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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Neural Network Code MATLAB

SAND2022-12606 O Neural Network Code MATLAB reads in an excel file, processes the data, trains a neural network, and tests the neural network. The code generates predictions of diffusion constants based on the data in the excel file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Allers, Joshua↗
DOE OSTI2015

Matlab Scripts and Sample Data Associated with Water Resources Research Article

Scripts and data acquired at the Mirror Lake Research Site, cited by the article submitted to Water Resources Research: Distributed Acoustic Sensing (DAS) as a Distributed Hydraulic Sensor in Fractured Bedrock M. W. Becker(1), T. I. Coleman(2), and C. C. Ciervo(1) 1 California State University, Long Beach, Geology Department, 1250 Bellflower Boulevard, Long Beach, California, 90840, USA. 2 Silixa LLC, 3102 W Broadway St, Suite A, Missoula MT 59808, USA. Corresponding author: Matthew W. Becker (matt.becker@csulb.edu).

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Plotting XPS Narrow Scans (and other Data) with MATLAB’s Powerful Plotting Capabilities, 2. An Introduction to Handle Graphics

The graphical representation of numerical data plays a vital role in chemistry, materials science, and every other scientific field. No matter how good your results are, poorly represented data can ultimately make your work confusing. Indeed, with an increase in the amount of data that is being gathered, e.g., by the Materials Genome Initiative, or in X-ray photoelectron spectroscopy (XPS) or time-of-flight secondary ion mass spectrometry (ToF-SIMS) depth profiles, the importance of effectively representing data has increased. Good figures also matter because many researchers will not look at more than the title, abstract, and perhaps a few key figures from a paper.

42 ENGINEERING↗
DOE OSTI2016

Kinetic modelling of chlorination of nitrided ilmenite using MATLAB

In the present study, chlorination of nitride ilmenite using 2{sup k} factorial design was investigated. The reduction experiments were carried out in a temperature range of 400°C to 500°C, chlorination duration from 1 hour to 3 hours and using different type of carbon reactant. Phases of raw materials and reduced samples were analyzed by X-ray diffraction (XRD). Ilmenite was reduced to TiO{sub x}C{sub y}N{sub z} through carbothermal and nitridation for further chlorination into titanium tetrachloride. The Design of Experiment analysis suggested that the types of carbon reactant contribute most influence to the extent of chlorination of nitride ilmenite. The extent of chlorination was highest at 500°C with 3 hours chlorination time and carbon nanotube as carbon reactant.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

MatLab Scripts

Explore the source record for details and available documents.

Ho, Clifford↗
DOE OSTI2012

ATS Spotted MSI Analysis with Matlab

Samples are placed on a surface using an acoustic transfer system (ATS). This results in one ore more small droplets on a surface. Typically there are hundreds to thousands of these droplets arrayed in a regular coordinate system. The surface is analyzed using mass spectrometry imaging (MSI) and at each position, one or more mass spectra are recorded. The purpose of the software is to help the user assign locations to the spots and build a report for each spot.

Bowen, Benjamin↗
DOE OSTI2019

2D-DIC Challenge MATLAB Analysis Code v. 1.0

This code replicates the analysis completed in the published article (see reference below) for the 2D-DIC Challenge (https://sem.org/dic-challenge/), conducted under the auspices of the Society for Experimental Mechanics (SEM). The purpose of the DIC Challenge is to provide a set of vetted and standard images, which all users and developers of Digital Image Correlation (DIC) software can use -DIC Challenge results from Sample 14 and Sample 15 of the DIC-Challenge images, and computes various statistics on the data, such as the noise, bias, and spatial resolution. P.L. Reu, E. Toussaint, E. Jones, H.A. Bruck, M. Iadicola, R. Balcaen, D.Z. Turner, T. Siebert, P. Lava, M. Simonsen (2018) Exp. Mech. 58(7):1067-1099, https://doi.org/10.1007/s11340-017-0349-0.

Jones, Elizabeth↗
DOE OSTI2024

FitIsoAndDeff and DeffCalculator Matlab Codes

These codes estimate effective diffusivity for species transport in materials and simultaneously fit multiple temperatures of measured isotherm and effective diffusivities for sorption transport of species through materials. Assumes triple-mode type sorption thermodynamics with mobile and immobile species in quasi-equilibrium.

Foley, BrandonR↗
DOE OSTI2011

MicroCT: Automated Analysis of CT Reconstructed Data of Home Made Explosive Materials Using the Matlab MicroCT Analysis GUI

This Standard Operating Procedure (SOP) provides the specific procedural steps for analyzing reconstructed CT images obtained under the IDD Standard Operating Procedures for data acquisition and MicroCT image reconstruction, per the IDD Quality Assurance Plan for MicroCT Scanning. Although intended to apply primarily to MicroCT data acquired in the HEAFCAT Facility at LLNL, these procedures may also be applied to data acquired at Tyndall from the YXLON cabinet and at TSL from the HEXCAT system. This SOP also provides the procedural steps for preparing the tables and graphs to be used in the reporting of analytical results. This SOP applies to production work - for R and D there are two other semi-automated methods as given in [4, 5].

42 ENGINEERING↗
DOE OSTI2011

MicroCT: Semi-Automated Analysis of CT Reconstructed Data of Home Made Explosive Materials Using the Matlab MicroCT Analysis GUI

This Standard Operating Procedure (SOP) provides the specific procedural steps for analyzing reconstructed CT images obtained under the IDD Standard Operating Procedures for data acquisition and MicroCT image reconstruction, per the IDD Quality Assurance Plan for MicroCT Scanning. Although intended to apply primarily to MicroCT data acquired in the HEAFCAT Facility at LLNL, these procedures may also be applied to data acquired at Tyndall from the YXLON cabinet and at TSL from the HEXCAT system. This SOP also provides the procedural steps for preparing the tables and graphs to be used in the reporting of analytical results. This SOP applies to R and D work - for production applications, use [4].

42 ENGINEERING↗
DOE OSTI2013

Creating a Vibration Data Visualization and Analysis Graphical User Interface in Matlab [Poster]

Vibration testing in W-14 results in large amounts of data that need to be preprocessed before being used in reports or for model verification. It can take a large amount of time to accomplish simple, repetitive tasks on many channels of data. A Graphical User Interface (GUI) streamlines visualization and simple processing of the data to make the process faster as well as more intuitive. Simple editing methods, such as data segmentation and axis conversion, put the data in a form that can be easily moved into a more advanced modal analysis or data plotting package.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗