Abstract

A test case for pressure field reconstruction from particle image velocimetry (PIV) and Lagrangian particle tracking (LPT) has been developed by constructing a simulated experiment from a zonal detached eddy simulation for an axisymmetric base flow at Mach 0.7. The test case comprises sequences of four subsequent particle images (representing multi-pulse data) as well as continuous time-resolved data which can realistically only be obtained for low-speed flows. Particle images were processed using tomographic PIV processing as well as the LPT algorithm ‘Shake-The-Box’ (STB). Multiple pressure field reconstruction techniques have subsequently been applied to the PIV results (Eulerian approach, iterative least-square pseudo-tracking, Taylor’s hypothesis approach, and instantaneous Vortex-in-Cell) and LPT results (FlowFit, Vortex-in-Cell-plus, Voronoi-based pressure evaluation, and iterative least-square pseudo-tracking). All methods were able to reconstruct the main features of the instantaneous pressure fields, including methods that reconstruct pressure from a single PIV velocity snapshot. Highly accurate reconstructed pressure fields could be obtained using LPT approaches in combination with more advanced techniques. In general, the use of longer series of time-resolved input data, when available, allows more accurate pressure field reconstruction. Noise in the input data typically reduces the accuracy of the reconstructed pressure fields, but none of the techniques proved to be critically sensitive to the amount of noise added in the present test case.

Highlights

  • Fluid pressure is directly related to phenomena like surface loading and sound generation and as such is an important quantity in many engineering problems

  • While surface pressure can experimentally be determined with pressure transducers and pressure-sensitive paint (PSP), pressure field reconstruction based on particle image velocimetry (PIV) and Lagrangian particle tracking (LPT) offers a number of unique advantages

  • A test case for PIV-based and LPT-based pressure evaluation techniques has been developed by constructing a simulated experiment from Zonal detached eddy simulation (ZDES) simulation data

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Summary

Introduction

Fluid pressure is directly related to phenomena like surface loading and sound generation (aeroacoustics) and as such is an important quantity in many engineering problems. While surface pressure can experimentally be determined with pressure transducers and pressure-sensitive paint (PSP), pressure field reconstruction based on particle image velocimetry (PIV) and Lagrangian particle tracking (LPT) offers a number of unique advantages (van Oudheusden 2013). Contrary to the more established measurement techniques, PIV/LPT-based pressure field reconstruction does not require instrumentation or surface preparation of the wind tunnel model. This allows for pressure determination in configurations where such modifications are not practical, e.g., very thin (or membrane-like) airfoils. It avoids the installation of large numbers of pressure transducers which is a common practice to

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Description of the test case
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Details of simulated experiment
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Calculation of particle tracks
Generation of synthetic particle images
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Tomographic PIV processing
Velocity error assessment
STB velocity error
Comparison of velocity errors
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Flow modelling assumptions
PIV‐based techniques
LPT‐based techniques
Pressure results
Pressure from PIV‐based techniques
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Pressure from LPT‐based techniques
Reconstruction of pressure length scales
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Conclusions
Findings
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Full Text
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