SIMULATED ANNEALING TECHNIQUE TO DESIGN MINIMUM COST EXCHANGER Owing to the wide utilization of heat exchangers in industrial processes, their  cost minimization is an important target for both designers and users。 Tra- ditional design approaches are based on iterative procedures which gradually change the design and geometric parameters to satisfy a given heat duty and constraints。 Although well proven, this kind of approach is time consuming and may not lead to cost effective design as no cost criteria are explicitly accounted for。 The present study explores the use of non-traditional optimization tech- nique called simulated annealing (SA), for design optimization of shell and  tube heat exchangers from an economic point of view。 The optimization pro- cedure involves the selection of the major geometric parameters such as tube diameters, tube length, baffle spacing, number of tube passes, tube layout,  type of head, baffle cut, etc。, and minimization of total annual cost is consi- dered as the design target。 The presented simulated annealing technique is simple in concept, few in parameters and easy for implementations。 Further- more, the SA algorithm explores the good quality solutions quickly, giving the designer more degrees of freedom in the final choice with respect to traditional methods。 The methodology takes into account the geometric and operational constraints typically recommended by design codes。 Three different case stu- dies are presented to demonstrate the effectiveness and accuracy of proposed algorithm。 The SA approach is able to reduce the total cost of the heat ex- changer compared to cost obtained by the previously reported GA approach。 84457

Keywords: simulated annealing; heat exchanger design; optimization;  heat transfer; mathematical modeling。 

Chemical process industries are currently facing the economic squeeze。 Global demand for oils and chemical products is low, revenue has fallen quickly and economic downturn has reduced the   availability of financing for working capital and investment。 This cut throat competition and shrinking profit margin forced the process industries  to  introspect critically the new investment decision。 Shell and tube heat ex- changers (STHE) are the most common type of ther- mal equipment employed in chemical process Indus- tries and contribute a major portion of capital invest- ment in new projects。 Because of their sheer large numbers in any chemical plants, small improvements in STHE design strategies offer big saving opportu-

Correspondening author: N。M。 Khalfe, , P。O。 Box 10085, 31961 Jubail Industrial City, Saudi Arabia。 

E-mail: khalfenadeem@hotmail。com 

Paper received: 4 February, 2011 Paper revised: 1 July, 2011 Paper accepted: 3 July, 2011 

nities。 Designers of STHE normally keep a design  margin to accommodate any uncertainties in design  calculations and to ensure that the heat exchanger  deliver its services in actual shop floor。 The need of the hour is to reduce the investment cost of STHE by trimming down the fat in design through more efficient design strategies。 The classical approach to STHE  design involves a significant amount of trial-and-error because an acceptable design needs to satisfy a  number of constraints (e。g。, fouling allowance and al- lowable pressure drops)。 Computer software mar- keted by companies such as Heat Transfer Research, Inc。 (HTRI), and Heat Transfer and Fluid Flow Service (HTFS) are used extensively  in  the  thermal design and rating of heat exchangers。 These packages incor- porate various design options for the heat exchangers including the variations in the tube diameter,  tube  pitch, shell type, number of tube passes, baffle spa- cing, baffle cut, etc。 Typically, a designer chooses va-

rious geometrical parameters such as tube  length,  shell diameter and the baffle spacing based on expe- rience to arrive at a possible  design。  If  the design does not satisfy the constraints, a new set of geomet- rical parameters must be chosen to check if there is any possibility of reducing the heat transfer area while satisfying the constraints。 Although well proven, this kind of approach is time consuming and may not  lead to cost effective design as no cost criteria are expli- citly accounted for。 Since several discrete combina- tions of the design configurations are possible, the  designer needs an efficient strategy to quickly locate  the design configuration having the minimum heat ex- changer cost。 Thus the optimal design of heat ex- changer can be posed as a large scale, discrete,  combinatorial optimization problem [1]。