Development of Artificial Neural Network based heat convection algorithm for thermal simulation of large rectangular cross-sectional area Earth-to-Air Heat Exchangers

An Earth-to-Air Heat Exchanger (ETAHE) is a low energy cooling and heating building component. It uses the ground's thermal storage to dampen ambient air temperature oscillations by delivering the air through a horizontally buried duct. To reduce airflow resistance, some hybrid ventilated buildings have recently adopted large cross-sectional area ducts. This paper describes the development of an Artificial Neural Network based Heat Convection (ANN-HC) algorithm to predict local average Nusselt Numbers along the duct surfaces. Furthermore, the ANN-HC algorithm is integrated with a transient three-dimensional heat transfer model based on finite element analysis of heat conduction in the ground domain surrounding the ETAHE to establish a new thermal modeling method for ETAHEs. A case study is presented to demonstrate the working principle of the new method. It is shown that the method can very well simulate the interactions between an ETAHE and its environment.