A unified fluid-structure interaction (FSI) formulation is presented for solid, liquid and mixed membranes. Nonlinear finite elements (FE) and the generalized-α scheme are used for the spatial and temporal discretization. The membrane discretization is based on curvilinear surface elements that can describe large deformations and rotations, and also provide a straightforward description for contact. The fluid is described by the incompressible Navier-Stokes equations, and its discretization is based on stabilized Petrov-Galerkin FE. The coupling between fluid and structure uses a conforming sharp interface discretization, and the resulting non-linear FE equations are solved monolithically within the Newton-Raphson scheme. An arbitrary Lagrangian-Eulerian formulation is used for the fluid in order to account for the mesh motion around the structure. The formulation is very general and admits diverse applications that include contact at free surfaces. This is demonstrated by two analytical and three numerical examples exhibiting strong coupling between fluid and structure. The examples include balloon inflation, droplet rolling and flapping flags. They span a Reynolds-number range from 0.001 to 2000. One of the examples considers the extension to rotation-free shells using isogeometric FE.

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Swirling jets undergoing vortex breakdown occur in many technical applications, e.g. vortex burners, turbines and jet engines. To simulate the highly nonlinear dynamics of the flow, it is necessary to use high-order numerical methods, leading to increased computational cost. To be able to perform simulations in acceptable turn-around time, an available LES code for solving the filtered compressible Navier-Stokes equations in cylindrical coordinates using compact finite-difference schemes was parallelized for massively-parallel architectures. The parallelization was done following the ghost-cell approach for filtering in the three spatial directions. The inter-process communication is handled using the message passing interface (MPI). The weak and strong scaling properties of the code indicate that it can be used for massively parallel simulations using several thousand processors.