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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

NASA Centennial Challenge: Three Dimensional (3D) Printed Habitat, Phase 2

The NASA Centennial Challenges: 3D-Printed Habitat Challenge seeks to develop the fundamental technologies necessary to manufacture an off-world habitat using mission recycled materials and/or local indigenous materials. The vision is that autonomous habitat manufacturing machines will someday be deployed to the Moon or Mars to construct shelters for human habitation. NASA and Bradley University, are holding a new US$ 2.5 million competition to design and build a 3-D printed habitat for deep space exploration, including the agency's journey to Mars. The multi-phase 3-D Printed Habitat Challenge, part of NASA's Centennial Challenges program, is designed to advance the additive construction technology needed to create sustainable housing solutions for Earth and beyond. The first phase of the competition ran through Sept. 27, 2015. This phase, a design competition, called on participants to develop state-of-the-art architectural concepts that take advantage of the unique capabilities 3-D printing offers. The top 3 prizes with a prize purse of $40,000 were awarded at the 2015 World Maker Faire in New York. The second phase of the competition is called the Structural Member Competition and it is divided into three levels happening in the spring and summer of 2017. The Compression Test Competition (Level 1) focuses on the fabrication technologies needed to manufacture structural components from a combination of indigenous materials and recyclables, or indigenous materials alone. For Level 1, teams will develop 3D printable materials, build a 3D printing machine, and print two specimens: a truncated cone and a cylinder. The Level 2 Beam Member Competition is the second of three sub-competitions within the overall Structural Member Competition. For Level 2, teams will print a beam that will be tested. The Level 3 Head to Head Competition is the third of three sub-competitions within the overall Structural Member Competition. For Level 3, teams will develop 3D printable materials, use a 3D printing machine, and print three compression specimens of the elected material, three flexural specimens of the elected material, and one dome structure. Tests conducted on the specimens and the dome structure will determine Level 3 scores and awards. On Earth these same habitat manufacturing capabilities could be used to produce housing wherever affordable housing is needed and access to conventional building materials and skills is limited. Terrestrially, it is envisioned that local indigenous materials (dirt, clay, sand, etc.) could be combined with readily available recyclable materials and used to construct semi-permanent shelters against environmental elements for human habitation. The goal of the 3D-Printed Habitat Challenge is to foster the development of new technologies necessary to additively manufacture a habitat using local indigenous materials with, or without, recyclable materials. This paper will summarize the Level 2 results of this NASA Centennial Challenge competition and it will discuss related technology advancement.

3D printing↗
NASA NTRS2018

Self Diagnostic Accelerometer Field Programmable Gate Array (SDA FPGA)

A self-diagnostic accelerometer (SDA) field programmable gate array (FPGA) may be capable of real time or near-real time diagnostic processing to determine potential accelerometer issues during flight or other mission critical operational situations. The SDA FPGA may determine accelerometer structural health and an attachment condition using an electronics system that is smaller, more energy efficient, and more cost effective than previous diagnostic tools. Advantages of the system may include diagnosing sensors automatically, immediately, actively (i.e., confirming the fault), and consistently, without the influence of a human operator. Customizable SDA algorithms may be adjusted to the specific needs of the sensor/environment.

Tokars, Roger P.↗
NASA NTRS2018

Spatial Correlation Structures in SMAP Near-Surface Soil Moisture (How Spatially Correlated are the Temporal Variations of Soil Moisture at Different Locations? and Why Is This of Interest?)

Spatial correlation structures can describe the degree to which soil moisture at a specified location co-varies in time with that at other, remote locations. Using four years of warm season SMAP Level 2 near-surface soil moisture data, we compute these spatial correlation structures for points across North America. The character of these structures is seen to differ geographically; the structures found for the west-central US, for example, are significantly more spatially extensive. We then demonstrate how these structures can potentially be used to reconstruct soil moisture fields during the pre-SMAP era. In this exercise, we consider as "truth" the soil moistures produced in a long-term offline land surface model simulation (1980-2014) that utilizes precipitation forcing based on a high density of precipitation gauges. Then, for a given location within the continent, we construct an"estimated" soil moisture time series based solely on historical soil moisture information simulated at least 300 km distant from the location, using the SMAP-based spatial correlation structures to determine how to make best use of the remote information. The reconstructed soil moistures are found to have significant skill relative to the assumed truth, suggesting that the same approach, when applied in areas of low rain gauge density (i.e., in areas for which historically simulated soil moistures are necessarily inaccurate), could provide useful historical soil moisture estimates through the SMAP-guided extraction of relevant information from neighboring gauged regions.

Koster, Randal↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13662-DND

Nonintrusive spectral analysis of high enthalpy hypersonic flow, simulating atmospheric entry, was produced for passive and ablative heat shield materials. A calibrated fiber-optic coupled spectrometer was use to determine shock structure and prominent radiative chemical species.

Drew Hires↗
NASA NTRS2022

Interplanetary Mesoscale Observatory (InterMeso): A Mission to Untangle Dynamic Mesoscale Structures Throughout the Heliosphere

Mesoscale dynamics are a fundamental process in space physics, but fall within an observational gap of current and planned missions. Particularly in the solar wind, measurements at the mesoscales (100s RE to a few degrees heliographic longitude at 1 au) are crucial for understanding the connection between the corona and an observer anywhere within the heliosphere. Mesoscale dynamics may also be key to revealing the currently unresolved physics regulating particle acceleration and transport, magnetic field topology, and the causes of variability in the composition and acceleration of solar wind plasma. Studies using single-point observations do not allow for investigations into mesoscale solar wind dynamics and plasma variability, nor do they allow for the exploration of the sub-structuring of large-scale solar wind structures like coronal mass ejections (CMEs), co-rotating/stream interaction regions (CIR/SIRs), and the heliospheric plasma sheet. To address this fundamental gap in our knowledge of the heliosphere at these scales, the Interplanetary Mesoscale Observatory (InterMeso) concept employs a multi-point approach using four identical spacecraft in Earth-trailing orbits near 1 au. Varying drift speeds of the InterMeso spacecraft enable the mission to span a range of mesoscale separations in the solar wind, achieving significant and innovative science return. Simultaneous, longitudinally-separated measurements of structures co-rotating over the spacecraft also allow for disambiguation of spatiotemporal variability, tracking of the evolution of solar wind structures, and determination of how the transport of energetic particles is impacted by these variabilities.

solar wind↗
NASA NTRS2022

Interplanetary Mesoscale Observatory (InterMeso): A mission to untangle dynamic mesoscale structures throughout the heliosphere

Mesoscale dynamics are a fundamental process in space physics, but fall within an observational gap of current and planned missions. Particularly in the solar wind, measurements at the mesoscales (100s RE to a few degrees heliographic longitude at 1 au) are crucial for understanding the connection between the corona and an observer anywhere within the heliosphere. Mesoscale dynamics may also be key to revealing the currently unresolved physics regulating particle acceleration and transport, magnetic field topology, and the causes of variability in the composition and acceleration of solar wind plasma. Studies using single-point observations do not allow for investigations into mesoscale solar wind dynamics and plasma variability, nor do they allow for the exploration of the sub-structuring of large-scale solar wind structures like coronal mass ejections (CMEs), co-rotating/stream interaction regions (CIR/SIRs), and the heliospheric plasma sheet. To address this fundamental gap in our knowledge of the heliosphere at these scales, the Interplanetary Mesoscale Observatory (InterMeso) concept employs a multi-point approach using four identical spacecraft in Earth-trailing orbits near 1 au. Varying drift speeds of the InterMeso spacecraft enable the mission to span a range of mesoscale separations in the solar wind, achieving significant and innovative science return. Simultaneous, longitudinally-separated measurements of structures co-rotating over the spacecraft also allow for disambiguation of spatiotemporal variability, tracking of the evolution of solar wind structures, and determination of how the transport of energetic particles is impacted by these variabilities.

solar wind↗
DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗
DOE OSTI2025

Identifying the connections between grain growth and flux expulsion in low RRR niobium SRF cavities

The SRF community has shown that high temperature annealing can improve the flux expulsion of niobium cavities during cooldown. The required temperature will vary between cavities and different batches of material, typically around 800 C and up to 1000 C. However, for niobium with a low residual resistance ratio (RRR), even 1000 C is not enough to improve its poor flux expulsion. The purpose of this study is to observe the grain growth behavior of low RRR niobium coupons subjected to high temperature annealing to identify the mechanism for improving flux expulsion. We observe that low RRR material experiences less grain growth than high RRR when annealed at the same temperature. We search for the limitations to grain growth in low RRR material and develop a diagnostic based on grain structure to determine the appropriate recipe for good flux expulsion. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, K. [Chicago U.] (ORCID:0000000325613308)↗
DOE OSTI2020

Magnetic structure of Fe 16 N 2 determined by polarized neutron diffraction on thin-film samples

Strain-free Fe 16 N 2 thin films were obtained on MgO (001) single-crystal substrates with Cr seed layers. Additionally, x-ray diffraction and transmission electron microscopy confirmed that the film is textured in all three spatial directions with crystallographic orientation determined by epitaxial constraints from the substrate. Average grain size was estimated to be in the range of tens of nanometers. Ten pieces of 40-nm-thick Fe 16 N 2 thin-film samples were stacked together for half-polarized neutron diffraction study at room temperature. A total of six reflections were usable, from which the magnetic structure of Fe 16 N 2 was determined and compared to existing models. Contrary to most electronic structure calculations, the present results suggest that the magnetic moment of Fe atoms at the 8h site is large and larger than that of the 4d site. Our results support the giant magnetization of Fe 16 N 2 .

36 MATERIALS SCIENCE↗
NASA NTRS1976

The autocorrelation structure of Tausworthe pseudorandom number generators

An algorithm for determining the autocorrelation structure of a new sequence generated from an original sequence by proper decimation (a shift with each q-th term of the original sequence used) is presented, once autocorrelations for any repeating number sequence are known. The autocorrelation structure of the Tausworthe random number generator (RNG), based on proper decimation by q, is accepted as a RNG structure in which a proper decimation generates a long interval over which autocorrelations are small for all shifts. It is shown that if L bits of an N-bit Tausworthe RNG are L-bit binary numbers, L + 1 levels of correlation will exist, and L levels of correlation will each occur twice per RNG cycle length.

Neuman, F.↗
NASA NTRS2003

A Rational Approach to Determine Minimum Strength Thresholds in Novel Structural Materials

Design of safe and survivable structures requires the availability of guaranteed minimum strength thresholds for structural materials to enable a meaningful comparison of strength requirement and available strength. This paper develops a procedure for determining such a threshold with a desired degree of confidence, for structural materials with none or minimal industrial experience. The problem arose in attempting to use a new, highly weight-efficient structural load tendon material to achieve a lightweight super-pressure balloon. The developed procedure applies to lineal (one dimensional) structural elements. One important aspect of the formulation is that it extrapolates to expected probability distributions for long length specimen samples from some hypothesized probability distribution that has been obtained from a shorter length specimen sample. The use of the developed procedure is illustrated using both real and simulated data.

Schur, Willi W.↗
NASA NTRS1982

Solution Accounts for Structural Damping

New analytical technique determines dynamic response of damped structures dominated by internal structural damping mechanisms. Though structural damping is often negligible compared with damping due to air friction and friction in joints, structural damping can be of major importance in structures having heavy damping treatments or in outer-space structures. Finite-element model includes nonlinear, nonviscous internal damping.

Roussos, L. A.↗
DOE OSTI2025

Conformational flexibility is a critical factor in designing broad-spectrum human norovirus protease inhibitors

Human norovirus (HuNoV) is a leading cause of gastroenteritis worldwide and is associated with significant morbidity, mortality, and economic impact. There are currently no licensed antiviral drugs for the treatment of HuNoV-associated gastroenteritis. The HuNoV protease plays a critical role in the initiation of virus replication by cleaving the polyprotein. Thus, it is an ideal target for developing antiviral small-molecule inhibitors. While rupintrivir, a potent small-molecule inhibitor of several picornavirus proteases, effectively inhibits GI.1 protease, it is an order of magnitude less effective against GII protease. Other GI.1 protease inhibitors also tend to be less effective against GII proteases. To understand the structural basis for the potency difference, we determined the crystal structures of proteases of GI.1, pandemic GII.4 (Houston and Sydney), and GII.3 in complex with rupintrivir. These structures show that the open substrate pocket in GI protease binds rupintrivir without requiring significant conformational changes, whereas, in GII proteases, the closed pocket flexibly extends, reorienting arginine-112 in the BII-CII loop to accommodate rupintrivir. Structures of R112A protease mutants with rupintrivir, coupled with enzymatic and inhibition studies, suggest R112 is involved in displacing both substrate and ligands from the active site, implying a role in the release of cleaved products during polyprotein processing. Thus, the primary determinant for differential inhibitor potency between the GI and GII proteases is the increased flexibility in the BII-CII loop of the GII proteases caused by the H-G mutation in this loop. Therefore, the inherent flexibility of the BII-CII loop in GII proteases is a critical factor to consider when developing broad-spectrum inhibitors for HuNoV proteases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Structural and biochemical analysis of the metallo-β-lactamase L1 from emerging pathogen Stenotrophomonas maltophilia revealed the subtle but distinct di-metal scaffold for catalytic activity

Emergence of Enterobacteriaceae harboring metallo-beta-lactamases (MBL) has raised global threats due to their broad antibiotic resistance profiles and the lack of effective inhibitors against them. We have been studied one of the emerging environmental MBL, the L1 from Stenotrophomonas maltophilia K279a . We determined several crystal structures of L1 complexes with three different classes of beta-lactam antibiotics (penicillin G, moxalactam, meropenem, and imipenem), with the inhibitor captopril and different metal ions (Zn +2 , Cd +2 , and Cu +2 ). All hydrolyzed antibiotics and the inhibitor were found binding to two Zn +2 ions mainly through the opened lactam ring and some hydrophobic interactions with the binding pocket atoms. Without a metal ion, the active site is very similarly maintained as that of the native form with two Zn +2 ions, however, the protein does not bind the substrate moxalactam. When two Zn +2 ions were replaced with other metal ions, the same di-metal scaffold was maintained and the added moxalactam was found hydrolyzed in the active site. Differential scanning fluorimetry and isothermal titration calorimetry were used to study thermodynamic properties of L1 MBL compared with New Deli Metallo-beta-lactamase-1 (NDM-1). Both enzymes are significantly stabilized by Zn +2 and other divalent metals but showed different dependency. These studies also suggest that moxalactam and its hydrolyzed form may bind and dissociate with different kinetic modes with or without Zn +2 for each of L1 and NDM-1. Our analysis implicates metal ions, in forming a distinct di-metal scaffold, which is central to the enzyme stability, promiscuous substrate binding and versatile catalytic activity. Statement: The L1 metallo-beta-lactamase from an environmental multidrug-resistant opportunistic pathogen Stenotrophomonas maltophilia K279a has been studied by determining 3D structures of L1 enzyme in the complexes with several beta-lactam antibiotics and different divalent metals and characterizing its biochemical and ligand binding properties. We found that the two-metal center in the active site is critical in the enzymatic process including antibiotics recognition and binding, which explains the enzyme's activity toward diverse antibiotic substrates. This study provides the critical information for understanding the ligand recognition and for advanced drug development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Atomistic Characterization of Gramicidin Channel Formation

We investigated gramicidin A (gA) subunit dimerization in lipid bilayers using microsecond-long replica-exchange umbrella sampling simulations, millisecond-long unbiased molecular dynamics simulations, and machine learning. Our simulations led to a dimer structure that is indistinguishable from the experimentally determined gA channel structures, with the two gA subunits joined by six hydrogen bonds (6HB). The simulations also uncovered two additional dimer structures, with different gA–gA stacking orientations that were stabilized by four or two hydrogen bonds (4HB or 2HB). When examining the temporal evolution of the dimerization, we found that two bilayer-inserted gA subunits can form the 6HB dimer directly, with no discernible intermediate states, as well as through paths that involve the 2HB and 4HB dimers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗
NASA NTRS1975

The effects of body geometry on the structure in the near wake zone of bodies in a flowing plasma

Plasma wind tunnel experiments were performed to investigate the effects of body geometry and size on the structure of the ion flux in the near wake zone behind the body in a streaming plasma. The results are applicable to the development of wake and sheath experiments for Spacelab. The experiments indicate that the body's dimension in the flow direction does not alter the gross features of the near wake structure, but primarily determines the relative amplitude of the peak structure and the downstream distance at which it occurs for a given body potential relative to the plasma.

Oran, W. A.↗