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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

The Nearby Evolved Stars Survey – I. JCMT/SCUBA-2 Submillimeter Detection of the Detached Shell of U Antliae

We present the highest resolution single-dish submillimetre observations of the detached shell source U Antliae to date. The observations were obtained at 450 and 850μm with SCUBA-2 instrument on the James Clerk Maxwell Telescope as part of the Nearby Evolved Stars Survey. The emission at 850μm peaks at 40 arcsec with hints of a second peak seen at ∼20 arcsec. The emission can be traced out to a radius of 56 arcsec at a 3σ level. The outer peak observed at 850μm aligns well with the peak observed at Herschel/PACS wavelengths. With the help of spectral energy distribution fitting and radiative transfer calculations of multiple-shell models for the circumstellar envelope, we explore the various shell structures and the variation of grain sizes along the in the circumstellar envelope. We determine a total shell dust mass of (2.0 ± 0.3) × 10−5 M⊙ and established that the thermal pulse that gave rise to the detached shell occurred 3500 ± 500 yr ago.

Dharmawardena, Thavisha E.↗
NASA NTRS2018

Interstellar Ices and Radiation-Induced Oxidations of Alcohols

Infrared spectra of ices containing alcohols that are known or potential interstellar molecules are examined before and after irradiation with 1 MeV protons at ~20 K. The low-temperature oxidation (hydrogen loss) of six alcohols is followed, and conclusions are drawn based on the results. The formation of reaction products is discussed in terms of the literature on the radiation chemistry of alcohols and a systematic variation in their structures. The results from these new laboratory measurements are then applied to a recent study of propargyl alcohol. Connections are drawn between known interstellar molecules, and several new reaction products in interstellar ices are predicted.

astrochemistry – infrared: ISM – ISM: molecules – ↗
NASA NTRS2021

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 °C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 °C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 °C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.d-2090s.

Scenario Model Intercomparison Project (ScenarioMI↗
NASA NTRSDate not supplied

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^8 determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

J Wayne Mullinax↗
NASA NTRSDate not supplied

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗
NASA NTRSDate not supplied

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗
DOE OSTI2020

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein function, many functional prediction tasks use only protein sequence. In this work, we isolate protein structure to make functional annotations for proteins in the Protein Data Bank in order to study the expressiveness of different structure-based prediction schemes. We present PersGNN - an end-to-end trainable deep learning model that combines graph representation learning with topological data analysis to capture a complex set of both local and global structural features. While variations of these techniques have been successfully applied to proteins before, we demonstrate that our hybridized approach, PersGNN, outperforms either method on its own as well as a baseline neural network that learns from the same information. PersGNN achieves a 9.3% boost in area under the precision recall curve (AUPR) compared to the best individual model, as well as high F1 scores across different gene ontology categories, indicating the transferability of this approach.

Swenson, Nicolas↗
DOE OSTI2024

Microstructure and Mechanical Properties of Ni-Based Superalloy Nimonic 105 with Varying Carbon Content

High carbon levels have been found to improve the fabricability of high-strength cast and wrought Ni-based superalloys, enabling the development of superior cast/wrought materials. However, carbon also strongly influences the microstructure and mechanical properties of the alloys. Nimonic 105 variants with three different carbon concentrations were manufactured. A bimodal grain size was found in the intermediate carbon content variant, while the high (low) carbon resulted in fine (coarse) grains thereby significantly affecting creep performance. The variations in grain structure were attributed to the primary carbides. An intermediate carbon level showed the best combination of strength and ductility in tension at high-temperature but little improvement in, or even inferior, creep performance. Discussion of the results will establish an understanding of the influence of carbon on the microstructure and mechanical properties of high strength cast and wrought superalloys, providing insights into obtaining high-quality alloys for future high-temperature applications.

Fang, Xiaotian↗
DOE OSTI2024

Effects of Size on Characteristics of Electroslag Remelted (ESR) HAYNES®282® alloy ingots

The effects of varying ingot diameters on the characteristics of round ESR ingots of 282 alloy are evaluated through a combined experimental and modeling study. Ingots of four different diameters --100 mm, 150 mm, 200 mm and 500 mm, were sectioned and analyzed using metallography to assess spatial variations in dendritic structure (primary / secondary dendrite arm spacings – PDAS/SDAS) across these ingots. Melt parameters of the processes were input into the simulation code, MeltFlow-ESR™ to theoretically predict PDAS/SDAS in the ingots. The values for PDAS/SDAS predicted by the simulations are compared with those measured by experiments and quantitative differences in these values are discussed in the context of the capability and limitations of the model and measurement methods. Both the predicted and measured values show that the PDAS/SDAS values increase with increasing ingot size. In addition, the relation with other ingot characteristics, such as local solidification time as well as the likelihood for freckle formation are discussed. The implication of these results for down-stream ingot processing and for ingot soundness are discussed.

Krishnamurthy, Ramanathan↗
DOE OSTI2025

Resilient Distributed Frequency Regulation of Renewable Generators under Communication Interruptions

Modern power systems (MPSs) face significant challenges due to the high penetration of renewable energy sources (RESs) and new types of loads such as electric vehicles (EVs). Traditional load frequency control (LFC) methods struggle with the intermittent, stochastic nature of RESs, the near-zero inertia of power-electronics-based generators, and the mobility of controllable loads and battery systems. This paper introduces a novel resilient distributed frequency regulation method to address these issues. The proposed method employs a state space model to represent the dynamic behavior of participating power sources while accounting for stochastic switching processes to model structural and parameter variations caused by disruptions such as generator connection/disconnection, communication interruptions, and physical faults. By integrating these dynamic and stochastic components, the method treats power grids as a comprehensive stochastic hybrid system. Our method enhances conventional frequency control by incorporating local stability control, neighborhood control decoupling, and coordination feedback. Theoretical analyses establish the stability, convergence, and resilience of the proposed method, and its effectiveness is validated through case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2002

A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments

Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Non-NASA Center↗
NASA NTRS2003

Small-Scale Interstellar Structure Toward the Open Cluster CHI Persei-Fuse II

The purpose of this study was to measure the physical conditions of gas along sight lines toward 6 stars in the core Chi Persei open cluster. These sight lines traverse gas in both the Orion and Perseus spiral arms of the Galaxy, at distances of 500 and 2000 pc, respectively. The stars have angular separations ranging from 45 to 280 arcsec; 60 arcsec corresponds to linear distances of 0.15 and 0.6 pc in the two arms. Thus, abundance variations in these observations would constitute evidence for small-scale variations in the properties of the interstellar medium. Ground-based Na I observations at high resolution (approx. 15 km/sec) toward 172 stars (including the 6 in this study) in the double open cluster h and Chi Persei have revealed complex spatial variation. These variations are especially evident in the gas at velocities of -40 and -55 km/sec, corresponding to the Perseus spiral arm. 21 cm observations of HI emission using the Low Resolution DRAO Survey, with a 12-arcmin beam, also show variations. Averaging the Na I apparent optical depth profiles of neighboring sight lines in order to mimic such a beam size reduces the variation, as compared to the individual Na I measurements, but still show variations larger than seen in the 21 cm profiles. Na I is not the dominant ionization state of Na in the interstellar medium. Thus, it is possible that the variations seen really trace physical structures in the interstellar medium, or they may simply result from variations in the radiation field seen by the gas, or be due to some other environmental circumstance. To distinguish among these possibilities in the present study we obtained FUSE spectra toward the 6 targets in order to measure the molecular hydrogen absorption profiles along these sight lines. The higher J states of H2 are populated by the ambient W radiation field, and thus can provide insight into the environment affecting the gas. If both the high and low J states reveal absorption line profiles with variations similar to that observed in Na I, this would indicate that the variations are due to real structures in the interstellar medium. On the other hand, if the only the high J profiles mimicked the Na I profiles, then the variations may be attributable to environmental effects. We found that the H2 profiles showed considerable variation over the 6 sight lines, and that the profiles, despite having somewhat lower velocity resolution, resemble the Na I profiles. Thus, it appears that the gas really does exhibit variations in physical structures along these sight lines. Useful follow-up work would be to obtain higher signal-to-noise FUSE observations of H2, since the present data are of only moderate quality, and to obtain data on additional targets in this double cluster, in order to map out in more detail the extent and magnitude of the small-scale variations.

Sonneborn, George↗
DOE OSTI2021

The variation in self-organized anode plasma pattern structure with solution electrolyte type in 1 atm DC glow discharge

Abstract Plasma self-organization on anode surfaces in 1 atm DC glow discharges remains poorly understood. This effort aims to elucidate the nature of self-organization through the experimental study of resulting patterns on liquid anode surfaces with 13 different electrolytes and thus improves our understanding of the underlying physical processes that give rise to self-organization by investigating electrolyte sensitivity. Self-organization pattern formation and behavior were studied as a function of discharge current, solution ionic strength, and their chemical property evaluation. The response of the patterns to variation in these parameters was measured using an imaging camera and optical emission spectroscopy. Observed pattern characteristic length scales for all of the electrolytes were ranged from 2 to 13 mm and typically increased with current over the investigated range of 20–80 mA. Complex self-organized pattern structures not reported to date were also observed. The parameters associated with pattern formation and morphology complexity are discussed and summarized.

Physics↗
DOE OSTI2021

Atomic Force Microscopy to Characterize Antimicrobial Peptide-Induced Defects in Model Supported Lipid Bilayers

Antimicrobial peptides (AMPs) interact with bacterial cell membranes through a variety of mechanisms, causing changes extending from nanopore formation to microscale membrane lysis, eventually leading to cell death. Several AMPs also disrupt mammalian cell membranes, despite their significantly different lipid composition and such collateral hemolytic damage hinders the potential therapeutic applicability of the AMP as an anti-microbial. Elucidating the mechanisms underlying the AMP–membrane interactions is challenging due to the variations in the chemical and structural features of the AMPs, the complex compositional variations of cell membranes and the inadequacy of any single experimental technique to comprehensively probe them. (1) Background: Atomic Force Microscopy (AFM) imaging can be used in combination with other techniques to help understand how AMPs alter the orientation and structural organization of the molecules within cell membranes exposed to AMPs. The structure, size, net charge, hydrophobicity and amphipathicity of the AMPs affect how they interact with cell membranes of differing lipid compositions. (2) Methods: Our study examined two different types of AMPs, a 20-amino acid, neutral, α-helical (amphipathic) peptide, alamethicin, and a 13-amino acid, non-α-helical cationic peptide, indolicidin (which intramolecularly folds, creating a hydrophobic core), for their interactions with supported lipid bilayers (SLBs). Robust SLB model membranes on quartz supports, incorporating predominantly anionic lipids representative of bacterial cells, are currently not available and remain to be developed. Therefore, the SLBs of zwitterionic egg phosphatidylcholine (PC), which represents the composition of a mammalian cell membrane, was utilized as the model membrane. This also allows for a comparison with the results obtained from the Quartz Crystal Microbalance with Dissipation (QCM-D) experiments conducted for these peptides interacting with the same zwitterionic SLBs. Further, in the case of alamethicin, because of its neutrality, the lipid charge may be less relevant for understanding its membrane interactions. (3) Results: Using AFM imaging and roughness analysis, we found that alamethicin produced large, unstable defects in the membrane at 5 µM concentrations, and completely removed the bilayer at 10 µM. Indolicidin produced smaller holes in the bilayer at 5 and 10 µM, although they were able to fill in over time. The root-mean-square (RMS) roughness values for the images showed that the surface roughness caused by visible defects peaked after peptide injection and gradually decreased over time. (4) Conclusions: AFM is useful for helping to uncover the dynamic interactions between different AMPs and cell membranes, which can facilitate the selection and design of more efficient AMPs for use in therapeutics and antimicrobial applications.

Swana, Kathleen W.↗
NASA NTRS1988

Advanced probabilistic methods for quantifying the effects of various uncertainties in structural response

The effects of actual variations, also called uncertainties, in geometry and material properties on the structural response of a space shuttle main engine turbopump blade are evaluated. A normal distribution was assumed to represent the uncertainties statistically. Uncertainties were assumed to be totally random, partially correlated, and fully correlated. The magnitude of these uncertainties were represented in terms of mean and variance. Blade responses, recorded in terms of displacements, natural frequencies, and maximum stress, was evaluated and plotted in the form of probabilistic distributions under combined uncertainties. These distributions provide an estimate of the range of magnitudes of the response and probability of occurrence of a given response. Most importantly, these distributions provide the information needed to estimate quantitatively the risk in a structural design.

Nagpal, Vinod K.↗
NASA NTRS1985

The combined effects of stress and moisture on the structural integrity of composites

A variational approach is used to model the moisture content and distribution profiles which cause swelling in polymers and composites which are used as aircraft structural components. The moisture intrusion stems from humidity, which makes the problem one of diffusion of mass from the environment into a semiinfinite plate with a given diffusion coefficient and thickness. Lagrangian, ordinary differential equations are defined for the mass diffusion, including driving force, mass potential and volume dissipation expressions. Account is taken of the effects of stress on diffusivity, including the dilatational stress caused by inhomogeneous swelling of the material. It is noted that material near the top and bottom of a part undergoes the most swelling, and the evolution of moisture diffusion in the materials is traced. Finally, experimental data are used to define differential equations for predicting the final moisture distribution within the material.

Hiel, C.↗
DOE OSTI2020

A method for mapping submicron-scale crystallographic order/disorder applied to human tooth enamel

Tooth enamel, the outermost layer of human teeth, is a complex, hierarchically structured biocomposite. The details of this structure are important in multiple human health contexts, from understanding the progression of dental caries (tooth decay) to understanding the process of amelogenesis and related developmental defects. Enamel is composed primarily of long, nanoscale crystallites of hydroxyapatite that are bundled by the thousands to form micron-scale rods. Studies with transmission electron microscopy show the relationships between small groups of crystallites and X-ray diffraction characterize averages over many rods, but the direct measurement of variations in local crystallographic structure across and between enamel rods has been missing. Here, we describe a synchrotron X-ray-based experimental approach and a novel analysis method developed to address this gap in knowledge. A ~500-nm-wide beam of monochromatic X-rays in conjunction with a sample section only 1 μm in thickness enables 2D diffraction patterns to be collected from small well-separated volumes within the enamel microstructure but still probes enough crystallites (~300 per pattern) to extract population-level statistics on crystallographic features like lattice parameter, crystallite size, and orientation distributions. Furthermore, the development of a quantitative metric to characterize relative order and disorder based on the azimuthal autocorrelation of diffracted intensity enables these crystallographic measurements to be correlated with their location within the enamel microstructure (e.g., between rod and interrod regions). These methods represent a step forward in the characterization of human enamel and will elucidate the variation of the crystallographic structure across and between enamel rods for the first time.

crystallographic order/disorder↗
DOE OSTI2020

Four direct measurements of the fine-structure constant 13 billion years ago

Observations of the redshift z = 7.085 quasar J1120+0641 are used to search for variations of the fine structure constant, a, over the redshift range 5:5 to 7:1. Observations at z = 7:1 probe the physics of the universe at only 0.8 billion years old. These are the most distant direct measurements of a to date and the first measurements using a near-IR spectrograph. A new AI analysis method is employed. Four measurements from the x - shooter spectrograph on the Very Large Telescope (VLT) constrain changes in a relative to the terrestrial value (α 0 ). The weighted mean electromagnetic force in this location in the universe deviates from the terrestrial value by Δα/α = (α z - α 0 )/α 0 = (-2:18 ± 7:27) × 10 -5 , consistent with no temporal change. Combining these measurements with existing data, we find a spatial variation is preferred over a no-variation model at the 3:9σ level.

79 ASTRONOMY AND ASTROPHYSICS↗