| Summary: | Convective heat transfer occurs in a wide range of engineering applications, from nuclear reactors to portable electronic devices. Accurate whole-field turbulence and flow measurements are crucial to understanding convective heat transfer in complex flow fields, thereby enabling optimal design of these devices. Particle image velocimetry (PIV) is the preferred whole-field flow measurement technique. However in many configurations the dynamic velocity range of conventional PIV is too limited to accurately resolve both high mean velocities and turbulence intensities in lower velocity regions. This paper employs high dynamic range (HDR) PIV with an advanced acquisition and processing technique based on multiple pulse separation (MPS) double-frame imaging. The methodology uses a conventional adaptive multi-grid algorithm for vector evaluation, and determines the optimal pulse separation in space and time in a post-processing routine. Two test cases are discussed: For an impinging synthetic jet flow (Case I), HDR PIV increases the dynamic velocity range 25-fold compared to conventional PIV. For an oscillatory buoyant plume from a pair of horizontal heated cylinders (Case II), the dynamic velocity range is increased 5.5 times. This technique has yielded new insights in synthetic jet heat transfer by correlating local surface heat transfer rates to near-wall turbulence intensity in a single whole-field measurement.
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