Nadeem A. Malik

A Lagrangian model for turbulent dispersion with turbulent-like flow structure: Comparison with direct numerical simulation for two-particle statistics

A wide range of relative two-particle dispersion statistics from the Lagrangian Kinematic Simulation (KS) model, which contains turbulent-like flow structures, compares well with Yeung’s [Phys. Fluids 6, 3416 (1994)] DNS results. In particular, the Lagrangian flatness factor μ4(t) compares excellently (better than Heppe’s [J. Fluid Mech. 357, 167 (1998)] nonlinear stochastic model). For higher Reynolds numbers the results from KS show that μ4(t) is significantly greater than 3 over a wide range of times within the inertial range of time scales.

3D Particle Tracking Velocimetry-Its Possibilities and Limitations

Particle Tracking Velocimetry (PTV) is an evolving technique for 3D velocity field measurements in an observation volume. When the observation is made from a platform moving with the flow velocity it also yields Lagrangian trajectories of individual particles. It is one of the techniques which can cover the increasing need for measurements in a Lagrangian frame. The principles of the technique have been published in Papantoniou & Maas (1990) and Kasagi & Nishino (1991). Here some recent developments as well as the testing of the tracking scheme on the Kinematic Simulation Inertial Model (KSIM) test flow field will be presented.

Kinematics of Small Scale Motions in Homogeneous Isotropic Turbulence

Using direct numerical simulation and ‘kinematic simulation’ (henceforth KS) of velocity fields, measurement, flow visualisation and novel kinematic analysis, the following aspects of small scale motions in turbulence were investigated: (i) Random advection and distortion of small scale motions by larger scale motions; (ii) the Lagrangian spectrum at high frequency of particles moving in small scale eddies and the effects of the time dependence of the eddies; (iii) the relative velocities Δu and the separation distance l between pairs of particles, to find the decorrelation time scales of Δu and the relation between the mean square separation \({\bar l^2}\) and the conditional displacements of single particles; (iv) how the forms of these motions can be inferred from the asymptotic forms of Fourier series and spectra; (v) the specific implications for Eulerian and Lagrangian spectra of the small scales being mostly associated with elongated regions of spiralling motions in which there are different orders of discontinuous derivatives of velocity normal to streamline surfaces. These studies suggest that small scale motion in isotropic turbulence has a characteristic spiralling structure, which is generally consistent with statistics, such as fractals, spectra and probability distributions.

Global Reaction Mechanism for Ethylene Flames with Preferential Diffusion

Two compact global mechanisms for ethylene (C2H4) diffusion flame combustion have been tailored to include important reaction steps for acetylene and benzene production. One mechanism (G11) contains 11 species with 10 reaction steps including acetylene (C2H2), and the other mechanism (G12) contains 12 species with a total of 11 reactions steps to include also the formation of benzene (C6H6). The reaction steps have been carefully selected to minimize the mechanism size for the use in large-scale computational fluid dynamics (CFD) simulations. Hence, the reaction constants have been optimized for the correct prediction of important radical concentrations. Particular focus has been on the mechanisms ability to reproduce important preferential diffusion effects and on the formation of H and C2H2 due to its importance to soot formation. The two global chemical models have been validated for a transient 1-dimensional diffusion flame configuration and show very good agreement with various detailed chemical schemes. The mechanisms are found to be nonstiff reducing typical computing time for a transient flamelet calculation (F. Mauss, 1998) from a few hours (171 species mechanism) to only a few minutes (G11).

Statistical and eddy structure approaches to turbulent mixing

For industrial and environmental purposes there is a need for broad concepts and general models to describe many types of mixing processes and situations. These concepts arise from exact conversation results,1 and the similarity of the velocity fields and the particle displacements in turbulent fields at high Reynolds number, especially in the presence of shear. However, the design and control of mixing, like other kinds of turbulent problems, is usually improved by considering quasideterministic models of how turbulent eddies affect the process. Such models are changing with new computations and experimental studies of turbulence structure. Mixing involves continuously bringing together volumes of fluid with different concentrations on small enough scales to effect mixing between molecules.The Lagrangian statistical analysis of the displacements of fluid elements enables joint moments of concentration to be calculated in terms of initial concentration distributions in the absence of diffusion and reactio...