A Grey Box Modeling Method for Fast Predicting Buoyancy-Driven Natural Ventilation Rates through Multi-Opening Atriums

Abstract

The utilization of buoyancy-driven natural ventilation in atrium buildings during transitional seasons helps create a healthy and comfortable indoor environment by bringing fresh air indoors. Among other factors, the air flow rate is a key parameter determining the ventilation performance of an atrium. In this study, a grey box modeling method is proposed and a prediction model is built for calculating the buoyancy-driven ventilation rate using three openings. This model developed from Bruce’s neutral height-based formulation and conservation laws is supported with a theoretical structure and determined with 7 independent variables and 4 integrated parameters. The integrated parameters could be estimated from a set of simulated data and in the results, the error of the semi-empirical predictive equation derived from CFD (computational fluid dynamics) simulated data is controlled within 10%, which indicates that a reliable predictive equation could be established with a rather small dataset. This modeling method has been validated with CFD simulated data, and it can be applied extensively to similar buildings for designing an expected ventilation rate. The simplicity of this grey box modeling should save the evaluation time for new cases and help designers to estimate the ventilation performance and choose building optimal opening designs.