, local misorientations, impurities, precipitates, and a large fraction of low-angle grain boundaries (2-10°, ~40–60%). The derived average grain size defined by high-angle grain boundaries (>10°) is ~30–50 μm. Tensile testing reveals a yield strength ranging from 552 to 635 MPa and a tensile-elongation-to-failure (TEF) of 0.09–0.42 for directly-printed samples, whereas these values are 592–690 MPa and 0.29–0.50 for samples machined from the as-built rectangular thin plates. In all samples, we observe a variation of tensile yield strength within ~15% but not the TEF, suggesting marginal microstructural changes despite a wide range of laser processing parameters. The large scatter of TEF in directly-printed samples originates from the sensitivity of thin gauge geometry (~2 mm 2 cross-section area) to the built-in flaws. We measured a substantially higher strain rate sensitivity (m~0.02–0.03) of L-PBF 316L compared to the coarse-grained counterparts (~0.006), together with a small activation volume of ~20–30b3 (where b is the Burgers vector of 316L). In conclusion, these deformation kinetics parameters suggest that the tensile plasticity of L-PBF 316L is controlled by a much finer microstructural length scale than the measured grain size, consistent with the high strength and juxtaposed nano- to macro-structures seen in these materials. Strategies to optimize the tensile properties of AM materials are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Characterizing the performance of node-aware strategies for irregular point-to-point communication on heterogeneous architectures

Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A case study in contrastive learning information combination: Application to technical forensics of additive manufacturing filament source identification

Combination of information from disparate data sources into a single decision is a core challenge in many fields, including the field of technical forensics. Technical forensics (TF) utilizes technical characterization of questioned samples to determine properties of that sample; these properties are then used to infer information of forensic interest, such as provenance, age, or attribution. TF is utilized in traditional forensic applications, such as the attribution of material fragments from an explosive, and in nuclear forensic applications, such as the attribution of actinides which have been interdicted out of regulatory control. The challenge of combining information from disparate sources, described alternately by many terms including “Data Fusion” and “Data Integration”, is exacerbated in the technical forensics domain due to at least two factors: the challenge of interpreting each information source singularly, and the relatively small data set sizes available. Extensive literature exists attempting to combine technical forensics information sources, both in manual and automated processes. These attempts are often bespoke to the specific information sources (such as the bi-, tri-, or quad-isotope chart (Moody, Grant, and Hutcheon 2005)), with some emerging examples of simple early- and late- fusion (, respectively). Simultaneous to the information combination efforts described in the previous paragraph, the field of natural language processing attempted (and largely succeeded) in combining information from multiple non-technical information sources. The ecosystem of “multi-modal” language models, which can take text and images as input, and generate text and images as output, became large and diverse by 2025 (Khan et al. 2025). In a generalized sense, many of these methods are trained by learning neural networks which can convert raw text or images into a vector of numbers describing the text or image, hereafter called “embeddings” and the neural networks performing the conversion are called “embedders”. By using a separate embedder for text and images, finding coincident text and images (such as images with their captions), and optimizing the parameters of the embedders such that the embeddings for the text and the image are similar, the field has found a bridge between text and images (Girdhar et al. 2023). It is the contention of the authors of this report that this insight is not limited to text and images but instead can be extended to any modality which can be found coincidently. The subject of the rest of this report is the application of this method to example multi-modal technical forensic data. Some details about the data used in this report are not appropriate for this report, and are included in a companion report (PNNL-38669).

36 MATERIALS SCIENCE↗

NASA NTRS1974

Principal components colour display of ERTS imagery

In the technique presented, colours are not derived from single bands, but rather from independent linear combinations of the bands. Using a simple model of the processing done by the visual system, three informationally independent linear combinations of the four ERTS bands are mapped onto the three visual colour dimensions of brightness, redness-greenness and blueness-yellowness. The technique permits user-specific transformations which enhance particular features, but this is not usually needed, since a single transformation provides a picture which conveys much of the information implicit in the ERTS data. Examples of experimental vector images with matched individual band images are shown.

Taylor, M. M.↗

NASA NTRS1982

Computational aspects of remapping digital imagery

One of the advantages of automated cartography is that map data stored in the digital computer can be plotted or displayed at any scale or projection by recomputing the coordinates of the data. This is especially easy in the case of vector (graphics) data but in the case of digital image (raster) data, remapping is a more difficult operation. Examples of the remapping of digital imagery would include rectification of a LANDSAT MSS to an orthographic or Mercator projection, warping of one image to register with another, or rotation, scale, or aspect changes of a digital image. Use of general purpose computers and array processors for this task will be covered. Data processing error will be discussed for each modelling/warping approach.

Zobrist, A. L.↗

DOE OSTI2019

Nitrogen-rich macrocyclic ligands, chelation complexes thereof, and process for selective chelation of radioactive bismuth ions with the ligands

Selective chelation of bismuth radionuclide ions from a mixture including actinium radionuclide ions involves exposing a ligand to an aqueous solution that includes bismuth radionuclide ions and actinium radionuclide ions under conditions whereby the bismuth radionuclide ions selectively chelate to the ligand for form cationic complexes of the bismuth radionuclide ions. and separating the cationic complexes of the bismuth radionuclide ions from the actinium radionuclide ions. The ligands have a structure based on a 12-membered cyclen ring and may include pendant functional groups that can be derivatized with biological targeting vectors for targeted alpha therapy.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2020

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗

DOE OSTI2022

Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics

X-ray photon correlation spectroscopy (XPCS) allows for the resolution of dynamic processes within a material across a wide range of length and time scales. X-ray speckle visibility spectroscopy (XSVS) is a related method that uses a single diffraction pattern to probe ultrafast dynamics. Interpretation of the XPCS and XSVS data in terms of underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS and XSVS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from molecular dynamics simulations. We compare the efficiency and accuracy of two alternative computational methods: the direct method computing the intensity at each diffraction vector separately, and a method based on fast Fourier transform that computes the intensities at all diffraction vectors at once. Furthermore, the computed X-ray speckle patterns capture the density fluctuations over a range of length and time scales and are shown to reproduce the known properties and relations of experimental XPCS and XSVS for liquids.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Magnetic Phase Transition in MnSi on the Base of the LSDA + U + SO Calculations of the Electronic Structure and the Spin-Fluctuation Theory

Spin states appearing near the magnetic phase transition in helicoidal ferromagnet MnSi are studied on the basis of the spin-fluctuation theory and the LSDA + U + SO calculations of the electronic structure. The temperature dependence of the uniform magnetic susceptibility is calculated near the magnetic phase transition temperature, and the result agrees well with the experiment. Spin correlators corresponding to various solutions of the equation of magnetic state are determined in the region of the magnetic phase transition expanded in temperature. It is shown that, in this region, a helicoidal short-range order appears in the form of the superposition of left and right spin spirals with stochastic weight coefficients. It is shown that the magnetic susceptibility divergences on the helicoid wave vector at the temperature of disappearance of local magnetization and during the transition to the paramagnetic state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1988

Storage and computationally efficient permutations of factorized covariance and square-root information arrays

A unified method to permute vector stored Upper triangular Diagonal factorized covariance and vector stored upper triangular Square Root Information arrays is presented. The method involves cyclic permutation of the rows and columns of the arrays and retriangularization with fast (slow) Givens rotations (reflections). Minimal computation is performed, and a one dimensional scratch array is required. To make the method efficient for large arrays on a virtual memory machine, computations are arranged so as to avoid expensive paging faults. This method is potentially important for processing large volumes of radio metric data in the Deep Space Network.

Muellerschoen, R. J.↗

NASA NTRS1993

Optical characterization of LDEF contaminant film

Dark brown molecular film deposits were found at numerous locations on the Long Duration Exposure Facility (LDEF) and have been documented in great detail by several investigators. The exact deposition mechanism for these deposits is as yet unknown, although direct and scattered atomic oxygen, and solar radiation interacting with materials outgassing products have all been implicated in the formation process. Specimens of the brown molecular film were taken from below the flange of the experimental tray located at position D10 on the LDEF. The tray was one of two, comprising the same experiment, the other being located on the wake facing side of the LDEF satellite at position B4. Having access to both trays, we were able to directly compare the effect that orientation with respect to the atomic oxygen flux vector had on the formation of the brown molecular film deposits. The film is thickest on surfaces facing toward the exterior, i.e. the tray corner, as can be seen by comparing the lee and wake aspects of the rivets. The patterns appear to be aligned not with the velocity vector but with the corner of the tray suggesting that flux to the surface is due to scattered atomic oxygen rather than direct ram impingement. The role of scattered flux is further supported by more faint plume patterns on the sides of the tray. The angle of these plumes is strongly aligned with the ram direction but the outline of the deposit implies that incident atoms are scattered by collisions with the edges of the opening resulting in a directed, but diffuse, flux of atomic oxygen to the surface. Spectral reflectance measurements in the 2 to 10 micron (4000 to 1000 wavenumbers) spectral range are presented for the film in the 'as deposited' condition and for the free standing film. The material was analyzed by FTIR (Fourier Transform Infrared) microspectroscopy using gold as the reference standard. The 'as deposited' specimen was on an aluminum rivet taken from beneath the tray flange while the free film was obtained by chipping some of the material from the rivet. The transmission spectrum over the 2 to 10 micron range for the free film is presented. This spectrum appears to be essentially the same as that presented by Crutcher et.al. for films formed at vent sites which faced into the ram direction and suggested to originate from urethanes and silicones used on the LDEF. Banks et. al. state that silicones, when exposed to atomic oxygen, release polymeric scission fragments which deposit on surfaces and form a glassy, dark contaminant layer upon further atomic oxygen exposure and solar irradiation.

Blakkolb, Brian K.↗

NASA NTRS1998

Arctic Sea Ice Motion from Wavelet Analysis of Satellite Data

Wavelet analysis of DMSP SSM/I (Special Sensor Microwave/Imager) 85 GHz and 37 GHz radiance data, SMMR (Scanning Multichannel Microwave Radiometer) 37 GHz, and NSCAT (NASA Scatterometer) 13.9 GHZ data can be used to obtain daily sea ice drift information for both the northern and southern polar regions. The derived maps of sea ice drift provide both improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing data from satellite synthetic aperture radars (SAR). Examples of derived ice-drift maps in the Arctic illustrate large-scale circulation reversals within a period of a couple weeks. Comparisons with ice displacements derived from buoys show good quantitative agreement. NASA Scatterometer (NSCAT) 13.9 GHZ data have been also used for wavelet analysis to derive sea-ice drift. First, the 40' incidence-angle, sigma-zero (surface roughness) daily map of whole Arctic region with 25 km of pixel size from satellite's 600 km swath has been constructed. Then, the similar wavelet transform procedure to SSM/I data can be applied. Various scales of wavelet transform and threshold have been tested. By overlaying , neighbor filtering, and block-averaging the results of multiscale wavelet transforms, the final sea ice drift vectors are much smooth and representative to the sea ice motion. This wavelet analysis procedure is robust and can make a major contribution to the understanding of ice motion over large areas at relatively high temporal resolutions. The results of wavelet analysis of SSM/I and NSCAT images and buoy data can be merged by some data fusion techniques and will help to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model.

Liu, Antony K.↗

NASA NTRS2000

Multiresolution With Super-Compact Wavelets

The solution data computed from large scale simulations are sometimes too big for main memory, for local disks, and possibly even for a remote storage disk, creating tremendous processing time as well as technical difficulties in analyzing the data. The excessive storage demands a corresponding huge penalty in I/O time, rendering time and transmission time between different computer systems. In this paper, a multiresolution scheme is proposed to compress field simulation or experimental data without much loss of important information in the representation. Originally, the wavelet based multiresolution scheme was introduced in image processing, for the purposes of data compression and feature extraction. Unlike photographic image data which has rather simple settings, computational field simulation data needs more careful treatment in applying the multiresolution technique. While the image data sits on a regular spaced grid, the simulation data usually resides on a structured curvilinear grid or unstructured grid. In addition to the irregularity in grid spacing, the other difficulty is that the solutions consist of vectors instead of scalar values. The data characteristics demand more restrictive conditions. In general, the photographic images have very little inherent smoothness with discontinuities almost everywhere. On the other hand, the numerical solutions have smoothness almost everywhere and discontinuities in local areas (shock, vortices, and shear layers). The wavelet bases should be amenable to the solution of the problem at hand and applicable to constraints such as numerical accuracy and boundary conditions. In choosing a suitable wavelet basis for simulation data among a variety of wavelet families, the supercompact wavelets designed by Beam and Warming provide one of the most effective multiresolution schemes. Supercompact multi-wavelets retain the compactness of Haar wavelets, are piecewise polynomial and orthogonal, and can have arbitrary order of approximation. The advantages of the multiresolution algorithm are that no special treatment is required at the boundaries of the interval, and that the application to functions which are only piecewise continuous (internal boundaries) can be efficiently implemented. In this presentation, Beam's supercompact wavelets are generalized to higher dimensions using multidimensional scaling and wavelet functions rather than alternating the directions as in the 1D version. As a demonstration of actual 3D data compression, supercompact wavelet transforms are applied to a 3D data set for wing tip vortex flow solutions (2.5 million grid points). It is shown that high data compression ratio can be achieved (around 50:1 ratio) in both vector and scalar data set.

Lee, Dohyung↗

NASA NTRS2000

SSMI Wind Speed Climatology of the Time of Monsoon Wind Offset in the Western Arabian Sea

Forecasting the time of onset of monsoon wind in the western Arabian Sea, which is believed to precede the onset of rainfall along the west coast of India, is an important unsolved problem. Prior to measurements of the surface wind field by satellite, there was an absence of suitable surface wind observations. NASA scatterometer (NSCAT) surface wind vectors revealed that the time of the 1997 onset of 12 m/s southwest monsoon wind speeds in the western Arabian Sea preceded the onset of monsoon rainfall in Goa, India, by 3 - 4 days. Wind speed and direction data were necessary to establish a dynamical mechanism between times of onset of 12 m/s wind speed off Somalia and rainfall in Goa. Except for NSCAT, no satellite scatterometer wind product recorded adequately sampled 2-day 1deg x 1deg averaged wind vectors, which are the required space and time scales, to examine the wind-rain relationship in other years. However, the greater-than-95% steadiness of summer monsoon winds allows an opportunity to use satellite measurements of surface wind speed. The Special Sensor Microwave Imager (SSMI) recorded surface wind speed with adequate sampling to produce a 1-day, 1deg x 1deg data product during 1988 - 1998. SSMI data had been uniformly processed throughout the period. Times of onset of 12 m/s wind speed off Somalia determined with the SSMI data set were 21 May 1988, 24 May 1989, 17 May 1990, 28 May 1991, 8 June 1992, 28 May 1993, 30 May 1994, 7 June 1995, 29 May 1996, 12 June 1997, and 15 May 1998. Uncertainty of the 1992 and 1996 times of onset were increased because of the absence of SSMI data on 6 and 7 June 1992 and on 30 May 1996. Correlations of timing of monsoon wind onset with El Nino will be described. Variability of the time difference between times of onset of 12 m/s wind speed and Goa rainfall will be discussed. At the time of submission of the abstract, the Goa rainfall data have not arrived from the India Meteorological Department.

Halpern, David↗

NASA NTRS2020

First-Order Runtime Verification using BDDs

Runtime Verification (RV) expedites the analyses of execution traces for detecting system errors and for statistical and quality analysis. Having started modestly, with checking temporal properties that are based on propositional (yes/no) values, the current practice of RV often involves properties that are parametrized by the data observed in the input trace. The specifications are based on various formalisms, such as automata, temporal logics, rule systems, and stream processing. Checking execution traces that are data intensive against a specification that imposes strong dependencies between the data, poses a nontrivial challenges; in particular if runtime verification has to be performed online, while many events that carry data appear within small time proximities. Towards achieving this goal, it was recently suggested to represent relations over the observed data values, based on BDDs, where data elements are enumerated and then converted into bit vectors. This representation provided a very simple and natural extension of an RV algorithm from propositional to first-order LTL, but more importantly, was shown to contribute to the memory compactness and to the speed, as was demonstrated using a corresponding implementation. We extend here the capabilities of BDD-based RV with the ability to express timing constraints, where the monitored events include (integer) clock values. We show how to efficiently operate on BDDs that represent both relations on (enumerations of) values and time dependencies, as required by the addition of the time constraints. We demonstrate our algorithm with an efficient implementation and provide experimental results.

Peled, Doron↗

DOE OSTI2023

Coolant Pump Predictive Data Analytics from Signatures Generated by the Recursive Short Time Fast Fourier Transform

Although a nuclear reactor is a hostile environment for sensors and signal transmissions, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure installed at the Advanced Test Reactor (ATR) nozzle trench area records acoustic signals that can capture reactor operating states. The distinct states produce unique signatures that can be identified and tracked using data processing and data analytics. The infrastructure relies on acoustic transmission through ATR in-pile structural components, piping, and coolant that transmit acoustically modified signals generated by the coolant pumps. This paper will discuss results from using the Recursive Short Time Fast Fourier Transform (RSTFFT) technique used to process acoustic signals and provide signatures that are identified and monitored by analytics. The RSTFFT is applied to ATR data to understand the vibration levels and signatures for different operating regimes as displayed by the spectrogram. The combination of coolant pumps for normal and high-power operation generate unique signatures. These acoustic signatures are used to develop machine learning approaches to automatically classify operating regimes. Two machine-learning models, Support Vector Machines and Linear Discriminant Analysis, were developed to classify two event classes. Class 1 is a normal steady-state operation, and Class 2 is any event that is due to start up, shut down, or other actions. Both types of machine learning models had over a 96% prediction accuracy for the two classes. These results lay the foundation for predictive analytic frameworks that can be leveraged by ATR to optimize operations and maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Research in Theoretical Particle Physics: Neutrino Masses and The Origin of CP-Violation

The main goal of this project was to investigate the theories of neutrino masses at the low scale and the origin of CP-violation in physics beyond the Standard Model. The origin of neutrino masses is one of the most pressing issues in particle physics. In this proposal, we investigated the theories for neutrino masses based on local total lepton number. In these theories anomaly cancellation predicts the existence of extra fermions with lepton number, and one of them is a good dark matter (DM) candidate. The cosmological constraints on the DM relic density implies that the lepton number symmetry breaking scale must be below the multi-TeV scale. Therefore, one can hope to test the origin of neutrino masses in current or future experiments. We investigated in great detail the anomaly cancellation in these gauge theories, study the different mechanisms for neutrino masses, study the predictions for direct and indirect dark matter experiments. Since these theories predict new sources of CP violation, we investigated the predictions for the electric dipole moments (EDM). The Higgs decays and the different signatures at the Large Hadron Collider were investigated in great detail. Finally, we studied the possible baryogenesis mechanisms in these theories in agreement with the EDM, DM and collider constraints. The origin of CP violation in the Standard Model is unknown. In this proposal, we investigated the simplest mechanisms for spontaneous CP-violation to explain the CP-violation in the CKM matrix and the value of the QCD vacuum angle. We discussed the Nelson-Barr mechanism in gauge theories predicting vector-like quarks from anomaly cancellation such as theories for local baryon number. We discussed the Bento-Branco-Parada mechanism in gauge theories to explain the CP-Violation in the CKM matrix. We will investigate models with two Higgs doublets in the context of the minimal theory for quark-lepton unification. We will show the non-decoupling effects in the Higgs sector, the main constraints coming from flavour violating processes when the Yukawa couplings are related by the gauge symmetry in theories for quark-lepton unification. We will investigate the predictions for electric dipole moments in these theories. The possibility to have successful baryogenesis was investigated. Finally, we investigated the relation between CP-violation in the quark and leptonic sectors. The future results from these studies could help us to understand two main issues in physics beyond the Standard Model: The Origin of Neutrino Masses and CP-violation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1981

Magnetic field observations on DE-A and -B

Magnetic field observations are conducted on each of the DE-A and -B satellites by a triaxial fluxgate magnetometer. In the basic mode the instrumental resolution is + or - 1.5 nT; in addition, the DE-A magnetometer has two modes of higher resolution: + or - 0.25 nT and + or - 20 pT. The sampling rate is 16 vector samples per second in all modes. The experiment objectives include observations of field-aligned currents, magnetospheric equatorial currents, and ULF waves. These observations, taking full advantage of the specifically selected orbits of the two spacecraft and of the unique combination of instruments, are performed to achieve a better understanding of the electrodynamic coupling within the atmosphere-ionosphere-magnetosphere system and of wave-particle interactions which contribute to the coupling processes.

Farthing, W. H.↗