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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Sulfuric Acid and Soot Particle Formation in Aircraft Exhaust

A combination of CN counts, Ames wire impactor size analyses and optical particle counter data in aircraft exhaust results in a continuous particle size distribution between 0.01 micrometer and 1 micrometer particle radius sampled in the exhaust of a Boeing 757 research aircraft. The two orders of magnitude size range covered by the measurements correspond to 6-7 orders of magnitude particle concentration. CN counts and small particle wire impactor data determine a nucleation mode, composed of aircraft-emitted sulfuric acid aerosol, that contributes between 62% and 85% to the total aerosol surface area and between 31% and 34% to its volume. Soot aerosol comprises 0.5% of the surface area of the sulfuric acid aerosol. Emission indices are: EIH2SO4 = 0.05 g/kgFUEL and (0.2-0.5) g/kgFUEL (for 75 ppmm and 675 ppmm fuel-S, respectively), 2.5E4<EISOOT<1.3E-3 g/kgFUEL, and EICN 8E14 and 1.3E16 particles/kgFUEL (for 75 and 675 ppmm fuel-S). The sulfur (gas) to H2SO4 (particle) conversion efficiency is between 10% and 25%.

Pueschel, Rudolf F.↗
NASA NTRS1980

Formation of bowl-shaped craters

High-explosive charges are used to form, in several types of granular media, laboratory-scale examples of the bowl-shaped craters that are found to be the largest and simplest class of impact structure on planetary and lunar surfaces. High-speed films of the experiments yield crater growth rate and particle displacement data, including quantitative stress, strain, displacement, and velocity data. These results are compared with the particle displacement and velocity data from large explosion experiments which have produced bowl-shaped craters. A time-sequence description of large, bowl-shaped impact crater formation is developed from the results of these comparisons, as well as those of the morphological features and structural deformations of large explosions and impact craters.

Piekutowski, A. J.↗
DOE OSTI2022

Median bed-material sediment particle size across rivers in the contiguous US

Abstract. Bed-material sediment particle size data, particularly the median sediment particle size (D50), are critical for understanding and modeling riverine sediment transport. However, sediment particle size observations are primarily available at individual sites. Large-scale modeling and assessment of riverine sediment transport are limited by the lack of continuous regional maps of bed-material sediment particle size. We hence present a map of D50 over the contiguous US in a vector format that corresponds to approximately 2.7 million river segments (i.e., flowlines) in the National Hydrography Dataset Plus (NHDPlus) dataset. We develop the map in four steps: (1) collect and process the observed D50 data from 2577 U.S. Geological Survey stations or U.S. Army Corps of Engineers sampling locations; (2) collocate these data with the NHDPlus flowlines based on their geographic locations, resulting in 1691 flowlines with collocated D50 values; (3) develop a predictive model using the eXtreme Gradient Boosting (XGBoost) machine learning method based on the observed D50 data and the corresponding climate, hydrology, geology, and other attributes retrieved from the NHDPlus dataset; and (4) estimate the D50 values for flowlines without observations using the XGBoost predictive model. We expect this map to be useful for various purposes, such as research in large-scale river sediment transport using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc. The map is available at https://doi.org/10.5281/zenodo.4921987 (Li et al., 2021a).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A search for charged massive particles in IMP 8 data

Data from the IMP 8 satellite are used here to rule out charged massive particles (CHAMPs) with masses between 2.4 and 56,000 TeV as the source of the dark matter in the Galactic halo. This limit is achieved under the assumption that CHAMPs are virialized.

Snowden-Ifft, D. P.↗
DOE OSTI2020

Microparticle cloud imaging and tracking for data-driven plasma science

Oceans of image and particle track data encountered in plasma interactions with microparticle clouds motivate development and applications of machine-learning (ML) algorithms. A local-constant-velocity tracker, a Kohonen neural network or self-organizing map, the feature tracking kit, and U-Net are described and compared with each other for microparticle cloud datasets generated from exploding wires, dusty plasmas, and atmospheric plasmas. Particle density and the signal-to-noise ratio have been identified as two important factors that affect the tracking accuracy. Fast Fourier transform is used to reveal how U-Net, a deep convolutional neural network developed for non-plasma applications, achieves the improvements for noisy scenes. Viscous effects are revealed in the ballistic motions of the particles from the exploding wires and atmospheric plasmas. Subdiffusion of microparticles satisfying Δr 2 ∝t k (k=0.84±0.02) is obtained from the dusty plasma datasets. Microparticle cloud imaging and tracking, when enhanced with data and ML models, present new possibilities for plasma physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2005

Planar particle/droplet size measurement technique using digital particle image velocimetry image data

A method for determining a mass flux of an entrained phase in a planar two-phase flow records images of particles in the two-phase flow. Respective sizes of the particles (the entrained phase) are determined as a function of a separation between spots identified on the particle images. Respective velocities of the particles are determined. The mass flux of the entrained phase is determined as a function of the size and velocity of the particles.

Wernet, Mark P.↗
DOE OSTI2024

Testing hadronic-model predictions of depth of maximum of air-shower profiles and ground-particle signals using hybrid data of the Pierre Auger Observatory

We test the predictions of hadronic interaction models regarding the depth of maximum of air-shower profiles, X max , and ground-particle signals in water-Cherenkov detectors at 1000 m from the shower core, S ( 1000 ) , using the data from the fluorescence and surface detectors of the Pierre Auger Observatory. The test consists of fitting the measured two-dimensional ( S ( 1000 ) , X max ) distributions using templates for simulated air showers produced with hadronic interaction models pos-, et--04, 2.3d and leaving the scales of predicted X max and the signals from hadronic component at ground as free-fit parameters. The method relies on the assumption that the mass composition remains the same at all zenith angles, while the longitudinal shower development and attenuation of ground signal depend on the mass composition in a correlated way. The analysis was applied to 2239 events detected by both the fluorescence and surface detectors of the Pierre Auger Observatory with energies between 10 18.5 eV to 10 19.0 eV and zenith angles below 60°. We found, that within the assumptions of the method, the best description of the data is achieved if the predictions of the hadronic interaction models are shifted to deeper X max values and larger hadronic signals at all zenith angles. Given the magnitude of the shifts and the data sample size, the statistical significance of the improvement of data description using the modifications considered in the paper is larger than 5 σ even for any linear combination of experimental systematic uncertainties. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

The phase function of Venus cloud particles from Mariner 10 data

Mariner 10 images of Venus taken at several phase angles were photometrically reduced. The analysis shows that the phase function of the cloud particles is not isotropic, as had been deduced earlier from the brightness distribution on spacecraft images taken at a single phase angle, but has a broad minimum near 60 deg and is forward-scattering. The scattering properties are in quantitative agreement with previous deductions from earth-based polarization measurements by Hansen and his associates.

Hapke, B.↗
NASA NTRS2004

Determining Sizes of Particles in a Flow from DPIV Data

A proposed method of measuring the size of particles entrained in a flow of a liquid or gas would involve utilization of data from digital particle-image velocimetry (DPIV) of the flow. That is to say, with proper design and operation of a DPIV system, the DPIV data could be processed according to the proposed method to obtain particle sizes in addition to particle velocities. As an additional benefit, one could then compute the mass flux of the entrained particles from the particle sizes and velocities. As in DPIV as practiced heretofore, a pulsed laser beam would be formed into a thin sheet to illuminate a plane of interest in a flow field and the illuminated plane would be observed by means of a charge-coupled device (CCD) camera aimed along a line perpendicular to the illuminated plane. Unlike in DPIV as practiced heretofore, care would be taken to polarize the laser beam so that its electric field would lie in the illuminated plane, for the reason explained in the next paragraph. The proposed method applies, more specifically, to transparent or semitransparent spherical particles that have an index of refraction different from that of the fluid in which they are entrained. The method is based on the established Mie theory, which describes the scattering of light by diffraction, refraction, and specular reflection of light by such particles. In the case of a particle illuminated by polarized light and observed in the arrangement described in the preceding paragraph, the Mie theory shows that the image of the particle on the focal plane of the CCD camera includes two glare spots: one attributable to light reflected toward the camera and one attributable to light refracted toward the camera. The distance between the glare spots is a known function of the size of the particle, the indices of refraction of the particle material, and design parameters of the camera optics. Hence, the size of a particle can be determined from the distance between the glare spots. The proposed method would be implemented in an algorithm that would automatically identify, and measure the distance between, the glare spots for each particle for which a suitable image has been captured in a DPIV image frame. The algorithm (see figure) would begin with thresholding of data from the entire image frame to reduce noise, thereby facilitating discrimination of particle images from the background and aiding in the separation of overlapping particles. It is important not to pick a threshold level so high that the light intensity between a given pair of glare spots does not fall below the threshold value, leaving the glare spots disconnected. The image would then be scanned in a sequence of rows and columns of pixels to identify groups of adjacent pixels that contain nonzero brightnesses and that are surrounded by pixels of zero brightness. Each such group would be assumed to constitute the image of one particle. Each such group would be further analyzed to determine whether the image was saturated; saturated particle images must be rejected because the locations of glare spots in saturated images cannot accurately be determined. Within each unsaturated particle image, the centroids (deemed to be the locations) of the glare spots would be determined by means of gradients of brightness distributions and three-point horizontal and three-point vertical Gaussian estimates based on the brightness values of the brightest pixels and the pixels adjacent to them. If the brightness of a given particle image contained only one peak, then it would be assumed that a second glare spot did not exist and that image would be rejected.

Wernet, M. P.↗
NASA NTRS2009

Particle-Image Velocimeter Having Large Depth of Field

An instrument that functions mainly as a particle-image velocimeter provides data on the sizes and velocities of flying opaque particles. The instrument is being developed as a means of characterizing fluxes of wind-borne dust particles in the Martian atmosphere. The instrument could also adapted to terrestrial use in measuring sizes and velocities of opaque particles carried by natural winds and industrial gases. Examples of potential terrestrial applications include monitoring of airborne industrial pollutants and airborne particles in mine shafts. The design of this instrument reflects an observation, made in field research, that airborne dust particles derived from soil and rock are opaque enough to be observable by use of bright field illumination with high contrast for highly accurate measurements of sizes and shapes. The instrument includes a source of collimated light coupled to an afocal beam expander and an imaging array of photodetectors. When dust particles travel through the collimated beam, they cast shadows. The shadows are magnified by the beam expander and relayed to the array of photodetectors. Inasmuch as the images captured by the array are of dust-particle shadows rather of the particles themselves, the depth of field of the instrument can be large: the instrument has a depth of field of about 11 mm, which is larger than the depths of field of prior particle-image velocimeters. The instrument can resolve, and measure the sizes and velocities of, particles having sizes in the approximate range of 1 to 300 m. For slowly moving particles, data from two image frames are used to calculate velocities. For rapidly moving particles, image smear lengths from a single frame are used in conjunction with particle- size measurement data to determine velocities.

Bos, Brent↗
DOE OSTI2025

Aspen Open Jets: unlocking LHC data for foundation models in particle physics

Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrates how data collected by the CMS experiment at the Large Hadron Collider can be useful in pre-training foundation models for HEP. Specifically, we introduce the AspenOpenJets (AOJs) dataset, consisting of approximately 178 M high p T jets derived from CMS 2016 Open Data. We show how pre-training the OmniJet-α foundation model on AOJs improves performance on generative tasks with significant domain shift: generating boosted top and QCD jets from the simulated JetClass dataset. In addition to demonstrating the power of pre-training of a jet-based foundation model on actual proton–proton collision data, we provide the ML-ready derived AOJs dataset for further public use.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1986

Visibility related to backscatter at 1.54 micron

The lidar process was shown to have the necessary potential to fulfill the need for a remote measurement of visibility. Visibility can be inferred from a lidar return optical extinction. The wavelength 1.54 micron was chosen, being near the visible wavelength region and having a high eye safety threshol, 200,000 times higher than 1.06 micron; 1.54 is the erbium laser wavelength. This research utilized 105 measured height profiles of natural droplet size distributions data, taken in clouds, fog, and haze. These profiles were examined to determine the completeness of the droplet counting data. It was found that the particle spectrometer data were incomplete in the very light ford and haze so this portion of the data was eliminated. Utilizing the Mie theory, these droplet size distribution profiles were converted to backscatter at 1.54 micron and extinction in the visible region, 0.55 micron. Using Koschmeider's relationship, the extinction profiles were converted to visibility. The visibility and backscatter profiles were compared to develop a relationship between visibility and backscatter at 1.54 micron.

Barber, T. L.↗
NASA NTRSDate not supplied

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

TBC↗
NASA NTRSDate not supplied

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

TBC↗
NASA NTRSDate not supplied

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

burner rig↗
DOE OSTI2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network

Solar energetic particles (SEPs) are an essential source of space radiation, and are hazardous for humans in space, spacecraft, and technology in general. In this paper, we propose a deep-learning method, specifically a bidirectional long short-term memory (biLSTM) network, to predict if an active region (AR) would produce an SEP event given that (i) the AR will produce an M- or X-class flare and a coronal mass ejection (CME) associated with the flare, or (ii) the AR will produce an M- or X-class flare regardless of whether or not the flare is associated with a CME. The data samples used in this study are collected from the Geostationary Operational Environmental Satellite's X-ray flare catalogs provided by the National Centers for Environmental Information. We select M- and X-class flares with identified ARs in the catalogs for the period between 2010 and 2021, and find the associations of flares, CMEs, and SEPs in the Space Weather Database of Notifications, Knowledge, Information during the same period. Each data sample contains physical parameters collected from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Experimental results based on different performance metrics demonstrate that the proposed biLSTM network is better than related machine-learning algorithms for the two SEP prediction tasks studied here. We also discuss extensions of our approach for probabilistic forecasting and calibration with empirical evaluation

79 ASTRONOMY AND ASTROPHYSICS↗