Modelling of the flow behavior of activated carbon cloths using a neural network approach

This work investigates the hydrodynamic and aerodynamic behaviors of recent adsorbents, activated carbon cloths (ACC). A first part presents their characteristics, a particular attention being given to the properties related to their woven structure. The influence of these characteristics on air and water pressure drops through ACC is shown by experimental measurements. It is established that a classic model set up for particular media, the Ergun model, does not enable a satisfying modelling of experimental data. An artificial neural network (ANN) is then used in order to include as explicative factors the cloths properties. The optimization of the ANN architecture is carried out, in terms of selection of the input neurons and number of hidden neurons. The generalization ability of the ANN is evaluated using a test dataset distinct from the training set. The influence of specific characteristics of cloths on their flow behavior is confirmed by an analysis of inputs sensibility, and the determination of their predictive influence.