Dense flow field interpolations from PTV data in the presence of generic solid boundaries

Authors

  • Bora Orcun Cakir von Karman Institute for Fluid Dynamics, Belgium; Delft University of Technology, The Netherlands
  • Andrea Sciacchitano Delft University of Technology, The Netherlands
  • Gabriel Gonzalez Saiz Delft University of Technology, The Netherlands
  • Bas van Oudheusden Delft University of Technology, The Netherlands

DOI:

https://doi.org/10.18409/ispiv.v1i1.31

Abstract

Three-dimensional flow measurements by Particle Tracking Velocimetry (PTV) provide scattered flow information, that often needs to be interpolated onto a regular grid. Therefore, the use of experimental data assimilation approaches such as VIC+ (Schneiders and Scarano, 2016) were proposed to enhance the instantaneously available spatial resolution limits beyond that of the PTV measurements. Nevertheless, there exists no prior attempt to perform the data assimilation when the flow is in direct contact with physical objects. Thus, in order to handle generic solid body intrusions within the flow fields of VIC+ application, the utilization of Arbitrary Lagrangian-Eulerian and immersed boundary treatment approaches of the computational fluid-structure interaction (FSI) frameworks are proposed. The introduced variants over the standard VIC+ 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.

Author Biography

Bora Orcun Cakir, von Karman Institute for Fluid Dynamics, Belgium; Delft University of Technology, The Netherlands

I have obtained my Bachelor of Science degree in Aerospace Engineering from Middle East Technical University in 2018 and my Master of Science degree in Aerospace Engineering from Delft University of Technology in 2020. After acting as an external research associate for 3,5 years, I have started my PhD studies at the Turbomachinery and Propulsion Department of von Karman Institute for Fluid Dynamics in January, 2021.

Downloads

Published

2021-08-01

Issue

Section

Deep Learning and Data Assimilation