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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
DOE OSTI2021

Impact of Solution Chemistry on Growth and Structural Features of Mo-Substituted Spinel Iron Oxides

The effect of crystallizing solution chemistry on the chemistry of subsequently as-grown materials was investigated for Mo-substituted iron oxides prepared by thermally activated co-precipitation. In the presence of Mo ions, we find that varying the oxidation state of the iron precursor from Fe(II) to Fe(III) causes a progressive loss of atomic long-range order with the stabilization of 2-4 nm particles for the sample prepared with Fe(III). The oxidation state of the Fe precursor also affects the distribution of Fe and Mo cations within the spinel structure. Increasing the Fe precursor oxidation state gives decreased Fe-ion occupation and increased Mo-ion occupation of tetrahedral sites, as revealed by the extended X-ray absorption fine structure. The stabilization of Mo within tetrahedral sites appears to be unexpected, considering the octahedral preferred coordination number of Mo(VI). The analysis of the atomic structure of the sample prepared with Fe(III) indicates a local ordering of vacancies and that the occupation of tetrahedral sites by Mo induces a contraction of the interatomic distances within the polyhedra as compared to Fe atoms. Moreover, the occupancy of Mo into the thermodynamic site preference of a Mo dopant in Fe 2 O 3 assessed by density functional theory calculations points to a stronger preference for Mo substitution at octahedral sites. Hence, we suggest that the synthetized compound is thermodynamically metastable, that is, kinetically trapped. Such a state is suggested to be a consequence of the tetrahedral site occupation by Mo ions. The population of these sites, known to be reactive sites enabling particle growth, is concomitant with the stabilization of very small particles. Furthermore, we confirmed our hypothesis by using a blank experiment without Mo ions, further supporting the impact of tetrahedral Mo ions on the growth of iron oxide nanoparticles. Our findings provide new insights into the relationships between the Fechemistry of the crystallizing solution and the structural features of the as-grown Mo-substituted Fe-oxide materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Microanalysis of Hypervelocity Impact Residues of Possible Interstellar Origin

The NASA Stardust spacecraft deployed two collector trays, one dedicated to the collection of dust from Comet Wild 2, and the other for the capture of interstellar dust (ISD). The samples were returned successfully to Earth in 2006, and now provide an unprecedented opportunity for laboratory-based microanalysis of materials from the outer solar system and beyond. Results from the cometary sample studies have demonstrated that Wild 2 contains much more refractory condensate material and much less pristine extra-solar material than expected, which further indicates that there was significant transport of inner solar system materials to the Kuiper Belt in the early solar system [1]. The analysis of the interstellar samples is still in the preliminary examination (PE) phase, due to the level of difficulty in the definitive identification of the ISD features, the overall low abundance, and its irreplaceable nature, which necessitates minimally invasive measurements [2]. We present here coordinated microanalysis of the impact features on the Al foils, which have led to the identification of four impacts that are possibly attributable to interstellar dust. Results from the study of four ISD candidates captured in aerogel are presented elsewhere [2].

Stroud, Rhonda M.↗
DOE OSTI2025

Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters

Abstract Obtaining microscopic structure-property relationships for grain boundaries is challenging due to their complex atomic structures. Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. Key steps for property prediction common to grain boundaries and other variable-sized atom clustered structures include: (1) describing the atomic structure as a feature matrix, (2) transforming the variable-sized feature matrix to a fixed length common to all structures, and (3) applying a machine learning algorithm to predict properties from the transformed matrices. We examine how these steps and different combinations of engineered features impact the accuracy of grain boundary energy predictions using a database of over 7000 grain boundaries. Additionally, we assess how different engineered features support interpretability, offering insights into the physics of the structure-property relationships.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Variable fragmentation mass spectrometry using chemi-ionization

A description is given of experiments which provide a verification of three features of Penning ionization mass spectrometry. One of these features is related to the ability to simplify a molecular fragmentation pattern and to intensify the molecular ion peak. Another feature is concerned with the ability to identify uniquely geometric isomers which are indistinguishable using high-energy electron impact methods. The third feature involves the ability to identify components in a mixture, which cannot be discerned using electron impact or chemical ionization methods alone. The investigation shows that Penning ionization is an efficient soft ionization technique which can be used to simplify mass spectra of pure compounds as well as mixtures.

Laudenslager, J. B.↗
NASA NTRS1992

Impact cratering record of Fennoscandia

A compilation of circular topographic, morphological, or geophysical structures in Fennoscandia and adjacent areas reveals 62 craterform structures of which 15 appear to be of extraterrestrial origin due to meteorite impact. The majority of the structures are probable and possible impact craters for which there is not yet sufficient proof for impact origin. Four of the proven impact craters contain large volumes of impact melt and many other features of intense shock metamorphism. The age of recognized impact craters vary from prehistoric to late Precambrian. We review the Fennoscandian impact cratering record giving examples of geophysical signatures of impact craters.

Pesonen, L. J.↗
NASA NTRS1992

A model for the formation of the extended paraboloidal halos around some impact craters on Venus

Many parabolic-shaped extended impact crater-related features have been found in Magellan synthetic aperture radar and emissivity data covering much of the surface of Venus. They are oriented east-west with the apex to the east and the impact crater located just west of the apex. A model for the formation of the parabolic features is developed based on the injection of small particles into the upper atmosphere at the time of impact, and their subsequent transport to the west by the east-west zonal winds. Fallout times from 50 km in the Venus atmosphere for particles of this size are about two hours, allowing westerly drifts of several hundred kilometers for zonal winds of 50 to 100 m s(exp -1).

Newman, W. I.↗
NASA NTRS2013

Sampling and Analysis of Impact Crater Residues Found on the Wide Field Planetary Camera-2 Radiator

After nearly 16 years in low Earth orbit (LEO), the Wide Field Planetary Camera-2 (WFPC2) was recovered from the Hubble Space Telescope (HST) in May 2009, during the 12 day shuttle mission designated STS-125. The WFPC-2 radiator had been struck by approximately 700 impactors producing crater features 300 microns and larger in size. Following optical inspection in 2009, agreement was reached for joint NASA-ESA study of crater residues, in 2011. Over 480 impact features were extracted at NASA Johnson Space Center's (JSC) Space Exposed Hardware clean-room and curation facility during 2012, and were shared between NASA and ESA. We describe analyses conducted using scanning electron microscopy (SEM) - energy dispersive X-ray spectrometry (EDX): by NASA at JSC's Astromaterials Research and Exploration Science (ARES) Division; and for ESA at the Natural History Museum (NHM), with Ion beam analysis (IBA) using a scanned proton microbeam at the University of Surrey Ion Beam Centre (IBC).

Kearsley, A. T.↗
NASA NTRS1995

Secondary ion mass spectrometry (SIMS) analysis of hypervelocity microparticle impact sites on LDEF surfaces

Two dimensional elemental ion maps have been recorded for hundreds of microparticle impact sites and contamination features on LDEF surfaces. Since the majority of the analyzed surfaces were metal-oxide-silicon (MOS) impact detectors from the Interplanetary Dust Experiment, a series of 'standard' and 'blank' analyses of these surfaces are included. Hypervelocity impacts of forsterite olivine microparticles on activated flight sensors served as standards while stylus and pulsed laser simulated 'impacts' served as analytical blanks. Results showed that despite serious contamination issues, impactor residues can be identified in greater than 1/3 of the impact sites. While aluminum oxide particles could not be detected on aluminum surfaces, they were detected on germanium surfaces from row 12. Remnants of manmade debris impactors consisting of paint chips and bits of metal were identified on surfaces from LDEF Rows 3 (west or trailing side), 6 (south), 9 (ram or leading side), 12 (north) and the space end. Higher than expected ratios of manmade microparticle impacts to total microparticle impacts were found on the space end and the trailing side. These results were consistent with time-tagged and time-segregated microparticle impact data from the IDE and other LDEF experiments. A myriad of contamination interferences were identified and their effects on impactor debris identification mitigated during the course of this study. These interferences include pre-, post and inflight deposited surface contaminants as well as indigenous heterogeneous material contaminants. Non-flight contaminations traced to human origins, including spittle and skin oils, contributed significant levels of alkali-rich carbonaceous interferences. A ubiquitous layer of in-flight deposited silicaceous contamination varied in thickness with location on LDEF, even on a micro scale. In-flight deposited (low velocity) contaminants include urine droplets and bits of metal film from eroded thermal blankets.

Simon, C. G.↗
NASA NTRS1976

Secondary impact craters of lunar basins

Numerous lunar features are examined and identified as being secondary to basins, that is, as having been formed by secondary impact of ejecta from basins. Most of the terra features previously attributed to volcanism and tectonism and many attributed previously to primary impact must be attributed to basin-secondary impact. Secondary craters of the Imbrium Basin cover a large part of the south-central near side. Imbrium secondaries are more numerous than primaries in the size ranges 3 or 4 to 10 km on the near side, and may be more numerous at diameters of 10-25 km. Preliminary stratigraphic dating results based on superposition relations among basin secondaries suggest that the Crisium and south Serenitatis basins are younger than Nectaris and Humboldtianum.

Wilhelms, D. E.↗
DOE OSTI2024

“Understanding Robustness Lottery”: A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches

Deep learning approaches have provided state-of-the-art performance in many applications by relying on large and overparameterized neural networks. However, such networks are very brittle and are difficult to deploy on resource-limited platforms. Model pruning, i.e., reducing the size of the network, is a widely adopted strategy that can lead to a more robust and compact model. Many heuristics exist for model pruning, but our understanding of the pruning process remains limited due to the black-box nature of a neural network model. Empirical studies show that some heuristics improve performance whereas others can make models more brittle. Here, this work aims to shed light on how different pruning methods alter the network’s internal feature representation and the corresponding impact on model performance. To facilitate a comprehensive comparison and characterization of the high-dimensional model feature space, we introduce a visual geometric analysis of feature representations. We evaluated a set of critical geometric concepts decomposed from the commonly adopted classification loss and used them to design a visualization system to compare and highlight the impact of pruning on model performance and feature representation. The proposed tool provides an environment for an in-depth comparison of pruning methods and a comprehensive understanding of how the model responds to common data corruption. By leveraging the proposed visualization, machine learning researchers can reveal the similarities between pruning methods and redundancy in robustness evaluation benchmarks, obtain geometric insights about the differences between pruned models that achieve superior robustness performance, and identify samples that are robust or fragile to model pruning and common data corruption.

Li, Zhimin [Univ. of Utah, Salt Lake City, UT (Uni↗
DOE OSTI2024

Robustness of topological persistence in knowledge distillation for wearable sensor data

Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Local Power Impact Experiment Design for a New Fuel Type for use in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. Reactor physics safety evaluations currently use Monte Carlo for the 21st Century (MC21), a continuous-energy Monte Carlo radiation transport code [3]. Existing MC21 models of the ATR and ATRC cores have a validation basis for use in neutronics analyses with HEU fuel. The models are used to support safety analyses that include comparisons to the safety requirements for the reactors. However, the use of the LOWE element in the ATR and ATRC is not currently covered by the current model validation basis. To deploy the new fuel type, extensive computational reactor physics support is necessary to support the use of LOWE in the ATR and ATRC. Therefore, LOWE requires a rigorous validation basis, aligned with that of HEU fuel, that takes advantage of the existing software tools and processes currently used for the ATR and ATRC. The experiment to validate of the MC21 models for determining power, the Power Impact Validation Experiment, will consist of two flux runs in the ATRC, one with fully HEU loading and one with a single LOWE element. Both flux runs will be instrumented with 20 sets of azimuthal fission wires and 3 sets of axial fission wires, as shown in Figure 4. Standard flux run methodology will be used [4]. Power Impact Validation Experiment data will be compared against MC21 calculated data, both for absolute fission rate accuracy and to determine the relative change in fission rates between the two runs. The results of the Power Impact Validation Experiment and subsequent evaluations will provide the validation basis for MC21 for use with LOWE elements. Key features of the Power Impact Validation Experiment include: (1) Two flux runs to allow for LOWE perturbed measurements to be compared to already validated measurements taken from a full core of HEU fuel, (2) Optimization of instrumentation to balance analytical needs with practical considerations (e.g., limited time window to count beta particles from fission products), and (3) Standard ATRC core loading, including both driver positions and flux traps, to minimize cost while remaining representative of typical ATR core loading.

42 ENGINEERING↗
DOE OSTI2021

Impacts of common faults on an air conditioner with a microtube condenser and analysis of fault characteristic features

Split system air conditioners are widely used to cool residential buildings, because of their low cost and simplicity. However, their efficiency is impacted by installation faults, which include: improper refrigerant charge (undercharge or overcharge), improper evaporator airflow, liquid line restrictions (LL), and the presence of non-condensable gas (NC) in the refrigerant. No known previously published research has studied the effect of these four faults on a system equipped with a microtube condenser, which has smaller tube size than a traditional condenser and therefore holds less refrigerant charge, but has a different configuration than a microchannel. Furthermore, very few have studied the impacts of LL and NC. Herein this paper describes laboratory fault tests of a microtube-equipped system, compares the fault impacts with those of a traditional system, and considers the characteristic fault features. The tested system uses R-410A refrigerant and has a scroll compressor, a fixed orifice expansion device, and two fin-tube heat exchangers. The tests were carried out under steady operation with a range of fault intensities and operating conditions. The microtube system’s performance degradation from faults is similar to systems with traditional heat exchangers, despite the reduced capacity to hold refrigerant charge.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1991

Magellan - Initial analysis of Venus surface modification

Images of the Venus surface provided by the Magellan mission make it possible to see the fine-scale features diagnostic of weathering, erosion, and deposition. These include ejecta deposits extending up to 1000 km to the west of several impact craters, windblown deposits, features containing both obstacles and a source of particulate material, and evidence for degradation by atmosphere-surface interactions and mass movements. Initial Magellan observations pertaining to the nature, rate, and history of surficial processes are analyzed. Emphasis is placed on radar imaging, but results from radiometry and altimetry observations are also discussed.

Arvidson, R. E.↗
NASA NTRS1996

High-Resolution Studies of Extreme-Ultraviolet Emission from CO by Electron Impact

We report a high-resolution study [0.0036 nm full width at half maximum (FWHM) of electron-impact-induced emission spectra of CO 1t 30, 75 and 100 eV electron-impact energies. The spectral features were acquired in optically thin conditions, and represent the highest resolution single-scattering emission spectrum of CO induced by electron impact yet available.

high-resolution↗
NASA NTRS2006

Postshock Annealing and Postannealing Shock in Equilibrated Ordinary Chondrites: Implications for the Thermal and Shock Histories of Chondritic Asteroids

In addition to shock effects in olivine, plagioclase, orthopyroxene and Ca-pyroxene, petrographic shock indicators in equilibrated ordinary chondrites (OC) include chromite veinlets, chromite-plagioclase assemblages, polycrystalline troilite, metallic Cu, irregularly shaped troilite grains within metallic Fe-Ni, rapidly solidified metal-sulfide intergrowths, martensite and various types of plessite, metal-sulfide veins, large metal and/or sulfide nodules, silicate melt veins, silicate darkening, low-Ca clinopyroxene, silicate melt pockets, and large regions of silicate melt. The presence of some of these indicators in every petrologic type-4 to -6 ordinary chondrite (OC) demonstrates that collisional events caused all equilibrated OC to reach shock stages S3-S6. Those type-4 to -6 OC that are classified as shock-stage S1 (on the basis of sharp optical extinction in olivine) underwent postshock annealing due to burial beneath materials heated by the impact event. Those type-4 to -6 OC that are classified S2 (on the basis of undulose extinction and lack of planar fractures in olivine) were shocked to stage S3-S6, annealed to stage S1 and then shocked again to stage S2. Some OC were probably shocked to stage 253 after annealing. It seems likely that many OC experienced multiple episodes of shock and annealing. Because 40Ar-39Ar chronological data indicate that MIL 99301 (LL6, Sl) was annealed approximately 4.26 Ga ago, presumably as a consequence of a major impact, it seems reasonable to suggest that other equilibrated S1 and S2 OC (which contain relict shock features) were also annealed by impacts. Because some type-6 S1 OC (e.g., Guarena, Kernouve, Portales Valley, all of which contain relict shock features) were annealed 4.44-4.45 Ga ago (during a period when impacts were prevalent and most OC were thermally metamorphosed), it follows that impact-induced annealing could have contributed significantly to OC thermal metamorphism.

Rubin, Alan E.↗
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↗