Computer data processing to compute NERVA transfer functions.
NERVA transfer functions evaluation by computer data processing, using Fourier algorithm
Benenson, H.↗
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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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The application of a computer data acquisition system for a new high temperature tribometer
The two data acquisition computer programs are described which were developed for a high temperature friction and wear test apparatus, a tribometer. The raw data produced by the tribometer and the methods used to sample that data are explained. In addition, the instrumentation and computer hardware and software are presented. Also shown is how computer data acquisition was applied to increase convenience and productivity on a high temperature tribometer.
Bonham, Charles D.↗
The application of a computer data acquisition system to a new high temperature tribometer
The two data acquisition computer programs are described which were developed for a high temperature friction and wear test apparatus, a tribometer. The raw data produced by the tribometer and the methods used to sample that data are explained. In addition, the instrumentation and computer hardware and software are presented. Also shown is how computer data acquisition was applied to increase convenience and productivity on a high temperature tribometer.
Bonham, Charles D.↗
Derivation of Integrated Load Distributions from Resampled Computational Data
Principal component analysis (PCA) has been the center of many surrogate models used to characterize fluid flows in recent years. However, little work has been done to character- ize the uncertainty in the PCA transform itself and its effect on derived surrogate models. To explore the uncertainty, a typical interpolated surrogate model is constructed for a represen- tative aerodynamic body from computational data. The computational data is then resampled to explore the robustness of the PCA transformation. The variations of the model predictions during this resampling are analyzed to get a measure of confidence in the PCA transformation, which is then applied to the interpolated surrogate model to get uncertainty on integrated force predictions. An initial test case has been explored with promising results.
Computational Fluid Dynamics↗
Derivation of Integrated Load Distributions from Resampled Computational Data
Principal component analysis (PCA) has been the center of many surrogate models used to characterize fluid flows in recent years. However, little work has been done to character- ize the uncertainty in the PCA transform itself and its effect on derived surrogate models. To explore the uncertainty, a typical interpolated surrogate model is constructed for a represen- tative aerodynamic body from computational data. The computational data is then resampled to explore the robustness of the PCA transformation. The variations of the model predictions during this resampling are analyzed to get a measure of confidence in the PCA transformation, which is then applied to the interpolated surrogate model to get uncertainty on integrated force predictions. An initial test case has been explored with promising results.
Principal Component Analysis↗
Satellite system considerations for computer data transfer
Communications satellites will play a key role in the transmission of computer generated data through nationwide networks. This paper examines critical aspects of satellite system design as they relate to the computer data transfer task. In addition, it discusses the factors influencing the choice of error control technique, modulation scheme, multiple-access mode, and satellite beam configuration based on an evaluation of system requirements for a broad range of application areas including telemetry, terminal dialog, and bulk data transmission.
Cook, W. L.↗
Computational Data for: "Introducing Metal-Sulfur Active Sites in Metal-Organic Frameworks via Post-Synthetic Modification for Hydrogenation Catalysis"
Computational Data for: "Introducing Metal-Sulfur Active Sites in Metal-Organic Frameworks via Post-Synthetic Modification for Hydrogenation Catalysis"
BBTA↗
AND TREE computer data structures for supervisory control of manipulation
Supervisory controlled manipulation system for complex manipulation tasks on unmanned space vehicles using AND TREE computer data structure
Hardin, P. A.↗
Cogeneration Technology Alternatives Study (CTAS). Volume 6: Computer data. Part 2: Residual-fired nocogeneration process boiler
Computer generated data on the performance of the cogeneration energy conversion system are presented. Performance parameters included fuel consumption and savings, capital costs, economics, and emissions of residual fired process boilers.
Knightly, W. F.↗
Developing machine learning for heterogeneous catalysis with experimental and computational data
Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.
Computational chemistry↗
Real-time computer data system for the 40- by 80-foot wind tunnel facility at Ames Research Center
The background material and operational concepts of a computer-based system for an operating wind tunnel are described. An on-line real-time computer system was installed in a wind tunnel facility to gather static and dynamic data. The computer system monitored aerodynamic forces and moments of periodic and quasi-periodic functions, and displayed and plotted computed results in real time. The total system is comprised of several off-the-shelf, interconnected subsystems that are linked to a large data processing center. The system includes a central processor unit with 32,000 24-bit words of core memory, a number of standard peripherals, and several special processors; namely, a dynamic analysis subsystem, a 256-channel PCM-data subsystem and ground station, a 60-channel high-speed data acquisition subsystem, a communication link, and static force and pressure subsystems. The role of the test engineer as a vital link in the system is also described.
Cambra, J. M.↗
Cogeneration technology alternatives study. Volume 6: Computer data
The potential technical capabilities of energy conversion systems in the 1985 - 2000 time period were defined with emphasis on systems using coal, coal-derived fuels or alternate fuels. Industrial process data developed for the large energy consuming industries serve as a framework for the cogeneration applications. Ground rules for the study were established and other necessary equipment (balance-of-plant) was defined. This combination of technical information, energy conversion system data ground rules, industrial process information and balance-of-plant characteristics was analyzed to evaluate energy consumption, capital and operating costs and emissions. Data in the form of computer printouts developed for 3000 energy conversion system-industrial process combinations are presented.
Source record↗
Real time computer data system for the 40 x 80 ft wind tunnel facility at Ames Research Center
The wind tunnel realtime computer system is a distributed data gathering system that features a master computer subsystem, a high speed data gathering subsystem, a quick look dynamic analysis and vibration control subsystem, an analog recording back-up subsystem, a pulse code modulation (PCM) on-board subsystem, a communications subsystem, and a transducer excitation and calibration subsystem. The subsystems are married to the master computer through an executive software system and standard hardware and FORTRAN software interfaces. The executive software system has four basic software routines. These are the playback, setup, record, and monitor routines. The standard hardware interfaces along with the software interfaces provide the system with the capability of adapting to new environments.
Cambra, J. M.↗
A brief description of an Earth Resources Technology Satellite (ERTS) computer data analysis and management program
A data analysis and management procedure currently being used at Marshall Space Flight Center to analyze ERTS digital data is described. The objective is to acquaint potential users with the various computer programs that are available for analysis of multispectral digital imagery and to show how these programs are used in the overall data management plan. The report contains a brief description of each computer routine, and references are provided for obtaining more detailed information.
Jayroe, R. R., Jr.↗
Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers
Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Supporting Data: Computational Investigation of the Chemical Bond between An(III) Ions and Soft-Donor Ligands
Data associated with the Inorganic Chemistry publication (DOI: 10.1021/acs.inorgchem.4c03924) was made publicly available in a FigShare repository (DOI: 10.6084/m9.figshare.28195664) to ensure reproducibility and support the PI's commitment to open-science that was included in the data management plan of the project.
Roy Chowdhury, Sabyasachi [Department of Chemistry↗
Advanced Computing, Data Science, and Artificial Intelligence Research Opportunities for Energy-Focused Transportation Science
The Energy Efficient Mobility Systems (EEMS) technology landscape is complex and rapidly evolving, which provides both tremendous opportunities and formidable challenges. Significant alterations to the mobility landscape are underway due to the advent of vehicle and infrastructure connectivity, autonomous driving, and rapid passenger- and freight-vehicle electrification. Advanced computing will play an increasingly important role in enabling the EEMS program to understand and identify the most important levers to improve the energy productivity of future integrated mobility systems. It is also driving new approaches to mobility and the research to unlock an affordable, efficient, safe, and accessible transportation future. Driving much of this change is the collection, analysis, and strategic use of massive amounts of diverse, complex data from infrastructure and vehicles with on-board sensors and data storage and transmission capabilities. Diverse and representative data are key to implementing approaches to maximize mobility energy productivity. While high-fidelity modeling of integrated transportation networks has strengthened our understanding of dynamic movement and behavior patterns, existing tools must be expanded beyond their current focus. This work necessitates data infrastructure investments (e.g., secure-streaming data platforms driven by ubiquitous sensors and video analytics) as well as investments in critical capabilities for large-scale automated analysis and organization using modern machine learning, statistics, and artificial intelligence. Other chief needs include agile, large-scale storage that can be quickly searched and queried for relevant data to support validation and model development, data-sharing agreements, and formatting standards for key data types. The future of public transit must be explored in greater detail, research must inform design, and opportunities must be identified for improving the mobility productivity of public transit in both urban and rural America.
33 ADVANCED PROPULSION SYSTEMS↗
Comparison of general circulation models to Earth Radiation Budget Experiment data - Computation of clear-sky fluxes
A clear-sky flux computation method is described which is representative of the Earth Radiation Budget Experiment data processing, while at the same time being enough straightforward for implementation in a general circulation model (GCM). The method is a hybrid version of Cess and Potter (1987) Method I and Method II clear-sky top-of-the-atmosphere flux computations for GCMs. The procedure is demonstrated using the ECMWF GCM.
Cess, Robert D.↗