Digital-twin for particle-laden viscoelastic fluids: ML-Based models to predict the drag coefficient of random arrays of spheres

MIT-EXPL/TDI/0038/2019. FEDER funds through the COMPETE 2020 Programme and National Funds through FCT (Portuguese Foundation for Science and Technology) under the projects UIDB/05256/2020, UID-P/05256/2020, APROVA (MIT-EXPL/TDI/0038/2019) - Aprendizagem PROfunda na modelação de escoamentos com fluid...

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Detalhes bibliográficos
Autor principal: Loiro, Carina Luzia Melo Monteiro (author)
Outros Autores: Fernandes, C. (author), McKinley, Gareth Huw (author), Faroughi, Salah Aldin (author)
Formato: conferencePoster
Idioma:eng
Publicado em: 2021
Assuntos:
Engenharia e Tecnologia::Engenharia Mecânica
Texto completo:http://hdl.handle.net/1822/73545
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/73545
Descrição
Resumo:MIT-EXPL/TDI/0038/2019. FEDER funds through the COMPETE 2020 Programme and National Funds through FCT (Portuguese Foundation for Science and Technology) under the projects UIDB/05256/2020, UID-P/05256/2020, APROVA (MIT-EXPL/TDI/0038/2019) - Aprendizagem PROfunda na modelação de escoamentos com fluidos de matriz Viscoelástica Aditivados com partículas (POCI-01-0145-FEDER-016665) and HPC-EUROPA3 (INFRAIA-2016-1-730897). The authors would like to acknowledge the Minho University cluster under the project NORTE-07-0162-FEDER000086 (URL: http://search6.di.uminho.pt), the Minho Advanced Computing Center (MACCcpca_a2_6052_2020) (URL: https://macc.fccn.pt) and Julich Super Computing Centre (jusuf-iceiprace-2020-0009) for providing HPC resources that have contributed to the research results reported within this poster

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