A CFD-based corrected nodal approach to better assess people exposure to pollutants in a room

Indoor air quality (IAQ) modeling predominantly relies on the nodal approach in the building simulation community, which assumes perfect mixing of indoor contaminants. However, Abadie and Limam (2007) among others questioned the homogeneity assumption for indoor pollutants in a room. Computational Fluid Dynamics (CFD) modeling is the most suitable method to use in this case but, despite the tremendous computational capacity now available, it remains time consuming to employs when dealing with long time or multiple zones to simulate like a small house or apartment.

Intermediate approaches have been developed such as zonal models or coarse-grid CFD but they required expertise to correctly adapt the mesh structure and ad hoc models to the proper studied case to reach good results. To better assess people exposure to pollutants in a room, we proposed a methodology, using corrections factors, that will correct the volume-averaged contaminant concentration obtained by the nodal approach to evaluate the exposure concentration at people location. In a recent study (Carnec et al. 2023), we show the existence of two factors able to perform such correction for a simple empty ventilated room by performing CFD simulations of the propagation of a passive scalar from the ventilation inlet for different airflow rates.

One, denoted λ_1 in what follows, consists of the ratio of the mass flow rate of pollutant extracted from the room (CFD) to that extracted with the nodal approach and the other prompted us to develop, a second correction factor λ_2, the ratio of spatial average breathing volume concentration to that of the total volume, both calculated by CFD. The shape of the correction factors profile, however, depends on aeraulic, thermal, and simulated pollution scenarios. Our objective is therefore to identify the time-dependent structure for these two correction factors based on input modeling parameters.

This structure should be adaptable and allow us to correct the nodal modeling solution to as many different configurations as possible. Our methodology involves setting up test cases, performing sensitivity analyses on the input parameters with respect to λ_1 and λ_2. Once we identify a suitable structure, we transform the nodal modeling solution into exposure concentration solving another mass balance equation. We adjust the mass flow rate exiting the room with λ_1 and multiply the mass balance solution by λ_2. We expect that both correction factors exhibit a self-similar character, and their profiles should be bounded, starting from 0 and converging toward 1.