Assessment of pressure field calculations from particle image velocimetry measurements

This paper explores the challenges associated with the determination of in-field pressure from DPIV (digital particle image velocimetry)-measured planar velocity fields for time-dependent incompressible flows. Several methods that have been previously explored in the literature are compared, including direct integration of the pressure gradients and solution of different forms of the pressure Poisson equations. Their dependence on grid resolution, sampling rate, velocity measurement error levels and off-axis recording was quantified using artificial data of two ideal sample flow fields—a decaying vortex flow and pulsatile flow between two parallel plates, and real DPIV and pressure data from oscillating flow through a diffuser. The need for special attention to mitigate the velocity error propagation in the pressure estimation is also addressed using a physics-preserving approach based on proper orthogonal decomposition (POD). The results demonstrate that there is no unique or optimum method for estimating the pressure field and the resulting error will depend highly on the type of the flow. However, the virtual boundary, omni-directional pressure integration scheme first proposed by Liu and Katz (2006 Exp. Fluids 41 227–40) performed consistently well in both synthetic and experimental flows. Estimated errors can vary from less than 1% to over 100% with respect to the expected value, though in contrast to more traditional smoothing algorithms, the newly proposed POD-based filtering approach can reduce errors for a given set of conditions by an order of magnitude or more. This analysis offers valuable insight that allows optimizing the choice of methods and parameters based on the flow under consideration