Fully Funded PhD Position in High-fidelity laser tomography of flow fields via data assimilation
Summary of PhD Program:
This project will develop data assimilation for high-fidelity flow-field reconstruction using LAT. Data assimilation (DA) algorithms seek to solve the equations governing fluid motion subject to databased constraints. Instead of training an end-to-end neural network using simulated data, DA algorithms integrate ground-true physics, into the network, so call physics-informed neural network. Therefore, high-fidelity flow-field images are expected to be reconstructed by DA-assisted LAT. The student who joins our group will learn the fundamentals of laser absorption tomography, computational and data-driven solutions for inverse problems. The student will have a high chance of working with renowned international researchers and industrial collaborators.
