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Author:

Zhang, Haotian (Zhang, Haotian.) | Ding, Xiaoxiao (Ding, Xiaoxiao.) | Zhang, Weirong (Zhang, Weirong.) (Scholars:张伟荣) | Zhang, Weijia (Zhang, Weijia.) | Xuan, Yingli (Xuan, Yingli.)

Indexed by:

EI Scopus SCIE

Abstract:

As infectious respiratory diseases are highly transmissible through the air, researchers have improved traditional total volume air distribution systems to reduce infection risk. Multi-vent module-based adaptive ventilation (MAV) is a novel ventilation type that facilitates the switching of inlets and outlets to suit different indoor scenarios without changing ductwork layout. However, little research has evaluated MAV module sizing and air velocity selection, both related to MAV system efficiency in removing contaminants and the corresponding level of protection for occupants in the ventilated room. Therefore, the module-source offset ratio (MSOR) is proposed, based on the MAV module size and its distance from an infected occupant, to inform selection of optimal MAV module parameters. Computational fluid dynamics simulations illustrated contaminant distribution in a two-person MAV equipped office. Discrete phase particles modelled respiratory contaminants from the infected occupant, and contaminant concentration distributions were compared under four MAV air distribution layouts, three air velocities, and three module sizes considered using the MSOR. Results indicate that lower air velocities favour rising contaminant levels, provided the ventilation rate is met. Optimal contaminant discharge can be achieved when the line of outlets is located directly above the infected occupant. Using this parameter to guide MAV system design, 85.7% of contaminants may be rendered harmless to the human body within 120 s using the default air vent layout. A more appropriate supply air velocity and air vent layout increases this value to 91.4%. These results are expected to inform the deployment of MAV systems to reduce airborne infection risk.

Keyword:

computational fluid dynamics infection control indoor air quality multi-vent module-based adaptive ventilation

Author Community:

  • [ 1 ] [Zhang, Haotian]Beijing Univ Technol, Key Lab Green Built Environm & Energy Efficient Te, Beijing 100124, Peoples R China
  • [ 2 ] [Ding, Xiaoxiao]Beijing Univ Technol, Key Lab Green Built Environm & Energy Efficient Te, Beijing 100124, Peoples R China
  • [ 3 ] [Zhang, Weirong]Beijing Univ Technol, Key Lab Green Built Environm & Energy Efficient Te, Beijing 100124, Peoples R China
  • [ 4 ] [Zhang, Weijia]Beijing Univ Technol, Key Lab Green Built Environm & Energy Efficient Te, Beijing 100124, Peoples R China
  • [ 5 ] [Xuan, Yingli]Tokyo Polytech Univ, Dept Architecture, Tokyo, Japan

Reprint Author's Address:

  • [Zhang, Weirong]Beijing Univ Technol, Key Lab Green Built Environm & Energy Efficient Te, Beijing 100124, Peoples R China;;

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Source :

BUILDING SIMULATION

ISSN: 1996-3599

Year: 2023

Issue: 1

Volume: 17

Page: 113-130

5 . 5 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:19

Cited Count:

WoS CC Cited Count: 4

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 14

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