Biomedical subjects

Bruce R Pearson

Publications and source records attributed to Bruce R Pearson.

4 recordsLinked to original sources

PubMed2005

Inverse structure functions.

While the ordinary structure function in turbulence is concerned with the statistical moments of the velocity increment Deltau measured over a distance r , the inverse structure function is related to the distance r where the turbulent velocity exits the interval Deltau. We study inverse structure functions of wind-tunnel turbulence which covers a range of Reynolds numbers Re(lambda) = 400-1100. We test a recently proposed relation between the scaling exponents of the ordinary structure functions and those of the inverse structure functions [S. Roux and M. H. Jensen, Phys. Rev. E 69, 16309 (2004)]. The relatively large range of Reynolds numbers in our experiment also enables us to address the scaling with Reynolds number that is expected to highlight the intermediate dissipative range. While we firmly establish the (relative) scaling of inverse structure functions, our experimental results fail both predictions. Therefore, the question of the significance of inverse structure functions remains open.

Journal Article↗

PubMed2005

Finite-size scaling of two-point statistics and the turbulent energy cascade generators.

Within the framework of random multiplicative energy cascade models of fully developed turbulence, finite-size-scaling expressions for two-point correlators and cumulants are derived, taking into account the observationally unavoidable conversion from an ultrametric to an Euclidean two-point distance. The comparison with two-point statistics of the surrogate energy dissipation, extracted from various wind tunnel and atmospheric boundary layer records, allows an accurate deduction of multiscaling exponents and cumulants, even at moderate Reynolds numbers for which simple power-law fits are not feasible. The extracted exponents serve as input for parametric estimates of the probabilistic cascade generator. Various cascade generators are evaluated.

Journal Article↗

PubMed2004

Delayed correlation between turbulent energy injection and dissipation.

The dimensionless kinetic energy dissipation rate C(epsilon) is estimated from numerical simulations of statistically stationary isotropic box turbulence that is slightly compressible. The Taylor microscale Reynolds number (Re(lambda)) range is 20< or approximately equal to Re(lambda) < or approximately equal to 220 and the statistical stationarity is achieved with a random phase forcing method. The strong Re(lambda) dependence of C(epsilon) abates when Re(lambda) approximately 100 after which C(epsilon) slowly approaches approximately 0.5, a value slightly different from previously reported simulations but in good agreement with experimental results. If C(epsilon) is estimated at a specific time step from the time series of the quantities involved it is necessary to account for the time lag between energy injection and energy dissipation. Also, the resulting value can differ from the ensemble averaged value by up to +/-30%. This may explain the spread in results from previously published estimates of C(epsilon).

Journal Article↗

PubMed2004

Intermittency exponent of the turbulent energy cascade.

We consider the turbulent energy dissipation from one-dimensional records in experiments using air and gaseous helium at cryogenic temperatures, and obtain the intermittency exponent via the two-point correlation function of the energy dissipation. The air data are obtained in a number of flows in a wind tunnel and the atmospheric boundary layer at a height of about 35 m above the ground. The helium data correspond to the centerline of a jet exhausting into a container. The air data on the intermittency exponent are consistent with each other and with a trend that increases with the Taylor microscale Reynolds number, R(lambda), of up to about 1000 and saturates thereafter. On the other hand, the helium data cluster around a constant value at nearly all R(lambda), this being about half of the asymptotic value for the air data. Some possible explanation is offered for this anomaly.

Journal Article↗