Intelligent techniques for prediction characteristics of shell and tube heat exchangers: A comprehensive review

Abstract

Heat exchangers are widely used in different chemical industries and energy systems. Among different types of heat exchangers, shell and tube heat exchangers are among the most conventional ones that have significant share in the market and industry. Performance of shell and tube heat exchangers is affected by a variety of factors which can lead to some difficulties and complications in the modeling by use of numerical simulation. Intelligent techniques like artificial neural networks would be practical solution for modeling and simulation of these heat exchangers with significant exactness. In this regard, scholars have applied these methods for performance prediction and modeling characteristics of shell and tube heat exchangers in recent years. In the present article, studies on the modeling of different characteristics of shell and tube heat exchangers such as Nusselt number, pressure loss and fouling are reviewed and their key findings are represented. The findings of the study revealed that employment of proper intelligent methods can lead to exact performance prediction of these devices with R2 values of as high as 0.99 for both heat transfer coefficient and pressure drop. Moreover, it is reported in the reviewed studies that performance of these approaches is influenced by a variety of factors such as the applied techniques in the model and their structure. The developed model by the intelligent techniques for would be applicable for performance prediction, design and optimization of shell and tube heat exchangers. Finally, some recommendations are provided for the future studies that would be helpful in development of more precise and comprehensive models.