FlowFit3: Efficient Data Assimilation Of LPT Measurements

Abstract

Lagrangian particle tracking (LPT) techniques such as Shake-The-Box provide accurate flow measurements by following the movement of tracer particles within a flow. The technique gives measured values of position, velocity and acceleration at the locations of the scattered particles as opposed to a Eulerian grid like with window based techniques such as PIV. This is advantageous for e.g spatially highly resolved flow statistics. Often it is also desirable to have access to a grid-structured representation of the data, especially for the calculation of spatial gradients of flow field measures. While a simple interpolation onto a grid is possible, data assimilation techniques using physics based regularization such as FlowFit2 or VIC+ and VIC#are frequently used nowadays. Through knowledge of the Navier-Stokes equations a higher spatial resolution can be obtained than from interpolation alone. We present the new and highly efficient FlowFit3 approach and its evaluation on synthetic data.