Modeling and comparative study of heat exchangers fouling in phosphoric acid concentration plant using experimental data

A Contribution to the Modelling of Fouling Resistance in Heat Exchanger-Condenser by Direct and Inverse Artificial Neural Network

“…A test was done with different data to optimise one of the inputsfor instance, different values of dimensionless condenser cooling seawater temperature (T * seawater ) on the one hand, and on the other hand, the simulated parameters were compared to the experimental data in order to check the accuracy of ANNi at way of the error given in the Eq. (16).…”

“…In order to evaluate the importance of the obtained results, they were compared with similar studies cited in the Introduction, [16][17][18][19] especially with the models that had the same or mostly the same inputs as we used. It was found that, in most models, the goal was to predict the fouling in heat exchangers.…”

“…In the work of Mohanraj et al 15 ANN gave an exceptional alternative methodology for the thermal analysis of heat exchangers. From the experimental data, Jradi et al 16 developed three accurate and reliable models of fouling phenomenon in three types of heat exchangers using three methods: Kern and Seaton model, Partial Least Squares model, and Artificial Neural Network model, in order to make a comparative study based on some statistical indices among these different models in regard to the modelling, and the losses prediction of heat exchangers performances due to the fouling phenomenon. The inputs to the ANN model used for the three types of exchangers were inlet and outlet temperatures, steam temperature, volume flow rate, density, and time.…”

Application of an Artificial Neural Network Method for the Prediction of the Tube-Side Fouling Resistance in a Shell-And-Tube Heat Exchanger

“…The heat exchanger is considered as an omnipresent and essential part of the energy performance strategy. Its principle of operation is to transfer thermal energy from one fluid to another without mixing them [1]. To improve the efficiency of heat transfer and optimize the energy recovery to ensure the best profitability of this equipment can be done by various techniques, such as: optimal design, appropriate control of functioning conditions, regular cleaning and predictive maintenance of heat exchangers.…”

“…One of the preponderant problems in the reduction of the performances of these installations is the fouling which created by the accumulation of solid materials on the side surfaces of heat exchangers [2]. Among several industries that are the most concerned by the fouling problem is the chemistry industries [1]. The geometry of the heat transfer surface, the operation conditions of the fluid and the heat exchanger are some variables that can have a huge effect on the fouling [3,4].…”