Time-Volume Estimation of Velocity Fields From Nonsynchronous Planar Measurements Using Linear Stochastic Estimation

Abstract

The work presented in this paper combines multiple nonsynchronous planar measurements to reconstruct an estimate of a synchronous, instantaneous flow field of the whole measurement set. Temporal information is retained through the linear stochastic estimation (LSE) technique. The technique is described, applied, and validated with a simplified combustor and fuel swirl nozzles (FSN) geometry flow for which three-component, three-dimensional (3C3D) flow information is available. Using the 3C3D dataset, multiple virtual “planes” may be extracted to emulate single planar particle image velocimetry (PIV) measurements and produce the correlations required for LSE. In this example, multiple parallel planes are synchronized with a single perpendicular plane that intersects each of them. As the underlying dataset is known, it therefore can be directly compared to the estimated velocity field for validation purposes. The work shows that when the input time-resolved planar velocity measurements are first proper orthogonal decomposition (POD) filtered, high correlation between the estimations and the validation velocity volumes are possible. This results in estimated full volume velocity distributions, which are available at the same time instance as the input field—i.e., a time-resolved velocity estimation at the frequency of the single input plane. While 3C3D information is used in the presented work, this is necessary only for validation; in true application, planar technique would be used. The study concludes that provided the number of sensors used for input LSE exceeds the number of POD modes used for prefiltering, it is possible to achieve correlation greater than 99%.