Real-time prediction of the deformation of microcapsules using Proper Orthogonal Decomposition

Microcapsules are liquid droplets enclosed by a thin elastic membrane. Being suspended in an external fluid, they undergo large deformations when flowing. Their deformation can be solved numerically, but the resolution of fluid–structure interactions (FSI) requires extremely long computation times. This is major constraint for instance identifying membrane mechanical properties from experimentations microcapsules flowing microfluidic channel similar size (Hu et al. PFE 2013). We propose to apply Model Order Reduction (MOR) predict real time steady-state capsule deformed shape, needed determine elasticity. A database shapes was obtained numerically solving three-dimensional (3D) FSI through finite element-boundary integral method coupling, and varying systematically two non-dimensionalized parameters problem: capillary number, ratio viscous forces, capsule-to-tube ratio. Among MOR techniques, we chose Proper Orthogonal Decomposition (POD) onto database, which provides vector basis principal components, defining multi-dimensional space. The advantage that, all mapped into this new space, form manifold (smooth hypersurface) that represents admissible solutions problem. show POD with walking technique successfully applied 3D microcapsule data sets, whether Lagrangian (e.g. known position fields) or Eulerian (i.e. acquired experimentally using methods like level sets). In both cases, problem dimensionality reduced, predicted within times milliseconds, accurately fit full simulations. paves way real-time computations capsules flow, while retaining physical ingredients