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Author:

Zhang, Haotian (Zhang, Haotian.) | Ding, Xiaoxiao (Ding, Xiaoxiao.) | Zhang, Weirong (Zhang, Weirong.)

Indexed by:

EI

Abstract:

As infectious respiratory diseases are highly transmissible through the air, researchers have improved traditional total volume air distribution systems to reduce the risk of infection. Multi-vent module-based adaptive ventilation (MAV) is a novel type of ventilation that facilitates the switching of inlets and outlets to suit different indoor scenarios without changing the ductwork layout. However, little research has been undertaken to evaluate the sizing of MAV modules and selection of air velocity, both of which are related to the efficiency of the MAV system in removing contaminants and the corresponding level of protection for occupants in the ventilated room. Therefore, this study proposed the module-source offset ratio (MSOR). The MSOR is based on the size of the MAV module and its distance from an infected occupant to inform the selection of the optimal MAV module parameters accordingly. Computational fluid dynamics simulations were conducted to study the distribution of contaminants in a two-person office equipped with MAV. Discrete phase particles were used to model the respiratory contaminants from the infected occupant, and contaminant concentration distributions were compared under four MAV air distribution layouts and three module sizes considered using the MSOR. The results indicate that for MAV systems, the optimal discharge of contaminants can be achieved when the line of outlets is located directly above the infected occupant. These results are expected to inform the deployment of MAV systems to reduce the risk of airborne infection. © 2023 IBPSA.All rights reserved.

Keyword:

Air Contamination Computational fluid dynamics Ventilation Indoor air pollution

Author Community:

  • [ 1 ] [Zhang, Haotian]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Ding, Xiaoxiao]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Zhang, Weirong]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing; 100124, China

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ISSN: 2522-2708

Year: 2023

Volume: 18

Page: 3401-3408

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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