Multi-objective Optimization And Design Of Shell-and-tube Heat Exchanger And Heat Exchanger Networks

As a basic heat transfer equipment heat exchangers find wide applications in chemical industry, power engineering, metallurgy, food, energy, aerospace and other engineering fields. Reducing the irreversible dissipation in the heat transfer processes and improving heat exchangers'performance by optimizing the heat exchanger design is an important measure to improve the energy efficiency, especially in the current situation that shortages in energy is growing and environment pollution is getting worse. In practice we often use many heat exchangers together. Therefore how to improve the performance of heat exchanger networks is also an important research topic. This thesis will focus on multi-objective optimization design of shell-and-tube heat exchangers and heat exchanger networks.The available objective functions for heat exchanger optimization designs may be classified into two groups, one is the minimum total cost of heat exchangers, and the other is the minimum dimensionless entropy generation in heat exchangers. The first can reduce the cost of heat exchanger, but at the expense of heat exchanger's performance. The second can improve the heat exchanger performance, but increase the cost of the heat exchanger. In order to reduce the cost and improve the performance simultaneously, in the present work the minimum total annual cost and the minimum entransy dissipation number are taken as two separate objective functions, and fast & elitist non-dominated sorting genetic algorithm (NSGA-II) is applied to solve the multi-objective optimization design problems of shell-and-tube heat exchangers and heat exchanger networks. In addition the heat exchanger multi-objective optimization design is programmed and the comparison with the single-objective optimization design is made.In the multi-objective optimization design of shell-and-tube heat exchangers, the minimum total annual cost and the minimum entransy dissipation number are selected as two objective functions, the tube inside diameter, tube length, the number of tubes, tube layout, baffle cut, central baffle spacing, inlet and outlet baffle spacing, tube pitch, tube-to-baffle hole diametric clearance, shell-to-baffle hole diametric clearance, diameter of the outer tube limit as design variables, and the admissible pressure drop and the requirements of heat exchanger design standards as the constraint conditions, thus the multi-objective optimization problem of heat exchanger designs is formulated. The genetic algorithm NSGA-II is employed to solve the multi-objective optimization problems. It is found that this optimization design method can reduce the heat exchanger cost and pumping power simultaneously.The heat exchanger network optimization design with the minimum cost as the objective function can significantly save the cost of heat exchanger networks upon the completion of heat transfer task. Therefore it is a very practical approach to heat exchanger network optimization design. Because of the special link of the entransy dissipation number of heat exchanger network to the heat transfer effectiveness and the minimum temperature difference, it is found that the heat exchanger network optimization with the entransy dissipation number as the objective function is just of theoretical value and not practical in the engineering applications. The multi-objective optimization design of heat exchanger networks with the entransy dissipation number and the total cost as two separate objective functions can reduce the cost and improve the heat transfer performance at the same time.