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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Folded Resonant Horns for Power Ultrasonic Applications

Folded horns have been conceived as alternatives to straight horns used as resonators and strain amplifiers in power ultrasonic systems. Such systems are used for cleaning, welding, soldering, cutting, and drilling in a variety of industries. In addition, several previous NASA Tech Briefs articles have described instrumented drilling, coring, and burrowing machines that utilize combinations of sonic and ultrasonic vibrational actuation. The main advantage of a folded horn, relative to a straight horn of the same resonance frequency, is that the folded horn can be made shorter (that is, its greatest linear dimension measured from the outside can be made smaller). Alternatively, for a given length, the resonance frequency can be reduced. Hence, the folded-horn concept affords an additional degree of design freedom for reducing the length of an ultrasonic power system that includes a horn.

Sherrit, Stewart↗
DOE OSTI2020

Simulation Analysis of Geometry and Material Effects for Dropkinson Bar

The reported research is motivated by the need to address a key issue affecting the Dropkinson bar apparatus. This unresolved issue is the interference of the stress wave reflected from the bar-beam boundary with the measurement of the stress-strain response of a material tested in the apparatus. The purpose of the wave beam that is currently connected to the bar is to dissipate the stress wave, but the portion of the wave reflected from the bar-beam boundary is still significant. First, we focused on understanding which parameters affect the reflected wave's arrival time at a strain gauge. Specifically, we used finite-element numerical simulations with the Sierra/SM module to study the effects of various bar-beam connection fixities, alternative wave beam materials, and alternative geometries of the Dropkinson bar system based on a monolithic design. The conclusion of this study is that a partial reflection always occurs at the bar-beam boundary (or, for a monolithic design, at a point where the bar geometry changes). Therefore, given a fixed total length of the bar, it is impossible to increase the reflected wave's arrival time by any significant amount. After reaching this conclusion, we focused instead on trying to minimize the energy of the reflected stress wave circulating up and down through the bar over a relatively long period of time (10 ms). Once again, we used numerical simulations with the Sierra/SM module to investigate the effects of various bar-beam connection fixities, alternative wave beam materials, and parameters of an asymmetric monolithic design of the bar-and-beam system. This study demonstrated that various parameters can significantly affect the energy of the wave reflections, with the difference between best and worst configurations being about one order of magnitude in terms of energy. Based on the obtained results, we conclude with concrete takeaways for Dropkinson bar users and propose potential directions for future research and optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Predicting departure from nucleate boiling with advanced data- and physics-driven approaches

The subcooled and low-quality saturated flow boiling critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) is one of the major limiting factors in the design and operation of pressurized water reactors (PWRs). Due to lack of agreement on its physical mechanisms, development of an accurate DNB-type CHF model has been elusive. The various steady-state (SS) predictive tools that have been proposed can be grouped into two categories: (1) data-driven methods—namely best-fit empirical correlations and look-up tables that result in relatively good agreement with specific experimental datasets but often fail to extend beyond their ranges of validity, and (2) the physics-based mechanistic models that rely on reasonable yet limited understanding of the underlying physics and apply constitutive relations to close the conservation equations. On one hand, with recent advances in computational capabilities and optimization techniques, machine learning (ML)-based methods constitute an alternative and a more advanced, data-driven approach. With enough data, they can be particularly useful in engineering fields where the physical phenomena are complex and challenging to model. On the other hand, a state-of-the-art physics-driven approach would not only provide more accurate prediction of SS CHF, but it would also help better understand and model transient applications. The data-driven regression models use deep feed-forward neural networks (NNs) and random forests to cross-validate with 1,865 CHF test cases, covering a wide range of flow conditions and channel geometries. The best-estimate ML-based predictors compare favorably with the widely used look-up table for annulus and plate, and sensitivity analysis has confirmed their effectiveness. The key advantage of ML-based methods is their online extensibility of applicability domain. The proposed physics-driven approach combines key assumptions and parameters in the relatively well-accepted theories of liquid sublayer dryout and near-wall bubble crowding. A more realistic understanding of local mechanisms has been modeled. The new model has been optimized and validated against 1,439 tube data, and it shows considerably improved performance when compared to a recent mechanistic model, demonstrating unbiased close agreement with measurements over a wide range of operating conditions. Future work will extend the improved physics-driven model to non-tube geometry applications and will couple the model with ML via a hybrid approach. The mechanistic SS work will also serve to improve understanding and to model transient CHF scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Homogenizing atomic dynamics by fractional differential equations

In this paper, we propose two ways to construct fractional differential equations (FDE) for approximating atomic chain dynamics. Taking harmonic chain as an example, we add a power function of fractional order to Taylor expansion of the dispersion relation, and determine the parameters by matching two selected wave numbers. This approximate function leads to an FDE after considering both directions for wave propagation. As an alternative, we consider the symbol of the force term, and approximate it by a similar function. It also induces an FDE. Both approaches produce excellent agreement with the harmonic chain dynamics. The accuracy may be improved by optimizing the selected wave numbers, or starting with higher order Taylor expansions. When resolved in the lattice constant, the resulting FDE's faithfully reproduce the lattice dynamics. When resolved in a coarse grid instead, they systematically generate homogenized algorithms. Numerical tests are performed to verify the proposed approaches. Moreover, FDE's are also constructed for diatomic chain and anharmonic lattice, to illustrate the generality of the proposed approaches. - Highlights: • Match the dispersion relation of linear chain by power function of fractional order, added on low order Taylor expansion. • Design FDE by approximating dispersion relation, or the symbol for the force term. • Solve the FDE by algorithm of spectral accuracy. • Obtain faithful and systematical homogenization when resolved at coarser grid. • Applies to general lattices: complex, nonlinear and multidimensional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1988

Two alternate proofs of Wang's lune formula for sparse distributed memory and an integral approximation

In Kanerva's Sparse Distributed Memory, writing to and reading from the memory are done in relation to spheres in an n-dimensional binary vector space. Thus it is important to know how many points are in the intersection of two spheres in this space. Two proofs are given of Wang's formula for spheres of unequal radii, and an integral approximation for the intersection in this case.

Jaeckel, Louis A.↗
DOE OSTI2018

A Gcn5-Related N -Acetyltransferase (GNAT) Capable of Acetylating Polymyxin B and Colistin Antibiotics in Vitro

Deeper exploration of uncharacterized Gcn5-related N-acetyltransferases has the potential to expand our knowledge of the types of molecules that can be acylated by this important superfamily of enzymes and may offer new opportunities for biotechnological applications. While determining native or biologically relevant in vivo functions of uncharacterized proteins is ideal, their alternative or promiscuous in vitro capabilities provide insight into key active site interactions. Additionally, this knowledge can be exploited to selectively modify complex molecules and reduce byproducts when synthetic routes become challenging. During our exploration of uncharacterized Gcn5-related N-acetyltransferases from Pseudomonas aeruginosa, we identified such an example. We found that the PA3944 enzyme acetylates both polymyxin B and colistin on a single diaminobutyric acid residue closest to the macrocyclic ring of the antimicrobial peptide and determined the PA3944 crystal structure. This finding is important for several reasons. (1) To the best of our knowledge, this is the first report of enzymatic acylation of polymyxins and thus reveals a new type of substrate that this enzyme family can use. (2) The enzymatic acetylation offers a controlled method for antibiotic modification compared to classical promiscuous chemical methods. (3) The site of acetylation would reduce the overall positive charge of the molecule, which is important for reducing nephrotoxic effects and may be a salvage strategy for this important class of antibiotics. Furthermore, while the physiological substrate for this enzyme remains unknown, our structural and functional characterization of PA3944 offers insight into its unique noncanonical substrate specificity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Instability of the layered orthorhombic post-perovskite phase of SrTiO 3 and other candidate orthorhombic phases under pressure

Although the tetragonal antiferro-electrically distorted (AFD) phase with space group I4/mcm is well known for SrTiO 3 to occur below 105 K, there are also some hints in the literature of an orthorhombic phase, either at the lower temperature or at high pressure. A previously proposed orthorhombic layered structure of SrTiO 3 , known as the post-perovskite or CaIrO 3 structure with space group Cmcm is shown to have significantly higher energy than the cubic or tetragonal phase and to have its minimum volume at larger volume than cubic perovskite. The Cmcm structure is thus ruled out. We also study an alternative Pnma phase obtained by two octahedral rotations about different axes. This phase is discovered to have slightly lower energy than the I4/mcm phase in spite of the fact that its parent, in-phase tilted P4/mbm phase is not found to occur. Our calculated enthalpies of formation show that the I4/mcm phase occurs at slightly higher volume than the cubic phase and has a negative transition pressure relative to the cubic phase, which suggests that it does not correspond to the high-pressure tetragonal phase. The enthalpy of the Pnma phase is almost indistinguishable from the I4/mcm phase. Alternative ferro-electric tetragonal and orthorhombic structures previously suggested in literature are discussed.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗
NASA NTRS2014

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Quattrochi, Dale A.↗
DOE OSTI2022

Transcriptome and metabolome integration in sugarcane through culm development

Abstract Sugarcane (Saccharum sp.) is a tropical and subtropical C4 plant with a high photosynthetic and carbon assimilation efficiency that stores sucrose. Culm biomass is also composed of bagasse fibre, a by‐product of the sugarcane industry. This high‐yielding grass, high in sucrose and lignocellulosic biomass, is considered an optimal feedstock as an alternative to fossil fuels and to produce a broad range of high‐value biomaterials. The ideal sugarcane production system would optimise the relative production of sugar and these new products. Multi‐omics correlation analysis was used to generate a global view of the essential metabolic pathways identifying critical genes involved in carbon partitioning during different stages of development. This research employed an unprecedented metabolic and transcriptomic dataset of 360 samples from a selection of 1440 culms of 24 genotypes at five different development stages. Chemical composition and metabolome analysis showed an increase through the culm development of lignin, sucrose, carbon, and amino acids such as aspartic acid, serine, alanine, methionine, threonine 3‐cyano‐L‐alanine, and citric acid. Transcriptome analysis revealed functionalities such as transcription, nucleotide transport and metabolism, and the biosynthesis of amino acids that are highly activated during the immature stage and highly down‐regulated during the most mature age.

Perlo, Virginie↗
DOE OSTI2023

Mechanical behavior analysis using small-size graphite disc compression testing with digital image correlation methods

The ASTM International Standard Test Method for Tensile Stress-Strain of Carbon and Graphite (ASTM C749) requires dog-bone shaped specimens. Unfortunately, specimen sizes required in ASTM C749 are much too large for irradiation within a test reactor and are incompatible with irradiation capsule volumes, molten salt degradation facilities, or oxidation apparatus. The ASTM International Standard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite (ASTM D8289) was developed as an alternative that provides a means for testing tensile properties using smaller specimens when geometric constraints are present. However, the important stress–strain relation throughout the test loading history that could be recorded using ASTM C749 is lost by using ASTM D8289 because of the difficulties involved with using traditional strain gauges or extensometers on such a small specimen. In this work, a digital image correlation (DIC) method, which uses a full-field noncontact surface displacement measurement technique, was applied along with the ASTM D8289 splitting tensile test on eight small samples of graphite grade Mersen 2114 to track their deformation during compressive loading. Initial results showed that the DIC technique can measure the surface displacement/strain on these small (Ø6 × 3 mm) graphite specimens with high accuracy and good repeatability, indicating that the DIC technique, combined with the small-disc splitting tensile test in ASTM D8289, can capture the strain evolution in the test. In conclusion, further comparison of measured strains with analytical and numerical simulation results provides additional understanding of the mechanical behaviour of this nuclear graphite material in complex stress states.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of reacting gas flowrates and hydration on the carbonation of anion exchange membrane fuel cells in the presence of CO 2

Anion exchange membrane fuel cells (AEMFCs) have been widely touted as a low-cost alternative to existing proton exchange membrane fuel cells. However, one of the limitations of this technology has been the severe performance penalty related to the introduction of CO 2 to the cell – typically in the air cathode feed. Introduction of CO 2 into AEMFCs results in cell carbonation, which imparts thermodynamic, kinetic and Ohmic overpotentials that can add up to hundreds of millivolts. Therefore, it is important to find strategies and operational protocols for AEMFCs that minimize these overpotentials. In this paper, we reserach the impacts of the anode and cathode flowrate, as well as the cell hydration level, on the extent of cell carbonation and cell polarization. Key findings include: (1) decreasing the cathode flowrate generally decreases the total CO 2 -related voltage loss while changing the anode flowrate has a minimal effect; (2) increasing cell hydration helps to mitigate the performance loss in the presence of CO 2 ; and (3) operational combinations are found that significantly reduce the CO 2 penalty compared to the present literature.

25 ENERGY STORAGE↗
DOE OSTI2014

Photoluminescence emission at room temperature in zinc oxide nano-columns

Highlights: • ZnO nanoparticles were obtained by microwave-hydrothermal method. • X-ray diffraction reveals a hexagonal structure. • Photoluminescence emission evidenced two absorption peaks, at around 480 nm and 590 nm wavelengths. - Abstract: Hydrothermal microwave method (HTMW) was used to synthesize crystalline zinc oxide (ZnO) nano-columns at the temperature of 120 °C with a soaking time of 8 min. ZnO nano-columns were characterized by using X-ray analyses (XRD), infrared spectroscopy (FT-IR), thermogravimetric analyses (TG-DTA), field emission gun and transmission electron microscopy (FEG-SEM and TEM) and photoluminescence properties (PL). XRD results indicated that the ZnO nano-columns are free of any impurity phase and crystallize in the hexagonal structure. Typical FT-IR spectra for ZnO nano-columns presented well defined bands, indicating a substantial short-range order in the system. PL spectra consist of a broad band at 590 nm and narrow band at 480 nm corresponding to a near-band edge emission related to the recombination of excitons and level emission related to structural defects. These results show that the HTMW synthesis route is rapid, cost effective, and could be used as an alternative to obtain ZnO nano-columns in the temperature of 120 °C for 8 min.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quasi-Two-Day and Diurnal Cloud Variation Timescales over Convectively Active Regions

Climatological features of the cloud variability on quasi-two-day (Q2D) and diurnal cycle (DC) timescales are investigated by utilizing the high-resolution satellite infrared brightness temperature (IRBT) observations from January 1998 to December 2019. A distinct land-sea contrast between the distributions of Q2D and DC signals is evident. Diurnally driven cloud activity mainly occurs over land and mountainous regions, and the Q2D timescale is more prominent over tropical ocean basins and land where organized convection is usually observed, e.g., Congo and Amazon Rainforests, the U.S. and subtropical South America during warm seasons. The long-term relationship between the Q2D variability and sea surface temperature (SST) shows that the clouds are more active on Q2D timescales over higher SST environments. The Q2D variability correlates well with both the Indian Ocean Dipole (IOD) and El Niño/Southern Oscillation (ENSO) from 1998 to 2019. The cloud variability associated with a range of convective available potential energy (CAPE) values is analyzed. The result over land shows that increased Q2D cloud variability emerges with higher CAPE, suggesting the coincidence of Q2D and organized convection, particularly given that this effect is strongest over regions with frequent mesoscale convective systems (MCSs) around the world. The cloud variability and the Q2D timescale analyses provide an alternative perspective to understand the global features of mesoscale convective systems. Overall, this study objectively examines the global variability of convective timescales related to the diurnal cycle and longer-lived convective systems to provide a greater understanding of how the global convection population varies in space and time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Simulation and Experimental Study of Metal Organic Frameworks Used in Adsorption Cooling

Metal-organic frameworks (MOFs) have recently attracted enormous interest over the past few years in energy storage and gas separation, yet there have been few reports for adsorption cooling applications. Adsorption cooling technology is an established alternative to mechanical vapor compression refrigeration systems and is an excellent alternative in industrial environments where waste heat is available. We explored the use of MOFs that have very high mass loading and relatively low heats of adsorption, with certain combinations of refrigerants to demonstrate a new type of highly efficient adsorption chiller. Computational fluid dynamics combined with a system level lumped-parameter model have been used to project size and performance for chillers with a cooling capacity ranging from a few kW to several thousand kW. These systems rely on stacked micro/mini-scale architectures to enhance heat and mass transfer. Recent computational studies of an adsorption chiller based on MOFs suggests that a thermally-driven coefficient of performance greater than one may be possible, which would represent a fundamental breakthrough in performance of adsorption chiller technology. Presented herein are computational and experimental results for hydrophyilic and fluorophilic MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reducing leakage current and enhancing polarization in multiferroic 3D super-nanocomposites by microstructure engineering

Abstract Multiferroic materials have generated great interest due to their potential as functional device materials. Nanocomposites have been increasingly used to design and generate new functionalities by pairing dissimilar ferroic materials, though the combination often introduces new complexity and challenges unforeseeable in single-phase counterparts. The recently developed approaches to fabricate 3D super-nanocomposites (3D‐sNC) open new avenues to control and enhance functional properties. In this work, we develop a new 3D‐sNC with CoFe 2 O 4 (CFO) short nanopillar arrays embedded in BaTiO 3 (BTO) film matrix via microstructure engineering by alternatively depositing BTO:CFO vertically-aligned nanocomposite layers and single-phase BTO layers. This microstructure engineering method allows encapsulating the relative conducting CFO phase by the insulating BTO phase, which suppress the leakage current and enhance the polarization. Our results demonstrate that microstructure engineering in 3D‐sNC offers a new bottom–up method of fabricating advanced nanostructures with a wide range of possible configurations for applications where the functional properties need to be systematically modified.

36 MATERIALS SCIENCE↗