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1.
ABSTRACT

A new Gaussian dispersion model, the Plume Rise Model Enhancements (PRIME), has been developed for plume rise and building downwash. PRIME considers the position of the stack relative to the building, streamline deflection near the building, and vertical wind speed shear and velocity deficit effects on plume rise. Within the wake created by a sharp-edged, rectangular building, PRIME explicitly calculates fields of turbulence intensity, wind speed, and streamline slope, which gradually decay to ambient values downwind of the building. The plume trajectory within these modified fields is estimated using a numerical plume rise model. A probability density function and an eddy diffusivity scheme are used for dispersion in the wake. A cavity module calculates the fraction of plume mass captured by and recirculated within the near wake. The captured plume is re-emitted to the far wake as a volume source and added to the uncaptured primary plume contribution to obtain the far wake concentrations.

The modeling procedures currently recommended by the U.S. Environmental Protection Agency (EPA), using SCREEN and the Industrial Source Complex model (ISC), do not include these features. PRIME also avoids the discontinuities resulting from the different downwash modules within the current models and the reported overpredictions during light-wind speed, stable conditions. PRIME is intended for use in regulatory models. It was evaluated using data from a power plant measurement program, a tracer field study for a combustion turbine, and several wind-tunnel studies. PRIME performed as well as or better than ISC/SCREEN for nearly all of the comparisons.  相似文献   
2.
A new Gaussian dispersion model, the Plume Rise Model Enhancements (PRIME), has been developed for plume rise and building downwash. PRIME considers the position of the stack relative to the building, streamline deflection near the building, and vertical wind speed shear and velocity deficit effects on plume rise. Within the wake created by a sharp-edged, rectangular building, PRIME explicitly calculates fields of turbulence intensity, wind speed, and streamline slope, which gradually decay to ambient values downwind of the building. The plume trajectory within these modified fields is estimated using a numerical plume rise model. A probability density function and an eddy diffusivity scheme are used for dispersion in the wake. A cavity module calculates the fraction of plume mass captured by and recirculated within the near wake. The captured plume is re-emitted to the far wake as a volume source and added to the uncaptured primary plume contribution to obtain the far wake concentrations. The modeling procedures currently recommended by the U.S. Environmental Protection Agency (EPA), using SCREEN and the Industrial Source Complex model (ISC), do not include these features. PRIME also avoids the discontinuities resulting from the different downwash modules within the current models and the reported overpredictions during light-wind speed, stable conditions. PRIME is intended for use in regulatory models. It was evaluated using data from a power plant measurement program, a tracer field study for a combustion turbine, and several wind-tunnel studies. PRIME performed as well as or better than ISC/SCREEN for nearly all of the comparisons.  相似文献   
3.
To assist in emergency response decisions and planning in case of releases of pressurized liquefied chlorine from railroad tank cars in industrial sites and cities, the FLACS Computational Fluid Dynamics (CFD) model has been used to simulate the transport and dispersion of the dense chlorine cloud. Two accident locations are studied: an actual railcar accident at an industrial site in Festus, MO, and a hypothetical railcar accident at a rail junction in the Chicago urban area. The results show that transport of a large dense gas release at ground level in an industrial site or large city could initially extend a hundred meters or more in the upwind and crosswind directions. The dense cloud may follow terrain drainage, such as river channels. Near the source, the obstacles tend to slow down the dense gas cloud and may constrain it and cause increased concentrations. Farther downwind, the obstacles may cause enhanced mixing and dilution once the cloud has grown larger. In some cases, significant amounts of cloud mass may become “trapped” in obstacle wakes for many minutes after the main cloud has passed. Although the CFD model can account for the details of the flow and dispersion much better than standard widely-used simple dense gas models, many similarities are found among the various models in their simulated variations with downwind distance of the maximum cloud centerline concentration.  相似文献   
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