POD-based analysis of flow past street canyons and buildings: flow feature isolation and its impact on pollutant dispersion

Abstract

Atmospheric pollution has emerged as a critical environmental issue in the present era. As indicated by the World Health Organization in 2022, roughly whole universal contaminant (99%) is vulnerable to air that fails to meet the standard of living .Beyond decreasing automotive exhaust, enhancing road contaminant diffusion has been affirmed as an efficacious approach to mitigate such well-being venture.This work conducts LES based on ROM technique POD to model the traffic-induced flow field within a street canyon. The phenomenon mechanism is investigated by extracting the corresponding dominant modes. The flow pattern predicted by LES ideally accords with the skimming flow (SF) regime identified by previous field measurements and mathematical modeling results, which often occurs when the aspect ratio H/W is higher than 0.7. The results show that the flow pattern of POD mode 1, the most influential mode, contains several dominant frequencies and captures approximately 14% of the energy. It respectively leads to the flow acceleration near the stagnation point and the separation area caused by the blocking effect, and the forced separation caused by the upstream structure. In addition, this mode also controls the flow reattachment above the downstream structure to a certain extent. The frequency with the highest amplitude is 0.68 Hz, which is associated with the highly coherent structure existing in the flow field; Contaminant density behind structure arrangements depends on wind corridors. Smaller wind corridors enhance the acceleration of nearby airflow, while the reattachment phenomenon between adjacent corridors becomes unstable, resulting in a reduced impact range. A wider wind corridor can effectively reduce air contaminants in city areas, with removal effectiveness directly related to corridor breadth.

Date of Award	2024
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Tim K.t. Tse (Supervisor)