Kek, Hong Yee and Tan, Huiyi and Chin, Desmond Daniel Vui Sheng and Lee, Yi and Ismail, Nur Dayana and Deris, Muhd. Suhaimi and Mohamed Kamar, Haslinda and Wong, Keng Yinn (2023) A CFD assessment on ventilation strategies in mitigating healthcare-associated infection in single patient ward. Progress in Energy and Environment, 24 (NA). pp. 35-45. ISSN 2600-7762
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Official URL: http://dx.doi.org/10.37934/progee.24.1.3545
Abstract
A promising ventilation strategy is an effective measure to enhance indoor air quality and protect the patients against healthcare-acquired infection. The Computational Fluid Dynamics (CFD) model represents a patient ward that was constructed using Computer-Aided Design (CAD) software. The simulated results were verified and validated based on the published data. A Renormalization Group (RNG) k-epsilon model based on the Eulerian approach was used to simulate the airflow turbulence, while a discrete phase model (DPM) based on the Lagrangian approach was used to predict the dispersion of airborne particles. This study examined four cases of ventilation strategies, with varying ventilation rates, positioning of supply air diffusers, and location of exhaust grilles. This study revealed that the installation of air curtain jet coupled with a ceiling-mounted air supply diffuser (case 3) above the patient-occupying zone has the highest wiping efficiency against the infectious particles. The utilization of ventilation strategy in case 3 managed to reduce the particle by approximately 3.3 times as compared to the baseline case. The study outcome also suggested that the exhaust grilles should be placed on the upper wall, to ensure a proper mixing of fresh air in the entire patient ward.
Item Type: | Article |
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Uncontrolled Keywords: | airborne infection, hospital, covid-19, patient ward, infectious particles |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Mechanical Engineering |
ID Code: | 108598 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 19 Nov 2024 06:31 |
Last Modified: | 19 Nov 2024 06:31 |
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