Cargando…
Digital rheometer twins: Learning the hidden rheology of complex fluids through rheology-informed graph neural networks
Precise and reliable prediction of soft and structured materials’ behavior under flowing conditions is of great interest to academics and industrial researchers alike. The classical route to achieving this goal is to construct constitutive relations that, through simplifying assumptions, approximate...
| Autores principales: | , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171907/ https://www.ncbi.nlm.nih.gov/pubmed/35544690 http://dx.doi.org/10.1073/pnas.2202234119 |