Professor Lian Shen

This group works on a multitude of crucial fluid dynamical problems involving multiphase flows, wind-wave interactions, and fluid-structure interactions using cutting-edge CFD tools that have widespread applications in weather and climate study, understanding various aspects of geophysical flows, and renewable energy harvesting, to mention a few. They are also actively involved in developing numerical schemes to efficiently and accurately devise fluid flow simulations for their research.

• Multiphase bubbly flows: The group will perform computational research on multiphase bubbly flows under breaking waves with and without forced wind conditions, which will be useful in understanding the complex coupling between the ocean and the atmosphere. They currently employ high-fidelity Direct Numerical Simulation (DNS) of the incompressible Navier-Stokes (NS) equations to resolve the turbulent flow field under a breaking wave, wherein the complex topology of the air-water interface is captured by a Coupled Level Set Volume of Fluid (CLSVOF) method. The data extracted from an ensemble of these simulations is utilized to identify and track bubble events using a parallelized post-processing pipeline which enables the researchers to extract information on the temporal evolution of the bubble size distribution and study mechanisms of direct entrainment and turbulent fragmentation. Furthermore, in order to investigate the dynamics of the small, sub-grid scale bubbles they couple the NS solver with an additional Boltzmann Transport Equation (BTE) containing terms involving air entrainment, dissolution and bubble interaction models, which is numerically solved to yield the void fraction of the sub-grid scale bubble cloud. They also study the generation and dynamics of the droplets (ocean spray) produced in the presence of wind in the course of a breaking wave event. They use a block-structured adaptive mesh refinement (BSAMR) framework to dynamically refine regions of the simulation domain to derive accurate numerical data on fine scale interfacial and vortical structures.
• Fish swimming mechanisms: The group works on fully coupled Fluid Structure Interaction (FSI) simulations, where structure deformations are coupled with fluid flow and vice versa. Using the Immersed Boundary Method (IBM) we can resolve complex structures and couple them with high resolution data obtained from DNS. They then solve for the structure position using Newton-Euler Equation. Their code has the capability to implement strong and loose coupling between fluid and structure, which enables the solver to handle a wide range of density ratios. The group aims to study the different locomotive mechanisms employed by fish, body and/or caudal fin (BCF) mode and median and/or paired fin (MPF) mode. The data collected from these simulations will help the researchers understand swimming efficiencies of different fish and to create more efficient underwater robots. They also plan to study the effect of fish traveling in schools and the impact different orientations have on efficiency. To accurately resolve vorticity fluctuation, they use adaptive mesh refinement (AMR) to efficiently refine regions of high vorticity gradients. 
• Wave-energy converters: The group is performing a high-fidelity numerical study on wave-energy converters (WECs) and their efficiency at generating electrical power from incoming waves. WECs generally use the oscillatory motion of objects in shallow water to power pumps that generate renewable energy. A budding technology, WECs can create a strong, steady source of renewable energy for shorelines around the world, a useful contribution as many of the other renewable energy sources are inconsistent throughout the day. Since it is a young technology, research on the fluid-structure interaction of WECs is important to do now. The researchers use the immersed boundary method to capture the geometry in the simulation, which allows them to test out complicated structure and different forms of WECs.

Research by this group was featured on the MSI website in August 2018: Modeling an Air-Pollution Filtration System.