Abstract
A technique based on a rotated hot wire has been developed to characterise the unsteady, three-dimensional flow field between compressor blade rows. Data are acquired from a slanted hot wire rotated through a number of orientations at each measurement point. Phase-averaged velocity statistics are obtained by solving a set of sensor response equations using a weighted, non-linear regression algorithm. The accuracy and robustness of the method were verified a priori by conducting a series of tests using synthetic data. The method is demonstrated by acquiring a full set of phase-averaged flow statistics in the wake of a compressor stator blade row. The technique allows three components of phase-averaged velocity, six components of phase-averaged deterministic stress, and six components of phase-averaged Reynolds stress to be recovered using a single rotated hot-wire probe.
Highlights
The fluid motion that develops between compressor blade rows is exceptionally complex
It is customary to divide the unsteadiness in compressors into two categories: (1) deterministic fluctuations related to the shaft and blade frequencies and (2) broadband stochastic fluctuations related to naturally occurring turbulence
The space–time dependence of flow statistics significantly complicates the closure of the phase-averaged Navier–Stokes equations, relative to the traditional Reynolds-averaged formulation (Reynolds and Hussain 1972)
Summary
The fluid motion that develops between compressor blade rows is exceptionally complex. The relative motion of alternate rotating and non-rotating blade rows (see Fig. 1). Produces a flow field that is inherently unsteady, threedimensional and multi-scale. It is customary to divide the unsteadiness in compressors into two categories: (1) deterministic fluctuations related to the shaft and blade frequencies and (2) broadband stochastic fluctuations related to naturally occurring turbulence. The mean square of (1) and (2) are manifest as deterministic stresses and Reynolds stresses, respectively. Statistical moments may exhibit periodicities in both space and time. The space–time dependence of flow statistics significantly complicates the closure of the phase-averaged Navier–Stokes equations, relative to the traditional Reynolds-averaged formulation (Reynolds and Hussain 1972)
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