Experimental investigation and radial basis function network modeling of direct evaporative cooling systems

Abstract

Radial basis function network method is used for modeling a direct evaporative cooling system. Air dry exit temperature, air pressure drop across the cooler and cooler efficiency are predicted using these models. The inputs are pad thickness, air inlet speed, air dry inlet temperature, relative humidity at the inlet and feed water temperature. The data for the models are taken from the experiments performed specifically for this purpose. Model validation is performed using twofold cross validation method. A grid search is used to determine optimal network parameters, such as, optimum number of radial basis elements and spread parameter. Validated models are tested against ordinary least squares models for the output variables. The results indicate that it is feasible to apply radial basis function networks to model direct evaporative coolers. © 2018 Elsevier Ltd