Accurate estimate of turbulent dissipation rate using PIV data

Abstract Quantifying the turbulent dissipation rate provides insight into the physics of the turbulent flows. However, the accuracy of estimating turbulent dissipation rate using velocity data measured by planar PIV is affected by the way of modeling the unresolved velocity gradient terms and the PIV spatial resolution. In this paper, we first give a brief review of different methods used to estimate turbulent dissipation rate. Then synthetic PIV data are generated from a turbulence DNS dataset for validating the effectiveness of different methods. Direct estimate of turbulent dissipation rate from its definition using velocity gradients, with the assumption of isotropy, local axisymmetry, or local isotropy, shows significant decrease as interrogation window size increases. On the other hand, the indirect estimation of turbulent dissipation rate from energy spectra and structure function demonstrate less severe decrease as interrogation window size increases. We further propose two modified methods. The Modified Structure Function Method relies on an empirical relationship established by analyzing the synthetic PIV data. For a given measured value turbulent dissipation rate under a given interrogation window size, the true value can be determined from this relationship. The Modified Spectra Curvefit Method accounts the averaging effect introduced by the interrogation window in PIV processing algorithm and thus gives a better calculation of the energy spectra. When the new spectra data are used to curve fit the - 5 / 3 slope, an improved estimate of turbulent dissipation rate is expected. Both modified methods are applied to experimental PIV data acquired from a turbulent jet experiment. They give nearly converged estimates of turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes.