An Earth-to-Air Heat Exchanger (ETAHE) uses the ground's thermal storage capacity to dampen ambient air temperature oscillations by delivering the outdoor air to the indoors through a horizontally buried duct. With their lower airflow resistance, large cross-sectional area ETAHEs have been found to be more energy efficient than the conventional small ones, especially when integrated in hybrid ventilation systems. However, the lack of available methods for determining the heat convection at the duct surfaces has made accurate energy simulation and proper system design overly difficult. In this study, numerical experiments using computational fluid dynamics (CFD) were conducted to investigate the airflow and thermal behavior in the large ducts. A two-layer turbulence model was used to ensure accuracy in resolving the flow information in the near-wall region, which is critical for predicting accurate heat convection. The modeling method was verified by comparing its results with measurements from literature. Parametric studies were conducted to identify the influential design and operation variables for the heat convection. Thirty numerical experimental setups designed with the Latin Hypercube Sampling method were simulated to prepare a database with six design parameters as the simulation inputs and average Nusselt numbers over the duct ceiling, wall, and floor as the outputs. Based on the database an artificial neural network (ANN) model was trained to build a mathematical relation between the design variables and the Nusselt numbers. The developed ANN model showed very accurate prediction when compared with test data.
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