4.5 Article

Prompt location of indoor instantaneous air contaminant source through multi-zone model-based probability method by utilizing airflow data from coarse-grid CFD model

期刊

INDOOR AND BUILT ENVIRONMENT
卷 31, 期 4, 页码 944-954

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/1420326X211046039

关键词

Inverse modelling; Coarse-grid CFD; Multi-zone model; Adjoint probability method; Indoor airborne pollutant

资金

  1. Shanghai Sailing Program [21YF1430700]
  2. National Science Foundation of China (NSFC) [51508326]

向作者/读者索取更多资源

This study combines the joint probability method and coarse-grid CFD method with the multi-zone model method to accelerate the process of obtaining the indoor airflow field and performing the inverse calculation of indoor airborne contaminant source location, improving accuracy and computational efficiency.
In order to ensure indoor air quality safety, locating the airborne contaminant sources accurately and quickly is extremely important so that timely measures can be taken to undermine the spread of pollutant and even eliminate the negative effects. Previous studies have shown that the multi-zone model can greatly reduce the inverse calculation time. However, the multi-zone model cannot describe the details of the indoor velocity field, which limits its application in complex multi-zone or large space buildings. On the premise of the accuracy and computational speed, based on the joint probability method, this study adopted the coarse-grid CFD method to speed up the process of acquiring the indoor airflow field, together with the multi-zone model method, to perform the inverse calculation of indoor airborne contaminant source location. In the backward calculation process, we conducted the 'transpose' of the velocity field to obtain adjoint matrix, instead of computing 'negative' of the velocity vector to save the calculation time. A two-dimensional ventilation model was utilized to validate the method, which proved the accuracy and time-saving potential of it. This study provides theoretical and practical prospect for the real-time inverse calculation of locating the indoor airborne contaminant sources.

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