Details

Autor(en) / Beteiligte

• Xu, Duo
• Chen, Jun

Titel

Accurate estimate of turbulent dissipation rate using PIV data

Ist Teil von

• Experimental thermal and fluid science, 2013-01, Vol.44, p.662-672

Ort / Verlag

Amsterdam: Elsevier Inc

Erscheinungsjahr

2013

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• ► Apply synthetic PIV data to evaluate the accuracy of different methods on evaluating turbulent dissipation rate using PIV data. ► Develop a Modified Structure Function Method and a Modified Spectra Method to improve the accuracy of dissipation rate estimate. ► Apply the new methods to experimental PIV data to demonstrates their effectiveness. 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.