Computational Fluid Dynamics Simulation of Airflow and Air Pattern in the Living Room for Reducing Coronavirus Exposure

Abstract

Viruses can be transmitted in indoor environments. Important factors in Indoor Air Quality (IAQ) are air velocity, relative humidity, temperature, and airflow pattern and Computational fluid dynamics (CFD) can use for IAQ assessment. The objective of this study is to CFD simulation in the living room to the prediction of the air pattern and air velocity. A computational fluid dynamic model was applied for airflow pattern and air velocity simulation. For simulation, GAMBIT, FLUENT, and CFD post software were used as preprocessing, processing, and post-processing, respectively. CFD validation was carried out by comparing the computed data with the experimental measurements. The final mesh number was set to 1,416,884 elementary cells and SIMPLEC algorithm was used for pressure-velocity coupling. PERSTO, and QUIK schemes have been used for the pressure terms, and the other variables, respectively. Simulations were carried out in ACH equals 3, 6 and 8 in four lateral walls. The maximum error and root mean square error from the air velocity were 14% and 0.10, respectively. Terminal settling velocity and relaxation time were equal to 0.302 ×10− 2 m/s and 0.0308 ×10− 2 s for 10 µm diameter particles, respectively. The stopping distance was 0.0089m and 0.011m for breathing and talking, respectively. The maximum of mean air velocity is in scenario 4 with ACH = 8 that mean air velocity is equal to 0.31 in 1.1m height, respectively. The results of this study showed that avoiding family gatherings is necessary for exposure control and suitable airflow and pattern can be improving indoor air conditions.

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