Thermodynamic Optimization Of Shell-and-tube Heat Exchangers With Helical Baffles Based On Genetic Algorithm

Heat exchanger is a kind of industrial equipment which can transfer the heat to other fluid by certain heat transfer way.It is widely used in industrial production.At the same time,heat exchanger plays an important role in energy recovery and saving.It is also an important method to improve the efficiency of energy utilization to use certain optimization methods to improve the performance of heat exchanger and reduce the energy dissipation in the working process.Shell-and-tube heat exchanger is the main type of heat exchanger,and shell-and-tube heat exchanger with helical baffles as a new type of heat exchanger,having the characteristics of low flow pressure drop,not easy to scale,higher heat transfer performance,etc.Which is the focus for future development.But there is little research on the optimization of shell and tube heat exchanger with helical baffles.In this paper,based on the minimum entropy generation method,the single objective and multi-objective optimization design program for shell-and-tube heat exchanger with helical baffles are compiled by using genetic algorithm,realized the structural optimization research.It is very important to select the objective function and decision variables and set the constraint conditions in the research of the optimization design of heat exchanger.Generally,there are two kinds of objective functions for the optimization design of heat exchanger,one is to seek the minimum total cost of heat exchanger,the other is to seek the minimum entropy production number which represents the irreversible dissipation of heat exchanger.However,“the entropy production paradox” will appear in the entropy production number proposed by Bejan.Therefore,used the improved entropy production untis as the objective function to avoid the problem of “the entropy production paradox” in this paper,which also shows that the improved entropy production number is more applicable.In this paper,the improved entropy production number is used as the objective function,and the structural parameters of shell-and-tube heat exchanger with helical baffles are taken as the decision variables,including helix angle,overlapped degree,tubes length,outer diameter of tubes,number of tubes.The allowable pressure drop and other design criteria of heat exchanger are taken as constraints to form the optimization problem.The conclusions are as follows:(1)Through the single objective optimization of the continuous lap helical baffles structure by genetic algorithm,it is found that the effectiveness of the heat exchanger is increased by 15.49%,the pump power consumption is reduced by 63.11%,the entropy production is reduced by 19.23%,the performance of the heat exchanger is improved,and the irreversible dissipation is reduced.Although the heat exchange area has increased,resulting in increased costs;Through the single objective optimization of staggered lap helical baffles structure,it is found that the effectiveness of the heat exchanger has been improved by 7.19%,the pump power consumption has been reduced by 52.29%,the entropy production has been reduced by 9.6%,the performance of the heat exchanger has also been improved.Moreover,it is found that the irreversible dissipation of continuous lap structure is smaller than that of overlapped structure.(2)Taking the minimum annual total cost as the objective function,the single objective optimization design of the continuous lap spiral baffle structure is carried out.The results show that the total cost is reduced by 61.3%,the effectiveness is reduced by 51.8%,and the pump power consumption is greatly increased.It can be seen that the total cost is the minimum optimization,which sacrifices the performance of the heat exchanger.(3)Based on the study of the total entropy production and the minimum cost of single objective optimization,it is found that the optimization of the two objectives are based on the sacrifice of another objective function,and there is a contradictory relationship between them.The single objective optimization has certain limitations for the optimization of heat exchanger.In order to solve this problem,this paper takes the minimum entropy production as one of the independent objective functions,the minimum cost as another independent objective function,applied the genetic algorithm to realize the multi-objective function optimization of spiral baffled shell-and-tube heat exchanger.The results show that the multi-objective optimization of genetic algorithm achieves the best "compromise" of two objective functions,which is more flexible and advantageous than the single objective optimization.