A Seasonal Design Evaluation of an Earth-Air Heat Exchanger for Cooling and Heating in Saharan Algerian Regions Using ANN Model

Abstract

Earth-Air Heat Exchanger (EAHE) systems leverage the consistent temperature of the ground to optimize the pre-conditioning of air for a building's ventilation. This technology involves a network of buried pipes or tubes through which outdoor air circulates before entering the building. The main objective of the paper is to study the modeling of the variation of the outlet temperature of the EAHE air-ground exchanger using neural networks. This modeling was carried out based on multilayer neural networks.