SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Scheme ensures maximum data received on average. Dual-rate scheme for maximizing data returned during spacecraft mission, adaptable, as is or with modifications, to high-frequency terrestrial data transmission. Data rate fixed in advance at minimum value guarantees reasonable prospect of success during bad weather. Dualrate strategy yields net data rate 2.5 times best achievable with single transmission rate.
Data from a 2 day period recorded by Magsat were used to produce world magnetic maps of the scalar total field and three vector component total fields. Subtracting the reference field of Magsat 6/80, a scalar anomalous field and three vector component anomalous fields were also mapped. After removing 718 bad points from the original data, every fifth point was picked for contouring. While the main geomagnetic field of the Earth is surprisingly well mapped considering the short data period, the anomaly maps suffer from data sparseness. The entire Magsat file collected at altitudes of 500-700 m in nonmountainous terrain and at 900-1,000 m in mountainous terrain was averaged to reduce the total data to 6,500 measurements, yielding a 0.1 deg sampling interval along the flight path. A U.S. aeromagnetic anomaly surface map was produced and the field was upward continued to a 300 km altitude. Differences in anomaly structure between the POGO data and the map produced were attributed to insufficient removal of the reference field. Reprocessing of the data using the GSFC reference field (9/80-2) should remove the low harmonic field and improve the anomalous field structure.
This paper compares the observed behavior of the (F2) layer of the ionosphere at Millstone Hill and Hobart with calculations from the field line interhemispheric plasma (FLIP) model for solar maximum, solstice conditions in 1990. During the study period the daily F(sub 10.7) index varied by more than a factor of 2 (123 to 280), but the 81-day mean F(sub 10.7) (F(sub 10.7 A)) was almost constant near 190. Calculations were performed with and without the effects of vibrationally excited N2 (N(sup *)(sub 2) which affects the loss rate of atomic oxygen ions. In the case without N(sup *)(sub 2) there is generally good agreement between the model and measurement for the daytime, peak density of the F region (NmF2). Both the model and the measurement show a strong seasonal anomaly with the winter noon densities a factor of 3 to 4 greater than the summer noon densities at Millstone Hill and a factor of 2 greater at Hobart. The seasonal anomaly in the model is caused by changes in the neutral composition as given by the mass spectrometer and incoherent scatter (MSIS) 86 neutral density model. There is generally little or no increase in the observed noon NmF2 as a function of daily F(sub 10.7) except at Millstone Hill in winter. In contrast to the generally good agreement between model and data at noon, the model badly underestimates the density at night at Millstone Hill at all seasons. At Hobart the model reproduces the nighttime density variations well in both winter and summer. The international reference ionosphere (IRI) model generally provides a good representation of the average behavior of noon NmF2 and hmF2 but because the data show a lot of day-to-day variability, there are often large differences. The FLIP model is able to reproduce this variability when hmF2 is specified. The IRI model peak densities are better than the FLIP densities at night, but the IRI model does not represent the Millstone Hill summer data very well at night in 1990.
The Self Powered EVA EMU Data Recorder (SPEEDR) is an FPGA (Field-programmable gate array) based device designed to collect high-rate EMU (Extravehicular Mobility Unit) PLSS (Primary Life Support Subsystem) data for download at a later time. The existing EMU PLSS data down-link capability during EVA is one data packet every 2 minutes and is subject to bad packets or loss of signal. High-rate PLSS data is generated by the ECWS (Enhanced Caution and Warning System) but is not normally captured or distributed. Access to high-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Shuttle flights post FY11, and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both IVA (Intravehicular Activity) and EVA (Extravehicular Activity) operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other ISS subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require "store then forward" methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer USB (Universal Serial Bus) port while data is being downloaded.
The Self-Powered Extravehicular Mobility Unit (EMU) Extravehicular Activity (EVA) Data Recorder (SPEEDR) is a field-programmable gate array (FPGA)-based device designed to collect high-rate EMU Primary Life Support Subsystem (PLSS) data for download at a later time. During EVA, the existing EMU PLSS data downlink capability is one data packet every 2 minutes and is subject to bad packets or loss of signal. Higher-rate PLSS data is generated by the Enhanced Caution and Warning System but is not normally captured or distributed. Access to higher-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Space Shuttle flights post Fiscal Year 2011 (FY11), and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both intravehicular activity (IVA) and EVA operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other International Space Station subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require store then forward methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer Universal Serial Bus (USB) port while data are being downloaded.
The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. This paper discusses how synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agriculture land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems discussed.
The magnetometer data was collected in multiple directions across the watershed hillslope at the NGEE Arctic Teller Road site at mile marker 27 (TL_MM27) on the Seward Peninsula, Alaska over multiple years in March 2018 and April 2023. The magnetic data were collected using a Geometrics Inc. G-858 gradiometer and G-857 base station in 2018 and the G-864 gradiometer and G857 base station in 2023. The data was collected (in all instances) by towing the gradiometer behind a snow machine around the watershed with the two sensors in a vertical profile with constant spacing during the continuous survey in that specific year. Magnetic total field measurements were collected by gradiometer and base station, and the data processing was performed in Geometrics MagMap2000 software. The processing steps were limited to removal of data spikes (despiking), reading dropouts, and correction/removal of bad GPS points. All offsets between sensors and GPS are stated within the data files and metadata, alongwith the processed and raw data. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).In this data submission there are two sets of raw magnetic data (.bin and .stn for 2018 and base for 2023; raw rover mag for 2023 is in .csv) inside two .zip files that identify the year the mag data was collected. The data are proprietary format to Geometrics and can be opened and processed with MagMap2000 which can be downloaded for free at Geometrics website. There are also two processed data files *.csv for each year and two metadata files *.csv.
Laser anemometry was used to make two independent measurements of the flow velocity by capturing individual Doppler signals with high-speed digitizing boards. The two independent measurements were cross-correlated to reduce the contribution of photo detector shot noise on the frequency determination and subsequently on the turbulence estimate. In addition, criteria were developed to eliminate "bad" Doppler bursts from the data set, which then allowed reasonable low turbulence estimates to be made. The laser anemometer measurements were obtained at the inlet of an annular cascade and at the exit of a flow calibration nozzle and were compared with hot-wire data.
As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to detect poor-quality exposures in large imaging surveys, with a focus on the DECam Legacy Survey (DECaLS) in regions of low extinction (i.e., E ( B − V ) < 0.04 ). Our semi-supervised pipeline integrates a vision transformer (ViT), trained via self-supervised learning (SSL), with a k-Nearest Neighbor (kNN) classifier. We train and validate our pipeline using a small set of labeled exposures observed by surveys with the Dark Energy Camera (DECam). A clustering-space analysis of where our pipeline places images labeled in good and bad categories suggests that our approach can efficiently and accurately determine the quality of exposures. Applied to new imaging being reduced for DECaLS Data Release 11, our pipeline identifies 780 problematic exposures, which we subsequently verify through visual inspection. Being highly efficient and adaptable, our method offers a scalable solution for quality control in other large imaging surveys.
Six Differential Microwave Radiometers (DMR) on COBE (Cosmic Background Explorer) measure the large-angular-scale isotropy of the cosmic microwave background (CMB) at 31.5, 53, and 90 GHz. Quality assurance software analyzes the daily telemetry from the spacecraft to ensure that the instrument is operating correctly and that the data are not corrupted. Quality assurance for DMR poses challenging requirements. The data are differential, so a single bad point can affect a large region of the sky, yet the CMB isotropy requires lengthy integration times (greater than 1 year) to limit potential CMB anisotropies. Celestial sources (with the exception of the moon) are not, in general, visible in the raw differential data. A 'quicklook' software system was developed that, in addition to basic plotting and limit-checking, implements a collection of data tests as well as long-term trending. Some of the key capabilities include the following: (1) stability analysis showing how well the data RMS averages down with increased data; (2) a Fourier analysis and autocorrelation routine to plot the power spectrum and confirm the presence of the 3 mK 'cosmic' dipole signal; (3) binning of the data against basic spacecraft quantities such as orbit angle; (4) long-term trending; and (5) dipole fits to confirm the spacecraft attitude azimuth angle.
An algorithm is presented which is able to locate isolated bad points and correct them without contaminating the rest of the good data. This work has been greatly influenced and motivated by what is currently done in the manual loft. It is not within the scope of this work to handle small random errors characteristic of a noisy system, and it is therefore assumed that the bad points are isolated and relatively few when compared with the total number of points. Motivated by the desire to imitate the loftsman a visual experiment was conducted to determine what is considered smooth data. This criterion is used to determine how much the data should be smoothed and to prove that this method produces such data. The method utimately converges to a set of points that lies on the polynomial that interpolates the first and last points; however convergence to such a set is definitely not the purpose of our algorithm. The proof of convergence is necessary to demonstrate that oscillation does not take place and that in a finite number of steps the method produces a set as smooth as desired.
The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. How synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather is discussed. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agricultural land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems are discussed.
This report is a follow-up study on M. Skeate’s study on System Drift Detection for Health Monitoring (Skeate, 2023). The following report highlights analyses of the panel’s behavior with extended use. This includes effects of burn-in on the panel from over-use and bad pixels (defined in Methodology.) Using data-forward statistical analyses across a sequence of scans, and given that the other conditions present in the data can be replicated, this study show that overtime use of panels does not affect bad pixel count. Also, I present conclusive evidence of a direct relationship between the regions of the panel that are exposed to radiation and burn-in damage to that region overtime. Additionally, this study also highlights the effect of the duty cycle on the dark current change in the panel.
Our Python module, colormap_module, presented here can be used to analyze and manipulate colormaps and has two main aims: (i) compare existing and new custom colormaps quantitatively by comparing their values in a color space, called CAM02-UCS, that directly shows how a human perceives their hue, saturation, and lightness values and (ii) create isoluminant colormaps from existing or custom colormaps and (iii) mix isoluminant colormap data with a 4th dimension of data by manipulating lightness values across the image and present the new image. Our module was designed to be a tool for the community to use as a whole, allowing scientists to present, analyze, and manipulate colormaps they have created and/or decided to use for a particular type of data. By being able to do this, the scientific community as a whole will think more about the colormaps they choose, see why particular colormaps are bad to use for certain types of data, and move toward using colormaps our eyes can interpret much more efficiently.
Our Python module, colormap_module, presented here can be used to analyze and manipulate colormaps and has two main aims: (i) compare existing and new custom colormaps quantitatively by comparing their values in a color space, called CAM02-UCS, that directly shows how a human perceives their hue, saturation, and lightness values and (ii) create isoluminant colormaps from existing or custom colormaps and (iii) mix isoluminant colormap data with a 4th dimension of data by manipulating lightness values across the image and present the new image. Our module was designed to be a tool for the community to use as a whole, allowing scientists to present, analyze, and manipulate colormaps they have created and/or decided to use for a particular type of data. By being able to do this, the scientific community as a whole will think more about the colormaps they choose, see why particular colormaps are bad to use for certain types of data, and move toward using colormaps our eyes can interpret much more efficiently.
The UHSAS-air is the bench version of the UHSAS that measures particle size from 0.06 to 1.0 micro-meters. Aerosol passes through a laser beam and the resulting intensity of scattered light is directly correlated to the diameter of the particle passing through the beam. This isntrument has been modified to volumetricaly control the Sheath Flow using an Alicat flow controller. Data is reported at 1.000s and missing data is reported as -9999 Multiple data flags are present in this version. Counts?: The coincident error is deemed minimal until the counts exceed 4000. Counts between 3000 and 4000 are flagged with a caution flag (1). After 4000 counts a bad flag (2) is triggered and the data should not be used. Noise?: Instrument noise detected in 65-75nm size range. 1: Caution slight noise observed. 2: High amount of noise observed data should not be used. Total? Sum of all the flags triggered Max Flag: Max flag triggered by the above QC test CloudFlag: Warns of the presence of a cloud. Clouds can cause shattering on the probe and result in questionable measurements. Data during these periods of thin clouds (1) or heavy clouds (2) should be used with extreme caution.
Electronic flat bands associated with quenched kinetic energy and heavy electron mass have attracted great interest for promoting strong electronic correlations and emergent phenomena such as high-temperature charge fractionalization and superconductivity. Intense experimental and theoretical research has been devoted to establishing the rich nontrivial metallic and heavy fermion phases intertwined with such localized electronic states. Here, in this study, we investigate the transition metal oxide spinel LiV 2 O 4 , an enigmatic heavy fermion compound lacking localized f orbital states. We use angle-resolved photoemission spectroscopy and dynamical mean-field theory to reveal a kind of correlation-induced flat band with suppressed interatomic electron hopping arising from intra-atomic Hund’s coupling. The appearance of heavy quasiparticles is ascribed to a proximate orbital-selective Mott state characterized by fluctuating local moments as evidenced by complementary magnetotransport measurements. The spectroscopic fingerprints of long-lived quasiparticles and their disappearance with increasing temperature further support the emergence of a high-temperature “bad” metal state observed in transport data. This work resolves a long-standing puzzle on the origin of heavy fermion behavior and unconventional transport in LiV 2 O 4 . Simultaneously, it opens a path to achieving flat bands through electronic interactions in d-orbital systems with geometrical frustration, potentially enabling the realization of exotic phases of matter such as the fractionalized Fermi liquids.
Water vapor imagery from the geostationary satellites such as GOES, Meteosat, and GMS provides synoptic views of dynamical events on a continual basis. Because the imagery represents a non-linear combination of mid- and upper-tropospheric thermodynamic parameters (three-dimensional variations in temperature and humidity), video loops of these image products provide enlightening views of regional flow fields, the movement of tropical and extratropical storm systems, the transfer of moisture between hemispheres and from the tropics to the mid- latitudes, and the dominance of high pressure systems over particular regions of the Earth. Despite the obvious larger scale features, the water vapor imagery contains significant image variability down to the single 8 km GOES pixel. These features can be quantitatively identified and tracked from one time to the next using various image processing techniques. Merrill et al. (1991), Hayden and Schmidt (1992), and Laurent (1993) have documented the operational procedures and capabilities of NOAA and ESOC to produce cloud and water vapor winds. These techniques employ standard correlation and template matching approaches to wind tracking and use qualitative and quantitative procedures to eliminate bad wind vectors from the wind data set. Techniques have also been developed to improve the quality of the operational winds though robust editing procedures (Hayden and Veldon 1991). These quality and control approaches have limitations, are often subjective, and constrain wind variability to be consistent with model derived wind fields. This paper describes research focused on the refinement of objective quality and control parameters for water vapor wind vector data sets. New quality and control measures are developed and employed to provide a more robust wind data set for climate analysis, data assimilation studies, as well as operational weather forecasting. The parameters are applicable to cloud-tracked winds as well with minor modifications. The improvement in winds through use of these new quality and control parameters is measured without the use of rawinsonde or modeled wind field data and compared with other approaches.