Dense interpolations of LPT data in the presence of generic solid objects

Abstract

Three-dimensional Lagrangian Particle Tracking measurements with Hellium Filled Soap Bubbles (HFSB) provide quantitative flow visualizations in large measurement volumes up to the cubic metre scale. However, the instantaneously available fluid information density is severely restricted by the finite spatial resolution of the measurements. Therefore, the use of experimental data assimilation approaches are utilized to exploit the temporal information of the flow measurements, along with the governing equations of the fluid motion, to increase the measurement spatial resolution. Nevertheless, only in the last years, attempts to apply data assimilation methods to enhance the Lagrangian particle tracking (LPT) resolution in proximity of solid boundaries have been performed. Thus, in order to handle generic solid body intrusions within the densely interpolated LPT data, two different approaches based on the computational fluid-structure interaction (FSI) frameworks are proposed. The introduced variants of the state of the art physics-driven data assimilation methods are assessed with a high fidelity numerical test case of flow over periodic hills. The accuracy superiority of the flow field reconstructions with the proposed approaches are denoted especially in close proximity of the interaction surface. An experimental application of the introduced methods is demonstrated to compute the pressure distribution over an unsteadily moving elastic membrane surface, revealing the time-resolved interaction between the flow structures and the membrane deformations.

Lagrangian particle tracking in the presence of obstructing objects

“…With the accurate object information and the complete flow field around it, binning methods [46] or more advanced data assimilation schemes like VIC# [47] or FlowFit [48], could be improved by employing correct boundary conditions during the conversion step, even calculating accurate surface pressure fields. Data-assimilation schemes with a proper boundary treatment have recently been proposed [49], and it is envisioned, that these methods can be combined in succeeding works.…”

Special Issue on Machine learning and data assimilation techniques for fluid flow measurements

“…The approach is based on the solution of the unsteady Navier-Stokes equations, whereby the Eulerian acceleration is treated as a forcing term, which is adjusted to minimize the discrepancy between the reconstructed and the measured velocities. Cakir et al [10] extend the use of the vortex-in-cell (VIC) framework to increase the spatial resolution of sparse LPT data in presence of solid objects within the measurement domain. The authors assess the performances of two methods, namely the arbitrary Lagrangian-Eulerian VIC+ and the immersed-boundary approach: the results showed the increased accuracy of these approaches in reconstructing the flow properties in proximity and on the surface of solid objects.…”