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Turbulence Model Selection for Heavy Gases Dispersion Modeling in Topographically Complex Area
Author(s): Farzad Mirzaei, Farshad Mirzaei, Eslam kashi
Keywords: Turbulence Modeling; computational fluid dynamics; EARSM; RNG k-ε model; Atmospheric Dispersion
Hazardous gas dispersions in the environments are among the most dangerous risks for people living close to chemical plants or storages. Heavy gases are potentially more dangerous, since they tend to stay at lower sections, and they disperse at a slower pace in the atmosphere. In this paper, various k-ε turbulence models (including k-ε, RNG k-ε, EARSM) and involved parameters have been assessed, compared and validated against the experimental data in various scenarios to find the most suitable one for atmospheric dispersion of dense-gases. This topic has been investigated and validated by the simulation of Kit-Fox experimental works in ANSYS CFX® 18. Precision of the CAD models, practicality, computational resource requirements and some other factors were all considered and were addressed in this paper to achieve a comprehensive solution for the atmospheric dispersion. The results here are suggesting that proper selection of turbulence model, and the Schmidt number is crucial. Our results suggest that using RNG k-ε model with the Schmidt number of 0.4 is the most promising combination in the case of atmospheric dense-gas dispersion, considering the accuracy and computational resource demand.