Photometric observations in South America and their relation to trapped radiation.
Tilting filter photometers to measure night airglow in South America, establishing charged particles energy flux upper limits
Eather, R. H.↗
SEARCH · Engineering Papers
Results for “particle filtering”
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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Atmospheric particulate measurements in Norfolk, Virginia
Characterization of atmospheric particulates was conducted at a site near the center of Norfolk, Virginia. Air quality was measured in terms of atmospheric mass loading, particle size distribution, and particulate elemental composition for a period of 2 weeks. The objectives of this study were (1) to establish a mean level of air quality and deviations about this mean, (2) to ascertain diurnal changes or special events in air quality, and (3) to evaluate instrumentation and sampling schedules. Simultaneous measurements were made with the following instruments: a quartz crystal microbalance particulate monitor, a light-scattering multirange particle counter, a high-volume air sampler, and polycarbonate membrane filters. To assess the impact of meteorological conditions on air quality variations, continuous data on temperature, relative humidity, wind speed, and wind direction were recorded. Particulate elemental composition was obtained from neutron activation and scanning electron microscopy analyses of polycarbonate membrane filter samples. The measured average mass loading agrees reasonably well with the mass loadings determined by the Virginia State Air Pollution Control Board. There are consistent diurnal increases in atmospheric mass loading in the early morning and a sample time resolution of 1/2 hour seems necessary to detect most of the significant events.
Storey, R. W., Jr.↗
Extracting spatial information from large aperture exposures of diffuse sources
The spatial properties of large aperture exposures of diffuse emission can be used both to investigate spatial variations in the emission and to filter out camera noise in exposures of weak emission sources. Spatial imaging can be accomplished both parallel and perpendicular to dispersion with a resolution of 5-6 arc sec, and a narrow median filter running perpendicular to dispersion across a diffuse image selectively filters out point source features, such as reseaux marks and fast particle hits. Spatial information derived from observations of solar system objects is presented.
Clarke, J. T.↗
Structure of the lunar crust at highland site Apollo Station 16
The seismic crustal structure of the moon is known in the region of Oceanus Procellarum from the analysis of artificial impact data. To extend this knowledge we have used data from natural lunar seismic events to search for secondary seismic wave arrivals in the form of peg-leg multiples caused by reflections at crustal interfaces and converted arrivals caused by refractions at crustal interfaces. A polarization filter has been applied to the data to enhance the rectilinear particle motion expected for the onset of these body wave arrivals in the scattered coda of lunar seismograms. The results of this work tentatively indicate that the highland site at station 16 has a 75 km thick crust with an intermediate 20 km interface, compared to the 60 km crust and 20 km interface in Oceanus Procellarum, a mare region. Since the 20 km upper crust appears to exist at both highland and mare sites, it probably does not represent a mare basalt layer but rather a more general feature of the crust. Crustal thickness may partially control elevation by isostasy.
Goins, N. R.↗
Soot Imaging and Measurement
Soot, sometimes referred to as smoke, is made up primarily of the carbon particles generated by most combustion processes. For example, large quantities of soot can be seen issuing from the exhaust pipes of diesel-powered vehicles. Heated soot also is responsible for the warm orange color of candle flames, though that soot is generally consumed before it can exit the flame. Research has suggested that heavy atmospheric soot concentrations aggravate conditions such as pneumonia and asthma, causing many deaths each year. To understand the formation and oxidation of soot, NASA Lewis Research Center scientists, together with several university investigators, are investigating the properties of soot generated in reduced gravity, where the absence of buoyancy allows more time for the particles to grow. The increased time allows researchers to better study the life cycle of these particles, with the hope that increased understanding will lead to better control strategies. To quantify the amount of soot present in a flame, Lewis scientists developed a unique imaging technique that provides quantitative and qualitative soot data over a large field of view. There is significant improvement over the single-point methods normally used. The technique is shown in the sketch, where light from a laser is expanded with a microscope objective, rendered parallel, and passed through a flame where soot particles reduce the amount of light transmitted to the camera. A filter only allows light at the wavelength of the laser to pass to the camera, preventing any extraneous signals. When images of the laser light with and without the flame are compared, a quantitative map of the soot concentration is produced. In addition to that data, a qualitative image of the soot in the flame is also generated, an example of which is displayed in the photo. This technique has the potential to be adapted to real-time process control in industrial powerplants.
Source record↗
Turbulent Statistics from Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition
Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.
Dahl, Milo D.↗
Turbulent Statistics from Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition
Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.
Dahl, Milo D.↗
Turbulent Statistics From Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition
Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.
Dahl, Milo D.↗
Development of an Indexing Media Filtration System for Long Duration Space Missions
The effective maintenance of air quality aboard spacecraft cabins will be vital to future human exploration missions. A key component will be the air cleaning filtration system which will need to remove a broad size range of particles derived from multiple biological and material sources. In addition, during surface missions any extraterrestrial planetary dust, including dust generated by near-by ISRU equipment, which is tracked into the habitat will also need to be managed by the filtration system inside the pressurized habitat compartments. An indexing media filter system is being developed to meet the demand for long-duration missions that will result in dramatic increases in filter service life and loading capacity, and will require minimal crew involvement. The filtration system consists of three stages: an inertial impactor stage, an indexing media stage, and a high-efficiency filter stage, packaged in a stacked modular cartridge configuration. Each stage will target a specific range of particle sizes that optimize the filtration and regeneration performance of the system. An 1/8th scale and full-scale prototype of the filter system have been fabricated and have been tested in the laboratory and reduced gravity environments that simulate conditions on spacecrafts, landers and habitats. Results from recent laboratory and reduce-gravity flight tests data will be presented. The features of the new filter system may also benefit other closed systems, such as submarines, and remote location terrestrial installations where servicing and replacement of filter units is not practical.
Filtration↗
Laboratory and field studies of ice-nucleating particles from open-lot livestock facilities in Texas
Abstract. In this work, an abundance of ice-nucleating particles (INPs) from livestock facilities was studied through laboratory measurements from cloud-simulation chamber experiments and field investigation in the Texas Panhandle. Surface materials from two livestock facilities, one in the Texas Panhandle and another from McGregor, Texas, were selected as dust proxies for laboratory analyses. These two samples possessed different chemical and biological properties. A combination of aerosol interaction and dynamics in the atmosphere (AIDA) measurements and offline ice spectrometry was used to assess the immersion freezing mode ice nucleation ability and efficiency of these proxy samples at temperatures above −29 ∘C. A dynamic filter processing chamber was also used to complement the freezing efficiencies of submicron and supermicron particles collected from the AIDA chamber. For the field survey, periodic ambient particle sampling took place at four commercial livestock facilities from July 2017 to July 2019. INP concentrations of collected particles were measured using an offline freezing test system, and the data were acquired for temperatures between −5 and −25 ∘C. Our AIDA laboratory results showed that the freezing spectra of two livestock dust proxies exhibited higher freezing efficiency than previously studied soil dust samples at temperatures below −25 ∘C. Despite their differences in composition, the freezing efficiencies of both proxy livestock dust samples were comparable to each other. Our dynamic filter processing chamber results showed on average approximately 50 % supermicron size dominance in the INPs of both dust proxies. Thus, our laboratory findings suggest the importance of particle size in immersion freezing for these samples and that the size might be a more important factor for immersion freezing of livestock dust than the composition. From a 3-year field survey, we measured a high concentration of ambient INPs of 1171.6 ± 691.6 L−1 (average ± standard error) at −25 ∘C for aerosol particles collected at the downwind edges of livestock facilities. An obvious seasonal variation in INP concentration, peaking in summer, was observed, with the maximum at the same temperature exceeding 10 000 L−1 on 23 July 2018. The observed high INP concentrations suggest that a livestock facility is a substantial source of INPs. The INP concentration values from our field survey showed a strong correlation with measured particulate matter mass concentration, which supports the importance of size in ice nucleation of particles from livestock facilities.
58 GEOSCIENCES↗
NASA Tech Briefs, August 2004
Topics covered include: Data Relay Board with Protocol for High-Speed, Free-Space Optical Communications; Software and Algorithms for Biomedical Image Data Processing and Visualization; Rapid Chemometric Filtering of Spectral Data; Prioritizing Scientific Data for Transmission; Determining Sizes of Particles in a Flow from DPIV Data; Faster Processing for Inverting GPS Occultation Data; FPGA-Based, Self-Checking, Fault-Tolerant Computers; Ultralow-Power Digital Correlator for Microwave Polarimetry; Grounding Headphones for Protection Against ESD; Lightweight Stacks of Direct Methanol Fuel Cells; Highly Efficient Vector-Inversion Pulse Generators; Estimating Basic Preliminary Design Performances of Aerospace Vehicles; Framework for Development of Object-Oriented Software; Analyzing Spacecraft Telecommunication Systems; Collaborative Planning of Robotic Exploration; Tools for Administration of a UNIX-Based Network; Preparing and Analyzing Iced Airfoils; Evaluating Performance of Components; Fuels Containing Methane of Natural Gas in Solution; Direct Electrolytic Deposition of Mats of MnxOy Nanowires; Bubble Eliminator Based on Centrifugal Flow; Inflatable Emergency Atmospheric-Entry Vehicles; Lightweight Deployable Mirrors with Tensegrity Supports; Centrifugal Adsorption Cartridge System; Ultrasonic Apparatus for Pulverizing Brittle Material; Transplanting Retinal Cells using Bucky Paper for Support; Using an Ultrasonic Instrument to Size Extravascular Bubbles; Coronagraphic Notch Filter for Raman Spectroscopy; On-the-Fly Mapping for Calibrating Directional Antennas; Working Fluids for Increasing Capacities of Heat Pipes; Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds; Liquid-Metal-Fed Pulsed Plasma Thrusters; Personal Radiation Protection System; and Attitude Control for a Solar-Sail Spacecraft.
Source record↗
An EPIC Tale of the Quiescent Particle Background
Extended Source Analysis Software Use Based Empirical Investigation: (1) Builds quiescent particle background (QPB) spectra and images for observations of extended sources that fill (or mostly fill) the FOV i.e., annular background subtraction won't work. (2) Uses a combination of Filter Wheel Closed (FWC) and corner data to capture the spectral, spatial, and temporal variation of the quiescent particle background. New Work: (1) Improved understanding of the QPB (aided by adding a whole lot of data since 2008). (2) Significantly improved statistics (did I mention a LOT more data?). (3) Better characterization and identification of anomalous states. (4) Builds backgrounds for some anomalous state. (5) New efficient method for non-anomalous states.
Snowden, S.L.↗
Preparing for Planetary Surface Exploration by Measuring Habitat Dust Intrusion with Filter Tests During an Analogue Mars Mission
As humans venture deeper into space more issues related to operations will become apparent. While the perils ofdust particles may not be widely recognized, it is one of the major issues astronauts will face on the surface of theMoon and Mars. Dust particles present a problem for both astronaut health and equipment as revealed during theApollo era lunar surface missions. Dust particles cling to spacesuits and field gear, which upon ingress would begincirculating throughout the spacecraft or habitat. An astronaut's health is compromised by the dust particle's potentialto embed in the lungs and cause respiratory illnesses. The extreme abrasiveness and granularity of the particles makeit near impossible to completely shield a spacecraft or habitat from dust related damage. NASA's Glenn ResearchCenter collaborated with Crew 188 at the Mars Desert Research Station (MDRS) in Utah to measure how much dustentered the habitat during a series of extravehicular activities (EVAs), or surface excursions. A NASA GRCdeveloped multistage filter system, coined the Scroll Filter System, was tested, for its effectiveness in removing dustthat entered the airlock and habitat after the EVAs. An optical particle counter measured the ambient airlockparticulates five times including: before the start of operations; after the crew left for EVA; in the middle of the EVAwith the settled air; before the crew entered the airlock after EVA; and finally, after the crew simulated repressurizationand suit brushing off in the airlock. Data was also collected in several of the working environmentlocations around MDRS and outside the habitat in the wind. Data collected from this research will help establishfilter equipment for life support systems and prescribed operations for astronaut transition from a planetary surfaceinto a desired clean habitat. Measurements may aid in updating a baseline expected dust load for a surface habitatand further facilitate the mitigation of astronaut's exposure to dust particles on the surface of celestial bodies.
Kobrick, Ryan L.↗
Estimating mass-absorption cross-section of ambient black carbon aerosols: theoretical, empirical, and machine learning models
The mass-absorption cross-section of black carbon (MAC BC ) is an essential parameter to link the atmospheric concentration of black carbon (BC) with its radiative forcing. When a direct calculation of MAC BC based on observations of aerosol light absorption and BC mass concentration is impossible, we rely on modeling and simulations to estimate MAC BC , but currently, there is no consensus model that can be relied on for accurate predictions across all atmospheric environments when BC particles have different coating thicknesses. Here, we applied five MAC BC prediction models (including three light scattering theories, an empirical model based on observations of particle mass concentrations, and a machine learning model developed in our previous work) to aerosols from three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) field campaigns. While many studies have found that increasing the complexity of the models helps to constrain biases of the estimated MAC BC , our effort is to evaluate the models based on the criteria of simplicity and accuracy. We find that our machine learning model (support vector machine for regression, SVM) generally performs well across all DOE ARM field campaign data, while the accuracy of core-shell Mie theory depends on the bias correction algorithm applied to filter-based light absorption data. Generally, the empirical model for internally-mixed particles that we considered tends to over-predict MAC BC , while Mie theory for externally-mixed particles tends to under-predict MAC BC . An examination of the influence of coating material on BC cores suggests that the performance of our current SVM model is degraded when the BC is thickly-coated (e.g., it has undergone aging and mixing with other materials in the atmosphere).
54 ENVIRONMENTAL SCIENCES↗
Development of an Indexing Media Filtration System for Long Duration Space Missions
The effective maintenance of air quality aboard spacecraft cabins will be vital to future human exploration missions. A key component will be the air cleaning filtration system which will need to remove a broad size range of particles including skin flakes, hair and clothing fibers, other biological matter, and particulate matter derived from material and equipment wear. In addition, during surface missions any extraterrestrial planetary dust, including dust generated by near-by ISRU equipment, which is tracked into the habitat will also need to be managed by the filtration system inside the pressurized habitat compartments. An indexing media filter system is being developed to meet the demand for long-duration missions that will result in dramatic increases in filter service life and loading capacity, and will require minimal crew involvement. These features may also benefit other closed systems, such as submarines, and remote location terrestrial installations where servicing and replacement of filter units is not practical. The filtration system consists of three stages: an inertial impactor stage, an indexing media stage, and a high-efficiency filter stage, packaged in a stacked modular cartridge configuration. Each stage will target a specific range of particle sizes that optimize the filtration and regeneration performance of the system. An 1/8th scale and full-scale prototype of the filter system have been fabricated and have been tested in the laboratory and reduced gravity environments that simulate conditions on spacecrafts, landers and habitats. Results from recent laboratory and reducegravity flight tests data will be presented.
Filtration↗
Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks
Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.
54 ENVIRONMENTAL SCIENCES↗
EUTERPE: A global gyrokinetic code for stellarator geometry
The current state of the EUTERPE code is described with emphasis on the implemented models and their numerical implementation. The code solves the multi-species electromagnetic gyrokinetic equations in the full volume of a three-dimensional domain. Noise reduction of the particle-in-cell method is achieved by using a δf-method and Fourier filters. The field equations are discretized with B-splines and the resulting system of equations is solved iteratively. For linear simulations a phase-factor transformation is applied in order to strongly reduce the necessary grid resolution. Apart from the full gyrokinetic model, other numerically less expensive hybrid models are also implemented. They are mainly tailored for comparison with fluid theory and for studying the interaction of the bulk plasma with fast particles. The code is parallelized for CPUs by particle and domain decomposition. Good scalability up to several thousand nodes is demonstrated.
97 MATHEMATICS AND COMPUTING↗
Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model
The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.
25 ENERGY STORAGE↗