A new design approach for shell-and-tube heat exchangers using genetic algorithms from economic point of view

A heat exchanger is a device that is used to transfer heat between two or more fluids that are at different temperatures. Heat exchangers are essential elements in a wide range of systems, including the human body, automobiles, computers, power plants, and comfort heating/cooling equipment. The most commonly used type of heat exchanger is the shell-and-tube heat exchanger, the optimal design of which is the main objective of this study. A primary objective in the heat exchanger design is the estimation of the minimum heat transfer area required for a given heat duty, as it governs the overall cost of the heat exchanger. However there is no concrete objective function that can be expressed explicitly as a function of design variables and in fact many numbers of discrete combinations of the design variables are possible. In the present study, genetic algorithms (GA) has been successfully applied for the optimal design of shell-and-tube heat exchanger by varying the design variables: outer tube diameter, tube layout, number of tube passes, outer shell diameter, baffle spacing and baffle cut. LMTD method is used to determine the heat transfer area for a given design configuration.