Application of the Taguchi and ANOVA Methods to Optimize Ventilation Parameters for Infection Risk Based on the Wells-Riley Model

Authors : Bahadır Erman YÜCE

Pages : 199-206

Doi:10.17798/bitlisfen.1222870

View : 275 | Download : 14

Publication Date : 2023-03-22

Article Type : Research Paper

Abstract :The coronavirus pandemic has caused many deaths and affected societies with social and economic problems as a consequence of its effect. Many different measures were taken to stop or reduce the spread of the virus like wearing a face mask and reorganizing school activities, transportation, and meetings. As an alternative to these measures, ventilation is a critical engineering solution that can help reduce the infection risk in the indoor environment. In this study, the effects of ventilation parameters insert ignore into journalissuearticles values(volume, ACH); and breathing rates on the Wells-Riley method-based infection risk probability were investigated by the Taguchi method. The orthogonal array was used to create the experimental design. Then, each parameter was analyzed according to the performance criterion insert ignore into journalissuearticles values(infection risk probability); using signal-to-noise insert ignore into journalissuearticles values(S/N); ratios and the order of importance of the parameters was calculated. Consequently, these data were used to identify worst-case and best-case scenarios to minimize the risk of infection in the indoor environment.
Keywords : Wells Riley, Optimization, Optimization, Infection risk, Covid 19

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