Modeling and optimizing for heat exchanger networks synthesis based on expert system and exergo—economic objective function

Selection of fouling factors is somewhat arbitrary in heat exchanger networks (HENs) synthesis. Fouling factors were reconsidered in this article for heat exchanger networks design. An objective function based on exergoeconomic analysis was introduced to assess optimal less conservative fouling factors. The objective took account of exergy consumption expense and heat exchanger capital cost at the same time. The exergy consumption of heat transfer in HENs was calculated using subsection integral on balanced composite curves. The proposed method was applied to an industrial case. Numerical results indicated that the optimal less conservative fouling factors were 80% of the original values and the heat transfer area of the system saved 350 m2 compared with root design. So it is necessary to reconsider the values of fouling factors for HENs design and that exergoeconomic analysis is useful in determining the optimal less conservative fouling factors.

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Economic optimization of heat exchanger networks based on geometric parameters using hybrid genetic-particle swarm algorithm technique

Journal of Engineering Design and Technology ◽

10.1108/jedt-05-2020-0183 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Amin Farzin ◽

Mehrangiz Ghazi ◽

Amir Farhang Sotoodeh ◽

Mohammad Nikian

Keyword(s):

Heat Exchanger ◽

Objective Function ◽

Heat Exchangers ◽

Annual Cost ◽

Design Parameters ◽

Total Annual Cost ◽

Economic Optimization ◽

Content Type ◽

Heat Exchanger Networks ◽

Shell And Tube

Purpose The purpose of this study is to provide a method for designing the shell and tube heat exchangers and examine the total annual cost of heat exchanger networks from the economic view based on the careful design of equipment. Design/methodology/approach Accurate evaluation of heat exchanger networks performance depends on detailed models of heat exchangers design. The simulations variables include nine design variables such as flow direction determination of each of the two fluids, number of tubes, number of tube passes, length of tubes, the arrangement of tubes, size and percentage of baffle cut, tube diameter and tube pitch. The optimal designing of the heat exchangers is based on geometrical and hydraulic modeling and using a hybrid genetic particle swarm optimization algorithm (PSO-GA) technique. In this paper, optimization and minimization of the total annual cost of heat exchanger networks are considered as the objective function. Findings In this study, a fast and reliable method is used to simulate, optimize design parameters and evaluate heat transfer enhancement. PSO-GA algorithms have been used to minimize the total annual cost, which includes investment costs of heat exchangers and pumps, operating costs (pumping) and energy costs for utilities. Three case studies of four, six and nine streams are selected to demonstrate the accuracy of the method. Reductions of 0.55%, 23.5% and 14.78% are obtained in total annual cost for the selected streams, respectively. Originality/value In the present study, a reliable method is used to simulate and optimize design parameters and the economic optimization of the heat exchanger networks. Taking into account the importance of shell and tube heat exchangers in industrial applications and the complexity in their geometry, the PSO-GA methodology is adopted to obtain an optimal geometric configuration. The total annual cost is chosen as the objective function. Applying this technique to case studies demonstrates its ability to accurately design heat exchangers to optimize the objective function of the heat exchanger networks by giving the detail of design.

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