Generative Adversarial Networks Enable Outlier Detection and Property Monitoring for Additive Manufacturing of Complex Structures [dataset]

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Henkes, Alexander ;Herrmann, Leon;Wessels, Henning;Kollmannsberger, Stefan

Description

Microstructure dataset utilized in "Generative Adversarial Networks Enable Outlier Detection and Property Monitoring for Additive Manufacturing of Complex Structures" (http://dx.doi.org/10.2139/ssrn.4711476 ):- lattice structures in folders lattice_structures and lattice_structures_defective were employed in Section 3.1- spherical voids in folders spherical_voids and spherical_voids_perturbed were employed in Section 3.2The lattice structures are extracted from the CT scans in "Image-based numerical characterization and experimental validation of tensile behavior of octet-truss lattice structures" (https://doi.org/10.1016/j.addma.2021.101949)

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.9

FAIR Score

65%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Mendeley Data

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Computer Vision and Pattern Recognition

Field

Computer Science

Domain

Physical Sciences

Confidence Score

52%

Source

Scholar Data Model

Keywords

Computational MechanicsStructural Health MonitoringDeep LearningHomogenizationDesign for Additive ManufactureNeural NetworkGenerative Adversarial Network

Normalization Factors

FT

43.27

CTw

1.00

MTw

1.00