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 <>
Affiliation: Kungliga Tekniska högskolan
Duration: 2024-01-16 – 2024-10-01
Classification: 20306


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.