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TPA computer program developed to balance turbine and pump work using performance maps. Requires input data on inlet properties, performance maps, and shaft speed. TPA then computes exit conditions and work terms. Work terms then balanced by varying input shaft speed. Written in FORTRAN 77.
Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based file systems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.
Many information sources can support air quality assessment and forecasting, including atmospheric chemistry model outputs, satellite retrievals of column chemical and aerosol constituents, and surface-based air quality monitoring data from both regulatory and low-cost instruments. Systematic integration of these data sources provides a major opportunity to improve understanding and management of air quality, but also presents technical barriers, especially in resource- and data-constrained settings in the Global South. This presentation describes a data fusion system, currently under development using the Google Earth Engine platform, which aims to integrate the information sources listed above to support comprehensive sub-city-scale assessment and management of air quality. Furthermore, the data fusion framework includes provisions for the quantification of uncertainties in the resulting fused estimates based on the variability of and among the input data sources. These capabilities will allow air quality managers to better understand their local air quality situation, including relative confidence in the fused estimates for different constituents, locations, and times, leading to better informed air quality management decisions. This presentation covers the underlying methodology of the data fusion and uncertainty quantification approaches, provides an update on the status of its implementation, and presents early qualitative and quantitative results.
The Delta-T Processor (DTP) computes the instantaneous downtrack error in a specified orbiter onboard navigation state vector recovered via downlink telemetry. The downtrack error, expressed in units of time, is computed based on current incoming Earth based range and Doppler navigation tracking data and the ground selected onboard navigation state vector. The computed time difference when used to modify the timetag of the vector used for onboard navigation reduces the instantaneous downtrack error in this vector to within the threshold of the DTP, the input data, and the onboard software. This threshold is currently estimated to be approximately 2 to 4 nautical miles. The DTP is not restricted to using only onboard vectors. Any vector, either input via the manual entry device or accessible via the vector administration table, may be used. The DTP does not require that both data types be available.
A detailed description of the Langley computer program PLOTWD which plots and fairs experimental wind-tunnel data is presented. The program was written for use primarily on the Langley CDC computer and CALCOMP plotters. The fundamental operating features of the program are that the input data are read and written to a random-access file for use during program execution, that the data for a selected run can be sorted and edited to delete duplicate points, and that the data can be plotted and faired using tension splines, least-squares polynomial, or least-squares cubic-spline curves. The most noteworthy feature of the program is the simplicity of the user-supplied input requirements. Several subroutines are also included that can be used to draw grid lines, zero lines, axis scale values and lables, and legends. A detailed description of the program operational features and each sub-program are presented. The general application of the program is also discussed together with the input and output for two typical plot types. A listing of the program code, user-guide, and output description are presented in appendices. The program has been in use at Langley for several years and has proven to be both easy to use and versatile.
A parameter-extraction algorithm was used to determine the lateral aerodynamic derivatives from flight data for the F-8 aircraft with supercritical wing. The flight data used were the recorded responses to aileron or rudder pulses for Mach numbers of 0.80, 0.90, and 0.98. Results of this study showed that a set of derivatives were determined which yielded a calculated aircraft response almost identical with the response measured in flight. Derivatives extracted from motion resulting from rudder inputs were somewhat different from those resulting from aileron inputs. It was found that the derivatives obtained from the rudder-input data were highly correlated in some instances. Those from the aileron input had very low correlations and appeared to be the more reliable.
Since the publication of the Computer User's Manual for Payload Acoustics Environment for Shuttle (PACES), the analytical model was validated by means of measured data from the first three shuttle lift-offs. During the validation process, new information became available and five changes were made to the input data and the computer program. Three changes affect the user. They are: a revision to the recommended exterior sound pressure levels, a revision to the recommended payload bay acoustic absorption coefficients, and a revision to the vertical station datum for the payload bay. The two other changes do not involve the user. The changes are associated with the output of confidence limits for the predicted space-average sound pressure levels in the payload bay, and a modification to the analytical representation of the payload bay door. The changes are discussed briefly in this Addendum to the Computer User's Manual.
The development and deployment of data processing systems to process Earth Observing System (EOS) data has proven to be costly and prone to technical and schedule risk. Integration of science algorithms into a robust operational system has been difficult. The core processing system, based on commercial tools, has demonstrated limitations at the rates needed to produce the several terabytes per day for EOS, primarily due to job management overhead. This has motivated an evolution in the EOS Data Information System toward a more distributed one incorporating Science Investigator-led Processing Systems (SIPS). As part of this evolution, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has developed a simplified processing system to accommodate the increased load expected with the advent of reprocessing and launch of a second satellite. This system, the Simple, Scalable, Script-based Science Processor (S42) may also serve as a resource for future SIPS. The current EOSDIS Core System was designed to be general, resulting in a large, complex mix of commercial and custom software. In contrast, many simpler systems, such as the EROS Data Center AVHRR IKM system, rely on a simple directory structure to drive processing, with directories representing different stages of production. The system passes input data to a directory, and the output data is placed in a "downstream" directory. The GES DAAC's Simple Scalable Script-based Science Processing System is based on the latter concept, but with modifications to allow varied science algorithms and improve portability. It uses a factory assembly-line paradigm: when work orders arrive at a station, an executable is run, and output work orders are sent to downstream stations. The stations are implemented as UNIX directories, while work orders are simple ASCII files. The core S4P infrastructure consists of a Perl program called stationmaster, which detects newly arrived work orders and forks a job to run the appropriate executable (registered in a configuration file for that station). Although S4P is written in Perl, the executables associated with a station can be any program that can be run from the command line, i.e., non-interactively. An S4P instance is typically monitored using a simple Graphical User Interface. However, the reliance of S4P on UNIX files and directories also allows visibility into the state of stations and jobs using standard operating system commands, permitting remote monitor/control over low-bandwidth connections. S4P is being used as the foundation for several small- to medium-size systems for data mining, on-demand subsetting, processing of direct broadcast Moderate Resolution Imaging Spectroradiometer (MODIS) data, and Quick-Response MODIS processing. It has also been used to implement a large-scale system to process MODIS Level 1 and Level 2 Standard Products, which will ultimately process close to 2 TB/day.
Quantification of spatially and temporally resolved water flows and water storage variations for all land areas of the globe is required to assess water resources, water scarcity and flood hazards, and to understand the Earth system. This quantification is done with the help of global hydrological models (GHMs). What are the challenges and prospects in the development and application of GHMs? Seven important challenges are presented. (1) Data scarcity makes quantification of human water use difficult even though significant progress has been achieved in the last decade. (2) Uncertainty of meteorological input data strongly affects model outputs. (3) The reaction of vegetation to changing climate and CO2 concentrations is uncertain and not taken into account in most GHMs that serve to estimate climate change impacts. (4) Reasons for discrepant responses of GHMs to changing climate have yet to be identified. (5) More accurate estimates of monthly time series of water availability and use are needed to provide good indicators of water scarcity. (6) Integration of gradient-based groundwater modelling into GHMs is necessary for a better simulation of groundwater-surface water interactions and capillary rise. (7) Detection and attribution of human interference with freshwater systems by using GHMs are constrained by data of insufficient quality but also GHM uncertainty itself. Regarding prospects for progress, we propose to decrease the uncertainty of GHM output by making better use of in situ and remotely sensed observations of output variables such as river discharge or total water storage variations by multi-criteria validation, calibration or data assimilation. Finally, we present an initiative that works towards the vision of hyper resolution global hydrological modelling where GHM outputs would be provided at a 1-km resolution with reasonable accuracy.
The Kepler Mission was launched in 2009 as NASAs first mission capable of finding Earth-size planets in the habitable zone of Sun-like stars. Its telescope consists of a 1.5-m primary mirror and a 0.95-m aperture. The 42 charge-coupled devices in its focal plane are read out every half hour, compressed, and then downlinked monthly. After four years, the second of four reaction wheels failed, ending the original mission. Back on earth, the Science Operations Center developed the Science Pipeline to analyze about 200,000 target stars in Keplers field of view, looking for evidence of periodic dimming suggesting that one or more planets had crossed the face of its host star. The Pipeline comprises several steps, from pixel-level calibration, through noise and artifact removal, to detection of transit-like signals and the construction of a suite of diagnostic tests to guard against false positives. The Kepler Science Pipeline consists of a pipeline infrastructure written in the Java programming language, which marshals data input to and output from MATLAB applications that are executed as external processes. The pipeline modules, which underwent continuous development and refinement even after data started arriving, employ several analytic techniques, many developed for the Kepler Project. Because of the large number of targets, the large amount of data per target and the complexity of the pipeline algorithms, the processing demands are daunting. Some pipeline modules require days to weeks to process all of their targets, even when run on NASA's 128-node Pleiades supercomputer. The software developers are still seeking ways to increase the throughput. To date, the Kepler project has discovered more than 4000 planetary candidates, of which more than 1000 have been independently confirmed or validated to be exoplanets. Funding for this mission is provided by NASAs Science Mission Directorate.
Techniques for recovering atmospheric refractivity profiles from simulated satellite-to-satellite tracking data are documented. Examples are given using the geometric configuration of the ATS-6/NIMBUS-6 Tracking Experiment. The underlying refractivity model for the lower atmosphere has the spherically symmetric form N = exp P(s) where P(s) is a polynomial in the normalized height s. For the simulation used, the Herglotz-Wiechert technique recovered values which were 0.4% and 40% different from the input values at the surface and at a height of 33 kilometers, respectively. Using the same input data, the model fitting technique recovered refractivity values 0.05% and 1% different from the input values at the surface and at a height of 50 kilometers, respectively. It is also shown that if ionospheric and water vapor effects can be properly modelled or effectively removed from the data, pressure and temperature distributions can be obtained.
The description of a transient analysis program for computing structural responses to input base accelerations is presented. A hybrid modal formulation is used and a procedure is demonstrated for generating and writing all modal input data on user tapes via NASTRAN. Use of several new Level 15 modules is illustrated along with a problem associated with reading the postprocessor program input from a user tape. An example application of the program is presented for the analysis of a spacecraft subjected to accelerations initiated by thrust transients. Experience with the program has indicated it to be very efficient and economical because of its simplicity and small central memory storage requirements.
The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.
One SA-3 missile was disassembled. The constituents of the second stage were thoroughly investigated for geometrical details. The second stage slotted composite propellant grain was subjected to mechanical properties testing, physiochemical analyses, and burning rate measurements at different conditions. To determine the propellant performance parameters, the slotted composite propellant grain was machined into a set of small-size tubular grains. These grains were fired in a small size rocket motor with a set of interchangeable nozzles with different throat diameters. The firings were carried out at three different conditions. The data from test motor firings, physiochemical properties of the propellant, burning rate measurement results and geometrical details of the second stage motor, were used as input data in a computer program to compute the internal ballistic characteristics of the second stage.
Computational method estimates weight of aircraft wings from theoretical relationships and empirical data. Permits comparison of alternative materials, methods of construction, and design philosophies. Method used to make tradeoffs in preliminary design phases on basis of simple input data and for more accurate calculations in later phases when more data are available.
A laser based method was employed to measure and numerically describe the architecture of a corn canopy. Use of the method provides an interception coefficient for classes of vegetation in layers of the canopy viewed in various directions. Architectural data obtained for similar corn canopies but measured by differing methods are comparable to the results obtained using the laser based method. These results provide input data to mathematical models employed in remote sensing for describing the radiation environment in a plant canopy and predicting its reflectance.
A comprehensive description of user problem definition for the PAN AIR (Panel Aerodynamics) system is given. PAN AIR solves the 3-D linear integral equations of subsonic and supersonic flow. Influence coefficient methods are used which employ source and doublet panels as boundary surfaces. Both analysis and design boundary conditions can be used. This User's Manual describes the information needed to use the PAN AIR system. The structure and organization of PAN AIR are described, including the job control and module execution control languages for execution of the program system. The engineering input data are described, including the mathematical and physical modeling requirements. Version 3.0 strictly applies only to PAN AIR version 3.0. The major revisions include: (1) inputs and guidelines for the new FDP module (which calculates streamlines and offbody points); (2) nine new class 1 and class 2 boundary conditions to cover commonly used modeling practices, in particular the vorticity matching Kutta condition; (3) use of the CRAY solid state Storage Device (SSD); and (4) incorporation of errata and typo's together with additional explanation and guidelines.
ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.