ANALYSIS OF PARTICLE FLOWS (PM1, PM5, PM10) IN FORCED VENTILATION SYSTEM USING CFD TECHNIQUE
1
Issued Date
2022-01-01
Resource Type
ISSN
0858849X
eISSN
25870009
Scopus ID
2-s2.0-85140779178
Journal Title
Suranaree Journal of Science and Technology
Volume
29
Issue
6
Rights Holder(s)
SCOPUS
Bibliographic Citation
Suranaree Journal of Science and Technology Vol.29 No.6 (2022)
Suggested Citation
Promtong M. ANALYSIS OF PARTICLE FLOWS (PM1, PM5, PM10) IN FORCED VENTILATION SYSTEM USING CFD TECHNIQUE. Suranaree Journal of Science and Technology Vol.29 No.6 (2022). Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/84621
Title
ANALYSIS OF PARTICLE FLOWS (PM1, PM5, PM10) IN FORCED VENTILATION SYSTEM USING CFD TECHNIQUE
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
About 80% of the time, people living indoors face an unacceptable quantity of tiny particles that can affect respiration systems and lead to serious health issues. This research objective focuses on investigating forced ventilation systems and how the crucial parameters relating to the particle, including the size, inlet velocity, and room ventilating system, can influence the movement of harmful particles. The Computational Fluid Dynamics (CFD) technique was introduced to investigate a room model's air movements and compared with experimental data. Due to the turbulent flow, two different turbulence models (k-ε and k-SST) were involved and have been discussed when calculating the flow field, as in the Reynolds stress closures. The simulated velocity profiles were found in good agreement with experimental data. To obtain additional information on particle propagations, the Discrete Phase Model (DPM) was introduced. It was found that flow patterns can dominate particle motions in the considered ventilation systems dependent on the size and inlet velocity. Due to having different inlet velocities, the number of escaped particles and the residence times were found to represent different values for each particle size. As a result, the 1 μm particles could completely escape from the room within 13 mins, but the larger 10 μm remained in the room for longer, finally escaping after 16 mins. This DPM modeling technique will be further introduced to study such infected particles’ movements in commercial or public places. Modifications to enhance the ventilation system's efficiency in particle removal will be crucial in discussions.