Non‐Gaussian dispersion in model smokestack plumes

Abstract

The dispersion of emissions from a plume in a cross stream was studied using both experimental and theoretical techniques. Wind tunnel experiments were done for three jet to cross stream velocity ratios: R = 0.5, 1, and 2. The concentration in the plane perpendicular to the cross stream was measured using light scattering and photographic image analysis. The analysis of the negatives revealed the presence of two counterrotating vortices that greatly affected dispersion of smoke in the plume.Convection and random turbulent dispersion were modeled with a statistical convection simulator on a CYBER 205 computer. The input velocities to the convection model were obtained using experimental measurements. The model revealed the effects of the vortices on dispersion, and the concentration distributions across the plume were determined once the vortices had dissipated. The existence of the counterrotating vortices and their effects upon plume dispersion showed that the Gaussian plume model, which is widely used for modeling pollutant dispersion, is inapplicable in the near range of the model stack. IntroductionThe problem of modeling transport and dispersion of atmospheric pollutants is becoming more important as more contaminants are emitted into the atmosphere from coal-fired power plants. The general trend in atmospheric modeling has been to consider that emissions from a power plant follow a Gaussian distribution in the atmosphere, subject to deviations in wind direction and speed.The major efforts thus far have been to develop dispersion models based on the assumption that turbulent dispersion is analogous to molecular diffusion, and can be represented by Fick's law. The Gaussian plume model, in which emission concentrations in the crosswind and vertical directions follow a Gaussian distribution, results from this assumption. However, the Gaussian model fails to account for the physical processes that are responsible for dispersion of emissions.The Gaussian model arises from the solution to the advection- Possibly the most important mechanism for dispersion in the near range of the stack is dispersion caused by the turbulent vortices within the plume itself. While random turbulent motions can be accounted for by statistical meamin the general Gaussian model, large-scale structured motions cannot be statistically represented. These large-scale plume vortices may dominate dispersion of power plant plumes as far downstream as 5 to 10 km.To examine the velocity profiles of a plume in a steady cross flow, several investigators have performed experiments on a jet in a cross flow. As noted by Demuren (1983), Andreopoulos and Rodi (1984), Crabb et al. (1981), and Moussa et al. (1977), a plume in a steady cross flow can be modeled as a jet in a cross flow. With the advent of measurement techniques such as hotwire anemometry and laser-Doppler velocimetry (LDV), experimental studies of jets in a cross stream have been greatly facilitated, and detailed quantitative data has been obtained.One of the most extensive experimental s...

Survey of autonomous gas leak detection and quantification with snapshot infrared spectral imaging

“…As implied by figure 3, the Gaussian plume model is only appropriate when the air flow is unobstructed, so that the model is not useful for locating leaks within the perimeter of complex industrial facilities but only far from leak sources. Large-scale plume vortices may even dominate dispersion of plumes 5 to 10 km downstream of the source [35]. Closer to the leak source, more accurate fluid dynamical models of the plume are needed, constructed from knowledge of the 3D shape of the structural environment [22,36].…”