Rania Jradi1,*, Christophe Marvillet2, Mohamed-Razak Jeday1
FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.5, pp. 1511-1519, 2022, DOI:10.32604/fdmp.2022.021925
Abstract The accumulation of undesirable deposits on the heat exchange surface represents a critical issue in industrial heat exchangers. Taking experimental measurements of the fouling is relatively difficult and, often, this method does not lead to precise results. To overcome these problems, in the present study, a new approach based on an Artificial Neural Network (ANN) is used to predict the fouling resistance as a function of specific measurable variables in the phosphoric acid concentration process. These include: the phosphoric acid inlet and outlet temperatures, the steam temperature, the phosphoric acid density, the phosphoric acid volume flow rate circulating in the… More >
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