Prediction of pressure drop from multivariate polynomial regression for membrane-based air-to-air energy recovery ventilator cores

Abstract

Ventilation is an active control method that can improve the indoor environment by removing indoor air pollution. The membrane-based air-to-air energy recovery ventilator is a ventilation device that utilizes the heat exchange between the discharged polluted air and fresh outdoor air during ventilation. This study analyzed the pressure drop characteristics of the ventilator core and aimed to develop an equation to predict the pressure drop using polynomial regression based on the size of the core, the airflow rate, and the opening ratio of the core. Within elements having the same opening ratio, the channel velocity (uc) and equivalent pressure drop (Pe) values showed a linear relationship, regardless of the element size. The opening ratio of the elements varied depending on the cell height. To analyze the correlation between the opening ratio of the element, substantial flow rate inside the element, and equivalent pressure drop, a multivariate polynomial regression analysis was conducted for the three variables. The difference between the values of the derived prediction formula and the experimental value was found to be within 5% across the entire range in which the experiment was conducted. Using the interaction formula of equivalent pressure drop, channel velocity, and opening ratio derived in this study, the pressure drop across the entire driving area could be predicted for an arbitrary cell height and width of the ventilator core, as well as the operating airflow rate.