Gas speed measurements using hot-wire anemometers (HWA) on a commercial laser powder bed fusion (LBPF) machine were recorded as a function of position (X, Y, Z) and nozzle type (standard and grid).

This repository contains scripts and supporting information for a set of demonstrations related to the 2022 AM-Bench challenge series.In particular, the data used in this demonstration comes from the 2018 AM-Bench challenge documented at https://www.nist.gov/ambench/amb2018-02-description.The script queries the AM-Bench 2018 repository located at https://ambench.nist.gov/, then processes the returned XML-based results, does some image processing, and generates plots of melt pool dep

Macro-scale tensile data on additively manufactured (AM) IN625 in the as-built microstructural condition at room temperature and at different strain rates are provided in this data publication. The specimens are machined in accordance with ASTM-E8 subsize specimen with a gauge width of 6 mm and a gauge thickness of 4 mm. Three specimens are tested at a nominal strain rate of 0.001 1/s and 2 specimens are tested at a nominal strain rate of 0.01 1/s on a servo hydraulic material testing machine using a constant crosshead displacement rate of 0.03175 mm/s and 0.3175 mm/s, respectively.

Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0.

The NISTmAb Interlaboratory NMR Study is a joint effort between 25 organizations to evaluate the performance of two-dimensional (2D) heteronuclear NMR as used to characterize the high order structure (HOS) of proteins, with the aim of harmonizing 2D-NMR methods to support industrial use of NMR as applied to mAb therapeutics. This study features nearly equal representation between laboratories from academia, government, and industry, including 4 laboratories from regulatory agencies.

X-ray computed tomography (XCT) datasets with known ground truth pores were developed using realistic XCT simulation. Non-overlapping spherical pores of varying sizes are randomly distributed in a cylindrical part near surfaces and within the core. Ground truth data, ground truth binary data, and reconstructed data for three different signal-to-noise ratios (SNRs) are provided. The data set can be used for evaluation and comparison of image segmentation/detection algorithms.

NIST developed a reference material consisting of synthetic fragments of the SARS-CoV-2 virus RNA, which is the target of molecular diagnostic tests. These RNA fragments can assist in the development and validation of RT-qPCR assays for the detection SARS-CoV-2. The RNA fragments are characterized for concentration using digital PCR methods, may be used to assess limits of detection for SARS-CoV-2 assays, and may calibrate other in-house or commercial SARS-CoV-2 controls. This dataset includes data used for RTGM 10169 SARs-Cov-2 Research Grade Test Material validation.

This challenge is to predict the macroscopic stress-strain response of compression samples across a range of temperatures taken from the base leg of the IN625 AMB2018-01 build in both the build direction (Z-axis) and a transverse-build direction (Y-axis). The specific temperatures of interest are 298 K, 523 K, and 773 K. The calibration data provided in this dataset corresponds to the build direction compression tests done at 298 K and 773 K.

This Photopolymer AM-Bench 2022 Challenge is to accurately model the relationship between photopatterned print fidelity and cure depth to exposure time with four resins, which serve to orthogonally probe the relationship between resin reactivity and viscosity. The data sets included here are broken down into three categories and are as follows: (1) resin characterization: Fourier transform infrared spectroscopy and rheometry, (2) light engine characterization: photomask dimensions, beam profilometry and radiometry, and (3) cure depth and profile: laser scanning confocal microscopy.

In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. Using OpenFOAM, we simulated the extrusion of filaments and droplets into a moving bath. OpenFOAM is an open source computational fluid dynamics solver. This repository contains the following Python tools: - Tools for generating input files for OpenFOAM v1912 or OpenFOAM v8 tailored to a conical or cylindrical nozzle extruding a filament into a static support bath. - Tools for monitoring the status of OpenFOAM simulations and aborting them if they are too slow.