Dai Yuwei, Zhang Fuyao, Wang Haidong
School of Environment and Architecture, University of Shanghai for Science and Technology, 516 Jungong Rd, Shanghai, 200093, China.
J Build Eng. 2023 Jun 1;68:106049. doi: 10.1016/j.jobe.2023.106049. Epub 2023 Feb 3.
A sudden outbreak of COVID-19 occurred in December 2019 and its rapid spread over the last two years caused a global pandemic. A special airborne transmission via aerosols called interunit dispersion is risky in a high-density urban environment, which needs more attention. In order to identify the source location of pollutants or viruses under the interunit transmission condition with natural ventilation, this study adopted the inverse Computational Fluid Dynamics (CFD) simulation with the adjoint probability method. The detailed process of the inverse modeling was presented. Also, the possible interunit transmission routes of the pollutants or viruses were analyzed. A three-story building model with single-sided openings was built. Six different combinations of fixed sensor locations were tested, and it was determined that setting sensors in the four corner regions of the building was the optimist strategy. A total of 25 cases with five different wind directions ( , , , , and ) were tested to verify the accuracy of the source location with inverse modeling. The results showed that 67%-78% of the rooms in the building can be identified with a limited number of pollutant sensors and all rooms can be identified with one additional sensor in the downstream room of the building under different wind direction. This research revealed that the inverse modeling method could be used to identify the pollutant source in the coupled indoor and outdoor environment. Further, this work can provide guidance for the pollutant monitor positions in the applications.
2019年12月突发新型冠状病毒肺炎疫情，在过去两年里其迅速传播，引发了全球大流行。在高密度城市环境中，一种通过气溶胶进行的特殊空气传播（称为单元间扩散）存在风险，这需要更多关注。为了在自然通风的单元间传输条件下识别污染物或病毒的源位置，本研究采用了伴随概率法的逆计算流体动力学（CFD）模拟。介绍了逆建模的详细过程。此外，分析了污染物或病毒可能的单元间传输途径。建立了一个带有单面开口的三层建筑模型。测试了六种不同的固定传感器位置组合，确定在建筑物的四个角区域设置传感器是最优策略。总共测试了25种不同风向（ 、 、 、 和 ）的情况，以验证逆建模确定源位置的准确性。结果表明，在不同风向条件下，使用有限数量的污染物传感器可以识别建筑物内67%-78%的房间，在建筑物下游房间增加一个传感器则可以识别所有房间。本研究表明，逆建模方法可用于识别室内外耦合环境中的污染物源。此外，这项工作可为实际应用中的污染物监测位置提供指导。
