Yuan Fang
- yuanfang1@student.unimelb.edu.au
- Desk 4.052, Level 4, Melbourne Connect
Thesis Title
Towards developing more general and more accurate turbulence models via machine learning methods
Research overview
My research involves exploring data-driven methods in the fluid dynamics field. Current work has been conducted on overcoming the conundrum that lies in the generalizability of the developed turbulence models. They commonly have poor performance on flows different from the training sets. Moreover, the interest is also in building turbulence models for more complicated flows, such as turbine and three-dimensional flows, and other models such as transition and heat flux models. During the process, the relevant underlying physics of the flow fields are hoped to be uncovered by resorting to data-driven methods.
Supervisors
Qualifications
M.Eng. Ship and Ocean Engineering, Shanghai Jiao Tong University, China (2020)
B.Eng. Ship and Ocean Engineering, Dalian Maritime University, China (2017)