Relative dispersion of a scalar plume in a turbulent boundary layer

2010 ◽  
Vol 661 ◽  
pp. 412-445 ◽  
Author(s):  
Q. LIAO ◽  
E. A. COWEN
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Concentration Distribution ◽  
Separation Distance ◽  
Relative Dispersion ◽  
Inertial Subrange ◽  
Probability Density Distribution ◽  
Extended Model ◽  
Relative Diffusivity ◽  
The Relationship

The relative dispersion of a scalar plume is examined experimentally. A passive fluorescent tracer is continuously released from a flush-bed mounted source into the turbulent boundary layer of a laboratory-generated open channel flow. A two-dimensional particle image velocimetry–laser-induced florescence (PIV–LIF) technique is applied to measure the instantaneous horizontal velocity and concentration fields. Measured results are used to investigate the relationship between the boundary-layer turbulence and the evolution of the distance-neighbour function, namely the probability density distribution of the separation distance between two marked fluid particles within a cloud of particles. Special attention is paid to the hypothesis that a diffusion equation can describe the evolution of the distance-neighbour function. The diffusion coefficient in such an equation, termed the ‘relative diffusivity’, is directly calculated based on the concentration distribution. The results indicate that the relative diffusivity statistically depends on particle separation lengths instead of the overall size of the plume. Measurements at all stages of the dispersing plume collapse onto a single curve and follow a 4/3 power law in the inertial subrange. The Richardson–Obukhov constant is estimated from the presented dataset. The relationship between the one-dimensional (1D) representation of the distance-neighbour function and its three-dimensional (3D) representation is discussed. An extended model for relative diffusivity beyond the inertial subrange is proposed based on the structure of the turbulent velocity field, and it agrees well with measurements. The experimental evidence implies that, while the diffusion of the distance-neighbour function is completely determined by the underlying turbulence, the overall growth rate of the plume is affected by both the turbulent flow and its actual concentration distribution.

scholarly journals Simulations of Nearshore Particle-Pair Dispersion in Southern California

2013 ◽  
Vol 43 (9) ◽  
pp. 1862-1879 ◽  
Author(s):  
Leonel Romero ◽  
Yusuke Uchiyama ◽  
J. Carter Ohlmann ◽  
James C. McWilliams ◽  
David A. Siegel
Keyword(s):  
Kinetic Energy ◽  
Southern California ◽  
Separation Distance ◽  
Horizontal Resolution ◽  
Particle Dispersion ◽  
Eddy Kinetic Energy ◽  
Relative Dispersion ◽  
Numerical Resolution ◽  
Relative Diffusivity ◽  
Pair Separation

Abstract Knowledge of horizontal relative dispersion in nearshore oceans is important for many applications including the transport and fate of pollutants and the dynamics of nearshore ecosystems. Two-particle dispersion statistics are calculated from millions of synthetic particle trajectories from high-resolution numerical simulations of the Southern California Bight. The model horizontal resolution of 250 m allows the investigation of the two-particle dispersion, with an initial pair separation of 500 m. The relative dispersion is characterized with respect to the coastal geometry, bathymetry, eddy kinetic energy, and the relative magnitudes of strain and vorticity. Dispersion is dominated by the submesoscale, not by tides. In general, headlands are more energetic and dispersive than bays. Relative diffusivity estimates are smaller and more anisotropic close to shore. Farther from shore, the relative diffusivity increases and becomes less anisotropic, approaching isotropy ~10 km from the coast. The degree of anisotropy of the relative diffusivity is qualitatively consistent with that for eddy kinetic energy. The total relative diffusivity as a function of pair separation distance R is on average proportional to R5/4. Additional Lagrangian experiments at higher horizontal numerical resolution confirmed the robustness of these results. Structures of large vorticity are preferably elongated and aligned with the coastline nearshore, which may limit cross-shelf dispersion. The results provide useful information for the design of subgrid-scale mixing parameterizations as well as quantifying the transport and dispersal of dissolved pollutants and biological propagules.

scholarly journals Observation of turbulent dispersion of artificially released SO<sub>2</sub> puffs with UV cameras

2018 ◽  
Vol 11 (11) ◽  
pp. 6169-6188 ◽  
Author(s):  
Anna Solvejg Dinger ◽  
Kerstin Stebel ◽  
Massimo Cassiani ◽  
Hamidreza Ardeshiri ◽  
Cirilo Bernardo ◽  
...  
Keyword(s):  
Concentration Distribution ◽  
Concentration Field ◽  
Turbulent Dispersion ◽  
Relative Dispersion ◽  
Inertial Subrange ◽  
Centre Of Mass ◽  
Dispersion Parameters ◽  
Data Set ◽  
Atmospheric Flow ◽  
Depth Analysis

Abstract. In atmospheric tracer experiments, a substance is released into the turbulent atmospheric flow to study the dispersion parameters of the atmosphere. That can be done by observing the substance's concentration distribution downwind of the source. Past experiments have suffered from the fact that observations were only made at a few discrete locations and/or at low time resolution. The Comtessa project (Camera Observation and Modelling of 4-D Tracer Dispersion in the Atmosphere) is the first attempt at using ultraviolet (UV) camera observations to sample the three-dimensional (3-D) concentration distribution in the atmospheric boundary layer at high spatial and temporal resolution. For this, during a three-week campaign in Norway in July 2017, sulfur dioxide (SO2), a nearly passive tracer, was artificially released in continuous plumes and nearly instantaneous puffs from a 9 m high tower. Column-integrated SO2 concentrations were observed with six UV SO2 cameras with sampling rates of several hertz and a spatial resolution of a few centimetres. The atmospheric flow was characterised by eddy covariance measurements of heat and momentum fluxes at the release mast and two additional towers. By measuring simultaneously with six UV cameras positioned in a half circle around the release point, we could collect a data set of spatially and temporally resolved tracer column densities from six different directions, allowing a tomographic reconstruction of the 3-D concentration field. However, due to unfavourable cloudy conditions on all measurement days and their restrictive effect on the SO2 camera technique, the presented data set is limited to case studies. In this paper, we present a feasibility study demonstrating that the turbulent dispersion parameters can be retrieved from images of artificially released puffs, although the presented data set does not allow for an in-depth analysis of the obtained parameters. The 3-D trajectories of the centre of mass of the puffs were reconstructed enabling both a direct determination of the centre of mass meandering and a scaling of the image pixel dimension to the position of the puff. The latter made it possible to retrieve the temporal evolution of the puff spread projected to the image plane. The puff spread is a direct measure of the relative dispersion process. Combining meandering and relative dispersion, the absolute dispersion could be retrieved. The turbulent dispersion in the vertical is then used to estimate the effective source size, source timescale and the Lagrangian integral time. In principle, the Richardson–Obukhov constant of relative dispersion in the inertial subrange could be also obtained, but the observation time was not sufficiently long in comparison to the source timescale to allow an observation of this dispersion range. While the feasibility of the methodology to measure turbulent dispersion could be demonstrated, a larger data set with a larger number of cloud-free puff releases and longer observation times of each puff will be recorded in future studies to give a solid estimate for the turbulent dispersion under a variety of stability conditions.

On the Three-Dimensional Turbulent Boundary Layer Generated by Secondary Flow

1960 ◽  
Vol 82 (1) ◽  
pp. 233-246 ◽  
Author(s):  
J. P. Johnston
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Secondary Flow ◽  
Three Dimensional ◽  
Cross Flow ◽  
Problem Solution ◽  
Boundary Layer Problem ◽  
Flow Components ◽  
Momentum Integral ◽  
The Relationship

A study of the secondary flow type of three-dimensional turbulent boundary layer is presented. Two objectives are achieved: (a) A mathematical model of the relationship between the cross-flow and main-flow components of the velocity vectors of the layer is established. (b) By utilization of the model some of the relationships required to carry out a boundary-layer problem solution by the use of the momentum-integral equations are developed.

A New Empirical Relationship Between The Form-Parameters H32 and H12 in Boundary Layer Theory

1962 ◽  
Vol 66 (621) ◽  
pp. 588-589 ◽  
Author(s):  
Hans Fernholz
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Velocity Profile ◽  
Skin Friction ◽  
Empirical Relationship ◽  
Boundary Layer Theory ◽  
Two Dimensional ◽  
Energy Integral ◽  
The Third ◽  
The Relationship

Provided the relationship between the form-parameters H32 and H12is known, the two-dimensional turbulent boundary layer may be calculated by means of the approximate theories of Walz and Truckenbrodt without the necessity for an explicit law for the velocity profile. This relationship H32=f(H12) introduces the influence of the velocity profiles into the calculation. It is the third empirical relationship—beside those for skin friction and dissipation— which is needed to solve the momentum and energy integral equations. The formulae or curves for H32=f(H12) which are given in published papers show considerable deviations from each other so that it was felt necessary to investigate this relationship again. Fig. 1 shows the different curves.

Development of Three-Dimensional Turbulent Boundary Layer in an Axially Rotating Pipe

1983 ◽  
Vol 105 (2) ◽  
pp. 154-160 ◽  
Author(s):  
K. Kikuyama ◽  
M. Murakami ◽  
K. Nishibori
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Richardson Number ◽  
Pipe Wall ◽  
Three Dimensional ◽  
Turbulent Fluctuations ◽  
Stabilizing Effect ◽  
Axial Velocity Distribution ◽  
Pipe Rotation ◽  
The Relationship

The time-mean velocities and turbulent fluctuations inside the turbulent boundary layers which developed in an axially rotating pipe were measured in the case where an undeveloped flow with a rectangular axial velocity distribution was introduced in the pipe. The pipe rotation gives two counter effects on the flow: one is a destabilizing effect due to a large shear caused by the rotating pipe wall and the other is a stabilizing effect due to the centrifugal force of the swirling velocity component of the flow. The destabilizing effect prevails in the inlet region, but the stabilizing effect becomes dominant in the downstream sections. The intensity of turbulence in the rotating pipe decreases ultimately below that in a stationary state of the pipe. Using the experimental results, the relationship between the mixing length and Richardson number proposed by Bradshaw was examined for the turbulent boundary layer that develops in the rotating pipe.

Measurement of the lift force on a particle fixed to the wall in the viscous sublayer of a fully developed turbulent boundary layer

1996 ◽  
Vol 316 ◽  
pp. 285-306 ◽  
Author(s):  
A. M. Mollinger ◽  
F. T. M. Nieuwstadt
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Lift Force ◽  
Friction Velocity ◽  
Detection System ◽  
Viscous Sublayer ◽  
Average Value ◽  
The Mean ◽  
Focus Detection ◽  
The Relationship

We have investigated the lift force on a small isolated particle which is attached to a flat smooth surface and embedded within the viscous sublayer of the turbulent boundary layer over this surface. We have developed a novel experimental technique with which it is possible to measure both the mean and fluctuating lift force by gluing the particle on top of a silicium cantilever. The deflection of this cantilever is measured with a focused laser beam. The sensitivity of the focus detection system allows us to measure a lift force with an average value around 10−8N and with a standard deviation of approximately 5% of the mean. This means that our device is at least a factor of 100 more sensitive than previous devices and at the same time able to measure the lift forces on smaller particles. Data for the mean lift force (FL+) as a function of the particle radius (a+), where both parameters have been non-dimensionalized with the kinematic viscosity v and the friction velocity u*, are obtained in the range 0.3 < a+ < 2. The data support the relationship: FL+ = (56.9 ± 1.1) (a+)1.87±0.04. Also results on the fluctuating lift force have been obtained. We find that the ratio of the r.m.s. to the mean lift force is approximately 2.8.

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