Data-based mechanistic modelling approach to determine the age of air in a ventilated space

Abstract

In literature, local mean age of air is used as an important index to evaluate indoor air quality in ventilated rooms. In this research, a data-based mechanistic approach is used to model the spatial–temporal mass distribution in an imperfectly mixed forced ventilated installation. A first-order transfer function model has proved to be sufficiently good in describing the mass transfer dynamics ( R t 2 = 0.987 ) of the system. Furthermore, it was possible to fully understand the physical meaning of the model parameter. The parameter is found to be an inverse of the age of air. This Data-Based Modelling approach proved to be more robust when dealing with measurement noise. Finally, the modelled age of air was validated with a classical step up determination of the age of air for experimental data. Good correlation ( R t 2 = 0.77 ) was found between both results, which proved the physical background of the model parameter.