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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Method to Extract Spatially Resolved Polycyclic Aromatic Hydrocarbon Emission from Spitzer Spectra: Application to M51

The mid-infrared spectrum contains rich diagnostics to probe the physical properties of galaxies, among which the pervasive emission features from polycyclic aromatic hydrocarbons (PAHs) offer promising means of estimating the star formation rate (SFR) relatively immune from dust extinction. This paper investigates the effectiveness of PAH emission as a SFR indicator on subkiloparsec scales by studying the Spitzer/IRS mapping-mode observations of the nearby grand-design spiral galaxy M51. We present a new approach of analyzing the spatial elements of the spectral data cube that simultaneously maximizes spatial resolution and spatial coverage, while yielding reliable measurements of the total, integrated 5–20 μm PAH emission. We devise a strategy of extracting robust PAH emission using spectra with only partial spectral coverage, complementing missing spectral regions with properly combined mid-infrared photometry. We find that in M51 the PAH emission correlates tightly with the extinction-corrected far-ultraviolet, near-ultraviolet, and Hα emission, from scales of ∼0.4 kpc close to the nucleus to 6 kpc out in the disk of the galaxy, indicating that PAH serves as an excellent tracer of SFR over a wide range of galactic environments. But regional differences exist. Close to the active nucleus of M51 the 6.2 μm feature is weaker, and the overall level of PAH emission is suppressed. The spiral arms and the central star-forming region of the galaxy emit stronger 7.7 and 8.6 μm PAH features than the inter-arm regions.

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

Infrared-Transparent Semiconductor Membranes for Electromagnetic Interference Shielding of Millimeter Waves

Here, it is demonstrated that single-crystalline and highly doped GaAs membranes are excellent candidates for realizing infrared-transparent shields of electromagnetic interference at millimeter frequencies. Measured optical transmittance spectra for the semiconductor membranes show resonant features between 750 and 2500 nm, with a 100% maximum transmittance. The shielding effectiveness of the membranes is extracted from measured scattering parameters between 65 and 85 GHz. Selected GaAs membranes and membranes/polyamide films exhibit shielding effectiveness ranging from 22 to 40 dB, which are suitable values to ensure the safe operation of infrared devices for commercial applications. Theoretical calculations based on a plane wave model show that the interplay of primary reflection and multiple internal reflections of the radio-frequency waves results in broadband shielding capabilities of the membrane between 10 and 300 GHz.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Strangers in a foreign land: ‘Yeastizing’ plant enzymes

Abstract Expressing plant metabolic pathways in microbial platforms is an efficient, cost‐effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour‐intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost‐effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data‐driven machine learning framework designed to extract ‘yeastizing’ rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design‐build‐test cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Novel Machine Learning Algorithm for Cloud Detection Using AERI Measurement Data

Infrared hyperspectral remote sensing has been widely used in the field of meteorology. Many scientists have carried out research on inversion methods of meteorological elements such as thermodynamic profile, boundary layer height, cloud base height, etc. In this study, a method based on machine learning for cloud detection using ground-based infrared hyperspectral radiation data is proposed. The features of outliers, the cloudy and cloud-free data of Atmospheric Emitted Radiance Interferometer (AERI) radiation are extracted. The “reference values” of cloudy and cloud-free are determined based on the observation data of Vaisala CL31 ceilometer within the time range of 8 min before the corresponding time of AERI. A support vector machine (SVM) algorithm is used for training. The dataset comes from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and North Slope Alaska (NSA) site from 2015 to 2017, and the ARM West Antarctic Radiation Experiment (AWARE) site in 2016 is also analyzed. The instruments used in this paper include AERI, ceilometer, etc. The experimental results reveal that the agreement of cloud detection results between the proposed algorithm and ceilometer is about 93% at each site. However, for high clouds or optically thin clouds, the agreement will decrease.

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

The distribution of galaxies within the 'Great Wall'

The galaxy distribution within the 'Great Wall', the most striking feature in the first three 'slices' of the CfA redshift survey extension is examined. The Great Wall is extracted from the sample and is analyzed by counting galaxies in cells. The 'local' two-point correlation function within the Great Wall is computed and the local correlation length, is estimated 15/h Mpc, about 3 times larger than the correlation length for the entire sample. The redshift distribution of galaxies in the pencil-beam survey by Broadhurst et al. (1990) shows peaks separated about by large 'voids', at least to a redshift of about 0.3. The peaks might represent the intersections of their about 5/h Mpc pencil beams with structures similar to the Great Wall. Under this hypothesis, sampling of the Great Walls shows that l approximately 12/h Mpc is the minimum projected beam size required to detect all the 'walls' at redshifts between the peak of the selection function and the effective depth of the survey.

Ramella, Massimo↗
NASA NTRS2008

Linear FMCW Laser Radar for Precision Range and Vector Velocity Measurements

An all fiber linear frequency modulated continuous wave (FMCW) coherent laser radar system is under development with a goal to aide NASA s new Space Exploration initiative for manned and robotic missions to the Moon and Mars. By employing a combination of optical heterodyne and linear frequency modulation techniques and utilizing state-of-the-art fiber optic technologies, highly efficient, compact and reliable laser radar suitable for operation in a space environment is being developed. Linear FMCW lidar has the capability of high-resolution range measurements, and when configured into a multi-channel receiver system it has the capability of obtaining high precision horizontal and vertical velocity measurements. Precision range and vector velocity data are beneficial to navigating planetary landing pods to the preselected site and achieving autonomous, safe soft-landing. The all-fiber coherent laser radar has several important advantages over more conventional pulsed laser altimeters or range finders. One of the advantages of the coherent laser radar is its ability to measure directly the platform velocity by extracting the Doppler shift generated from the motion, as opposed to time of flight range finders where terrain features such as hills, cliffs, or slopes add error to the velocity measurement. Doppler measurements are about two orders of magnitude more accurate than the velocity estimates obtained by pulsed laser altimeters. In addition, most of the components of the device are efficient and reliable commercial off-the-shelf fiber optic telecommunication components. This paper discusses the design and performance of a second-generation brassboard system under development at NASA Langley Research Center as part of the Autonomous Landing and Hazard Avoidance (ALHAT) project.

Pierrottet, Diego↗
NASA NTRS2005

Thermoelectric Air/Soil Energy-Harvesting Device

A proposed thermoelectric device would exploit natural temperature differences between air and soil to harvest small amounts of electric energy. Because the air/soil temperature difference fluctuates between nighttime and daytime, it is almost never zero, and so there is almost always some energy available for harvesting. Unlike photovoltaic cells, the proposed device could operate in the absence of sunlight. Unlike a Stirling engine, which could be designed to extract energy from the air/soil temperature difference, the proposed device would contain no moving parts. The main attractive feature of the proposed device would be high reliability. In a typical application, this device would be used for low-power charging of a battery that would, in turn, supply high power at brief, infrequent intervals for operating an instrumentation package containing sensors and communication circuits. The device (see figure) would include a heat exchanger buried in soil and connected to a heat pipe extending up to a short distance above the ground surface. A thermoelectric microgenerator (TEMG) would be mounted on top of the heat pipe. The TEMG could be of an advanced type, now under development, that could maintain high (relative to prior thermoelectric generators) power densities at small temperature differentials. A heat exchanger exposed to the air would be mounted on top of the TEMG. It would not matter whether the air was warmer than the soil or the soil warmer than the air: as long as there was a nonzero temperature difference, heat would flow through the device and electricity would be generated. A study of factors that could affect the design and operation of the device has been performed. These factors include the thermal conductances of the soil, the components of the device, the contacts between the components of the device, and the interfaces between the heat exchangers and their environments. The study included experiments that were performed on a model of the device to demonstrate feasibility. Because a TEMG suitable for this device was not available, a brass dummy component having a known thermal conductance of 1.68 W/K was substituted for the TEMG in the models to enable measurement of heat flows. The model included a water-based heat pipe 30 in. (76.2 cm) long and 1 in. (2.54 cm) in diameter, wrapped with polyethylene insulation to reduce radial heat flow. Several different side heat exchangers were tested. On the basis of the measurements, it was predicted that if a prototype of the device were equipped with a TEMG, daily temperature fluctuations would cause its output power to fluctuate between 0 and about 0.1 mW, peaking to 0.35 mW during early afternoon.

Snyder, Jeffrey↗
DOE OSTI2022

Development of Nanocrystalline Graphite from Lignin Sources

Carbon composites are attractive to a variety of high-impact applications, such as carbon fibers, batteries, and vehicle parts, due to their multifunctional properties. The properties of carbon are highly dependent on the allotrope the carbon takes and the functionality, impurities, and defects contained within the structure. The increase in demand for sustainable carbon sources in energy storage devices motivates interest in understanding synthesis parameters of lignin value-added products. Also, as the dependence on oil for fuel decreases, alternative sources for carbon in many applications will be needed. In this work, the thermochemical conversion of lignin powders from different feedstocks was evaluated via small and wide-angle X-ray scattering techniques to resolve the amorphous, disordered, and crystalline domains present in the lignin carbons. Scattering analyses indicated an evolution of hierarchical structures along with an increase in ordered domains as a function of carbonization temperature. Qualitative and quantitative methods were used to describe isotropic scattering intensity profiles at multiple length scales. The use of power law models in the mesoscopic region served as the basis to describe morphological changes related to structural features, for example, graphene stacking, degree of roughness, and surface fractals. Kraft softwood and switchgrass produced carbon powder with the most crystalline domains and the least surface roughness. Softwoods reached the highest degree of crystallinity followed by switchgrass samples and had less variability in particle sizes. These results suggest lignin carbons extracted from softwoods and switchgrass are viable substitutes for graphite. Interpretation of X-ray scattering data from lignin carbon powders elucidates feedstock- and processing-dependent morphological features across multiple length scales providing a straightforward framework to evaluate the feasibility of leveraging lignin carbons for producing tunable application-specific materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Phonetic acquisition in cortical dynamics, a computational approach

Many computational theories have been developed to improve artificial phonetic classification performance from linguistic auditory streams. However, less attention has been given to psycholinguistic data and neurophysiological features recently found in cortical tissue. We focus on a context in which basic linguistic units-such as phonemes-are extracted and robustly classified by humans and other animals from complex acoustic streams in speech data. We are especially motivated by the fact that 8-month-old human infants can accomplish segmentation of words from fluent audio streams based exclusively on the statistical relationships between neighboring speech sounds without any kind of supervision. In this paper, we introduce a biologically inspired and fully unsupervised neurocomputational approach that incorporates key neurophysiological and anatomical cortical properties, including columnar organization, spontaneous micro-columnar formation, adaptation to contextual activations and Sparse Distributed Representations (SDRs) produced by means of partial N-Methyl-D-aspartic acid (NMDA) depolarization. Its feature abstraction capabilities show promising phonetic invariance and generalization attributes. Our model improves the performance of a Support Vector Machine (SVM) classifier for monosyllabic, disyllabic and trisyllabic word classification tasks in the presence of environmental disturbances such as white noise, reverberation, and pitch and voice variations. Furthermore, our approach emphasizes potential self-organizing cortical principles achieving improvement without any kind of optimization guidance which could minimize hypothetical loss functions by means of-for example-backpropagation. Thus, our computational model outperforms multiresolution spectro-temporal auditory feature representations using only the statistical sequential structure immerse in the phonotactic rules of the input stream.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Reductive Leaching of Chalcopyrite by Chromium(II) Chloride for the Rapid and Complete Extraction of Copper

A hydrometallurgical process is developed to lower the costs of copper production and thereby sustain the use of copper throughout the global transition to renewable energy technologies. The unique feature of the hydrometallurgical process is the reductive treatment of chalcopyrite, which is in contrast to the oxidative treatment more commonly pursued in the literature. Chalcopyrite reduction by chromium(II) ion is described for the first time and superior kinetics are shown. At high concentrate loadings of 39, 78, and 117 gL –1 , chalcopyrite reacted completely within minutes at room temperature and pressure. The XRD, SEM-EDS, and XPS measurements indicate that chalcopyrite reacts to form copper(I) chloride (CuCl). After the reductive treatment, the mineral products are leached by iron(III) sulfate to demonstrate the complete extraction of copper. The chromium(II) ion may be regenerated by an electrolysis unit inspired by an iron chromium flow battery in a practical industrial process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Laboratory comparisons of organic materials to interstellar dust and the Murchison meteorite

Spectra of objects which lie along several lines of sight through the diffuse interstellar medium (DISM) reveal an absorption feature near 3.4 micrometers, which has been attributed to saturated aliphatic hydrocarbons on interstellar grains. The similarity of the absorption bands near 3.4 micrometers (2950 cm-1) along different lines of sight indicates that the carrier of this band lies in the diffuse dust. Several materials have been proposed as "fits" to the 3.4 micrometers feature over the years. A comparison of these identifications is presented. These comparisons illustrate the need for high resolution, high signal-to-noise observational data as a means of distinguishing between laboratory organics as matches to the interstellar material. Although any material containing hydrocarbons will produce features in the 3.4 micrometers region, the proposed "matches" to the DISM do differ in detail. These differences may help in the analyses of the chemical composition and physical processes which led to the production of the DISM organics, although ISO Observations through the 5-8 micrometers spectral region are essential for a definitive identification. A remarkable similarity between the spectrum of the diffuse dust and an organic extract from the Murchison meteorite suggests that some of the interstellar organic material may be preserved in primitive solar system bodies. The 3.4 micrometers absorption feature (in the rest frame) has recently been detected in external galaxies, indicating the widespread availability of organic material for incorporation into planetary systems.

NASA Center ARC↗
DOE OSTI2022

FSVPy: A python-based package for fluorescent streak velocimetry (FSV)

Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and electrical systems. In this work, we explore the use of fluorescent particle-streak analysis to directly measure the local velocity field of a pressure-driven flow, introducing a new Python package (FSVPy) to perform the analysis. Fluorescent streak velocimetry combines high-speed imaging with highly fluorescent particles to produce images that contain fluorescent streaks, whose length and intensity can be related to the local flow velocity. By capturing images throughout the sample volume, the three-dimensional velocity field can be quantified and reconstructed. We demonstrate this technique by characterizing the channel flow profiles of several non-Newtonian fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and Polyethylene Glycol. We then explore more complex flows, where significant acceleration is created due to microscale features encountered within the flow. We demonstrate the ability of FSVPy to process streaks of various shapes and use the variable intensity along the streak to extract position-specific velocity measurements from individual images. Thus, we demonstrate that FSVPy is a flexible tool that can be used to extract local velocimetry measurements from a wide variety of fluids and flow conditions.

Mechanics↗
DOE OSTI2019

Visual Detection with Context for Document Layout Analysis

We present 1) a work in progress method to visually segment key regions of scientific articles using an object detection technique augmented with contextual features, and 2) a novel dataset of region-labeled articles. A continuing challenge in scientific literature mining is the difficulty of consistently extracting high-quality text from formatted PDFs. To address this, we adapt the object-detection technique Faster R-CNN for document layout detection, and incorporate contextual information that leverages the inherently localized nature of article contents to improve the region detection performance. Due to the limited availability of region-labels for scientific articles, we also contribute a novel dataset of region annotations, the first version of which covers 9 region classes and 822 article pages. Initial experimental results demonstrate a 23.9% absolute improvement in mean average precision over the baseline by incorporating contextual features, and a processing speed 14x faster than a text-based technique. Ongoing work on further improvements is also discussed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Influence of Shock Wave on the Flutter Behavior of Fan Blades Investigated

Modern fan designs have blades with forward sweep; a lean, thin cross section; and a wide chord to improve performance and reduce noise. These geometric features coupled with the presence of a shock wave can lead to flutter instability. Flutter is a self-excited dynamic instability arising because of fluid-structure interaction, which causes the energy from the surrounding fluid to be extracted by the vibrating structure. An in-flight occurrence of flutter could be catastrophic and is a significant design issue for rotor blades in gas turbines. Understanding the flutter behavior and the influence of flow features on flutter will lead to a better and safer design. An aeroelastic analysis code, TURBO, has been developed and validated for flutter calculations at the NASA Glenn Research Center. The code has been used to understand the occurrence of flutter in a forward-swept fan design. The forward-swept fan, which consists of 22 inserted blades, encountered flutter during wind tunnel tests at part speed conditions.

Srivastava, Rakesh↗
DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lineshape response of plastic scintillator to pair production of 4.44 MeV γ’s

We measure the distribution of energy deposited in a 40 × 88 mm plastic scintillator by e + e – pair production of 4.44 MeV γ-rays. He, we observe the double-escape peak of 3.42 MeV from pair production by tagging 511 keV annihilation radiation in two high-Z scintillators. The source is a standard commercial neutron source using α-emitting 241 Am encapsulated with 9 Be, which has a reaction branch feeding the first I π = 2 + state of 12 C making the 4.44 MeV γ-rays. We demonstrate the extraction of the double-escape peak from the large neutron-produced backgound, and explore some of the features and difficulties of this technique with our apparatus.

Beta calibration↗
DOE OSTI2021

Learning the Low Frequency Earthquake Activity on the Central San Andreas Fault

Abstract Low frequency earthquakes (LFEs) originating below the central San Andreas Fault are associated with slow‐slip beneath the seismogenic zone within the more ductile portion of the crust. Monitoring efforts over 15 years detected >1 million LFEs. We train a gradient boosted tree model using statistical features describing the seismic waveforms to estimate the hourly LFE event count. The burst‐like LFE behavior is reproduced, while lower amplitudes are predicted during the most active periods. The hourly event counts are up to 18% greater than the catalog. The ability to continuously monitor LFE activity provides insight to when geodetic measurements of slow slip are possible, without the need for developing a computational‐intensive template‐matching catalog. Similar waveform statistical features are found between detecting LFEs and tremors, which provides additional evidence tremors are composed of LFEs. The approach extracts information contained in continuous seismic waveforms that might benefit detecting precursory signals.

58 GEOSCIENCES↗
DOE OSTI2020

Nonadiabatic Energy Fluctuations of Scale-Invariant Quantum Systems in a Time-Dependent Trap

We consider the nonadiabatic energy fluctuations of a many-body system in a time-dependent harmonic trap. In the presence of scale-invariance, the dynamics becomes self-similar and the nondiabatic energy fluctuations can be found in terms of the initial expectation values of the second moments of the Hamiltonian, square position, and squeezing operators. Nonadiabatic features are expressed in terms of the scaling factor governing the size of the atomic cloud, which can be extracted from time-of-flight images. We apply this exact relation to a number of examples: the single-particle harmonic oscillator, the one-dimensional Calogero-Sutherland model, describing bosons with inverse-square interactions that includes the non-interacting Bose gas and the Tonks-Girdardeau gas as limiting cases, and the unitary Fermi gas. We illustrate these results for various expansion protocols involving sudden quenches of the trap frequency, linear ramps and shortcuts to adiabaticity. Our results pave the way to the experimental study of nonadiabatic energy fluctuations in driven quantum fluids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗