Feasibility evaluation of computational fluid dynamics approach for inhalation exposure assessment: Case study for biocide spray

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Abstract

Consumer products contain chemical substances that threaten human health. The zero-dimensional modeling methods and experimental methods have been used to estimate the inhalation exposure concentration of consumer products. The model and measurement methods have a spatial property problem and time/cost-consuming problem, respectively. For solving the problems due to the conventional methodology, this study investigated the feasibility of applying computational fluid dynamics (CFD) for the evaluation of inhalation exposure by comparing the experiment results and the zero-dimensional results with CFD results. To calculate the aerosol concentration, the CFD was performed by combined the 3D Reynolds averaged Navier–Stokes equations and a discrete phased model using ANSYS FLUENT. As a result of comparing the three methodologies performed under the same simulation/experimental conditions, we found that the zero-dimensional spray model shows an approximately five times underestimated inhalation exposure concentration when compared with the CFD results and measurement results in near field. Additionally, the results of the measured concentration of aerosols at five locations and the CFD results at the same location were compared to show the possibility of evaluating inhalation exposure at various locations using CFD instead of the experimental method. The CFD results according to measurement positions can rationally predict the measurement results with low error. In conclusion, in the field of exposure science, a guideline for exposure evaluation using CFD, was found that complements the shortcomings of the conventional methodology, the zero-dimensional spray model and measurement method.

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Park, D., & Lee, J. H. (2021). Feasibility evaluation of computational fluid dynamics approach for inhalation exposure assessment: Case study for biocide spray. Applied Sciences (Switzerland), 11(2), 1–16. https://doi.org/10.3390/app11020634

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