LES Inlet Condition Generation Using Stereoscopic PIV and Linear Stochastic Estimation

Abstract Development of a generally applicable inlet condition generation method for Large Eddy Simulation (LES) is challenging and limits application to complex engineering flows. Inlet velocity time-series are required, at temporal/spatial resolutions consistent with LES numerics, covering the entire computational inlet plane, and for a time period allowing statistical stationarity. Ideally measurements would be used, but capture of large area, long duration time histories is problematic. Several generation techniques have been proposed, but compliance with measurements is normally guaranteed only for single point statistical data. The present work demonstrates how Stereoscopic Particle Image Velocimetry (SPIV) may be used to generate conditions simultaneously matching 1-point statistics, 2-point spatial correlations, and frequency spectra. A validation test case is selected containing complex flow structures typical of engineering applications. Linear Stochastic Estimation (LSE) and high-pass filtering are combined to match the LES inflow area with the smaller SPIV area required for accurate spatial resolution. A single synchronous velocity field is created from multiple non-concurrent SPIV fields. The method extends the inflow complexity that can be considered and provides improvement over existing methods.