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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding performance variability in standard and pipelined parallel Krylov solvers

In this work, we collect data from runs of Krylov subspace methods and pipelined Krylov algorithms in an effort to understand and model the impact of machine noise and other sources of variability on performance. We find large variability of Krylov iterations between compute nodes for standard methods that is reduced in pipelined algorithms, directly supporting conjecture, as well as large variation between statistical distributions of runtimes across iterations. Based on these results, we improve upon a previously introduced nondeterministic performance model by allowing iterations to fluctuate over time. We present our data from runs of various Krylov algorithms across multiple platforms as well as our updated non-stationary model that provides good agreement with observations. We also suggest how it can be used as a predictive tool.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Characteristics, of TIROS, GOES, DMSP and LANDSAT Systems

The characteristics of the TIROS, GOES, DMSP and LANDSAT systems of satellites are described. The data listed for each system are altitude of orbit, inclination/position, orbit type, orbits per day, expected operational lifetime and the sensor systems. The sensor systems are described as to wavelength of each channel, resolution, field of view and other pertinent information. Data information such as availability rate, collection method, primary use/application and how to obtain additional information is also given.

Gray, T. I., Jr.↗
NASA NTRS1983

Computing Graphical Confidence Bounds

Approximation for graphical confidence bounds is simple enough to run on programmable calculator. Approximation is used in lieu of numerical tables not always available, and exact calculations, which often require rather sizable computer resources. Approximation verified for collection of up to 50 data points. Method used to analyze tile-strength data on Space Shuttle thermal-protection system.

Mezzacappa, M. A.↗
NASA NTRS1984

X-29 flight-research program

The X-29A aircraft is the first manned, experimental high-performance aircraft to be fabricated and flown in many years. The approach for expanding the X-29 flight envelope and collecting research data is described including the methods for monitoring wind divergence, flutter, and aeroservoelastic coupling of the aerodynamic forces with the structure and the flight-control system. Examples of the type of flight data to be acquired are presented along with types of aircraft maneuvers that will be flown. A brief description of the program management structure is also presented and the program schedule is discussed.

Putnam, T. W.↗
NASA NTRS1983

X-29 flight research program

The X-29A aircraft is the first manned, experimental high-performance aircraft to be fabricated and flown in many years. The approach for expanding the X-29 flight envelope and collecting research data is described including the methods for monitoring wing divergence, flutter, and aeroservoelastic coupling of the aerodynamic forces with the structure and the flight-control system. Examples of the type of flight data to be acquired are presented along with types of aircraft maneuvers that will be flown. A brief description of the program management structure is also presented and the program schedule is discussed.

Putnam, T. W.↗
NASA NTRS1987

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.-S.↗
NASA NTRS1987

Predictability of process resource usage: A measurement-based study of UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗
NASA NTRS1989

Predictability of process resource usage - A measurement-based study on UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗
NASA NTRS2004

Variable Stiffness Spar Wind-Tunnel Model Development and Testing

The concept of exploiting wing flexibility to improve aerodynamic performance was investigated in the wind tunnel by employing multiple control surfaces and by varying wing structural stiffness via a Variable Stiffness Spar (VSS) mechanism. High design loads compromised the VSS effectiveness because the aerodynamic wind-tunnel model was much stiffer than desired in order to meet the strength requirements. Results from tests of the model include stiffness and modal data, model deformation data, aerodynamic loads, static control surface derivatives, and fuselage standoff pressure data. Effects of the VSS on the stiffness and modal characteristics, lift curve slope, and control surface effectiveness are discussed. The VSS had the most effect on the rolling moment generated by the leading-edge outboard flap at subsonic speeds. The effects of the VSS for the other control surfaces and speed regimes were less. The difficulties encountered and the ability of the VSS to alter the aeroelastic characteristics of the wing emphasize the need for the development of improved design and construction methods for static aeroelastic models. The data collected and presented is valuable in terms of understanding static aeroelastic wind-tunnel model development.

Florance, James R.↗
NASA NTRS2006

PSD Determination using a Simultaneous-Phase Acquisition Interferometer for the Constellation-X Spectroscopy X-ray Telescope (SXT) Mirrors

We investigated the use of a simultaneous-phase acquisition interferometer (a 4D FizCamTM 1500) for determining the PSD of the extremely-high aspect ratio (500: 1) glass mirrors for the Constellation-X SXT telescope. We found that the results obtained are strongly influenced by the methodology employed while collecting the data and outline a best method for this type of measurement.

Lehan, J. P.↗
NASA NTRS2016

Search for Transient Gravitational Waves in Coincidence with Short-Duration Radio Transients During 2007-2013

We present an archival search for transient gravitational-wave bursts in coincidence with 27 single-pulse triggers from Green Bank Telescope pulsar surveys, using the LIGO (Laser Interferometer Gravitational Wave Observatory), Virgo (Variability of Solar Irradiance and Gravity Oscillations) and GEO (German-UK Interferometric Detector) interferometer network. We also discuss a check for gravitational-wave signals in coincidence with Parkes fast radio bursts using similar methods. Data analyzed in these searches were collected between 2007 and 2013. Possible sources of emission of both short-duration radio signals and transient gravitational-wave emission include star quakes on neutron stars, binary coalescence of neutron stars, and cosmic string cusps. While no evidence for gravitational-wave emission in coincidence with these radio transients was found, the current analysis serves as a prototype for similar future searches using more sensitive second-generation interferometers.

Abbott, B. P.↗
NASA NTRS2010

Application of Ensemble Detection and Analysis to Modeling Uncertainty in Non Stationary Process

Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.

Racette, Paul↗
NASA NTRS2018

Extraction of Doppler Observables from Open-Loop Recordings for the Juno Radio Science Investigation

The goal of the Juno Gravity Science investigation is to estimate the gravitational field of Jupiter by measurement of the spacecraft velocity during periods of closest approach. Velocity is measured by the Doppler shift of dual X- and Ka-band radio links between the Juno spacecraft, in orbit around Jupiter, and the DSS-25 antenna of the Deep Space Network (DSN). During times of closest-approach, Juno experiences large dynamic ranges caused by the orbital dynamics and spin signatures caused by the spin-stabilized spacecraft that are detectable by the receivers at DSS-25. Open-loop recordings of received voltages are processed to compute Doppler observables utilized in the estimation of the gravity field. Presented is a method to process open-loop data collected by the DSN to compensate for the spin signature of the spacecraft, removal of artifacts from Doppler observables caused by the high dynamic environment, and improve performance of the digital phase-locked loop utilized in the data processing.

Buccino, Dustin R.↗
NASA NTRSDate not supplied

Sparse Linear Algebra Toolkit for Computational Aerodynamics

Finding solutions to sparse linear systems of equations is an essential step in Computational Engineering applications of interest to NASA. Linear systems of equations are composed and solved in almost every computational engineering application. The characteristics of linear systems vary greatly from one application to another. Accordingly, there are a wide variety of methods for the solution of linear systems of equations. The operations and methods prepared by the authors are focused on linear systems of interest to NASA, primarily those associated with Computational Fluid Dynamics (CFD), Aeroelasticity, and Aeroacoustics. The Sparse Linear Algebra Toolkit (SLAT) is a coordinated collection of software featuring operations, methods, and data structures that are useful when solving sparse linear systems of equations on modern computer architectures. The implemented operations and methods are designed and tuned for parallelism in shared memory, in distributed memory, and across the hybrid combination of distributed-shared memory. The toolkit includes novel methods and implementations for modern architectures and facilitates development of new approaches for meeting NASA’s evolving computational engineering challenges using evolving computer architectures that are not available in vendor libraries. In this paper, significant features and interfaces within SLAT are presented and verified for simulations performed with NASA’s CFD solver, FUN3D. The runtime and scaling performance of the Generalized Minimum Residual (GMRES) method implemented in SLAT is analyzed for the linear subproblems within the solution of turbulent Navier-Stokes equations employed in the simulation of high-lift configurations. Prior to this work, the SPARSKIT GMRES implementation was the only Krylov subspace method available within FUN3D. A strong scaling study shows the SLAT GMRES implementation facilitates accurate Reynolds-averaged Navier-Stokes CFD solutions between 15% and 56% faster than the SPARSKIT GMRES implementation.

Stephen L Wood↗
DOE OSTI2020

Machine-Learning-Driven, Site-Specific Weather Forecasting for Grid-Interactive Efficient Buildings: Preprint

Emerging grid-interactive efficient buildings (GEBs) have great potential to provide much-needed demand flexibility to electric grids while fulfilling their own control targets by co-optimizing smart appliances, solar photovoltaics, electric vehicles, and energy storage at buildings. To enable the optimal operation of GEBs, site-specific weather information—such as temperature, solar irradiance, relative humidity, and wind speed—is crucial; however, this information is generally unavailable or expensive to obtain. This paper develops advanced machine learning methods to provide precise weather forecasts for individual building sites using readily available weather station data. Support vector regression and artificial neural networks have been employed to learn the spatiotemporal correlations between the weather conditions at nearby weather stations and the individual building site. The proposed site-specific weather forecasting methods have been validated using 1-year actual weather measurement data collected in the Denver metro area. Results show that the developed machine-learning-driven methods can accurately forecast the temperature at the target building site 1 hour ahead with mean absolute error less than 0.72°C and a 48% improvement over the persistence method. Site-specific weather forecasts will improve the understanding of the microclimate effect and its impact on building energy consumption. This information will drive efficiency upgrades and adjustments of building control strategies to improve energy savings and increase flexibility in building loads.

30 DIRECT ENERGY CONVERSION↗
NASA NTRSDate not supplied

Cross-Measurement Comparisons for a CFD Validation Dataset on Mach 2.5 Axisymmetric Turbulent Shock-Wave/Boundary-Layer Interactions

Experimental data for a shock-wave/boundary-layer interaction has been collected using multiple measurement techniques. Unfortunately, diversity of methods for acquisition begets an aggregation of data which does not directly quantify the same properties of the flowfield. The objective in this paper was to (a) present the collection of flowfield measurements in one venue in a format more usable for those validating CFD models against the data, (b) evaluate the degree to which the experimental data support each other, and (c) highlight the differences and relative advantages/shortcomings of each measurement techniques. To present the various measured quantities into common format, CFD results from a companion paper also submitted for presentation at this meeting are utilized. For the case where the boundary layer remains attached, there is agreement between the various measurements as well as with Reynolds-averaged Navier-Stokes simulation solutions. As the impinging shock strength is increased beyond the point of separating the boundary layer, the congruity of the data wanes. Generally, agreement among the measurements exceeds the degree to which the CFD solutions agree with experiments. This suggests that unmodeled physical phenomena, such as transient motion of the reflected shock and separation bubble, give rise to the discrepancies observed in the computational results.

Shock-wave Boundary-layer interaction↗
NASA NTRS2008

The Citizens and Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote Sensing Data with Local Environmental Awareness

"Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on environmental issues.

Acker, James↗
DOE OSTI2021

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation

Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular-weight threshold required for single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure-determination methods. Here, a data-processing scheme is presented that combines routines from X-ray crystallography and new algorithms that have been developed to solve structures from tomograms of nanocrystals. This pipeline handles image-processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. The tolerance of this workflow to the effects of radiation damage is also assessed. The simulations indicate a trade-off between a wider tilt range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors, but not merging errors, can be overcome with additional data sets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.

59 BASIC BIOLOGICAL SCIENCES↗