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.

One additively manufactured (AM) laser powder bed fusion (PBF-L) Inconel 625 mesoscale tensile specimen (gauge dimensions approximately 0.2mm x 0.2 mm x 1mm) was extracted from build AMB2022-CBM-B1 specimen TH1 and tested at room temperature using a quasistatic strain rate of 0.001/s to failure.  Microstructure was measured using x-ray computed tomography (XRCT) and scanning electron microscopy (SEM) techniques on the specimen gauge section or adjacent material.  Large-area electron backscatter diffraction was used to measure crystallographic texture and grain size/morphology of the entire

Additively manufactured (AM) laser powder bed fusion (PBF-L) Inconel 625 blocks were built with two different scan strategies: XY and X-only.  96 tensile specimens were extracted from blocks at different tensile axis orientations with respect to the build direction to yield the following conditions: XY scan strategy (0, 30, 45, 60, and 90 degree orientation w.r.t. build direction) and X-only scan strategy (0, 60, 90 degree orientation w.r.t.

These images, videos, and tables show experimental data, where single lines of viscoelastic inks were extruded into moving viscoelastic support baths. Lines were printed at varying angles relative to the camera, such that videos and images captured the side of horizontal lines, cross-sections of horizontal lines, and the side of vertical lines. Metadata including pressure graphs, programmed speeds, toolpaths, and rheology data are also included.

In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. This repository includes Python code for analyzing and managing images and videos of the printing process during extrusion of single filaments. The zip file contains the state of the code when the associated paper was submitted. The link to the GitHub page goes to version 1.0.0, which is the same as the code attached here. From there, you can also access the current state of the code.Associated with: L. Friedrich, R. Gunther, J.

Round 9 Test DatasetThis is the test data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 9 Holdout DatasetThis is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

The absolute laser absorption was measured simultaneously with X-ray imaging during laser melting of Ti-6Al-4V solid metal. The data included here are the time-resolved absolute absorbed power and the Xray images acquired at the same time, along with timing data for synchronization. Also included is information about the experimental configuration including applied laser power, laser beam spatial profile, and the experimental setup. A text document is included that describes all files.

Round 8 Train DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering (QA on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.