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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 181 records · Page 10

Acoustic loads on upper-surface-blown powered-lift systems

Powered-lift concepts are utilized in aircraft currently under development for STOL application. One of the concepts, upper surface blowing, places the jet exit just above the upper surface of the wing to produce powered lift from the jet exhaust blowing over the deflected flap. New data are presented to show the effects of airspeed, angle of attack, and angle of jet impingement. Scaling relationships are investigated concerning their applicability for extrapolating data to a different model size. The effects of a number of test parameters are examined and full-scale spectra are predicted from model data. It is concluded that scale models are an effective means for obtaining fluctuating pressure spectra for use in aircraft design. The prediction of full-scale loads from model data will require geometrically accurate models and closely spaced measurement locations.

Willis, C. M.↗

Towards a distributed information architecture for avionics data

Avionics data at the National Aeronautics and Space Administration's (NASA) Jet Propulsion Laboratory (JPL consists of distributed, unmanaged, and heterogeneous information that is hard for flight system design engineers to find and use on new NASA/JPL missions. The development of a systematic approach for capturing, accessing and sharing avionics data critical to the support of NASA/JPL missions and projects is required. We propose a general information architecture for managing the existing distributed avionics data sources and a method for querying and retrieving avionics data using the Object Oriented Data Technology (OODT) framework. OODT uses XML messaging infrastructure that profiles data products and their locations using the ISO-11179 data model for describing data products. Queries against a common data dictionary (which implements the ISO model) are translated to domain dependent source data models, and distributed data products are returned asynchronously through the OODT middleware. Further work will include the ability to 'plug and play' new manufacturer data sources, which are distributed at avionics component manufacturer locations throughout the United States.

Information architecture↗

A lattice model for data display

In order to develop a foundation for visualization, we develop lattice models for data objects and displays that focus on the fact that data objects are approximations to mathematical objects and real displays are approximations to ideal displays. These lattice models give us a way to quantize the information content of data and displays and to define conditions on the visualization mappings from data to displays. Mappings satisfy these conditions if and only if they are lattice isomorphisms. We show how to apply this result to scientific data and display models, and discuss how it might be applied to recursively defined data types appropriate for complex information processing.

Hibbard, William L.↗

Introduction to Coupled Atmosphere/Ocean Modeling and Data Assimilation [for NWP, Subseasonal to Seasonal Prediction, Reanalysis]

An introduction to coupled modeling and data assimilation was presented, along with the current status of the community efforts. Motivation was shown for running forecasts with a coupled model from weather to seasonal scales, as was motivation for doing the data assimilation coupled as well. The different "flavors" of coupled data assimilation in use or planned at different modeling centers were discussed. Finally, a set of current and potential problem with coupled modeling and data assimilation were illustrated.

Molod, Andrea↗

Behavior of volatiles in Mars' polar areas - A model incorporating new experimental data

A model has been developed to explain the north polar water vapor results obtained by the Viking orbiter Mars atmospheric water detector; it has also been used to compute the thickness of seasonally deposited CO2 frost, the variation of the total atmospheric pressure, and wind velocities due to mass motions associated with CO2 condensation. A north polar water ice thickness in excess of 1 m and an ice albedo a of 0.34(+0.06,-0.03) are inferred from a comparison of the model and experimental data. The model results confirm an earlier conclusion that the atmosphere over the ice is saturated. It is suggested that concentration of the atmospheric inert gases in the polar region, combined with local topography and arctic circulation patterns, could be responsible for the south remnant cap not being at the south pole

Davies, D. W.↗

FNAS UAH UVSP and complimentary data analysis and modeling

Several data sets obtained by the UVSP and HXIS instruments on board SMM were studied. From these data, several events of sequences of events were selected that are specially representative of the plethora of active region energetic phenomena that was simultaneously observed by UVSP and HXIS. The selection criteria was to have available both types of observations in active region flares that are not so bright that the UVSP instrument was switched off for protection, and at the same time flares that are not so dim in X-Rays that HXIS will have collected significant data. Another criteria of secondary importance was to select events where auxiliary optical data is available.

Fontenla, Juan M.↗

Rendezvous requirements and candidate worst case flights from the October 1973 space shuttle traffic model

Data appearing in the October 1973 space shuttle traffic model were analyzed to determine the rendezvous requirements for the proposed shuttle flights occurring between 1980 and 1991. Four families of flights have been identified, namely, single-payload rendezvous, multiple-payload rendezvous, payload and tug rendezvous, and tug only rendezvous. Charts have been prepared which summarize the respective data. Observations are presented for each of the four flight families, and worst case flights are proposed from each family for further analysis.

Kreiter, T. J.↗

Analysis of NASA Common Research Model Dynamic Data

Recent NASA Common Research Model (CRM) tests at the Langley National Transonic Facility (NTF) and Ames 11-foot Transonic Wind Tunnel (11-foot TWT) have generated an experimental database for CFD code validation. The database consists of force and moment, surface pressures and wideband wing-root dynamic strain/wing Kulite data from continuous sweep pitch polars. The dynamic data sets, acquired at 12,800 Hz sampling rate, are analyzed in this study to evaluate CRM wing buffet onset and potential CRM wing flow separation.

Balakrishna, S.↗

The Benchmark Active Controls Technology Model Aerodynamic Data

The Benchmark Active Controls Technology (BACT) model is a part of the Benchmark Models Program (BMP). The BMP is a NASA Langley Research Center program that includes a series of models which were used to study different aeroelastic phenomena and to validate computational fluid dynamics codes. The primary objective of BACT testing was to obtain steady and unsteady loads, accelerations, and aerodynamic pressures due to control surface activity in order to calibrate unsteady CFD codes and active control design tools. Three wind-tunnel tests in the Transonic Dynamics Tunnel (TDT) have been completed. The first and parts of the second and third tests focused on collecting open-loop data to define the model's aeroservoelastic characteristics, including the flutter boundary across the Mach range. It is this data that is being presented in this paper. An extensive database of over 3000 data sets was obtained. This database includes steady and unsteady control surface effectiveness data, including pressure distributions, control surface hinge moments, and overall model loads due to deflections of a trailing edge control surface and upper and lower surface

Scott, Robert C.↗

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) is a facility data management application developed for the NASA Ames arc jet facilities. The current decentralized data management practices limit statistical tracking, synchronization between video/time series, search capability, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗

Big-data Efficient Automated Science Transfer (BEAST): an open-source software architecture for arc jet data management, modeling, and automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗

Global Modeling and Data Assimilation: Documentation of the Tangent Linear and Adjoint Models of the Relaxed Arakawa-Schubert Moisture Parameterization of the NASA GEOS-1 GCM - Volume 11

A detailed description of the development of the tangent linear model (TLM) and its adjoint model of the Relaxed Arakawa-Schubert moisture parameterization package used in the NASA GEOS-1 C-Grid GCM (Version 5.2) is presented. The notational conventions used in the TLM and its adjoint codes are described in detail.

Suarez, Max J.↗

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day-of-launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers to include NASA's Launch Services Program and NASA's Ground Systems Development and Operations Program. They currently do not have the capability to display and overlay profiles of upper-level observations and numerical weather prediction model forecasts. The LWOs requested the Applied Meteorology Unit (AMU) develop a tool in the form of a graphical user interface (GUI) that will allow them to plot upper-level wind speed and direction observations from the Kennedy Space Center (KSC) 50 MHz tropospheric wind profiling radar, KSC Shuttle Landing Facility 915 MHz boundary layer wind profiling radar and Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Processing System (AMPS) radiosondes, and then overlay forecast wind profiles from the model point data including the North American Mesoscale (NAM) model, Rapid Refresh (RAP) model and Global Forecast System (GFS) model to assess the performance of these models. The AMU developed an Excel-based tool that provides an objective method for the LWOs to compare the model-forecast upper-level winds to the KSC wind profiling radars and CCAFS AMPS observations to assess the model potential to accurately forecast changes in the upperlevel profile through the launch count. The AMU wrote Excel Visual Basic for Applications (VBA) scripts to automatically retrieve model point data for CCAFS (XMR) from the Iowa State University Archive Data Server (http://mtarchive.qeol.iastate.edu) and the 50 MHz, 915 MHz and AMPS observations from the NASA/KSC Spaceport Weather Data Archive web site (http://trmm.ksc.nasa.gov). The AMU then developed code in Excel VBA to automatically ingest and format the observations and model point data in Excel to ready the data for generating Excel charts for the LWO's. The resulting charts allow the LWOs to independently initialize the three models 0-hour forecasts against the observations to determine which is the best performing model and then overlay the model forecasts on time-matched observations during the launch countdown to further assess the model performance and forecasts. This paper will demonstrate integration of observed and predicted atmospheric conditions into a decision support tool and demonstrate how the GUI is implemented in operations.

Bauman, William H., III↗

Data Driven Model Development for the Supersonic Semispan Transport (S(sup 4)T)

We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models and a data-driven system identification procedure. It is shown via analysis of experimental Super- Sonic SemiSpan Transport (S4T) wind-tunnel data using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Kukreja, Sunil L.↗

NAME Modeling and Data Assimilation: A Strategic Overview

In this presentation a strategic overview of modeling and related data analysis and assimilation components of the North American Monsoon Experiment (NAME) are given. Building on the NAME science plan, a strategy is outlined for accelerating progress on the fundamental modeling issues pertaining to NAME science goals. The strategy takes advantage of NAME enhanced observations, and should simultaneously provide model-based guidance to the evolving multi-tiered NAME observing program. The NAME modeling strategy recognizes three distinct, but related, roles that observations play in model development and assessment. These are: (1) to guide model development by providing constraints on model simulations at the process level (e.g. convection, land/atmosphere and ocean/atmosphere interactions); (2) to help assess the veracity of model simulations of the various key NAMS phenomena (e.g. low level jets, land sea breezes, tropical storms), and the linkages to regional and larger-scale climate variability; and (3) to provide initial and boundary conditions, and verification data for model predictions.

Schubert, Siegfried↗

Compilation of Test Data on 111 Free-Spinning Airplane Models Tested in the Langley 15-Foot and 20-Foot Free-Spinning Tunnels

A compilation of free-spinning-airplane model data on the spin and recovery characteristics of 111 airplanes is presented. These data were previously published in separate memorandum reports and were obtained from free-spinning tests in the Langley 15-foot and the Langley 20-foot free-spinning tunnels. The model test data presented include the steady-spin and recovery characteristics of each model for various combinations of aileron and elevator deflections and for various loadings and dimensional configurations. Dimensional data, mass data, and a three-view drawing of the corresponding free-spinning tunnel model are also presented for each airplane. The data presented should be of value to designers and should facilitate the design of airplanes incorporating satisfactory spin-recovery characteristics.

Malvestuto, Frank S.↗