Deep Learning Investigation for Turbulent Flows
Title: |
Deep Learning Investigation for Turbulent Flows |
DNr: |
NAISS 2023/22-1326 |
Project Type: |
NAISS Small Compute |
Principal Investigator: |
Kin Wing Wong <kwwo@kth.se> |
Affiliation: |
Kungliga Tekniska högskolan |
Duration: |
2024-01-16 – 2024-10-01 |
Classification: |
20306 |
Homepage: |
https://www.physics.kth.se/ne/sunrise |
Keywords: |
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Abstract
This request for the computing allocation is for a master thesis project that will be commenced in Jan 2024. The work is focused on generation of 3D turbulent flow data with passive scalar based on DNS using foam-extend. The generated data will be tested with the NIF data approximation framework to achieve both dimensionality reduction and the exploration of integrating NIF for super-resoution of turbluent flow data.