SEARCH · Search NASA

Results for “data generation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Toward Understanding the Differences between Mesoscale and Large-Eddy Simulations of Tropical Cyclones

In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.

17 WIND ENERGY↗

DOE OSTI2026

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2007

Displaying and Analyzing Antenna Radiation Patterns

Radiant Energy Display and Analysis Software Package (REDAP) is a computer program for processing antenna-radiation- pattern data that have been preprocessed by a data-collection program and stored in a spherical-coordinate format. REDAP is designed specifically for application to data generated in testing of antennas in an anechoic chamber at Johnson Space Center; parts of REDAP may be reusable for processing antenna-test data collected elsewhere. REDAP provides a graphical user interface (GUI) and executes mathematical and plotting routines on a personal computer.

Siekierski, Jim↗

DOE OSTI2025

Livewire: Automatic Annotations

Diogenes processes datasets to provide data quality metrics for the Livewire platform and creates standardized data dictionaries from data annotations. Diogenes needs data annotations that clearly outline thenformat and organization of the data. It also relies on the type, class, and unit of each data piece for comprehensive analysis, which it cannot determine independently. The Annotation Tool significantly reduces the time needed to create annotations for Diogenes by generating data annotations with the correct formatting and content. It also employs machine learning and hard-coded models to automatically annotate data class, quality type, and data units.

33 - ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1986

A fast data acquisition system for the study of transient events by high repetition rate time-of-flight mass spectrometry

Recent advances in commercially available data acquisition electronics embodying high speed A/D conversion coupled to increased memory storage have now made practical (at least within time intervals of a third of a millisecond or more) the capturing of all of the data generated by a high repetition rate time-of-flight mass spectrometer producing complete spectra every 25 to 35 microseconds. Such a system was assembled and interfaced with a personal computer for control and management of data. The applications are described for recording time-resolved spectra of individual vapor plumes induced from the pulsed-laser heating of material. Each laser pulse triggers the system to generate automatically a 3-dimensional (3-D) presentation of the time-resolved spectra with m/z labeling of the major mass peaks, plus an intensity versus time display of both the laser pulse and the resulting vapor pulse. The software also permits storing of data and its presentation in various additional forms.

Lincoln, K. A.↗

DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1973

Fundamental study of transpiration cooling

Isothermal and non-isothermal pressure drop data and heat transfer data generated on porous 304L stainless steel wire forms, sintered spherical stainless steel powder, and sintered spherical OFHC copper powder are reported and correlated. Pressure drop data was collected over a temperature range from 500 R to 2000 R and heat transfer data collected over a heat flux range from 5 to 15 BTU/in2/sec. It was found that flow data could be correlated independently of transpirant temperature and type (i.e., H2, N2). It was also found that no simple relation between heat transfer coefficient and specimen porosity was obtainable.

Koh, J. C. Y.↗

NASA NTRS1989

Time-resolved simplified chemical kinetics modelling using computational singular perturbation

A CO-CH4-air reaction system is used to demonstrate the computational singular perturbation (CSP) method for deriving time-resolved simplified chemical kinetics models. CSP provides a programmable algorithm to group the given collection of elementary reactions into reaction groups which are ordered according to their speed. The concept of Importance Index k(m)exp s is introduced: k(m)exp s is defined to be a number between 0 and 1 which measures the importance of the m-th reaction group to the s-th reactant and can readily be computed from data generated by CSP. It is suggested that the robustness of the solutions of the reaction system can be qualitatively assessed by inspecting the Importance Index data.

Lam, S. H.↗

NASA NTRS2010

The Geostationary Operational Satellite R Series SpaceWire Based Data System Architecture

The GOES-R program selected SpaceWire as the best solution to satisfy the desire for simple and flexible instrument to spacecraft command and telemetry communications. Data generated by GOES-R instruments is critical for meteorological forecasting, public safety, space weather, and other key applications. In addition, GOES-R instrument data is provided to ground stations on a 24/7 basis. GOES-R requires data errors be detected and corrected from origin to final destination. This paper describes GOES-R developed strategy to satisfy this requirement

Krimchansky, Alexander↗

NASA NTRS2011

Preliminary Computational Analysis of the (HIRENASD) Configuration in Preparation for the Aeroelastic Prediction Workshop

This paper presents preliminary computational aeroelastic analysis results generated in preparation for the first Aeroelastic Prediction Workshop (AePW). These results were produced using FUN3D software developed at NASA Langley and are compared against the experimental data generated during the HIgh REynolds Number Aero- Structural Dynamics (HIRENASD) Project. The HIRENASD wind-tunnel model was tested in the European Transonic Windtunnel in 2006 by Aachen University0s Department of Mechanics with funding from the German Research Foundation. The computational effort discussed here was performed (1) to obtain a preliminary assessment of the ability of the FUN3D code to accurately compute physical quantities experimentally measured on the HIRENASD model and (2) to translate the lessons learned from the FUN3D analysis of HIRENASD into a set of initial guidelines for the first AePW, which includes test cases for the HIRENASD model and its experimental data set. This paper compares the computational and experimental results obtained at Mach 0.8 for a Reynolds number of 7 million based on chord, corresponding to the HIRENASD test conditions No. 132 and No. 159. Aerodynamic loads and static aeroelastic displacements are compared at two levels of the grid resolution. Harmonic perturbation numerical results are compared with the experimental data using the magnitude and phase relationship between pressure coefficients and displacement. A dynamic aeroelastic numerical calculation is presented at one wind-tunnel condition in the form of the time history of the generalized displacements. Additional FUN3D validation results are also presented for the AGARD 445.6 wing data set. This wing was tested in the Transonic Dynamics Tunnel and is commonly used in the preliminary benchmarking of computational aeroelastic software.

Chwalowski, Pawel↗

DOE OSTI2024

G EANT 4 atomic relaxation data for transfermium nuclei (Z = 101–104)

Advanced theoretical methods can accurately calculate various atomic observables and predict electronic structure. Still, systematic computations of the radiative and non-radiative transition probabilities and energies are missing for the actinides and all the transfermium elements. However, these compilations are needed for comprehensive Monte-Carlo simulations (such as GEANT4) of the radioactive decay of transfermium nuclei. These simulations can forma basis for data analysis of experiments, especially with complex detection setups. Investigation of the transfermium nuclei is crucial for understanding the nature of the nuclear force. In this study, simulations based on data from the Jena Atomic Calculator (JAC) and the data from the Evaluated Atomic Data Library (EADL) present in GEANT4 were found compatible for the three elements Ba(Z = 56), U(Z = 92), and Fm(Z = 100), thus, validating the JAC calculations. For Z> 100, we also found sound agreement between simulations that used data generated with JAC and experimental results involving No(Z = 102) and Rf(Z = 104) isotopes. In conclusion, these results demonstrate that JAC can produce reliable atomic data sets for transfermium elements, which will assist in analyzing nuclear-decay-spectroscopy experiments.

GEANT4↗

DOE OSTI2026

Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics

The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Here, our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA’s petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Computer science↗

DOE OSTI2024

A New Reduced Order Model For The Mechanistic Creep Behavior Of UO 2

This manuscript describes an ongoing NEAMS effort to better determine the performance of advanced nuclear fuels, in particular the creep behavior of doped UO$_2$ for light water reactors. In our previous work, we outlined a method to utilize data generated from lower length scale simulations and implement it into the engineering scale fuel performance analysis. This process has been further refined, and in addition, new data has been used to train the surrogate model which has also been substantially improved since the previous iteration. The new model is compared against the current empirical model used in BISON using both scoping calculations to define the performance over the parameter space and using integral instrumented fuel assessment cases to determine the impact of these models on the overall fuel performance. Suggestions and guidance for future improvements to this method are provided to ensure the model covers relevant parameter space and phenomena.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1999

Earth Science Data Archive and Access at the NASA/Goddard Space Flight Center Distributed Active Archive Center (DAAC)

The Goddard Distributed Active Archive Center (DAAC), as an integral part of the Earth Observing System Data and Information System (EOSDIS), is the official source of data for several important earth remote sensing missions. These include the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) launched in August 1997, the Tropical Rainfall Measuring Mission (TRMM) launched in November 1997, and the Moderate Resolution Imaging Spectroradiometer (MODIS) scheduled for launch in mid 1999 as part of the EOS AM-1 instrumentation package. The data generated from these missions supports a host of users in the hydrological, land biosphere and oceanographic research and applications communities. The volume and nature of the data present unique challenges to an Earth science data archive and distribution system such as the DAAC. The DAAC system receives, archives and distributes a large number of standard data products on a daily basis, including data files that have been reprocessed with updated calibration data or improved analytical algorithms. A World Wide Web interface is provided allowing interactive data selection and automatic data subscriptions as distribution options. The DAAC also creates customized and value-added data products, which allow additional user flexibility and reduced data volume. Another significant part of our overall mission is to provide ancillary data support services and archive support for worldwide field campaigns designed to validate the results from the various satellite-derived measurements. In addition to direct data services, accompanying documentation, WWW links to related resources, support for EOSDIS data formats, and informed response to inquiries are routinely provided to users. The current GDAAC WWW search and order system is being restructured to provide users with a simplified, hierarchical access to data. Data Browsers have been developed for several data sets to aid users in ordering data. These Browsers allow users to specify spatial, temporal, and other parameter criteria in searching for and previewing data.

Leptoukh, Gregory↗

NASA NTRSDate not supplied

DiskSat: Demonstration Mission for a Two-Dimensional Satellite Architecture

The DiskSat is a quasi-two-dimensional satellite bus architecture designed for applications requiring high power, large apertures, and/or high maneuverability in a low-mass satellite. A representative DiskSat structure is a composite flat panel, one meter in diameter and 2.5 cm thick. The volume is almost 20 liters, equivalent to a hypothetical 20U CubeSat, while the structural mass is less than 3 kg. The surface area is large enough to host over 200 W of solar cells without deployable solar panels. For launch, multiple DiskSats are stacked in a fully enclosed container/deployer using a simple mechanical interface and are released individually in orbit. The Aerospace Corporation, with the support of the NASA Space Technology Mission Directorate (STMD), is preparing a flight of four DiskSats for launch in 2024 to demonstrate the feasibility of both the dispenser and the DiskSat bus. In addition, the flight is expected to demonstrate several features of the DiskSat including the unprecedented high power-to-mass ratio, the maneuverability of the bus using low-thrust electric propulsion, and the ability to fly continuously in a low-drag orientation, enabling operations in very low Earth orbits (VLEO). The DiskSats will be launched in and deployed from a dispenser that provides a containerized rideshare environment; the dispenser fully encloses the DiskSats during launch and then opens to dispense the satellites one at a time once in orbit. The dispenser is modular in design and expandable from the capacity of four DiskSats for this flight to as many as 20 DiskSats for future flights. NASA STMD seeks disruptive and innovative technologies that could help lead to the next-generation systems for future science and exploration missions. DiskSat is a potentially disruptive technology leading to new, enabling architectures using ever-more capable small spacecraft. Data generated from this flight will inform the drafting of a DiskSat standard intended to encourage easy and frequent access to space, in the same manner as the CubeSat standard. DiskSat is expected to become a standard format for rideshare-compatible, high-power, maneuverable, low-mass satellites for Earth-orbit, cis-lunar, and deep space applications.

Richard Welle↗

NASA NTRS1973

Environmental control system transducer development study

A failure evaluation of the transducers used in the environmental control systems of the Apollo command service module, lunar module, and portable life support system is presented in matrix form for several generic categories of transducers to enable identification of chronic failure modes. Transducer vendors were contacted and asked to supply detailed information. The evaluation data generated for each category of transducer were compiled and published in failure design evaluation reports. The evaluation reports also present a review of the failure and design data for the transducers and suggest both design criteria to improve reliability of the transducers and, where necessary, design concepts for required redesign of the transducers. Remedial designs were implemented on a family of pressure transducers and on the oxygen flow transducer. The design concepts were subjected to analysis, breadboard fabrication, and verification testing.

Brudnicki, M. J.↗

NASA NTRS2013

Tool for Rapid Analysis of Monte Carlo Simulations

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very difficult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The first version of this tool was a serial code and the current version is a parallel code, which has greatly increased the analysis capabilities. This paper describes the new implementation of this analysis tool on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Restrepo, Carolina↗

NASA NTRS2019

Recent Enhancements to NASA’s PCBoom Sonic Boom Propagation Code

This paper presents the recent updates the author has made to PCBoom sonic boom propagation code on its computational efficiency, predictive capability, and file operations. The updated version has recently been released and has a Burgers’ equation solver, which is computationally more efficient than that in the older version by 2 to 3 orders of magnitude. The updated version also enhances the accuracy of the sonic boom propagation prediction by accounting for the full wind effects on the shock wave propagation. Predictions from the updated PCBoom are compared with predictions from the older version and with data from flight tests. Other upgrades and changes that have been made in the latest version include support for Unix-like operating systems, bug fixes, and generation of new types of output files that allow for better manipulation of PCBoom-generated data.

Lonzaga, Joel B.↗