Postdoctoral Research Associate

Full time: 35 hours/week 

Fixed-term: 36 months

The opportunity: 

Solutions of long and flexible polymer molecules do not flow like water. Even when flowing slowly, these fluids exhibit hydrodynamic instabilities and a new type of turbulence, so-called elastic turbulence (ET). When flowing faster, polymer solutions exhibit a new state – elasto-inertial turbulence (EIT) – seen in subcritical wall-bounded (pipe) flows. Considerable progress has been made in probing ET and EIT flows in state-of-the-art viscoelastic models, but questions remain as to how these models actually connect to experimental observations. At the heart of this is the continuing suspicion about the fidelity of theoretical models to describe experiments. An opportunity thus exists to develop new methods for the investigation of viscoelastic fluid flows that rely on integrating experimental, theoretical, and machine-learning methods that can lead to quantitative agreement between experimental observations and models. 

This postdoc forms parts of an integrated research program in which experiments and simulations will be designed to access extensive time and space information in order to perform experiment/simulation comparison. We will use statistical methods to identify similarities and discrepancies between experiments and simulations, as well as machine learning tools. The project itself falls into three separate “aims”, and the post holder will work on all three: Aim 1 will focus on 2D flows and simulations to obtain the best possible agreement (statistics, flow structures, etc) between experiments and simulations. ML methods will be developed and applied to identify and optimize simulation parameters. An important part of this aim is to estimate the polymer stresses in the experimental flows using data-driven methods. Aim 2 will explore the uniqueness of the elastic turbulence flow state in flows with streamline curvature and in parallel shear flows, in both 2D and 3D flows. Aim 3 will relax the low inertia condition and explore the relationship between ET and EIT in 2D flows. 

There will be extensive opportunities for travel to visit our experimental collaborators at the University of Pennsylvania, as well as collaborators in DAMTP, University of Cambridge and the University of Vermont.  

This post is full-time (35 hours per week).

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