SCI和EI收录∣中国化工学会会刊

Chin.J.Chem.Eng. ›› 2016, Vol. 24 ›› Issue (1): 71-78.DOI: 10.1016/j.cjche.2015.11.025

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A new approach to quantifying vehicle induced turbulence for complex traffic scenarios

Yesul Kim1, Li Huang1, Sunling Gong1,2, Charles Q. Jia1   

  1. 1 Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON M5S 3E5 Canada;
    2 Air Quality Research Division, Environment Canada, Toronto, ON M3H 5T4 Canada
  • Received:2014-12-04 Revised:2015-07-06 Online:2016-02-23 Published:2016-01-28
  • Contact: Charles Q. Jia

A new approach to quantifying vehicle induced turbulence for complex traffic scenarios

Yesul Kim1, Li Huang1, Sunling Gong1,2, Charles Q. Jia1   

  1. 1 Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON M5S 3E5 Canada;
    2 Air Quality Research Division, Environment Canada, Toronto, ON M3H 5T4 Canada
  • 通讯作者: Charles Q. Jia

Abstract: Traffic-related pollutants adversely affect air quality, especially in regions near major roadways. The vehicleinduced turbulence (VIT) is a significant factor that controls the initial dilution, dispersion, and ultimately the chemical and physical fate of pollutants by altering the conditions in the microenvironment. This study used a computational fluid dynamics (CFD) software FLUENT to model the vehicle-induced turbulence (VIT) generated on roadways, with a focus on impact of vehicle-vehicle interactions, traffic density and vehicle composition on turbulent kinetic energy (TKE). We show, for the first time, that the overall TKE from multiple vehicles traveling in series can be estimated by superimposing the TKE of each vehicle, without considering the distance between themwhile the distance is greater than one vehicle length. This finding is particularly significant since it enables a new approach to VIT simulations where the overall TKE is calculated as a function of number of vehicles. We found that the interactions between vehicles traveling next to each other in adjacent lanes are insignificant, regardless the directions of the traffic flow. Consequently, simulations of different traffic scenarios can be substantially simplified by treating two-way traffic as one-way traffic, with less than 5% difference in the overall volume-averaged TKE. We also developed equations that allow the estimation of the overall volume-averaged TKE as a function of the number and the type of vehicles.

Key words: Computational fluid dynamics, Turbulent kinetic energy, Vehicle-induced turbulence, Road-induced turbulence, Mixed traffic

摘要: Traffic-related pollutants adversely affect air quality, especially in regions near major roadways. The vehicleinduced turbulence (VIT) is a significant factor that controls the initial dilution, dispersion, and ultimately the chemical and physical fate of pollutants by altering the conditions in the microenvironment. This study used a computational fluid dynamics (CFD) software FLUENT to model the vehicle-induced turbulence (VIT) generated on roadways, with a focus on impact of vehicle-vehicle interactions, traffic density and vehicle composition on turbulent kinetic energy (TKE). We show, for the first time, that the overall TKE from multiple vehicles traveling in series can be estimated by superimposing the TKE of each vehicle, without considering the distance between themwhile the distance is greater than one vehicle length. This finding is particularly significant since it enables a new approach to VIT simulations where the overall TKE is calculated as a function of number of vehicles. We found that the interactions between vehicles traveling next to each other in adjacent lanes are insignificant, regardless the directions of the traffic flow. Consequently, simulations of different traffic scenarios can be substantially simplified by treating two-way traffic as one-way traffic, with less than 5% difference in the overall volume-averaged TKE. We also developed equations that allow the estimation of the overall volume-averaged TKE as a function of the number and the type of vehicles.

关键词: Computational fluid dynamics, Turbulent kinetic energy, Vehicle-induced turbulence, Road-induced turbulence, Mixed traffic