These measurements were performed as part of the 2018 Additive Manufacturing Benchmark Test Series (AM-Bench), specifically supporting the melt pool geometry challenge (CHAL-AMB2018-02-MP) and cooling rate challenge (CHAL-AMB2018-02-CR). This dataset and the associated experiments are part of a continuing series of controlled benchmark tests, in conjunction with a conference series, with two initial goals, 1) to allow modelers of Additive Manufacturing processes to test their simulations against rigorous, highly controlled additive manufacturing benchmark test data, and 2) to encourage additive manufacturing practitioners to develop novel mitigation strategies for challenging build scenarios. More information regarding the AMBench 2018 study can be found at www.nist.gov/ambench. Multiple laser scan tracks were performed on bare nickel-based superalloy IN625 substrates using three different combinations of laser power and scan speed. A high-speed infrared camera was used to measure the infrared emissions during each scan track, allowing measurement of the melt pool length and cooling rate of the solidified material. Details related to this dataset are provided in the associated NIST Journal of Research article (in press). The associated publication with experiment details and ex-situ characterization is Lane et. al. 2020 (https://doi.org/10.1007/s40192-020-00169-1).For dataset description article; refer to https://doi.org/10.6028/NIST.AMS.100-53

These measurements were performed as part of the 2018 Additive Manufacturing Benchmark Test Series (AM-Bench), specifically supporting the melt pool geometry challenge (CHAL-AMB2018-02-MP) and cooling rate challenge (CHAL-AMB2018-02-CR). This dataset and the associated experiments are part of a continuing series of controlled benchmark tests, in conjunction with a conference series, with two initial goals, 1) to allow modelers of Additive Manufacturing processes to test their simulations against rigorous, highly controlled additive manufacturing benchmark test data, and 2) to encourage additive manufacturing practitioners to develop novel mitigation strategies for challenging build scenarios. More information regarding the AMBench 2018 study can be found at www.nist.gov/ambench. Multiple laser scan tracks were performed on bare nickel-based superalloy IN625 substrates using three different combinations of laser power and scan speed. A high-speed infrared camera was used to measure the infrared emissions during each scan track, allowing measurement of the melt pool length and cooling rate of the solidified material. Details related to this dataset are provided in the associated NIST Journal of Research article (in press). The associated publication with experiment details and ex-situ characterization is Lane et. al. 2020 (https://doi.org/10.1007/s40192-020-00169-1).For dataset description article; refer to https://doi.org/10.6028/NIST.AMS.100-53

This document provides details on the experiment and associated measurement files available for download in the dataset ?In Situ Thermography During Laser Powder Bed Fusion of a Nickel Superalloy 625 Artifact with Various Overhangs and Supports.? The measurements were acquired during the fabrication of a small nickel superalloy 625 (IN625) artifact using a commercial laser powder bed fusion (LPBF) system. The artifact consists of two half-arch features with increasing degrees of overhangs, from 5° to 85°, in increments of 10°. The artifact geometry and process are controlled to ensure consistent processing along the overhang geometry, thus enabling the effect due to overhang geometry and support structures to be isolated from effects due to inter-layer scan-strategy variations that are typical in commercial LPBF processes. The measurements include high-speed thermography of each layer, from which radiant temperature, cooling rate, and melt pool length are calculated. The objective of this experiment and data dissemination is twofold. First, to provide data for the modeling community for model validation to ensure that their models are accurately accounting for the effect of overhang geometries and support structures in thermal models. The second objective is to provide fundamental insight into these effects for researchers and process designers.

The following data files include in-situ thermographic measurement results and various additional experiment design data associated with laser-scanned single tracks and multi-track pads on bare (no-powder) nickel superalloy In718 for the 2022 Additive Manufacturing Benchmark (AM-Bench) test series. These data are associated with the AMB2022-03 series of modeling challenges described here: https://www.nist.gov/system/files/documents/2022/05/26/AMB2022-03%20Measurement%20and%20Challenge%20Descriptions_1.01.pdf. However, these data may also be used in future AM-Bench challenges. These laser-scanning tests and thermographic measurements were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT, https://www.nist.gov/el/ammt-temps).Information on the directory structure and file formats are provided in the README.txt file. Note that this dataset will be periodically updated, and additional data will be added as it is made available. Future publications will also provide more in-depth description of the data in this dataset, as will links to available analysis code and scripts. Refer to the Version number below, and updates described in this Description and the README.txt file.

The following data files include in-situ thermographic measurement results, scan strategy, and various additional data associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects for the 2022 Additive Manufacturing Benchmark (AM-Bench) test series. These data are associated with the AMB2022-01 series of modeling challenges described here: https://www.nist.gov/ambench/amb2022-01-benchmark-measurements-and-challenge-problems. However, these data may also be used in future AM-Bench challenges. These AM builds and thermographic measurements were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT, https://www.nist.gov/el/ammt-temps).Information on the directory structure and file formats are provided in the 2715_README.txt file. Note that this dataset will be periodically updated, and additional data will be added as it is made available. Future publications will also provide more in-depth description of the data in this dataset, as will links to available analysis code and scripts. Refer to the Version number below, and updates described in this Description and the 2715_README.txt file.

The following data files include in-situ thermographic measurement results, scan strategy, and various additional data associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects for the 2022 Additive Manufacturing Benchmark (AM-Bench) test series. These data are associated with the AMB2022-01 series of modeling challenges described here: https://www.nist.gov/ambench/amb2022-01-benchmark-measurements-and-challenge-problems. However, these data may also be used in future AM-Bench challenges. These AM builds and thermographic measurements were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT, https://www.nist.gov/el/ammt-temps).Information on the directory structure and file formats are provided in the 2715_README.txt file. Note that this dataset will be periodically updated, and additional data will be added as it is made available. Future publications will also provide more in-depth description of the data in this dataset, as will links to available analysis code and scripts. Refer to the Version number below, and updates described in this Description and the 2715_README.txt file.

This dataset provides surface height data from nickel super alloy 625 experiment samples built through laser powder bed fusion additive manufacturing. The experiment methodically varied part position and orientation relative to the build plate and recoater blade and details of the experiment and dataset are available in a Journal of Research at NIST article.

This data repository provides a central location for a body of work using one build of nickel-based alloy 718 (IN718) material and resulted in three different studies. The IN718 parts were manufactured by laser powder bed fusion using a range of laser energy densities (manipulation of processing variables) and orientations with respect to the build direction. The influence of processing variables on resulting grain structures, pore structures, and mechanical properties were studied in the as-built (not heat treated) condition. Some machining was completed to manufacture specific specimen geometries, while other specimens were left with rough as-built surfaces. All data associated with each of the three studies is included in this single data repository and organized into sub-folders. The three studies are briefly described below.The first study investigated the relationships among the high-cycle fatigue (HCF) life, surface roughness, and processing parameters. Standardized fatigue specimens were manufactured using 25 different sets of processing parameters by varying laser power, scan speed, layer thickness, and build orientation. Surface roughness measurements were conducted using white light interferometry; HCF life was measured; and fractography analysis was performed using scanning electron microscopy. Build orientation affected HCF life due to the relationship between build orientation and surface roughness. Increasing surface roughness decreased the fatigue life due to increasing number of surface-crack initiation sites. For a fixed build orientation, the laser-energy density, outside of the optimal range, decreased the fatigue life due to lack-of-fusion pores at low laser-energy densities and more spherical pores at high laser-energy densities.The second study investigated the effects of build orientation and laser-energy density on the pore structure, microstructure, and tensile properties. Three different build conditions were selected from the original 25 in the previous study, namely, the conditions that resulted in the worst and best fatigue lifetimes: 0° build orientation and 38 J/mm3 laser-energy density, 0° build orientation and 62 J/mm3 laser-energy density, and 60° build orientation and 62 J/mm3 laser-energy density. In terms of microstructure, all three conditions exhibited a predominantly <001> texture in the build direction, elongated grains and sub-grain boundaries. Build orientation (0° versus 60°) produced a difference in yield strength due to anisotropic grain morphology and effective grain size. The low laser-energy density specimens showed a significant decrease in all mechanical properties compared to the optimal laser-energy density specimens because the amount and size of the lack-of-fusion porosity.The third study chose to further down sample to only two materials conditions with the same laser energy density (62 J/mm3), but two build orientations (0° and 60°). The differences in processing parameters lead to subtle variations in pore networks and thus complicate the prediction of void-sensitive mechanical behaviors, including location of fracture. This study expands upon the void descriptor function (VDF), by accounting for interactions among neighboring pores and stress concentrations induced by non-spherical pores or voids. The modified VDF is evaluated against 120 computationally generated fracture simulations and six physical tensile specimens (three for each condition). The latter set of experiments, which include X-ray computed tomography measurements before and after deformation, enables evaluation against physically realistic and representative pores in AM metals. The modified VDF accurately predicts fracture location for 94 out of 120 simulated specimens. In the experimental data set, the modified VDF accurately predicts the location of fracture in four out of six specimens compared.

This data repository provides a central location for a body of work using one build of nickel-based alloy 718 (IN718) material and resulted in three different studies. The IN718 parts were manufactured by laser powder bed fusion using a range of laser energy densities (manipulation of processing variables) and orientations with respect to the build direction. The influence of processing variables on resulting grain structures, pore structures, and mechanical properties were studied in the as-built (not heat treated) condition. Some machining was completed to manufacture specific specimen geometries, while other specimens were left with rough as-built surfaces. All data associated with each of the three studies is included in this single data repository and organized into sub-folders. The three studies are briefly described below.The first study investigated the relationships among the high-cycle fatigue (HCF) life, surface roughness, and processing parameters. Standardized fatigue specimens were manufactured using 25 different sets of processing parameters by varying laser power, scan speed, layer thickness, and build orientation. Surface roughness measurements were conducted using white light interferometry; HCF life was measured; and fractography analysis was performed using scanning electron microscopy. Build orientation affected HCF life due to the relationship between build orientation and surface roughness. Increasing surface roughness decreased the fatigue life due to increasing number of surface-crack initiation sites. For a fixed build orientation, the laser-energy density, outside of the optimal range, decreased the fatigue life due to lack-of-fusion pores at low laser-energy densities and more spherical pores at high laser-energy densities.The second study investigated the effects of build orientation and laser-energy density on the pore structure, microstructure, and tensile properties. Three different build conditions were selected from the original 25 in the previous study, namely, the conditions that resulted in the worst and best fatigue lifetimes: 0° build orientation and 38 J/mm3 laser-energy density, 0° build orientation and 62 J/mm3 laser-energy density, and 60° build orientation and 62 J/mm3 laser-energy density. In terms of microstructure, all three conditions exhibited a predominantly <001> texture in the build direction, elongated grains and sub-grain boundaries. Build orientation (0° versus 60°) produced a difference in yield strength due to anisotropic grain morphology and effective grain size. The low laser-energy density specimens showed a significant decrease in all mechanical properties compared to the optimal laser-energy density specimens because the amount and size of the lack-of-fusion porosity.The third study chose to further down sample to only two materials conditions with the same laser energy density (62 J/mm3), but two build orientations (0° and 60°). The differences in processing parameters lead to subtle variations in pore networks and thus complicate the prediction of void-sensitive mechanical behaviors, including location of fracture. This study expands upon the void descriptor function (VDF), by accounting for interactions among neighboring pores and stress concentrations induced by non-spherical pores or voids. The modified VDF is evaluated against 120 computationally generated fracture simulations and six physical tensile specimens (three for each condition). The latter set of experiments, which include X-ray computed tomography measurements before and after deformation, enables evaluation against physically realistic and representative pores in AM metals. The modified VDF accurately predicts fracture location for 94 out of 120 simulated specimens. In the experimental data set, the modified VDF accurately predicts the location of fracture in four out of six specimens compared.

Single-track laser scans were produced with Yb-fiber lasers on bare plates of IN625 and IN718 using three different laser powder bed fusion machines. The laser power, scan speed, and laser spot diameter varied. Tracks were cross-sectioned and metallographically prepared. Optical micrographs were taken on etched samples. Melt pool depth and width measurements were made on optical micrographs. The dataset includes optical micrographs and melt pool width and depth measurements. These are supplemental experiments to the single-track laser scans for Additive Manufacturing Benchmark 2018 and 2022 challenges (https://www.nist.gov/ambench/am-bench-data-and-challenge-problems-0). Some of the data is associated with publications (1) https://doi.org/10.1016/j.jmapro.2021.10.053 and (2) https://doi.org/10.1007/s40192-022-00289-w.Users are strongly encouraged to first review the ?Master_TrackList_Measuremetns.xlsx? file for description of each image file.