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 depths. This work was originally done by Miyu Mudalamane (University of Delaware) during a 2021 Summer Undergraduate Research Fellowship at NIST supervised by Chandler Becker and Gretchen Greene (NIST Office of Data and Informatics, ODI).It was later adapted as this notebook by Jordan Raddick (Johns Hopkins University) in consultation with NIST ODI staff.Additional datasets and challenge problem documentation are available through the NIST Public Data Repository record at https://data.nist.gov/od/id/6D6EC9B3A4147BE2E05324570681EEC91931 with an associated publication (https://link.springer.com/article/10.1007/s40192-020-00169-1) documenting the experiments.
About this Dataset
| Title | AM-Bench image analysis demonstration |
|---|---|
| Description | 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 depths. This work was originally done by Miyu Mudalamane (University of Delaware) during a 2021 Summer Undergraduate Research Fellowship at NIST supervised by Chandler Becker and Gretchen Greene (NIST Office of Data and Informatics, ODI).It was later adapted as this notebook by Jordan Raddick (Johns Hopkins University) in consultation with NIST ODI staff.Additional datasets and challenge problem documentation are available through the NIST Public Data Repository record at https://data.nist.gov/od/id/6D6EC9B3A4147BE2E05324570681EEC91931 with an associated publication (https://link.springer.com/article/10.1007/s40192-020-00169-1) documenting the experiments. |
| Modified | 2022-09-27 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | additive manufacturing , benchmark , AM-Bench |
{
"identifier": "ark:\/88434\/mds2-2801",
"accessLevel": "public",
"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "Chandler A. Becker"
},
"programCode": [
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"@type": "dcat:Dataset",
"description": "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 depths. This work was originally done by Miyu Mudalamane (University of Delaware) during a 2021 Summer Undergraduate Research Fellowship at NIST supervised by Chandler Becker and Gretchen Greene (NIST Office of Data and Informatics, ODI).It was later adapted as this notebook by Jordan Raddick (Johns Hopkins University) in consultation with NIST ODI staff.Additional datasets and challenge problem documentation are available through the NIST Public Data Repository record at https:\/\/data.nist.gov\/od\/id\/6D6EC9B3A4147BE2E05324570681EEC91931 with an associated publication (https:\/\/link.springer.com\/article\/10.1007\/s40192-020-00169-1) documenting the experiments.",
"language": [
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],
"title": "AM-Bench image analysis demonstration",
"distribution": [
{
"accessURL": "https:\/\/github.com\/usnistgov\/ambench-sciserver-outreach",
"format": "Python scripts in a GitHub repository",
"description": "Scripts to process and analyze melt track cross-sections in images from the 2018 AM-Bench challenge (https:\/\/www.nist.gov\/ambench)",
"title": "AM-Bench image analysis demonstration"
}
],
"license": "https:\/\/www.nist.gov\/open\/license",
"bureauCode": [
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"modified": "2022-09-27 00:00:00",
"publisher": {
"@type": "org:Organization",
"name": "National Institute of Standards and Technology"
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"theme": [
"Mathematics and Statistics:Image and signal processing",
"Manufacturing:Additive manufacturing",
"Materials:Metals"
],
"issued": "2022-10-20",
"keyword": [
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"benchmark",
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]
}
