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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Determining Compression Characteristics of Honeycomb Material - 19674

The objective is to determine compression test characteristics of stainless steel honeycomb material to be able to represent honeycomb structures accurately in analytical models used to simulate hypothetical accident scenarios of shipping packages. Honeycomb is a material used primary in the aerospace industry due to its high strength-to-weight ratio. Because it doesn't have a shelf life and can withstand high heats, it is an excellent candidate for a structural material in package designs. Honeycomb has orthotropic material properties. The honeycomb currently being evaluated is made of metal ribbons spot welded together to form hexagon pattern between metal plates. The hexagon ribbons are brazed to the metal plates. The complexity of the honeycomb significantly lengthens the simulation time, which is further complicated when the brazing, welding, and imperfections of the material is considered. This means to affectively represent the honeycomb in simulation programs, such as Abaqus, the material needs to be approximated as a uniform orthotropic material. This requires material properties in each of the three directions, T, W, and L. The T direction is defined as the 'strong' direction, perpendicular to the honeycomb sheet. The L direction is parallel the ribbon and the W direction is perpendicular to the ribbon. Honeycomb has 3 different compression stages. Stage 1 is the initial compression where the honeycomb maintains its structural integrity and does not permanently deform from loads from normal operations. Stage 2 is when the initial buckling causes irreversible damage to the honeycomb. Stage 2 is the one we are most interested in because it absorbs the most energy from a hypothetical accident scenario. During Stage 2, the honeycomb fails layer-by-layer, indicating that the more layers, the longer material crushing is sustained, and thus the more energy that is absorbed. Stage 3 is final compression, similar to compressing solid metal. During stage 3 the stress increases with a diminishing rate of elongation and the honeycomb is completely failed where the plates between the honeycomb core sandwich the crushed honeycomb ribbon. The stress-strain graph bellow shows compression test of 3 different samples in the T direction. The red lines divide the three stages. The far left is Stage 1, the middle stage 2, and the right stage 3. The data collected is displayed in the table below. The expressions in the table represent the regression formula that represents each stage of the compression on a stress-strain graph. Stage 1 is assumed to intersect with the origin; data for stage 3 for the crush in W and L directions where unable to be gathered due to the nature of failure for those directions. Stage 1 and 2 are linear regressions while stage 3 is a degree 2, to best match the curve. Linear regression is used on stage 2 because ultimately that represents the energy absorbed. With more data, a degree n x 2 regression would be a more appropriate regression for stage 2, where n is the number of layers. The table below is the approximation of each scenario and stage. Each stage starts and ends at the intersection of the next stage. There where two main objectives for these tests: firstly to understand how honeycomb performs under extreme compression, and secondly to be able to numerically represent the honeycomb structure. Both of these where completed to varying degrees. It is important understood how the honeycomb fails. If it is crushed in the T direction it retains its integrity even after being crushed, however when crushed in the L and W crush direction, if it fails, it disintegrates, and loses all integrity. Also, the more layers the more time the material spends in stage 2. Failure is started by buckling, thus if there is any imperfection, the stress will not spike but transition straight into stage 2. The data collected and aggregated can be used for initial simulation of honeycomb used in packages. The initial testing has set the ground work for more data to be collected in order to verify results and to allow more confidence in the simulation results. This is only the initial data collected. The next steps is to continue to collect more data to verify results and to test more variants of honeycomb, with different brazing, layers, and shape.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Staging memory for massively parallel processor

The invention herein relates to a computer organization capable of rapidly processing extremely large volumes of data. A staging memory is provided having a main stager portion consisting of a large number of memory banks which are accessed in parallel to receive, store, and transfer data words simultaneous with each other. Substager portions interconnect with the main stager portion to match input and output data formats with the data format of the main stager portion. An address generator is coded for accessing the data banks for receiving or transferring the appropriate words. Input and output permutation networks arrange the lineal order of data into and out of the memory banks.

Batcher, Kenneth E.↗
NASA NTRS1951

Matching Characteristics of J35-A-23 Compressor and Two-stage Turbine

Component data on the J35-A-23 compressor and two-stage turbine were used to determine the problems in matching the two units for operatio n in a turbojet engine. Possible operating regions were determined an d an equilibrium operating line was also determined for the assumed c onditions of zero flight speed and a jet nozzle area approximately 5. 5 percent greater than the wide-open nozzle area.

Dugan, James F., Jr.↗
DOE OSTI2024

HERO WEC 2024 Hydraulic Configuration Deployment Data

The following submission includes raw and processed data from the in water deployment of NREL's Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), in the form of parquet files, TDMS files, CSV files, bag files and MATLAB workspaces. This dataset was collected in March 2024 at the Jennette's pier test site in North Carolina. This submission includes the following: - Data description document (HERO WEC FY24 Hydraulic Deployment Data Descriptions.doc) - This document includes detailed descriptions of the type of data and how it was processed and/or calculated. - Processed MATLAB workspace - The processed data is provided in the form of a single MATLAB workspace containing data from the full deployment. This workspace contains data from all sensors down sampled to 10 Hz along with all array Value Added Products (VAPs). - MATLAB visualization scripts - The MATLAB workspaces can be visualized using the file "HERO_WEC_2024_Hydraulic_Config_Data_Viewer.m/mlx". The user simply needs to download the processed MATLAB workspaces, specify the desired start and end times and run this file. Both the .m and .mlx file format has been provided depending on the user's preference. - Summary Data - The fully processed data was used to create a summary data set with averages and important calculations performed on 30-minute intervals to align with the intervals of wave resource data reported from nearby CDIP ocean observing buoys located 20km East of Jennette's pier and 40km Northeast of Jennette's pier. The wave resource data provided in this data set is to be used for reference only due the difference in water depth and proximity to shore between the Jennette's pier test site and the locations of the ocean observing buoys. This data is provided in the Summary Data zip folder, which includes this data set in the form of a MATLAB workspace, parquet file, and excel spreadsheet. - Processed Parquet File - The processed data is provided in the form of a single parquet file containing data from all HERO WEC sensors collected during the full deployment. Data in these files has been down sampled to 10 Hz and all array VAPs are included. - Interim Filtered Data - Raw data from each sensor group partitioned into 30-minute parquet files. These files are outputs from an intermediate stage of data processing and contain the raw data with no Quality Control (QC) or calculations performed in a format that is easier to use than the raw data. - Raw Data - Raw, unprocessed data from this deployment can be found in the Raw Data zip folder. This data is provided in the form of TDMS, CSV, and bag files in the original format output by the MODAQ system. - Python Data Processing Script - This links to an NREL public github repository containing the python script used to go from raw data to fully processed parquet files. Additional documentation on how to use this script is included in the github repository. This data set has been developed by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗
NASA NTRS2003

ICESat Observations of Southern Alaska Glaciers

In late February and March, 2003, the Ice, Cloud, and land Elevation Satellite (ICESat) measured ice and land elevations along profiles across southern Alaska. During this initial data acquisition stage ICESat observations were made on 8-day repeat tracks to enable calibration and validation of the ICESat data products. Each profile consists of a series of single point values derived from centroid elevations of an $\approx$70 m diameter laser footprint. The points are s4pakated by $\approx$172 m along track. Data siets of 8-day observations (an ascending and descending ground track) crossed the Bering and Malaspina Glacier. Following its 1993--1995 surge; the Bering Glacier has undergone major terminus retreat as well as ike thinning in the abtation zone. During the later part of the 20th century, parts of the Malaspina thinned by about 1 m/yr. The multiple observation profiles across the Bering and Malaspina piedmont lobes obtained in February/March are being geolocated on Landsat images and the elevation profiles will be used for a number o scientific objectives. Based on our simulations of ICESat performance over the varied ice surface of the Jakobshavn Glacier of GReenland, 2003, we expect to measure annual, and possibly seasonal, ice elevation changes on the large Alaskan glaciers. Using elevation data obtained from a second laser, we plan to estimate ice elevation changes on the Bering Glacier between March and October 2003.

Sauber, Jeanne↗
NASA NTRS2011

Ares I-X Range Safety Simulation Verification and Analysis Independent Validation and Verification

NASA s Ares I-X vehicle launched on a suborbital test flight from the Eastern Range in Florida on October 28, 2009. To obtain approval for launch, a range safety final flight data package was generated to meet the data requirements defined in the Air Force Space Command Manual 91-710 Volume 2. The delivery included products such as a nominal trajectory, trajectory envelopes, stage disposal data and footprints, and a malfunction turn analysis. The Air Force s 45th Space Wing uses these products to ensure public and launch area safety. Due to the criticality of these data, an independent validation and verification effort was undertaken to ensure data quality and adherence to requirements. As a result, the product package was delivered with the confidence that independent organizations using separate simulation software generated data to meet the range requirements and yielded consistent results. This document captures Ares I-X final flight data package verification and validation analysis, including the methodology used to validate and verify simulation inputs, execution, and results and presents lessons learned during the process

Merry, Carl M.↗
NASA NTRS1990

Overview of CFD flow modeling and validation: NASA. Ames Research Center

NASA Ames Center personnel presented data on stages of code development and corresponding experiments in the application of computational fluid dynamics for aeronautical investigations. Specific subjects included algorithms, grid generation, facilities, instrumentation, and data acquisition. Numerical simulation and flow modelling were described to show the procedure for calibration and validation.

Marvin, Joe G.↗
NASA NTRS1961

Investigation of the Performance of an Axial-Flow-Pump Stage Designed by the Blade-Element Theory: Blade-Element Data

An axial-flow-pump stage was designed by utilizing blade-element methods in conjunction with axial-flow-compressor blade-element theory. This report presents the blade-element data of the pump stage in both the noncavitating and cavitating conditions. The noncavitating blade- element performance is compared with design rules. The results indicated that some modification of the compressor design equations for computing minimum-loss incidence and deviation angles may be necessary for application to an axial-flow-pump design. Minimum values of observed rotor loss were slightly lower than anticipated from compressor results. At the design flow coefficient the rotor-blade elements were not operating at the reference incidence angles, and the experimental efficiency was lower than the design value. The observed head rise was very close to the design. An attempt was made to estimate the potential of this rotor by using the minimum measured values of loss coefficient and observed energy input at the design flow. Performance of the pump at a suction specific speed of approximately 13,000 (cavitation number k approximately equals 0.12) showed only a slight dropoff in performance in the cavitation inception region from the noncavitating results. The observed performance at a suction specific speed of approximately 16,000 (k approximately equals 0.09) is also presented for comparison.

Crouse, James E.↗
NASA NTRS1999

Effects of Hot Streak Shape on Rotor Heating in a High-Subsonic Single-Stage Turbine

Experimental data have shown that combustor temperature non-uniformities can lead to the excessive heating of first-stage rotor blades in turbines. This heating of the rotor blades can lead to thermal fatigue and degrade turbine performance. The results of recent studies have shown that variations in the circumferential location (clocking) of the hot streak relative to the first-stage vane airfoils can be used to minimize the adverse effects of the hot streak. The effects of the hot streak/airfoil count ratio on the heating patterns of turbine airfoils have also been evaluated. In the present investigation, three-dimensional unsteady Navier-Stokes simulations have been performed for a single-stage high-pressure turbine operating in high subsonic flow. In addition to a simulation of the baseline turbine, simulations have been performed for circular and elliptical hot streaks of varying sizes in an effort to represent different combustor designs. The predicted results for the baseline simulation show good agreement with the available experimental data. The results of the hot streak simulations indicate: that a) elliptical hot streaks mix more rapidly than circular hot streaks, b) for small hot streak surface area the average rotor temperature is not a strong function of hot streak temperature ratio or shape, and c) hot streaks with larger surface area interact with the secondary flows at the rotor hub endwall, generating an additional high temperature region.

Dorney, Daniel J.↗
DOE OSTI2020

Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage

Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment.

Abed Abud, Adam↗
NASA NTRS2012

Noise Whitening in Airborne Wind Profiling With a Pulsed 2-Micron Coherent Doppler Lidar at NASA Langley Research Center

Two different noise whitening methods in airborne wind profiling with a pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia are presented. In order to provide accurate wind parameter estimates from the airborne lidar data acquired during the NASA Genesis and Rapid Intensification Processes (GRIP) campaign in 2010, the adverse effects of background instrument noise must be compensated properly in the early stage of data processing. The results of the two methods are presented using selected GRIP data and compared with the dropsonde data for verification purposes.

Beyon, Jeffrey Y.↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Developing processing techniques for Skylab data

The author has identified the following significant results. The effects of misregistration and the scan-line-straightening algorithm on multispectral data were found to be: (1) there is greatly increased misregistration in scan-line-straightening data over conic data; (2) scanner caused misregistration between any pairs of channels may not be corrected for in scan-line-straightened data; and (3) this data will have few pure field center pixels than will conic data. A program SIMSIG was developed implementing the signature simulation model. Data processing stages of the experiment were carried out, and an analysis was made of the effects of spatial misregistration on field center classification accuracy. Fifteen signatures originally used for classifying the data were analyzed, showing the following breakdown: corn (4 signatures), trees (2), brush (1), grasses, weeds, etc. (5), bare soil (1), soybeans (1), and alfalfa (1).

Nalepka, R. F.↗
NASA NTRS2003

Monitoring and Assimilation of MIPAS and SCIAMACHY Ozone Data

Preliminary results are presented from experiments that integrate ozone observations from two ENVISAT-borne instruments with the ozone data assimilation system developed at NASA's Data Assimilation Office (DAO). The data used are ozone total column provided by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and stratospheric profiles from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument. The DAO's existing system sequentially assimilates the Solar Backscatter Ultraviolet/2 total and partial ozone column data. Incorporation of SCIAMACHY and MIPAS data is done in two stages. First, the observations are monitored. The monitoring consists of computing the differences between Envisat observations and the ozone system forecast, i.e. observed-minus-forecast (O-F) residuals. The O-F residuals are then analyzed using simple statistical methods to examine the spatial distribution of differences, which are large for SCIAMACHY near the terminator. In the second stage, the MIPAS data will be actively assimilated along with the SBW/2 observations; any preliminary results of note will be discussed.

Wargan, K.↗
NASA NTRS2008

The Development of the Ares I-X Flight Test

The National Aeronautics and Space Administration (NASA) Constellation Program (CxP) has identified a series of tests to provide insight into the design and development of the Ares I Crew Launch Vehicle (CLV) and the Orion Crew Exploration Vehicle (CEV). Ares I-X was created as the first suborbital development flight test to help meet CxP objectives. The Ares I-X flight vehicle is an early operational model of Ares, with specific emphasis on Ares I and ground operation characteristics necessary to meet Ares I-X flight test objectives. Ares I-X will encompass the design and construction of an entire system that includes the Flight Test Vehicle (FTV) and associated operations. The FTV will be a test model based on the Ares I design. Select design features will be incorporated in the FTV design to emulate the operation of the CLV in order to meet the flight test objectives. The operations infrastructure and processes will be customized for Ares I-X, while still providing data to inform the developers of the launch processing system for Ares/Orion. The FTV is comprised of multiple elements and components that will be developed at different locations. The components will be delivered to the launch/assembly site, Kennedy Space Center (KSC), for assembly of the elements and components into an integrated, flight-ready, launch vehicle. The FTV will fly a prescribed trajectory in order to obtain the necessary data to meet the objectives. Ares I-X will not be commanded or controlled from the ground during flight, but the FTV will be equipped with telemetry systems, a data recording capability and a flight termination system (FTS). The in-flight part of the test includes a trajectory to simulate maximum dynamic pressure during flight and perform a stage separation representative of the CLV. The in-flight test also includes separation of the Upper Stage Simulator (USS) from the First Stage and recovery of the First Stage. The data retrieved from the flight test will be analyzed and used in the design and development of the Ares I vehicle. This paper will discuss the challenges in developing a new launch vehicle in a very short timeframe. The duration from formal Authority to Proceed to launch is 32 months with launch scheduled for April, 2009. The discussion will include changes to organizational structure, system engineering approaches, and early lessons learned for a fast tracked and highly visible project.

Ess, Robert H.↗
NASA NTRS1983

Remote sensing of agricultural crops and soils

Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

Bauer, M. E.↗
DOE OSTI2023

Characterizing the performance of node-aware strategies for irregular point-to-point communication on heterogeneous architectures

Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.

97 MATHEMATICS AND COMPUTING↗