Exploratory project 2019 - deep learning for particle-laden viscoelastic flow modelling

dc.contributor.author	Fernandes, C.	por
dc.contributor.author	Faroughi, S. A.	por
dc.contributor.author	Nóbrega, J. M.	por
dc.contributor.author	McKinley, G. H.	por
dc.date.accessioned	2021-01-25T13:52:20Z
dc.date.available	2021-01-25T13:52:20Z
dc.date.issued	2020-10
dc.description.abstract	[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.	por
dc.distribution	international	por
dc.identifier.citation	C. Fernandes, S.A. Faroughi, J.M. Nóbrega, G.H. McKinley, “Exploratory Project 2019 - Deep learning for particle-laden viscoelastic flow modelling”, MIT Portugal 2020 Annual Conference, Lisbon, Portugal, 15 October, 2020	por
dc.identifier.uri	https://hdl.handle.net/1822/69655
dc.language.iso	eng	por
dc.peerreviewed	no	por
dc.rights	openAccess	por
dc.subject.fos	Engenharia e Tecnologia::Engenharia Mecânica	por
dc.title	Exploratory project 2019 - deep learning for particle-laden viscoelastic flow modelling	por
dc.type	conferencePoster	por
dspace.entity.type	Publication	en
sdum.conferencePublication	MIT Portugal 2020 Annual Conference	por

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