ON PASSIVE SCALAR DERIVATIVE STATISTICS IN GRID TURBULENCE

The probability density function, and related statistics, of scalar (t emperature) derivative fluctuations in decaying grid turbulence with a n imposed cross-stream, passive linear temperature profile, is studied for a turbulence Reynolds number range, Re(l), varying from 50 to 120 0, (corresponding to a Taylor Reynolds number range 30 < R(lambda) < 1 30). It is shown that the temperature derivative skewness in the direc tion of the mean gradient, S(thetay) has a value of 1.8 +/- 0.2 (twice the value observed in shear flows), and has no significant variation with Reynolds number. The ratio of the temperature derivative standard deviation along the gradient to that normal to it is approximately 1. 2 +/- 0.1 also, with no variation with Re. The kurtosis of the derivat ives increases approximately as Re(l)0.2. The results show that the ra re, intense temperature deviations that produce the skewed scalar deri vative, increase in frequency, but their area fraction (of the total f ield) becomes smaller as the Reynolds number increases. Thus, since S( thetay) remains constant, they become sharper and more intense, occurr ing deeper in the tails of the probability density function. Measureme nts in a thermal mixing layer, which has a nonlinear mean temperature profile, are also presented, and these show a similar value of S(theta y) to the linear profile case. The experiments broadly confirm the two -dimensional numerical simulations of Holzer and Siggia [Phys. Fluids (in press)], as well as other recent simulations, although there are s ome differences.