Fast prediction of indoor pollutant dispersion based on reduced-order ventilation models

Abstract

In order to provide realistic ventilation flow rates, it is of great importance to know indoor pollutant concentration field quickly and efficiently resulting from any type of indoor-pollutant-source distribution, further facilitating the design and control of indoor ventilation systems for practical application. This work introduces the development of reduced-order ventilation models for transient pollutant dispersion. In particular, we focus on transients resulting from a step change in pollutant source distributions. We further focus on the decay problem. A reduced-order ventilation model is the solution for this decay problem, which is derived from a large coupled system of Ordinary Differential Equations (ODEs) for concentration that can be cast in terms of a matrix exponential, that is accurately represented with only a few dominant eigenmodes. Using a 2D ventilation case, dominant eigenmodes with their physical relevance and pollutant concentration results are presented. We find that the first 4 eigenmodes are sufficient to predict the pollutant concentration decay for the current test case. We also find that the complex eigenmodes play an important role in the indoor recirculation processes.