Application of Stochastic Methods to Estimate Fouling Heat Exchanger

Among the problems often encountered in the industry is the fouling of heat exchangers which can be defined as the deposition of undesirable materials, such as scale, suspended solids, and even insoluble salts on the internal surfaces of the heat exchanger. The presence of these deposits represents a resistance to fluid flow and heat transfer and increases the pressure loss and reduces the efficiency of the exchanger. Fouling of heat exchangers is unavoidable but can be mitigated by. Effective implementation of appropriate cleaning techniques. Periodic cleaning of heat exchangers is one option among the techniques to minimize losses due to fouling. However, cleaning activities in heat exchangers are costly. Consequently, the use of the reverse method with a fouling model to describe the fouling behavior and the experimental data makes it possible to obtain a better estimate of the value of the thermal resistance of fouling and thus a precise date for the cleaning. Our work consists in estimating the fouling resistance of the exchangers of the phosphoric acid concentration unit of the Tunisian chemical group using stochastic methods such as the genetic algorithm (GA) and the special swarm optimization (PSO). This method demonstrates a convergence towards the global minimum, even in the presence of several local minima, with great precision.