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Long-term prediction of dynamic distribution of passive contaminant in complex recirculating ventilation system

Recirculating ventilation systems may act as carriers of hazardous substances. The long-term prediction of the dynamic distribution of contaminants in this type of system is crucial for the evaluation of pollution and further design of more efficient ventilation systems. However, few convenient meth...

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Detalles Bibliográficos
Autores principales: Shao, Xiaoliang, Li, Xianting, Ma, Xiaojun, Zhu, Fenfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126526/
https://www.ncbi.nlm.nih.gov/pubmed/32287971
http://dx.doi.org/10.1016/j.buildenv.2017.05.012
Descripción
Sumario:Recirculating ventilation systems may act as carriers of hazardous substances. The long-term prediction of the dynamic distribution of contaminants in this type of system is crucial for the evaluation of pollution and further design of more efficient ventilation systems. However, few convenient methods can predict the dynamic distribution of contaminants, because the dynamic supply air concentrations resulting from air recirculation are unknown, especially over long time periods, such as months or years. In this study, a novel method is proposed to predict the dynamic distribution of contaminants over a long time period in a complex recirculating ventilation system, where an algebraic expression based on the indices of the response coefficient is applied to account for the relationship between the contaminant distribution inside the room and various boundary conditions. The method is established by obtaining comprehensive mathematical descriptions of the relationships between concentrations of contaminants in the air handling units, supply air inlets, return air outlets, and fresh air. Hourly supply air concentrations can be easily obtained by solving a matrix, and the dynamic distribution of contaminants is then calculated using an expression based on the response coefficient. The reliability of the proposed method is analyzed by both experimental and numerical methods. A simplified method is suggested to accelerate the time-consuming calculation of the response coefficient. The proposed method is beneficial for predicting three-dimensional dynamic distribution of contaminants in complex ventilation systems with an acceptable accuracy and time cost.