Generating Input Data for Microstructure Modelling: A Deep Learning Approach Using Generative Adversarial Networks

For the generation of representative volume elements a statistical description of the relevant parameters is necessary. These parameters usually describe the geometric structure of a single grain. Commonly, parameters like area, aspect ratio, and slope of the grain axis relative to the rolling direc...

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Detalles Bibliográficos
Autores principales: Pütz, Felix, Henrich, Manuel, Fehlemann, Niklas, Roth, Andreas, Münstermann, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579462/
https://www.ncbi.nlm.nih.gov/pubmed/32977556
http://dx.doi.org/10.3390/ma13194236

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579462/
https://www.ncbi.nlm.nih.gov/pubmed/32977556
http://dx.doi.org/10.3390/ma13194236

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