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At least 307 records · Page 17

Enriching the Twitter Stream Increasing Data Mining Yield and Quality Using Machine Learning

Social media data streams are important sources of real-time and historical global information for science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are exploring the Twitter data stream for its potential in augmenting the validation program of NASA Earth science missions, specifically the Global Precipitation Measurement (GPM) mission. We have implemented a tweet processing infrastructure that outputs classified precipitation tweets. Inputs are "passive" tweets, along with a smaller number of tweets from "active" participants, i.e., those knowingly contributing to our effort. The "active" tweets, presumably of higher quality, enrich the Twitter stream. "Active" sources include data scraped from other social media (e.g., public Facebook posts) and data from existing crowdsourcing programs (e.g., mPING reports). In addition, there is likely relevant precipitation information in images and documents that are the end points of links often included in tweets. Information derived from these "active" sources could then be tweeted into the Twitter stream, thus enriching its quality. The objective of our current work is to mine these tweet­ linked images and documents, using neural networks, to increase the information content and quality related to precipitation. For images, we classified them as either precipitation-related or not. For training and validation, we used images obtained via the Google custom search API. We created two models: (1) by training a simple Convolutional Neural Network and (2) by using transfer learning principles to adapt a pre-trained object recognition model. For documents, both those linked to tweets and the tweet contents, we trained Hierarchical Attention Networks to determine precipitation occurrence, type, and intensity. For training and validation, we used a keyword-filtered tweet data set labelled with ground truth data from Dark Sky (an API to retrieve weather-related labels) and the National Severe Storms Laboratory's Multi­ Radar/Multi-Sensor (MRMS) system. Our results demonstrated the efficacy of our machine learning approaches for enriching the Twitter stream, to derive information potentially useful for validation of earth science satellite data.

Albayrak, Arif↗

Uncertainty Analysis of Historical Hurricane Data

An analysis of variance (ANOVA) study was conducted for historical hurricane data dating back to 1851 that was obtained from the U. S. Department of Commerce National Oceanic and Atmospheric Administration (NOAA). The data set was chosen because it is a large, publicly available collection of information, exhibiting great variability which has made the forecasting of future states, from current and previous states, difficult. The availability of substantial, high-fidelity validation data, however, made for an excellent uncertainty assessment study. Several factors (independent variables) were identified from the data set, which could potentially influence the track and intensity of the storms. The values of these factors, along with the values of responses of interest (dependent variables) were extracted from the data base, and provided to a commercial software package for processing via the ANOVA technique. The primary goal of the study was to document the ANOVA modeling uncertainty and predictive errors in making predictions about hurricane location and intensity 24 to 120 hours beyond known conditions, as reported by the data set. A secondary goal was to expose the ANOVA technique to a broader community within NASA. The independent factors considered to have an influence on the hurricane track included the current and starting longitudes and latitudes (measured in degrees), and current and starting maximum sustained wind speeds (measured in knots), and the storm starting date, its current duration from its first appearance, and the current year fraction of each reading, all measured in years. The year fraction and starting date were included in order to attempt to account for long duration cyclic behaviors, such as seasonal weather patterns, and years in which the sea or atmosphere were unusually warm or cold. The effect of short duration weather patterns and ocean conditions could not be examined with the current data set. The responses analyzed were the storm latitude, longitude and intensity, as recorded in the data set, 24 or 120 hours beyond the current state. Several ANOVA modeling schemes were examined. Two forms of validation were used: 1) comparison with official hurricane prediction performance metrics and 2) cases studies conducted on hurricanes from the 2005 season, which were not included within the model construction and ANOVA assessment. In general, the ANOVA technique did not perform as well as the established official prediction performance metrics published by NOAA; still, the technique did remarkably well in this demonstration with a difficult data set and could probably be made to perform better with more knowledge of hurricane development and dynamics applied to the problem. The technique provides a repeatable prediction process that eliminates the need for judgment in the forecast.

Green, Lawrence L.↗

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗

Avoidance of disruptions on KSTAR due to vertical displacement events via novel real-time stability assessment

Disruption avoidance via the DECAF approach has been achieved on KSTAR using a novel real-time vertical stability assessment and a multiactuator feedback control strategy. The development of disruption avoidance strategies with reactor-relevant reliability is an urgent activity, enabling future fusion power plants. The stability metric employed is based on a new formulation of a vertical force gradient balance metric evaluated across the poloidal cross section of the plasma, with parameters tuned using historical data. Evaluation of this metric on a validation set of 400 recent KSTAR shots indicates >82% of Vertical displacement events can be avoided via feedback control. Essential to its calculation is the two-dimensional toroidal current density distribution in the plasma. Measurement of this profile faster than fully-converged equilibrium reconstructions can deliver is found to improve forecaster performance and is achieved with a surrogate model that takes as input magnetic diagnostic measurements and outputs the current profile on a basis comprising the top principal components of historical current profiles (from past equilibrium reconstructions). This method solves the non-uniqueness problem typically faced when reconstructing current profiles directly from diagnostics, while improving computational time and accuracy. On average, profiles produced by this model reach coefficients of determination of >0.99 with respect to those from equilibrium reconstructions. The avoidance actuators employed include poloidal field coils and an electron cyclotron current drive system. The multiactuator approach, as shown in this first demonstration, allows disruption avoidance while minimizing impact to operational performance. This ability, along with its flexibility and speed, makes this new approach an attractive option for avoiding these types of disruptions in reactors.

Tobin, Matthew [Columbia Univ., New York, NY (Unit↗

Modeling the interactions between the ocean and the environment for microwave radar sensing

An extensive set of X-band microwave backscatter measurements has been analyzed to determine its dependence on winds near the surface, atmospheric stability, and long-wave slopes. These radar measurements, made from a tower in the Gulf of Mexico, were performed in conjunction with an extensive set of simultaneous environmental measurements. The CW microwave system operated at an incidence angle of 45 deg, with antennas directed into winds and waves. Model functions for the radar cross section (RCS) and the modulation transfer function (MTF) are developed that depend on the geophysical variables, including wind stress. Statistical analysis shows that these models functions yield a significant smaller error when fit to the RCS data than a simple wind-speed function displays. A Taylor-series expansion of the returned power from a small area provides a unified function that demonstrates the complementary roles of wave slope and atmospheric fluctuations on both the RCS, the MTF, and the coherence. The issue of linearity of the MTF is addressed with this data set, yielding evidence that this is a valid assumption. These results have direct application to the remote sensing of the mean and fluctuating winds, and the wave spectrum with coherent and incoherent active radars.

Weissman, David E.↗

Analysis of positron lifetime spectra in polymers

A new procedure for analyzing multicomponent positron lifetime spectra in polymers was developed. It requires initial estimates of the lifetimes and the intensities of various components, which are readily obtainable by a standard spectrum stripping process. These initial estimates, after convolution with the timing system resolution function, are then used as the inputs for a nonlinear least squares analysis to compute the estimates that conform to a global error minimization criterion. The convolution integral uses the full experimental resolution function, in contrast to the previous studies where analytical approximations of it were utilized. These concepts were incorporated into a generalized Computer Program for Analyzing Positron Lifetime Spectra (PAPLS) in polymers. Its validity was tested using several artificially generated data sets. These data sets were also analyzed using the widely used POSITRONFIT program. In almost all cases, the PAPLS program gives closer fit to the input values. The new procedure was applied to the analysis of several lifetime spectra measured in metal ion containing Epon-828 samples. The results are described.

Singh, Jag J.↗

LDV measurements in dynamically separated flows

Two component, phase averaged mean velocity data have been obtained with an Laser Doppler Velocimeter (LDV) system, on the upper surface, near the leading edge of an oscillating airfoil undergoing compressible dynamic stall. In particular, the effect of oscillation amplitude has been studied. The results show that at an oscillation amplitude of 10 degrees, a separation bubble forms, that eventually bursts on the upstroke, well beyond the static stall angle. At 2 degrees amplitude, the bubble forms on the upstroke, but dynamic stall occurs on the downstroke. The results reveal new flow physics and the data sets serve as valuable quantitative information for validation of unsteady flow codes at transitional Reynolds numbers. The maximum velocity seen in the flow is about 1.6 times the free stream value and it occurs slightly downstream of the suction peak location. Some of the measurement difficulties are also discussed.

Chandrasekhara, M. S.↗

Data Collected During the Post-Flight Survey of Micrometeoroid and Orbital Debris Impact Features on the Hubble Wide Field Planetary Camera 2

Over a period of five weeks during the summer of 2009, personnel from the NASA's Orbital Debris Program Office and Meteoroid Environment Office performed a post-flight examination of the Hubble Space Telescope (HST) Wide Field Planetary Camera 2 (WFPC-2) radiator. The objective was to record details about all micrometeoroid and orbital debris (MMOD) impact features with diameters of 300 micron and larger. The WFPC-2 was located in a clean room at NASA's Goddard Space Flight Center. Using a digital microscope, the team examined and recorded position, diameter, and depth information for each of 685 craters. Taking advantage of the digital microscope's data storage and analysis features, the actual measurements were extracted later from the recorded images, in an office environment at the Johnson Space Center. Measurements of the crater include depth and diameter. The depth was measured from the undisturbed paint surface to the deepest point within the crater. Where features penetrate into the metal, both the depth in metal and the paint thickness were measured. In anticipation of hypervelocity tests and simulations, several diameter measurements were taken: the spall area, the area of any bare metal, the area of any discolored ("burned") metal, and the lips of the central crater. In the largest craters, the diameter of the crater at the surface of the metal was also measured. The location of each crater was recorded at the time of inspection. This paper presents the methods and results of the crater measurement effort, including the size and spatial distributions of the impact features. This effort will be followed by taking the same measurements from hypervelocity impact targets simulating the WFPC-2 radiator. Both data sets, combined with hydrocode simulation, will help validate or improve the MMOD environment in low Earth orbit.

Opiela, J. N.↗

Modeling ARRM Xenon Tank Pressurization Using 1D Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Xenon storage↗

Modeling Xenon Tank Pressurization using One-Dimensional Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Thermodynamic tank modeling↗

Boundary layer transition measured by DIT on the PSP rotor in forward flight

A well-defined reference set of data for CFD and comprehensive code validation for a scaled helicopter main rotor with boundary layer transition in forward flight is presented (Fig. 1). The boundary layer transition was measured using differential infrared thermography (DIT) on the top (suction) side of the three-bladed NASA/Army “PSP rotor”, in the NASA Langley 14- by 22-Foot Subsonic Tunnel at an advance ratio of 0.3 (115kt).

Boundary layer transistion↗

A Novel Ultrasonic Fully Reversible Bending Fatigue Test Specimen for Simulated Gear Tooth Bending Fatigue

Gears in vertical lift applications will typically experience greater than 107bending fatigue cycles over their design lifetime. Currently, fatigue life prediction of gears exceeding 107cycles are based on empirical correlations, since collection of fatigue data beyond 107 cycles is impractical with traditional fatigue testing methods. Ultrasonic fatigue testing enables fatigue testing in excess of 109cycles in as few as 14 hours. In this paper, a novel specimen design for ultrasonic fatigue testing to accurately represent the geometry, stress profile, and residual stress of gear teeth in reversible bending fatigue is presented. The specimen design is discussed in detail, testing is performed to validate operating principles, and an initial fatigue data set of 8 specimens is presented.

Single Tooth Bending Fatigue↗

A Novel Ultrasonic Fully Reversible Bending Fatigue Test Specimen for Simulated Gear Tooth Bending Fatigue

Gears in vertical lift applications will typically experience greater than 107bending fatigue cycles over their design lifetime. Currently, fatigue life prediction of gears exceeding 107cycles are based on empirical correlations, since collection of fatigue data beyond 107 cycles is impractical with traditional fatigue testing methods. Ultrasonic fatigue testing enables fatigue testing in excess of 109cycles in as few as 14 hours. In this paper, a novel specimen design for ultrasonic fatigue testing to accurately represent the geometry, stress profile, and residual stress of gear teeth in reversible bending fatigue is presented. The specimen design is discussed in detail, testing is performed to validate operating principles, and an initial fatigue data set of 8 specimens is presented.

Single Tooth Bending Fatigue↗

Kelvin waves in total column ozone

Tropical Kelvin waves have been observed previously in ozone mixing ratio data from the SBUV (Solar Backscatter Ultraviolet) and LIMS (Limb Infrared Monitor of the Stratosphere) instruments on board the Nimbus-7 satellite. The present study investigates Kelvin wave features in total column ozone, using version 6 data from the Total Ozone Mapping Spectrometer (TOMS) instrument (also on Nimbus-7). Results show eastward-propagating zonal waves 1-2 with periods approx. 5-15 days, amplitudes approx. 3-5 Dobson Units (1-2% of the time mean), and latitudinal symmetry typical of Kelvin waves. The analyses and a linear model in this study suggest that the primary source of the perturbations is slow Kelvin waves in the lower-to-middle stratosphere. Maximum Kelvin wave signatures occur in conjunction with westward lower-to-middle stratospheric equatorial zonal winds (a quasi-biennial oscillation (QBO) wind modulation effect). The significance of these results is that the TOMS data are shown to be useful for investigations with global coverage of a major component of tropical stratospheric dynamics, Kelvin waves. The TOMS data set with its excellent coverage and high quality should be useful in validating model studies in the relatively data sparse and dynamically difficult tropical region.

Ziemke, J. R.↗

Directory interchange format manual, version 4.0

The Directory Interchange Format (DIF) is a data structure used to exchange directory-level information about data sets among information systems. In general the format consists of a number of fields that describe the attributes of a directory entry and text blocks that contain a descriptive summary of and references for the directory entry. All fields and the summary are preceded by labels identifying their contents. All values are ASCII character strings. The structure is intended to be flexible, allowing for future changes in the contents of directory entries. The manual is structured as follows: section 1 is a general description of what constitutes a directory entry; section 2 describes the content of the individual fields within the data structure, together with some examples. Also included in the six appendices is a description of the syntax used within the examples; samples of the directory interchange format applied to different data sets; the allowable discipline keywords; a current list of valid location keywords; a list of allowable parameter keywords; a list of acronyns and a glossary of terms used; and a description of the Standard Formatted Data Unit header, which may be added to the front of a DIF file to identify the file as a registered standard format.

Source record↗

In Situ Validation of the Soil Moisture Active Passive (SMAP) Satellite Mission

SMAP is a new NASA mission proposed for 2014 that would provide a number of soil moisture and freeze/thaw products. The soil moisture products span spatial resolutions from 3 to 40 km. In situ soil moisture observations will be one of the key elements of the validation program for SMAP. Data from the currently available set of soil moisture observing sites and networks need improvement if they are to be useful. Problems include a lack of standardization of instrumentation and installation and the disparity in spatial scale between the point-scale in situ data (a few centimeters) and the coarser satellite products. SMAP has initiated activities to resolve these issues for some of the existing resources. The other challenge to soil moisture validation is the need to expand the number of sites and their geographic distribution. SMAP is attempting to increase the number of sites and their value in validation through collaboration. The issues and solutions involving in situ validation being investigated will be described along with recent results from SMAP validation projects.

validation↗

Generating Ground Reference Data for a Global Impervious Surface Survey

We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or nonimpervious.

Image Processing↗