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Sparse identification and machine learning techniques on viscoelastic fluid flows

Grant number: 23/06035-2
Support Opportunities:Scholarships abroad - Research Internship - Doctorate
Start date: September 01, 2023
End date: August 31, 2024
Field of knowledge:Physical Sciences and Mathematics - Mathematics - Applied Mathematics
Principal Investigator:Cassio Machiaveli Oishi
Grantee:Fabio Vinicius Goes Amaral
Supervisor: Steven Brunton
Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
Institution abroad: University of Washington, United States  
Associated to the scholarship:21/07034-4 - Computational sumulations and artificial inteligence for solving non-newtonian fluid flows, BP.DR

Abstract

In this project we will investigate the combination of Sparse Identification Non-linear Dynamics (SINDy) and AutoEncoders (AE) for studying viscoelastic fluid flows. SINDy is a valuable tool for identifying the governing equations of a system based on observational data, while AE can generate reduced-order models that make solving fluid flow problems more computationally efficient. This combination of techniques can lead to a better understanding of the complex behavior exhibited by viscoelastic fluids, and can help develop more accurate models for simulating and analyzing parametrized systems. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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