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This data set is based on the GTOPO30 Digital Elevation Model (DEM) produced by the United States Geological Survey EROS Data Center (USGS EDC). The BOReal Ecosystem-Atmosphere Study (BOREAS) region (1,000 km x 1000 km) was extracted from the GTOPO30 data and reprojected by BOREAS staff into the Albers Equal-Area Conic (AEAC) projection. The pixel size of these data is 1 km. The data are stored in binary, image format files.
The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.
This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.
National databases that collect various kinds of textual threat reports such as ASRS, CERT, and NVD manually process their reports individually. They then offer data products to disseminate the aggregate information, like newsletters, alerts or individual report searching. The goal of this research is to connect these individual reports thematically and temporally to identify emerging or recurring threats, by analyzing large collections of text, source code, collaboration and communication patterns. This capability, I argue, enables us to identify the emergence and recurrence of such themes, and the contexts in which they re-occur, facilitating faster and more capable mitigation. I propose two models to shed light on this goal: An empirical model of vulnerabilities as bugs, the commit flow model, and one of the vulnerabilities and aviation safety threats as topics, the topic flow model. I use as gold standard existing manual workflows in both domains, reflected in the existing data products by these organizations, and empirically evaluate if the automated model scan match or outperform existing manual practices.
Soil moisture reflects the amount of water available to crops in the top layer of soil. As such, considering soil moisture provides important insight into water availability and ultimately crop yields in agricultural settings. In studies of climate change, food security, and health, however, soil moisture is rarely empirically considered despite its connection to crop health and yields. In this project, we aim to advance understanding of climate impacts on food security by incorporating soil moisture into quantitative models of child health. Combining spatially referenced health survey data from the Demographic and Health Surveys for 2005 and 2010 in Senegal and 2007, 2011, and 2014 in Bangladesh, with soil moisture data from the Famine Early Warning System Network Land Data Assimilation System, we explore the linkages between sub-annual and sub-seasonal climate conditions and child malnutrition in two rainfed agriculture dependent countries—Bangladesh and Senegal. Results suggest that soil moisture, measured on very short time scales, may be associated with reductions in anthropometric weight-for-height z-scores, but the relationship is highly dependent upon geographic context.
The National Aeronautics and Space Administration (NASA) plans to conduct surveys of community response to quiet supersonic flight to collect dose-response data for international regulators. Previous models of noise dose versus annoyance response ignored uncertainty in the noise dose experienced by survey respondents. This dose error causes attenuation bias and results in inaccurate dose-response relationships. The impacts of dose errors can be explored by introducing error into the dose estimates of a simulated community noise survey. The simulated population annoyance response is determined by specific noise response characteristics, including the onset of annoyance intercept, rate of increasing annoyance, participant intercept variability, and response rates. This paper explores the effects of dose errors on notional populations created by perturbing the noise response characteristics observed in participants in a recent NASA flight test, QSF18. The QSF18-based population parameters were shifted up to ±20% to create the study populations. For the anticipated dose range of the X-59, changes to the onset of annoyance intercept have the greatest impact on erroneous model results. Quantifying point estimate errors illustrates the impact of dose error, with errors up to 14 dB observed for a fixed high annoyance percentage.
The National Aeronautics and Space Administration (NASA) plans to conduct surveys of community response to quiet supersonic flight to collect dose-response data for international regulators. Previous models of noise dose versus annoyance response ignored uncertainty in the noise dose experienced by survey respondents. This dose error causes attenuation bias and results in inaccurate dose-response relationships. The impacts of dose errors can be explored by introducing error into the dose estimates of a simulated community noise survey. The simulated population annoyance response is determined by specific noise response characteristics, including the onset of annoyance intercept, rate of increasing annoyance, participant intercept variability, and response rates. This paper explores the effects of dose errors on notional populations created by perturbing the noise response characteristics observed in participants in a recent NASA flight test, QSF18. The QSF18-based population parameters were shifted up to ±20% to create the study populations. For the anticipated dose range of the X-59, changes to the onset of annoyance intercept have the greatest impact on erroneous model results. Quantifying point estimate errors illustrates the impact of dose error, with errors up to 14 dB observed for a fixed high annoyance percentage.
The performance of two externally blown flap (EBF) wind tunnel models was compared with an engine exhaust flap impingement correlation parameter. One model was a four engine EBF triple slotted flap transport. Isolated engine wake surveys were conducted to define the wake properties of five separate engine configurations for which performance data were available. The other model was a two engine EBF transport for which the engine wake properties were estimated. The correlation parameter was a function of engine exhaust dynamic pressure at the flap location, area of engine exhaust flap impingement, total exhaust area at the flap location, and engine thrust. The distribution of dynamic pressure for the first model was measured; however, the distribution for the second model was assumed to be uniform.
Engineering prediction methods with the capability to calculate induced effects of lee-side separation vorticity associated with circular and noncircular missiles at high angles of attack in supersonic flow are compared. Methods of interest include a discrete vortex cloud technique, concentrated vortex models, and solutions of Euler's equations with specified separation. Comparison of measured and predicted surface pressure distributions and flow field surveys are presented for bodies with circular and elliptic cross sections. Two flow models for computing lee-side vortex-induced effects on control fins in the vicinity of the vortex field are examined, and suggestions regarding the appropriate flow model for specific situations are included.
An assessment of APNASA was conducted at NASA Glenn Research Center under the Fundamental Aeronautics Program to determine their predictive capabilities. The geometry selected for this study was Stage 35 which is a single stage transonic compressor. A speedline at 100% speed was generated and compared to experimental data at 100% speed for two turbulence models. Performance of the stage at 100% speed and profiles of several key aerodynamic parameters are compared to the survey data downstream of the stator in this report. In addition, hub leakage was modeled and compared to solutions without leakage and the available experimental data.
A critical task involved with being able to predict flight loads accurately in aerospace finite element models (FEMs) is the prior verification of the FEMs by conducting modal survey testing (MST). Experience comparing dynamic response of initial FEMs to MST data tends to demonstrate that FEMs can have unacceptable accuracy even when best modeling practices are followed. One inherent source of inaccuracy in linear dynamic FEMs is the modeling of nonlinear joints with mechanisms such as spherical bearings. These joints are usually designed to freely translate or rotate under the high levels of loading experienced in flight. Engineers who create linear FEMs conventionally model these joints without any stiffness in the mechanism degrees of freedom to meet this design intent. However, inaccuracy is observed during test validation of these FEMs, which usually relies on low-level force excitation orders of magnitude below flight load levels. This low-level modal test rarely overcomes the joint friction that is present, and thus the mechanism joints are able to react loads. This divide between the test results and the FEM creates a significant challenge to the engineer who is performing the correlation, in that the engineer has no basis for what stiffness value should be used to make the FEM match the test results. A compounding challenge is that complicated built-up aerospace structures commonly have multiple joints through a load path where each joint will “stick” and “slip” at different levels of force input. Explicitly matching the dynamics of a system containing these nonlinear mechanisms would require a nonlinear FEM, which is prohibitively costly for dynamic simulations of most aerospace systems. The objective of this paper is to present a workflow that can efficiently cycle through many iterations of a FEM, allowing a Monte Carlo style examination of the design space to identify candidate stiffness values for nonlinear mechanism joints. The outlined approach is specific to MSC Nastran and utilizes MSC Nastran’s symbolic substitution capabilities, coupled with the IMAT™ and Attune™ software packages developed by ATA Engineering, Inc. (ATA). The workflow is demonstrated with a case study from the correlation effort for The Boeing Company’s Crew Space Transportation (CST)-100 Starliner FEM. Keywords: Correlation, MSC Nastran, IMAT™, Attune™, Finite Element Model, Modal Testing
The potential uses of remotely sensed data as applied to the transportation planning process are presented. By utilizing the remote sensing technology developed by the National Aeronautics and Space Administration in the various space programs, it is hoped that both the expense and errors inherent in the conventional data collection techniques can be avoided. Additional bonuses derived from the use of remotely sensed data are those of the permanent record nature of the data and the traffic engineering data simultaneously made available. The major mathematical modeling phases and the role remotely sensed data might play in replacing conventionally collected data are discussed. Typical surveys undertaken in the overall planning process determine the nature and extent of travel desires, land uses, transportation facilities and socio-economic characteristics. Except for the socio-economic data, data collected in the other surveys mentioned can be taken from photographs in sufficient detail to be useful in the modeling procedures.
We have discovered five millisecond pulsars (MSPs) in a survey of 14 unidentified Ferm;'LAT sources in the southern sky using the Parkes radio telescope. PSRs J0101-6422, J1514-4946, and J1902-5105 reside in binaries, while PSRs J1658-5324 and J1747-4036 are isolated. Using an ephemeris derived from timing observations of PSR JOl01-6422 (P=2.57ms, DH=12pc/cubic cm ), we have detected gamma-ray pulsations and measured its proper motion. Its gamma-ray spectrum (a power law of Gamma = 0.9 with a cutoff at 1.6 GeV) and efficiency are typical of other MSPs, but its radio and gamma-ray light curves challenge simple geometric models of emission. The high success rate of this survey -- enabled by selecting gamma-ray sources based on their detailed spectral characteristics -- and other similarly successful searches indicate that a substantial fraction of the local population of MSPs may soon be known.
In October 1997, the 6-ton robotic spacecraft, Cassini, will lift off from Cape Canaveral atop a Titan IV B rocket, beginning a 7-year journey to Saturn. Upon completion of that voyage, Cassini will send the Huygens probe into the atmosphere of Saturn's largest moon, Titan. Cassini will then spend years studying Saturn's vast realm of rings, icy moons, and magnetic fields. The size and complexity of this endeavor mandates the involvement of many organizations. The Jet Propulsion Laboratory (JPL) manages the project for NASA and is responsible for the spacecraft design, development, and assembly. The NASA Lewis Research Center is the launch system integrator. As is typical for such a spacecraft, a test-verified finite element model is required for loads analysis. JPL had responsibility for the Cassini modal survey and the development of the spacecraft test-verified finite element model. Test verification is a complex and sometimes subjective process. Because of this, NASA Lewis independently verified and validated the Cassini spacecraft modal survey.
Methods to improve the performance of reflux heat pipes for heat recovery applications were examined both analytically and experimentally. Various models for the estimation of reflux heat pipe transport capacity were surveyed in the literature and compared with experimental data. A high transport capacity reflux heat pipe was developed that provides up to a factor of 10 capacity improvement over conventional open tube designs; analytical models were developed for this device and incorporated into a computer program HPIPE. Good agreement of the model predictions with data for R-11 and benzene reflux heat pipes was obtained.
Factors influencing effective program planning for V/STOL wind-tunnel testing are discussed. The planning sequence itself, which includes a short checklist of considerations that could enhance the value of the tests, is also described. Each of the considerations, choice of wind tunnel, type of model installation, model development and test operations, is discussed, and examples of appropriate past and current V/STOL test programs are provided. A short survey of the moderate to large subsonic wind tunnels is followed by a review of several model installations, from two-dimensional to large-scale models of complete aircraft configurations. Model sizing, power simulation, and planning are treated, including three areas is test operations: data-acquisition systems, acoustic measurements in wind tunnels, and flow surveying.
Spacecraft trend analysis is a vital mission operations function performed by satellite controllers and engineers, who perform detailed analyses of engineering telemetry data to diagnose subsystem faults and to detect trends that may potentially lead to degraded subsystem performance or failure in the future. It is this latter function that is of greatest importance, for careful trending can often predict or detect events that may lead to a spacecraft's entry into safe-hold. Early prediction and detection of such events could result in the avoidance of, or rapid return to service from, spacecraft safing, which not only results in reduced recovery costs but also in a higher overall level of service for the satellite system. Contemporary spacecraft trending activities are manually intensive and are primarily performed diagnostically after a fault occurs, rather than proactively to predict its occurrence. They also tend to rely on information systems and software that are oudated when compared to current technologies. When coupled with the fact that flight operations teams often have limited resources, proactive trending opportunities are limited, and detailed trend analysis is often reserved for critical responses to safe holds or other on-orbit events such as maneuvers. While the contemporary trend analysis approach has sufficed for current single-spacecraft operations, it will be unfeasible for NASA's planned and proposed space science constellations. Missions such as the Dynamics, Reconnection and Configuration Observatory (DRACO), for example, are planning to launch as many as 100 'nanospacecraft' to form a homogenous constellation. A simple extrapolation of resources and manpower based on single-spacecraft operations suggests that trending for such a large spacecraft fleet will be unmanageable, unwieldy, and cost-prohibitive. It is therefore imperative that an approach to automating the spacecraft trend analysis function be studied, developed, and applied to missions such as DRACO with the intent that mission operations costs be significantly reduced. The goal of the Constellation Spacecraft Trend Analysis Toolkit (CSTAT) project is to serve as the pathfinder for a fully automated trending system to support spacecraft constellations. The development approach to be taken is evolutionary. In the first year of the project, the intent is to significantly advance the state of the art in current trending systems through improved functionality and increased automation. In the second year, the intent is to add an expert system shell, likely through the adaptation of an existing commercial-off-the-shelf (COTS) or government-off-the-shelf (GOTS) tool to implement some level of the trending intelligence that humans currently provide in manual operations. In the third year, the intent is to infuse the resulting technology into a near-term constellation or formation-flying mission to test it and gain experience in automated trending. The lessons learned from the real missions operations experience will then be used to improve the system, and to ultimately incorporate it into a fully autonomous, closed-loop mission operations system that is truly capable of supporting large constellations. In this paper, the process of automating trend analysis for spacecraft constellations will be addressed. First, the results of a survey on automation in spacecraft mission operations in general, and in trending systems in particular will be presented to provide an overview of the current state of the art. Next, a rule-based model for implementing intelligent spacecraft subsystem trending will be then presented, followed by a survey of existing COTS/GOTS tools that could be adapted for implementing such a model. The baseline design and architecture of the CSTAT system will be presented. Finally, some results obtained from initial software tests and demonstrations will be presented.
Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.