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Research theme area:
Fluid Mechanics, advanced image analysis, noise removal, pressure field reconstruction, and particle image velocimetry.
Abstract:
The candidate will collaborate with researchers from the FAPESP-Shell Research Centre for Greenhouse Gas Innovation of POLI-USP at the University of São Paulo. Summary of the program and projects can be found at the RCGI website (https://sites.usp.br/rcgi/).
The selected candidate will employ machine learning and other techniques based on the NavierStokes equations to perform flow analysis with a focus on noise removal and pressure field reconstruction. The candidate is expected to work with experimental and numerical data, especially from electrolyzer and fuel cell flows.
Description:
The applicant will contribute in line with the main objectives of the project:
Work with flows obtained by computational fluid dynamics simulation, synthetic images or experimentally. Use and/or develop computational algorithms (filters and/or neural networks) to remove noise from flow images. Develop computational algorithms
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