Capturing functional relations in fluid–structure interaction via machine learning

While fluid–structure interaction (FSI) problems are ubiquitous in various applications from cell biology to aerodynamics, they involve huge computational overhead. In this paper, we adopt a machine learning (ML)-based strategy to bypass the detailed FSI analysis that requires cumbersome simulations...

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Detalles Bibliográficos
Autores principales: Soni, Tejas, Sharma, Ashwani, Dutta, Rajdeep, Dutta, Annwesha, Jayavelu, Senthilnath, Sarkar, Saikat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Engineering
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8984386/
https://www.ncbi.nlm.nih.gov/pubmed/35401993
http://dx.doi.org/10.1098/rsos.220097

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8984386/
https://www.ncbi.nlm.nih.gov/pubmed/35401993
http://dx.doi.org/10.1098/rsos.220097

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