Evaluation of local energy dissipation rate using time resolved PIV

Numerous industrial approaches input large quantities of power to achieve a desired outcome. The question is whether that power is most efficiently transformed into process to achieve the specific purpose of heat, mass transfer, mixing etc. To optimize heat/mass transfer, small scale eddies should have maximum energy and they should be close to the interface. In contrast, optimum mixing performance is achieved by large eddies distributed uniformly over entire volume of contactor. In summary, the 'Energy budget'; i.e. how the supplied energy is distributed between eddies of different sizes is very important. Such a distribution is represented by the turbulent energy spectrum. In the current work, we utilize high speed particle image velocimetry (PIV) to record the variation of liquid velocity over a plane in time-resolved fashion. The local energy spectrum is obtained by taking FFT of velocity time series at each point in planar PIV data. A model energy spectrum by Pope ('Turbulent Flows' Cambridge University Press, 2000) was fitted to experimental spectrum giving the energy flux (equivalent to the turbulent energy dissipation rate) at each point. The salient feature of this method is the ability to calculate local energy dissipation rate without using the estimates of velocity gradients. The results obtained in current work are less susceptible to the noise in PIV velocity data. The local energy spectrum and energy dissipation rate measurements will enable us to put a close check on the energy budget in the process equipment. It will allow tailoring the turbulence to the specific application, significantly enhancing the operating efficiency.

[1]  S. S. Shy,et al.  A nearly isotropic turbulence generated by a pair of vibrating grids , 1997 .

[2]  Lewis F. Richardson,et al.  Weather Prediction by Numerical Process , 1922 .

[3]  S. Corrsin,et al.  The use of a contraction to improve the isotropy of grid-generated turbulence , 1966, Journal of Fluid Mechanics.

[4]  Hassan Peerhossaini,et al.  Heat and mass fluxes across density interfaces in a grid-generated turbulence , 2005 .

[5]  Hugh L. Dryden,et al.  A review of the statistical theory of turbulence. , 1943 .

[6]  Geoffrey Ingram Taylor,et al.  Statistical theory of turbulenc , 1935, Proceedings of the Royal Society of London. Series A - Mathematical and Physical Sciences.

[7]  L. F. G. Simmons,et al.  Experimental Investigation and Analysis of the Velocity Variations in Turbulent Flow , 1934 .

[8]  A. Townsend,et al.  Decay of isotropic turbulence in the initial period , 1948, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[9]  John R. Fessler,et al.  Preferential concentration of particles by turbulence , 1991 .

[10]  A. Sadiki,et al.  Investigation of turbulence modification in a non-reactive two-phase flow , 2004 .

[11]  G. Taylor The Spectrum of Turbulence , 1938 .

[12]  T. Kármán,et al.  The Fundamentals of the Statistical Theory of Turbulence , 1937 .

[13]  G. Batchelor,et al.  Decay of vorticity in isotropic turbulence , 1947, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[14]  T. Kármán,et al.  On the Statistical Theory of Isotropic Turbulence , 1938 .

[15]  J. Foucaut,et al.  PIV optimization for the study of turbulent flow using spectral analysis , 2004 .

[16]  M. Sommerfeld,et al.  Experimental investigation of turbulence modulation by solid particles in a grid-generated vertical flow , 2000 .

[17]  Jerry Westerweel,et al.  Turbulence statistics from optical whole-field measurements in particle-laden turbulence , 2006 .

[18]  Fulvio Scarano,et al.  Theory of non-isotropic spatial resolution in PIV , 2003 .

[19]  H. L. Grant,et al.  The inhomogeneity of grid turbulence , 1957, Journal of Fluid Mechanics.

[20]  S. Kleis,et al.  Modification of grid-generated turbulence by solid particles , 1993, Journal of Fluid Mechanics.

[21]  H. L. Dryden,et al.  Measurements of Intensity and Scale of Wind-Tunnel Turbulence and Their Relation to the Critical Reynolds Number of Spheres , 1937 .

[22]  K. Squires,et al.  Preferential concentration of particles by turbulence , 1991 .

[23]  J. Westerweel,et al.  The effect of a discrete window offset on the accuracy of cross-correlation analysis of digital PIV recordings , 1997 .

[24]  C. Meneveau,et al.  Decaying turbulence in an active-grid-generated flow and comparisons with large-eddy simulation , 2003, Journal of Fluid Mechanics.