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NASA NTRS1974

Aircraft observations of Venus' near-infrared reflection spectrum - Implications for cloud composition

A comparison of aircraft-based measurement data on Venus' near-infrared (1.2- to 4.1-micron) reflection spectrum with computer generated spectra of a number of cloud candidates shows a 75-% or more concentrated water solution of sulfuric acid to give the only acceptable match to the profile of Venus' strong 3-micron absorption feature. However, the measurement data obtained also show a modest decline in reflectivity from 2.3-micron to 1.2-micron wavelength, which is inconsistent with the flat spectrum of sulfuric acid in this spectral region. It is hypothesized that this decline is due to impurities in the sulfuric acid droplets.

Pollack, J. B.↗

NASA NTRS2000

Suppression of Cavity-Driven Flow Separation in a Simulated Mixed Compression Inlet

A test facility designed to simulate a bifurcated subsonic diffuser operating within a mixed compression inlet is described. The subsonic diffuser in this facility modeled a bypass cavity feature often used in mixed compression inlets for engine flow matching and normal shock control. A bypass cavity-driven flow separation was seen to occur in the subsonic diffuser without applied flow control. Flow control in the form of vortex generators and/or a partitioned bypass cavity cover plate were used to eliminate this flow separation, providing a 2% increase in area-averaged total pressure recovery, and a 70% reduction in circumferential distortion intensity.

Wendt, Bruce J.↗

NASA NTRS2001

Pricing the Computing Resources: Reading Between the Lines and Beyond

Distributed computing systems have the potential to increase the usefulness of existing facilities for computation without adding anything physical, but that is realized only when necessary administrative features are in place. In a distributed environment, the best match is sought between a computing job to be run and a computer to run the job (global scheduling), which is a function that has not been required by conventional systems. Viewing the computers as 'suppliers' and the users as 'consumers' of computing services, markets for computing services/resources have been examined as one of the most promising mechanisms for global scheduling. We first establish why economics can contribute to scheduling. We further define the criterion for a scheme to qualify as an application of economics. Many studies to date have claimed to have applied economics to scheduling. If their scheduling mechanisms do not utilize economics, contrary to their claims, their favorable results do not contribute to the assertion that markets provide the best framework for global scheduling. We examine the well-known scheduling schemes, which concern pricing and markets, using our criterion of what application of economics is. Our conclusion is that none of the schemes examined makes full use of economics.

Nakai, Junko↗

NASA NTRS2010

Using Whispering-Gallery-Mode Resonators for Refractometry

A method of determining the refractive and absorptive properties of optically transparent materials involves a combination of theoretical and experimental analysis of electromagnetic responses of whispering-gallery-mode (WGM) resonator disks made of those materials. The method was conceived especially for use in studying transparent photorefractive materials, for which purpose this method affords unprecedented levels of sensitivity and accuracy. The method is expected to be particularly useful for measuring temporally varying refractive and absorptive properties of photorefractive materials at infrared wavelengths. Still more particularly, the method is expected to be useful for measuring drifts in these properties that are so slow that, heretofore, the properties were assumed to be constant. The basic idea of the method is to attempt to infer values of the photorefractive properties of a material by seeking to match (1) theoretical predictions of the spectral responses (or selected features thereof) of a WGM of known dimensions made of the material with (2) the actual spectral responses (or selected features thereof). Spectral features that are useful for this purpose include resonance frequencies, free spectral ranges (differences between resonance frequencies of adjacently numbered modes), and resonance quality factors (Q values). The method has been demonstrated in several experiments, one of which was performed on a WGM resonator made from a disk of LiNbO3 doped with 5 percent of MgO. The free spectral range of the resonator was approximately equal to 3.42 GHz at wavelengths in the vicinity of 780 nm, the smallest full width at half maximum of a mode was approximately equal to 50 MHz, and the thickness of the resonator in the area of mode localization was 30 microns. In the experiment, laser power of 9 mW was coupled into the resonator with an efficiency of 75 percent, and the laser was scanned over a frequency band 9 GHz wide at a nominal wavelength of approximately equal to 780 nm. Resonance frequencies were measured as functions of time during several hours of exposure to the laser light. The results of these measurements, plotted in the figure, show a pronounced collective frequency drift of the resonator modes. The size of the drift has been estimated to correspond to a change of 8.5 x 10(exp -5) in the effective ordinary index of refraction of the resonator material.

Matsko, Andrey↗

NASA NTRS2020

WISEA J041451.67-585456.7 and WISEA J181006.18-101000.5: The First Extreme T-type Subdwarfs?

We present the discoveries of WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5, two low-temperature (1200–1400 K), high proper motion T-type subdwarfs. Both objects were discovered via their high proper motion (>0farcs5 yr(exp -1)); WISEA J181006.18−101000.5 as part of the NEOWISE proper motion survey and WISEA J041451.67−585456.7 as part of the citizen science project Backyard Worlds; Planet 9. We have confirmed both as brown dwarfs with follow-up near-infrared spectroscopy. Their spectra and near-infrared colors are unique among known brown dwarfs, with some colors consistent with L-type brown dwarfs and other colors resembling those of the latest-type T dwarfs. While no forward model consistently reproduces the features seen in their near-infrared spectra, the closest matches suggest very low metallicities ([Fe/H] ≼ −1), making these objects likely the first examples of extreme subdwarfs of the T spectral class (esdT). WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5 are found to be part of a small population of objects that occupy the “substellar transition zone,” and have the lowest masses and effective temperatures of all objects in this group.

T subdwarfs↗

DOE OSTI2023

Double Higgs production at NNLO interfaced to parton showers in GENEVA

In this work, we study the production of Higgs boson pairs at next-to-next-to-leading order in QCD matched to parton showers, using the Geneva framework and working in the heavy-top-limit approximation. This includes the resummation of large logarithms of the zero-jettiness T 0 up to the next-to-next-to-next-to-leading-log accuracy. This process features an extremely large momentum transfer, which makes its study particularly relevant for matching schemes such as that employed in Geneva, where the resummation of a variable different from that used in the ordering of the parton shower is used. To further study this effect, we extend the original shower interface designed for Pythia8 to include other parton showers, such as Dire and Sherpa.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Mapathons versus automated feature extraction: a comparative analysis for strengthening immunization microplanning

Background: Social instability and logistical factors like the displacement of vulnerable populations, the difficulty of accessing these populations, and the lack of geographic information for hard-to-reach areas continue to serve as barriers to global essential immunizations (EI). Microplanning, a population-based, healthcare intervention planning method has begun to leverage geographic information system (GIS) technology and geospatial methods to improve the remote identification and mapping of vulnerable populations to ensure inclusion in outreach and immunization services, when feasible. We compare two methods of accomplishing a remote inventory of building locations to assess their accuracy and similarity to currently employed microplan line-lists in the study area. Methods: The outputs of a crowd-sourced digitization effort, or mapathon, were compared to those of a machine-learning algorithm for digitization, referred to as automatic feature extraction (AFE). The following accuracy assessments were employed to determine the performance of each feature generation method: (1) an agreement analysis of the two methods assessed the occurrence of matches across the two outputs, where agreements were labeled as “befriended” and disagreements as “lonely”; (2) true and false positive percentages of each method were calculated in comparison to satellite imagery; (3) counts of features generated from both the mapathon and AFE were statistically compared to the number of features listed in the microplan line-list for the study area; and (4) population estimates for both feature generation method were determined for every structure identified assuming a total of three households per compound, with each household averaging two adults and 5 children. Results: The mapathon and AFE outputs detected 92,713 and 53,150 features, respectively. A higher proportion (30%) of AFE features were befriended compared with befriended mapathon points (28%). The AFE had a higher true positive rate (90.5%) of identifying structures than the mapathon (84.5%). The difference in the average number of features identified per area between the microplan and mapathon points was larger (t = 3.56) than the microplan and AFE (t = -2.09) (alpha = 0.05). Conclusions: Our findings indicate AFE outputs had higher agreement (i.e., befriended), slightly higher likelihood of correctly identifying a structure, and were more similar to the local microplan line-lists than the mapathon outputs. These findings suggest AFE may be more accurate for identifying structures in high-resolution satellite imagery than mapathons. However, they both had their advantages and the ideal method would utilize both methods in tandem.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1985

Laboratory identification of the emission features near 3.5 microns in the pre-main sequence star HD 97048

This paper presents the results of a laboratory study of formaldehyde (H2CO) suspended in low temperature molecular matrices with compositions similar to what may be found in the 'dirty ice' mantles of grains. It is shown that the emission features near 3.5 microns in the pre-main-sequence star HD 97048 can be matched by a mixture of chemical complexes of H2CO with surrounding molecules in the grain. Furthermore, a discussion is presented of various possible excitation mechanisms for this emission. The conclusion is, that for the features near 3.5 microns in HD 97048, UV pumped IR fluorescence is the most likely mechanism.

Van Der Zwet, G. P.↗

DOE OSTI2025

You Only Look Once v5 and Multi-Template Matching for Small-Crack Defect Detection on Metal Surfaces

This paper compares the performance of Deep Learning (DL) and multi-template matching (MTM) models for detecting small defects. DL models extract distinguishing features of objects but require a large dataset of images. In contrast, alternative computer vision techniques like MTM need a relatively small dataset. The lack of large datasets for small metal-surface defects has inhibited the adoption of automation in small-defect detection in remanufacturing settings. This motivated this preliminary study to compare template-based approaches, like MTM, with feature-based approaches, such as DL models, for small-defect detection on an initial laboratory and remanufacturing industry dataset. This study used You Only Look Once v5 (YOLOv5) as the DL model and compared its performance against the MTM model for small-crack detection. The findings of our preliminary investigation are as follows: (i) YOLOv5 demonstrated higher performance than MTM in detecting small cracks; (ii) an extra-large variant of YOLOv5 outperformed a small-size variant; (iii) the size and object variety of the data are crucial in achieving robust pre-trained weights for use in transfer learning; and (iv) enhanced image resolution contributes to precise object detection.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗

NASA NTRS1997

The 2140 cm-1 (4.673 microns) solid CO band: the case for interstellar O2 and N2 and the photochemistry of nonpolar interstellar ice analogs

The infrared spectra of CO frozen in nonpolar ices containing N2, CO2, O2, and H2O and the UV photochemistry of these interstellar/precometary ice analogs are reported. The spectra are used to test the hypothesis that the narrow 2140 cm-1 (4.673 microns) interstellar absorption feature attributed to solid CO might be produced by CO frozen in ices containing nonpolar species such as N2 and O2. It is shown that mixed molecular ices containing CO, N2, O2, and CO2 provide a good match to the interstellar band at all temperatures between 12 and 30 K both before and after photolysis. The optical constants (real and imaginary parts of the index of refraction) in the region of the solid CO feature are reported for several of these ices. The N2 and O2 absorptions at 2328 cm-1 (4.296 microns) and 1549 cm-1 (6.456 microns), respectively, are also shown. The best matches between the narrow interstellar band and the feature in the laboratory spectra of nonpolar ices are for samples which contain comparable amounts of N2, O2, CO2, and CO. Co-adding the CO band from an N2:O2:CO2:CO = 1:5:1/2:1 ice with that of an H2O:CO = 20:1 ice provides an excellent fit across the entire interstellar CO feature. The four-component, nonpolar ice accounts for the narrow 2140 cm-1 portion of the feature which is associated with quiescent regions of dense molecular clouds. Using this mixture, and applying the most recent cosmic abundance values, we derive that between 15% and 70% of the available interstellar N is in the form of frozen N2 along several lines of sight toward background stars. This is reduced to a range of 1%-30% for embedded objects with lines of sight more dominated by warmer grains. The cosmic abundance of O tied up in frozen O2 lies in the 10%-45% range toward background sources, and it is between 1% and 20% toward embedded objects. The amount of oxygen tied up in CO and CO2 frozen in nonpolar ices can be as much as 2%-10% toward background sources and on the order of 0.2%-5% for embedded objects. Similarly 3%-13% of the carbon is tied up in CO and CO2 frozen in nonpolar ices toward field stars, and 0.2%-6% toward embedded objects. These numbers imply that most of the N is in N2, and a significant fraction of the available O is in O2 in the most quiescent regions of dense clouds. Ultraviolet photolysis of these ices produces a variety of photoproducts including CO2, N2O, O3, CO3, HCO, H2CO, and possibly NO and NO2. XCN is not produced in these experiments, placing important constraints on the origin of the enigmatic interstellar XCN feature. N2O and CO3 have not been previously considered as interstellar ice components.

NASA Discipline Exobiology↗

NASA NTRS2009

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the standard algorithm. When the utmost accuracy must be achieved, the modified algorithm extracts atoms more conservatively but still exhibits computational gains over classical MPD. The MPD++ algorithm was demonstrated using an over-complete dictionary on real life data. Computational times were reduced by factors of 1.9 and 44 for the emphases of accuracy and performance, respectively. The modified algorithm extracted similar amounts of energy compared to classical MPD. The degree of the improvement in computational time depends on the complexity of the data, the initialization parameters, and the breadth of the dictionary. The results of the research confirm that the three modifications successfully improved the scalability and computational efficiency of the MPD algorithm. Correlation Thresholding decreased the time complexity by reducing the dictionary size. Multiple Atom Extraction also reduced the time complexity by decreasing the number of iterations required for a stopping criterion to be reached. The Course-Fine Grids technique enabled complicated atoms with numerous variable parameters to be effectively represented in the dictionary. Due to the nature of the three proposed modifications, they are capable of being stacked and have cumulative effects on the reduction of the time complexity.

Christensen, Daniel↗

DOE OSTI2024

Comparison of hardening and microstructures of ferritic/martensitic steels irradiated with fast neutrons and dual ions

Ferritic/martensitic steels T91 and HT9 were irradiated with neutrons (BOR-60 reactor) and dual ions (9 MeV Fe 3+ and 3.42 MeV energy degraded He 2+ ) from 369 to 520 °C and damage levels of 16.6 to 72 dpa to quantify the possibility of using ion irradiation to simulate neutron irradiation in terms of microstructures and mechanical properties. Nanoindentation testing was performed to obtain the bulk equivalent hardness of the dual-ion irradiated samples. For the neutron irradiated samples, both nanoindentation and Vickers hardness testing were conducted. Transmission Electron Microscopy (TEM) characterizations of the cavities, dislocation loops and precipitates were conducted to account for the strengthening contribution of each microstructure element. The good agreement between the microstructure-predicted (dispersed barrier hardening) and measured strength of the irradiated specimens demonstrated the accuracy of the strengthening model and the nanoindentation tests. Furthermore, the comparison of mechanical property and microstructure changes in ion and neutron irradiated structural materials indicated that ion irradiation replicated many neutron irradiation features. However, a single 70 °C temperature shift is insufficient to match all complex microstructures of neutron vs. ion irradiation over the irradiation temperature range of 369–520 °C.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Machine learning-based microstructure prediction during laser sintering of alumina

Abstract Predicting material’s microstructure under new processing conditions is essential in advanced manufacturing and materials science. This is because the material’s microstructure hugely influences the material’s properties. We demonstrate an elegant machine learning algorithm that faithfully predicts the microstructure under new conditions, without the need of knowing the governing laws. We name this algorithm, RCWGAN-GP, which is regression-based conditional generative adversarial networks with Wasserstein loss function and gradient penalty. This algorithm was trained with experimental SEM micrographs from laser-sintered alumina under various laser powers. The RCWGAN-GP realistically regenerates the SEM micrographs under the trained laser powers. Impressively, it also faithfully predicts the alumina’s microstructure under unexplored laser powers. The predicted microstructure features, including the morphology of the sintered particles and the pores, match the experimental SEM micrographs very well. We further quantitatively examined the prediction accuracy of the RCWGAN-GP. We trained the algorithm with computer-created micrograph datasets of secondary-phase growth governed by the well-known Johnson–Mehl–Avrami (JMA) equation. The RCWGAN-GP accurately regenerates the micrographs at the trained time series, in terms of the grains’ shapes, sizes, and spatial distributions. More importantly, the predicted secondary phase fraction accurately follows the JMA curve.

08 HYDROGEN↗

DOE OSTI2021

QLiG: Query Like a Graph For Subgraph Matching

A graph is a natural and flexible modeling approach to represent entities and relationships between them in real-world. A Knowledge Graphs (KG) is a specialized graph with formal and structured representation of facts, relationships, annotated with semantic descriptions. Subgraph matching is one of the fundamental graph problems to identify relationships, interactions and activities of interest within a large graph. A query specification is a collection of abstract components, operations, and constraints to express a pattern. The specification can be implemented in different ways based on underlying data model. Various graph query specifications have been developed over the years and have led to the development of different open-sourced and vendor-specific query languages. Such specification are modeled as an extension of relational algebra used to develop relational query languages such as SQL. Such relational concepts do not inherently support graph queries. There is a need to represent graph queries in terms on graph-based components to expedite query construction by non-database experts. We present a graph-based query approach QLiG (pronounced cleeg), to perform subgraph matching in Labeled Property Graph. We present the query specifications, salient features, and a use case to show functional examples.

Purohit, Sumit↗

NASA NTRS1991

Field-aligned current associated with a distorted two-cell convection pattern during northward interplanetary magnetic field

The influence of the ionospheric conductance on the field-aligned current associated with a distorted two-cell convection pattern during northward IMF was investigated using the Heppner-Maynard (1987) convection model and the Utah State University conductivity model described by Rasmussen and Schunk (1987). Results show that the variation of the ionospheric conductivity distribution can significantly affect the features of the field-aligned current for northward IMF, where matching or mismatching between the conductance gradient and the convection electric field plays a key role. It was found that the increase of the field-aligned current in the polar cap observed during summer is mainly due to the increasing contribution from the Pedersen current, and that the increase of the field-aligned current in both the oval region and the evening-midnight sector during the active aurora period is mainly due to the increasing contribution from the Hall current.

Zhu, L.↗

NASA NTRS1994

Stereo imaging based particle velocimeter

Three dimensional coordinates of an object are determined from it's two dimensional images for a class of points on the object. Two dimensional images are first filtered by a Laplacian of Gaussian (LOG) filter in order to detect a set of feature points on the object. The feature points on the left and the right images are then matched using a Hopfield type optimization network. The performance index of the Hopfield network contains both local and global properties of the images. Parallel computing in stereo matching can be achieved by the proposed methodology.

Batur, Celal↗

NASA NTRS2004

The Collisions of Chondrules Behind Shock Waves

One of the reasons that the mechanism(s) responsible for the formation of chondrules has remained so elusive is that each proposed mechanism must be able to explain a large number of features observed in chondrules. Most models of chondrule formation focus on matching the expected thermal histories of chondrules: rapid heating followed by cooling during crystallization at rates between approx. 10-1000 K/hr [1], and references therein]. Thus far, only models for large shock waves in the solar nebula have quantitatively shown that the thermal evolution of millimeter-sized particles in the nebula can match these inferred thermal histories [2-4]. While this is a positive step for the shock wave model, further testing is needed to see if other properties of chondrules can be explained in the context of this model. One area of interest is understanding the collisional evolution of chondrules after they encounter a shock wave. These collisions could lead to sticking, destruction, or bouncing. Here we focus on understanding what conditions are needed for these different outcomes to occur and try to reconcile the seemingly contradictory conclusions reached by studies of compound chondrule formation and chondrule destruction by collisions behind a shock wave.

Ciesla, F. J.↗