Publicação
Exploratory project 2019 - deep learning for particle-laden viscoelastic flow modelling
| Resumo: | [extract] Objetives: explore the possibility of using Deep Learning (DL) techniques to evaluate the drag coefficient of small non-Brownian particles translating and settling in nonlinear viscoelastic fluids. The long-term objective is the development of a 3D numerical code for particle-laden viscoelastic flows (PLVF), which will contribute to understanding many advanced manufacturing and industrial operations, specifically the hydraulic fracturing process. |
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| Autores principais: | Fernandes, C. |
| Outros Autores: | Faroughi, S. A.; Nóbrega, J. M.; McKinley, G. H. |
| Assunto: | Engenharia e Tecnologia::Engenharia Mecânica |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | póster em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | [extract] Objetives: explore the possibility of using Deep Learning (DL) techniques to evaluate the drag coefficient of small non-Brownian particles translating and settling in nonlinear viscoelastic fluids. The long-term objective is the development of a 3D numerical code for particle-laden viscoelastic flows (PLVF), which will contribute to understanding many advanced manufacturing and industrial operations, specifically the hydraulic fracturing process. |
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