This resource is the implementation in XML Schema [1] of a data model that describes the Additive Manufacturing Benchmark 2022 series data. It provides a robust set of metadata for the build processes and their resulting specimens and for measurements made on these in the context of the AM Bench 2022 project.The schema was designed to support typical science questions which users of a database with metadata about the AM Bench results might wish to pose. The metadata include identifiers assigned to build products, derived specimens, and measurements; links to relevant journal publications, documents, and illustrations; provenance of specimens such as source materials and details of the build process; measurement geometry, instruments and other configurations used in measurements; and access information to raw and processed data as well as analysis descriptions of these datasets.This data model is an abstraction of these metadata, designed using the concepts of inheritance, normalization, and reusability of an object oriented language for ease of extensibility and maintenance. It is simple to incorporate new metadata as needed.A CDCS [2] database at NIST was filled with metadata provided by the contributors to the AM Bench project. They entered values for the metadata fields for an AM Bench measurement, specimen or build process in tabular spreadsheets. These entries were translated to XML documents compliant with the schema using a set of python scripts. The generated XML documents were loaded into the database with a persistent identifier (PID) assigned by the database.[1] https://www.w3.org/XML/Schema[2] https://www.nist.gov/itl/ssd/information-systems-group/configurable-data-curation-system-cdcs/about-cdcs

The following data files are provided in support of the 2022 Additive Manufacturing Benchmark test series (AM-Bench 2022) modeling challenges associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects. These AM builds performed on the NIST Additive Manufacturing Metrology Testbed (AMMT). Description of the associated measurements and model are provided on the AMB2022-01 challenge description webpage (https://www.nist.gov/ambench), and information on the directory structure and file formats available in the 2607_README.txt file.Note that this dataset may be periodically updated. Refer to the Version number below, and updates described in this Description and the README file.

The following data files are provided in support of the 2022 Additive Manufacturing Benchmark test series (AM-Bench 2022) modeling challenges associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects. These AM builds performed on the NIST Additive Manufacturing Metrology Testbed (AMMT). Description of the associated measurements and model are provided on the AMB2022-01 challenge description webpage (https://www.nist.gov/ambench), and information on the directory structure and file formats available in the 2607_README.txt file.Note that this dataset may be periodically updated. Refer to the Version number below, and updates described in this Description and the README file.

The following data files are provided in support of the 2022 Additive Manufacturing Benchmark test series (AM-Bench 2022) modeling challenges associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects using variety of custom scan strategies. These AM builds were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT, https://www.nist.gov/el/ammt-temps). Note that these 3D builds are an extension of those for the AMB2022-01 challenges, and part geometry, materials data, and 'nominal' 3D build data are available in the corresponding data repository (https://doi.org/10.18434/mds2-2607)Description of the associated 3D builds and measurements are provided on the AMB2022-02 challenge description webpage (https://www.nist.gov/ambench). Note that this dataset may be periodically updated. Refer to the Version number below, and updates described in this Description and the README file.

The following data files are provided in support of the 2022 Additive Manufacturing Benchmark test series (AM-Bench 2022) modeling challenges associated with laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects using variety of custom scan strategies. These AM builds were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT, https://www.nist.gov/el/ammt-temps). Note that these 3D builds are an extension of those for the AMB2022-01 challenges, and part geometry, materials data, and 'nominal' 3D build data are available in the corresponding data repository (https://doi.org/10.18434/mds2-2607)Description of the associated 3D builds and measurements are provided on the AMB2022-02 challenge description webpage (https://www.nist.gov/ambench). Note that this dataset may be periodically updated. Refer to the Version number below, and updates described in this Description and the README file.

This dataset includes the files pertaining to a 3D additive manufacturing experiment performed on the Additive Manufacturing Metrology Testbed (AMMT) by Ho Yeung on July 11, 2019. The experiment included 55 separate laser scanned 'pads' created on a bare-metal plate. Each pad corresponds to a different laser processing setting, described in the paper Yeung et al. 2020 (https://doi.org/10.1016/j.mfglet.2020.07.005). Files include the input command files, in-situ process monitoring data and metadata, and ex-situ microscope photographic images of the pad surfaces. This data is one of a set of 'AMMT Process Monitoring Datasets', as part of the Metrology for Real-Time Monitoring of Additive Manufacturing project at the National Institute of Standards and Technology (https://www.nist.gov/el/ammt-temps/datasets).

This dataset includes the files pertaining to a 3D additive manufacturing experiment performed on the Additive Manufacturing Metrology Testbed (AMMT) by Ho Yeung on July 11, 2019. The experiment included 55 separate laser scanned 'pads' created on a bare-metal plate. Each pad corresponds to a different laser processing setting, described in the paper Yeung et al. 2020 (https://doi.org/10.1016/j.mfglet.2020.07.005). Files include the input command files, in-situ process monitoring data and metadata, and ex-situ microscope photographic images of the pad surfaces. This data is one of a set of 'AMMT Process Monitoring Datasets', as part of the Metrology for Real-Time Monitoring of Additive Manufacturing project at the National Institute of Standards and Technology (https://www.nist.gov/el/ammt-temps/datasets).

The following data files are provided in support of the AM Bench 2022 modeling challenges associated with bare plate single track and pad laser scans performed on the NIST Additive Manufacturing Metrology Testbed (https://www.nist.gov/el /ammt-temps). These measurements were used in the AMB2022-03 set of challenges associated with track melt pool geometry (CHAL-AMB2022-03-TMPG) and pad melt pool geometry (CHAL-AMB2022-03-PMPG). Description of the associated measurements and modeling challenges are provided on the AMB2022-03 challenge description webpage (https://www.nist.gov/document/amb2022-03-measurement-and-challenge-descriptions-version-101).

The following data files are provided in support of the AM Bench 2022 modeling challenges associated with bare plate single track and pad laser scans performed on the NIST Additive Manufacturing Metrology Testbed (https://www.nist.gov/el /ammt-temps). These measurements were used in the AMB2022-03 set of challenges associated with track melt pool geometry (CHAL-AMB2022-03-TMPG) and pad melt pool geometry (CHAL-AMB2022-03-PMPG). Description of the associated measurements and modeling challenges are provided on the AMB2022-03 challenge description webpage (https://www.nist.gov/document/amb2022-03-measurement-and-challenge-descriptions-version-101).

This dataset includes files from the experiment titled 'OverhangPartX4' pertaining to 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 include the input command files, materials data, in-situ process monitoring data, and metadata. This data is one of a set of 'AMMT Process Monitoring Datasets', as part of the Metrology for Real-Time Monitoring of Additive Manufacturing project at the National Institute of Standards and Technology (NIST). Ex-situ part characterization data, including X-ray computed tomography measurements, will be provided as they are made available. Readers should refer to the AMMT datasets web page for updates (https://www.nist.gov/el/ammt-temps/datasets).