This dataset includes files generated from post-build X-ray computed tomography (XCT) measurements of the four parts built as part of the "Overhang Part X4" in-situ process monitoring dataset (available at https://doi.org/10.18434/M32233). The "Overhang Part X4" dataset was a three-dimensional (3D) additive manufacturing (AM) build performed on the Additive Manufacturing Metrology Testbed (AMMT) by Ho Yeung and Brandon Lane on June 28, 2019. The files in this dataset include XCT image sequences for each part, and stereolithography files (.STL) of the surface data extracted from XCT, measured by Maxwell Praniewicz at the Precision Machining Research Consortium at Georgia Institute of Technology, Atlanta, GA.

This data set consists of both measured and simulated optical intensities scattered off periodic line arrays, with simulations based upon an average geometric model for these lines. These data were generated in order to determine the average feature sizes based on optical scattering, which is an inverse problem for which solutions to the forward problem are calculated using electromagnetic simulations after a parameterization of the feature geometry. Here, the array of features measured and modeled is periodic in one-dimension (i.e., a line grating) with a nominal line width of 100 nm placed at 300 nm intervals, or pitch = 300 nm; the short-hand label for the features is "L100P300." The entirety of the modeled data is included, over two thousand simulations that are indexed using a top, middle, and bottom linewidth as floating parameters. Two subsets of these data, featuring differing sampling strategies, are also provided. This data set also contains angle-resolved optical measurements with uncertainties for nine arrays which differ in their dimensions due to lithographic variations using a focus/exposure matrix, as identified in a previous publication (https://doi.org/10.1117/12.777131). We have previously reported line widths determined from these measurements based upon non-linear regression to compare theory to experiment. Machine learning approaches are to be fostered for solving such inverse problems. Data are formatted for direct use in "Model-Based Optical Metrology in R: MoR" software which is also available from data.nist.gov. (https://doi.org/10.18434/T4/1426859). Note: Certain commercial materials are identified in this dataset in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the materials are necessarily the best available for the purpose.

A web database is provided which can be used to calculate photon cross sections for scattering, photoelectric absorption and pair production, as well as total attenuation coefficients, for any element, compound or mixture (Z <= 100) at energies from 1 keV to 100 GeV. XCOM provides two forms of output: (a) tables which correspond closely in format to existing tables in the literature; (b) graphical display of the tabular data. Access to the database is provided through a web-based form located at: http://physics.nist.gov/PhysRefData/Xcom/html/xcom1.html.

The data from this instrument consists of sets of measurements of Xray intensity as a function of diffraction angle. Almost all of it is collected using a position-sensitive detector (PSD), and is stored in CIF format.

The dataset contains several MATLAB files and input files for the software package JCMsuite that enable the modeling of optical imaging of finite multi-line arrays.

,Aplikacja/demo technologiczne powstała w ramach projektu „Innowacyjny proces technologiczny wykorzystujący zunifikowany silnik renderujący, optymalizujący procesy obliczeń geometrycznych wyświetlających obraz przestrzeni 3d w czasie rzeczywistym na potrzeby tworzenia gier multiplatformowych” nr POIR.01.01.01-00-1366/20 współfinansowanego przez Unię Europejską ze środków Europejskiego Funduszu Rozwoju Regionalnego w ramach Programu Operacyjnego Inteligentny Rozwój 2014-2020.,Udostępniana aplikacja ma charakter prototypu badawczo-technologicznego (demo technologicznego) opracowanego w ramach prac B+R. Prototyp umożliwia import i wyświetlanie scen 3D oraz testowanie wybranych algorytmów renderowania obrazu w czasie rzeczywistym (m.in. raycasting, raytracing, radiosity) na platformach PC (Windows) oraz Android (API Vulkan).,Jednocześnie należy podkreślić, że zespół badawczy napotkał istotne ograniczenia technologiczne, w szczególności w zakresie uzyskania wymaganych parametrów wydajności (FPS) dla części założeń projektu. W konsekwencji nie osiągnięto kluczowych kamieni milowych, a projekt nie został doprowadzony do etapu wdrożeniowego. Udostępniany prototyp nie stanowi produktu komercyjnego, lecz efekt prac badawczo-rozwojowych zakończonych niepowodzeniem w kontekście pierwotnie zakładanych celów.,

This dataset includes the files pertaining to a 3D additive manufacturing build performed on the Additive Manufacturing Metrology Testbed (AMMT) by Ho Yeung on July 8, 2018. The files include the input command files and in-situ process monitoring data, and metadata. This data is the first of the AMMT Process Monitoring Reference Datasets (https://www.nist.gov/el/ammt-temps/datasets), as part of the Metrology for Real-Time Monitoring of Additive Manufacturing project (https://www.nist.gov/programs-projects/metrology-real-time-monitoring-additive-manufacturing).Details on the experiment design, data formats and processing, and file structures can be found in the data description article: https://doi.org/10.6028/jres.124.033