Institute of Building Energy, School of Civil Engineering, Faculty of Infrastructure Engineering, Dalian University of Technology, 2 Linggong Road, Ganjingzi District, Dalian, 116024, China.
Civil and Architectural Engineering College, Dalian University, 10 Xuefu Street, Economic and Technological Development Zone, Dalian, 116622, China.
Environ Sci Pollut Res Int. 2021 Nov;28(43):61380-61396. doi: 10.1007/s11356-021-14987-z. Epub 2021 Jun 26.
.In this study, we continue to analyze the diffusion mechanism of ultrafine particles and the particle coagulation phenomenon with a size range of 26-287 nm exhausted from vehicles during the process of passing through a 100-m-long tunnel using the realizable k-ε model and dynamic grid technique. A three-dimensional model consisting of a 100-m highway tunnel and four side-by-side gasoline vehicles (L × W × H = 4.5 m × 1.8 m × 1.5 m) was established in the STAR-CCM+ computational fluid dynamics software. The gasoline vehicles traveled simultaneously under different situations of three driving speeds of 60 km h, 40 km h, and 20 km h during the simulation. Through data analysis and research, it was found that the coagulation process of particles is very complicated, especially at low speeds. When the vehicle speed is 20 km h, the variation in particle concentration at the vehicle wake near the tailpipe (at the vertical plane located 0.1 m behind the exhaust pipe) causes a large error if the coagulation action is not considered. The relative error of the average particle concentration at 0.5 s of the vertical section 0.1 m away from the exhaust pipe is as high as 193.51%. The relative error in the entire tunnel is only 2.82%, which is less than 5%. Thus, it is recommended that particle coagulation should be considered when analyzing particle dispersion in the near-wake region behind the vehicle and the breathing areas, especially when the vehicle travels slowly inside the tunnel. However, when evaluating the particle concentration and exposure levels for the entire tunnel, coagulation can be ignored without significant errors, especially at a high vehicle speeds. This study clarified the importance of coagulation in different areas and its influence on the diffusion of particulate matter. This is conducive to further analysis of the diffusion characteristics of particulate matter and can appreciably reduce the pollution degree in a tunnel by changing the coagulation efficiency of particulate matter in the future.
在这项研究中,我们继续使用可实现的 k-ε 模型和动态网格技术,分析车辆在通过 100 米长的隧道过程中排出的 26-287nm 超细颗粒的扩散机制和颗粒团聚现象。在 STAR-CCM+计算流体动力学软件中建立了一个由 100 米高速公路隧道和四辆并排的汽油车(L×W×H=4.5m×1.8m×1.5m)组成的三维模型。模拟过程中,四辆汽油车在三种不同行驶速度(60km/h、40km/h 和 20km/h)下同时行驶。通过数据分析和研究,发现颗粒的团聚过程非常复杂,特别是在低速时。当车速为 20km/h 时,如果不考虑团聚作用,靠近排气管的车辆尾部(位于排气管后面 0.1m 的垂直平面上)的颗粒浓度变化会导致很大的误差。距排气管 0.5s 处垂直段 0.1m 处的平均颗粒浓度的相对误差高达 193.51%。整个隧道的相对误差仅为 2.82%,小于 5%。因此,建议在分析车辆尾部近尾流区和呼吸区的颗粒扩散时,应考虑颗粒团聚作用,特别是车辆在隧道内低速行驶时。然而,在评估整个隧道的颗粒浓度和暴露水平时,忽略团聚作用不会产生显著误差,尤其是在车辆速度较高时。本研究阐明了团聚作用在不同区域的重要性及其对颗粒物扩散的影响。这有助于进一步分析颗粒物的扩散特性,并在未来通过改变颗粒物的团聚效率来显著降低隧道内的污染程度。