بهینه سازی طراحی مبدل های حرارتی پوسته ای و لوله ای با استفاده از تجزیه و تحلیل حساسیت جهانی و الگوریتم جستجوی هماهنگ

This study explores the use of global sensitivity analysis (GSA) and harmony search algorithm (HSA) for design optimization of shell and tube heat exchangers (STHXs) from the economic viewpoint. To reduce the size of the optimization problem, non-influential geometrical parameters which have the least effect on total cost of STHXs are identified using GSA. The HSA which is a meta-heuristic based algorithm is then applied to optimize the influential geometrical parameters. To demonstrate the effectiveness and accuracy of the proposed algorithm, an illustrative example is studied. Comparing the HSA results with those obtained using genetic algorithm (GA) reveals that the HSA can converge to optimum solution with higher accuracy.

Shell and tube heat exchangers (STHXs) are the most widely used heat exchangers in process industries because of their relatively simple manufacturing and their adaptability to different operating conditions. The design of STHXs, including thermodynamic and fluid dynamic design, cost estimation and optimization, represents a complex process containing an integrated whole of design rules and empirical knowledge of various fields [1]. There are many previous studies on the optimization of heat exchangers. Several investigators have used different strategies based on simulated annealing [2], genetic algorithm [1], [3], [4], [5], [6], [7] and [8] and traditional mathematical optimization algorithms [9], [10] and [11] for various objectives like minimum entropy generation [3], [12] and [13] and minimum cost of the STHXs [1], [7], [8], [9], [10], [11] and [14]. Some of these studies focuses mainly on a single geometrical parameter like optimum baffle spacing [9], [10] and [15] and some others try to optimize a variety of geometrical and operational parameters of the STHXs. Determination of the most influential parameters from a set of the candidate design parameters can greatly affect the performance of the optimization process. There has been some parametric studies on air cooled heat exchangers (ACHEs) trying to investigate the influence of the design parameters on the performance of the ACHEs [13] and [16] and some similar studies have been done on STHXs [3], [9] and [17]. However, most of these works only study the effect of single parameter change while the other parameters of the heat exchanger are evaluated at a selected point in parameter space. For a problem whose sensitivity feature varies from one region of the parameter space to another, this type of parameter study would not shed much light in understanding the sensitivity behavior of the problem over the entire domain of parameter space. In order to determine the influential input parameters over defined parameter space global sensitivity analysis (GSA) should be performed. The main objectives of this study are (a) to identify the most influential geometrical parameters that affect total cost of STHXs by means of GSA in order to reduce the size of the optimization problem and (b) to optimize the influential parameters of STHXs from economic point of view. The HSA which is a recently developed meta-heuristic algorithm is used for design optimization of STHXs. The algorithm ability is demonstrated using an illustrative example. The HSA results are compared with those obtained using genetic algorithm (GA) on the same example.

This study demonstrates successful application of harmony search algorithm for the optimal design of shell and tube heat exchangers. The HSA is simple in concept, few in parameters and easy for implementation. Moreover, it does not require any derivative information. These features increase the applicability of the HSA, particularly in thermal systems design, where the problems are usually non-convex and have a large amount of discrete variables or discontinuity in the objective function. One of the features presented in this study is the use of global sensitivity analysis. The aim of the sensitivity analysis is to identify geometrical parameters that have the largest impact on total cost of STHXs. The GSA could successfully found the most important parameters. The algorithm ability was demonstrated using an illustrative example and the performance was compared with genetic algorithm. Results reveal that the proposed algorithm can converge to optimum solution with higher accuracy in comparison with genetic algorithm.