Search NASA⌕ Search

SEARCH · Search NASA

Results for “data analytics”

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.

At least 307 records · Page 17

Space transportation system solid rocket booster thrust vector control system

The Solid Rocket Booster, Thrust Vector Control (TVC) system was designed in accordance with the following requirements: self-contained power supply, fail-safe operation, 20 flight uses after exposure to seawater landings, optimized cost, and component interchangeability. Trade studies were performed which led to the selection of a recirculating hydraulic system powered by Auxiliary Power Units (APU) which drive the hydraulic actuators and gimbal the solid rocket motor nozzle. Other approaches for the system design were studied in arriving at the recirculating hydraulic system powered by an APU. These systems must withstand the imposed environment and be usable for a minimum of 20 Space Transportation System flights with a minimum of refurbishment. The TVC system has completed the major portion of qualification and verification tests and is prepared to be cleared for the first Shuttle flight (STS-1). Substantiation data will include analytical and test data.

Verble, A. J., Jr.↗

Build-Up Approach to Updating the Mock Quiet Spike Beam Model

When a new aircraft is designed or a modification is done to an existing aircraft, the aeroelastic properties of the aircraft should be examined to ensure the aircraft is flight worthy. Evaluating the aeroelastic properties of a new or modified aircraft can include performing a variety of analyses, such as modal and flutter analyses. In order to produce accurate results from these analyses, it is imperative to work with finite element models (FEM) that have been validated by or correlated to ground vibration test (GVT) data, Updating an analytical model using measured data is a challenge in the area of structural dynamics. The analytical model update process encompasses a series of optimizations that match analytical frequencies and mode shapes to the measured modal characteristics of structure. In the past, the method used to update a model to test data was "trial and error." This is an inefficient method - running a modal analysis, comparing the analytical results to the GVT data, manually modifying one or more structural parameters (mass, CG, inertia, area, etc.), rerunning the analysis, and comparing the new analytical modal characteristics to the GVT modal data. If the match is close enough (close enough defined by analyst's updating requirements), then the updating process is completed. If the match does not meet updating-requirements, then the parameters are changed again and the process is repeated. Clearly, this manual optimization process is highly inefficient for large FEM's and/or a large number of structural parameters. NASA Dryden Flight Research Center (DFRC) has developed, in-house, a Mode Matching Code that automates the above-mentioned optimization process, DFRC's in-house Mode Matching Code reads mode shapes and frequencies acquired from GVT to create the target model. It also reads the current analytical model, as we11 as the design variables and their upper and lower limits. It performs a modal analysis on this model and modifies it to create an updated model that has similar mode shapes and frequencies as those of the target model. The Mode Matching Code output frequencies and modal assurance criteria (MAC) values that allow for the quantified comparison of the updated model versus the target model. A recent application of this code is the F453 supersonic flight testing platform, NASA DFRC possesses a modified F-15B that is used as a test bed aircraft for supersonic flight experiments. Traditionally, the finite element model of the test article is generated. A GVT is done on the test article ta validate and update its FEM. This FEM is then mated to the F-15B model, which was correlated to GVT data in fall of 2004, A GVT is conducted with the test article mated to the aircraft, and this mated F-15B/ test article FEM is correlated to this final GVT.

Herrera, Claudia Y.↗

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Silva, Walter A.↗

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Walter A. Silva↗

Verification of an Analytical Method for Measuring Crystal Nucleation Rates in Glasses from DTA Data

A recently proposed analytical (DTA) method for estimating the nucleation rates in glasses has been evaluated by comparing experimental data with numerically computed nucleation rates for a model lithium disilicate glass. The time and temperature dependent nucleation rates were predicted using the model and compared with those values from an analysis of numerically calculated DTA curves. The validity of the numerical approach was demonstrated earlier by a comparison with experimental data. The excellent agreement between the nucleation rates from the model calculations and fiom the computer generated DTA data demonstrates the validity of the proposed analytical DTA method.

Ranasinghe, K. S.↗

NASA ESDIS Employs the Latest Generation Web Analytics Tool

Under the auspices of NASA's Earth Observing System Data and Information System (EOSDIS), The Earth Science Data and Information System (ESDIS) Project distributes science data to a wide community of users through its Distributed Active Archive Centers (DAACs). Much of this data is made available via interactive websites - which involve links, downloads, on page interaction, and referrals to additional online pages. To meet the earth science data and information needs of many data users representing numerous different science domains, over 80 specialized websites are supported by multiple distributed organizations under the ESDIS umbrella.

Web Metrics↗

Surface pressure data on a series of analytic forebodies at Mach numbers from 1.70 to 4.50 and combined angles of attack and sideslip

Tabulated surface pressure data for a series of four forebodies which have analytically defined cross sections and which are based on a parabolic arc profile having a 20 deg half angle at the nose are presented without analysis. The first forebody has a circular cross section, and the second has a cross section which is an ellipse with an axis ratio of 2/1. The third has a cross section defined by a lobed analytic curve. The fourth forebody has cross sections which develop smoothly from circular at the pointed nose through the lobed analytic curve and back to circular at the aft end. The data generally cover angles of attack from -5 deg to 20 deg at angles of sideslip from 0 deg to 5 deg for Mach numbers of 1.70, 2.50, 3.95, and 4.50 at a constant Reynolds number.

Townsend, J. C.↗

A field- and laboratory-based quantitative analysis of alluvium: Relating analytical results to TIMS data

Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the McDowell Mountains northeast of Scottsdale, Arizona during August 1994. The raw data were processed to emphasize lithologic differences using a decorrelation stretch and assigning bands 5, 3, and 1 to red, green, and blue, respectively. Processed data of alluvium flanking the mountains exhibit moderate color variation. The objective of this study was to determine, using a quantitative approach, what environmental variable(s), in the absence of bedrock, is/are responsible for influencing the spectral properties of the desert alluvial surface.

Wenrich, Melissa L.↗

Analytical Framework for Rodent/NHP Data Set Utilization to Inform Human CNS Risk Estimation

Objectives Review and inform on tactics to analyze & communicate data from animal research (e.g., rodents, mini-pigs, NHPs, et al) exposed to single and combinations of spaceflight hazards, using NASA’s Human System Risk Board (HSRB) process for the Behavioral Medicine Risk - To quantitatively inform Behavioral Medicine Risk posture - i.e., likelihood (L) and consequence (C) - To help inform estimation of crew health standards for operational task performance (i.e., Fitness For Duty, Space Permissible Exposure Levels, Permissible Operational Limits).

Brain↗

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Earth Observation data are a vital resource for studying long term changes, but the large data volumes can be challenging to analyze. Time series analysis in particular is hampered by the typical thin-time-slice file organization. We examine several potential solutions inspired in large part by the data-parallel methods that have arisen with cloud computing. These solutions include various combinations of data re-organization, spatial indexing, distributed storage and pre-computation that we term "Analytics Optimized Data Stores" (AODS). We find that even simple solutions (such as a data cube) produce more than an order of magnitude improvement; the best provide two to three orders of magnitude improvement. The most performant solutions have tradeoffs in terms of generality or storage footprint, but may nonetheless be useful components in data analytics frameworks where performance is critical.

parallel processing (computers)↗

Analytical models and system topologies for remote multispectral data acquisition and classification

Simple analytical models are presented of the radiometric and statistical processes that are involved in multispectral data acquisition and classification. Also presented are basic system topologies which combine remote sensing with data classification. These models and topologies offer a preliminary but systematic step towards the use of computer simulations to analyze remote multispectral data acquisition and classification systems.

Huck, F. O.↗

Experimental investigation of the landing dynamics of three-legged spacecraft models

An experimental investigation was conducted to obtain accurate data from two three-legged spacecraft landing systems for purposes of validating current and future computer programs for legged landers. Two landing-gear systems were investigated: an inverted tripod system and a cantilever system. Tests were conducted for eight landing conditions chosen to obtain stability data, maximum loads, and maximum strokes for correlation with analytical results. Data from the two models are not directly comparable because of geometry and mass differences, but both are considered to be typical models of the respective landing-gear systems. Results indicate that maximum accelerations for both models, which occurred during a nearly flat landing on a horizontal surface, were nearly the same (approximately minus 18g). Maximum primary strut forces occurred for landings into a 20 deg slope and were 40 kiloNewtons (9000 lbf) and 47 kiloNewtons (10 500 lbf) for the inverted tripod and cantilever models, respectively; and maximum primary strut strokes for both models were 19 cm (7.4 in.). The inverted tripod model was slightly more stable than the cantilever model because of a larger ratio of footpad radius to center-of-gravity height.

Stubbs, S. M.↗

Development of and flight results from the Space Acceleration Measurement System (SAMS)

Described here is the development of and the flight results from the Space Acceleration Measurement System (SAMS) flight units used in the Orbiter middeck, Spacelab module, and the Orbitercargo bay. The SAMS units are general purpose microgravity accelerometers designed to support a variety of science experiments with microgravity acceleration measurements. A total of six flight units have been fabricated; four for use in the Orbiter middeck and Spacelab module, and two for use in the Orbiter cargo bay. The design of the units is briefly described. The initial two flights of SAMS units on STS-40 (June 1991) and STS-43 (August 1991) resulted in 371 megabytes and 2.6 gigabytes of data respectively. Analytical techniques developed to examine this quantity of acceleration data are described and sample plots of analyzed data are illustrated. Future missions for the SAMS units are listed.

Delombard, Richard↗

Development of and flight results from the Space Acceleration Measurement System (SAMS)

This paper describes the development of and flight results from the Space Acceleration Measurement System (SAMS) flight units used in the Orbiter middeck, Spacelab module and the Orbiter cargo bay. The SAMS units are general purpose microgravity accelerometers designed to support a variety of science experiments with microgravity acceleration measurements. A total of six flight units have been fabricated; four for use in the Orbiter middeck and Spacelab module, and two for use in the Orbiter cargo bay. The design of the units is briefly described. The initial two flights of SAMS units on STS-40 (June 1991) and STS-43 (August 1991) resulted in 371 megabytes and 2.6 gigabytes of data, respectively. Analytical techniques developed to examine this quantity of acceleration data are described and sample plots of analyzed data are illustrated. Future missions for the SAMS units are listed.

Delombard, Richard↗

Topex Microwave Radiometer thermal control - Post-system-test modifications and on-orbit performance

The Topex Microwave Radiometer has had an excellent thermal performance since launch. The instrument, however, went through a hardware modification right before launch to correct for a thermal design inadequacy that was uncovered during the spacecraft thermal vacuum test. This paper reports on how the initially obscure problem was tracked down, and how the thermal models were revised, validated, and utilized to investigate the solution options and guide the hardware modification decisions. Details related to test data interpretation, analytical uncertainties, and model-prediction vs. test-data correlation, are documented. Instrument/spacecraft interface issues, where the problem originated and where in general pitfalls abound, are dealt with specifically. Finally, on-orbit thermal performance data are presented, which exhibit good agreement with flight predictions, and lessons learned are discussed.

Lin, Edward I.↗