火积耗散理论在管壳式换热器优化设计中的应用
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摘要
换热器在众多高能耗工业领域中具有广泛的应用,同时和能量的节约、转换、回收以及新能源的开发都有着密切的联系。通过优化设计提高换热器的性能,减少换热过程热量的不可逆耗散,是提高能源利用率的重要措施,在能源日益短缺和环境污染逐步恶化的今天具有重要的意义。本文将致力于单目标和多目标管壳式换热器优化设计的研究。
换热器优化设计的关键问题是选择一个合适的优化目标函数。本文首先以无量纲化的总火积耗散(总火积耗散数)为目标函数,以换热器的一些几何参数和冷流体的出口温度为设计变量,以容许压降和换热器设计标准要求为约束条件,形成了换热器的优化设计问题,并应用遗传算法求解了相应的优化问题。通过比较优化前后的设计方案,发现通过优化设计,在提高换热器有效度的同时,明显减少了泵功的消耗。通过和其它换热器优化设计方法(譬如传统的最小成本法)对比,发现以总火积耗散数为目标函数的换热器优化设计方法在提高换热器性能和减少能量的损耗方面具有明显的优势。
但以总火积耗散数为目标函数的单目标换热器优化设计方法存在一定缺陷,即对于以液体为换热介质的换热器,有限温差导热引起的火积耗散远大于流动阻力引起的火积耗散,以二者的和作为目标函数进行单目标优化设计时很容易忽略流动阻力因素的影响。为了解决这一问题,本文以有限温差导热引起的火积耗散数和流体阻力引起的火积耗散数为两个独立的目标函数,应用多目标遗传算法构造了换热器的多目标优化设计方法。通过分析多目标优化过程中换热器性能参数的变化,以及对多目标和单目标优化结果之间的比较,我们发现换热器的多目标优化设计方法具有更大的优势。
Heat exchangers are widely applied in high energy consumption industries and are closely related to the energy saving, conversion, recovery as well as the exploitation of new energy sources. To improve the performance of heat exchanger and reduce the irreversible loses occurring in the heat exchange process by optimizing the heat exchanger design is one of important ways to increase the energy efficiency and is of great importance under the current situation that the energy shortage and environment deterioration becomes more and more severe. In the present work, the single-or multi-objective optimization of shell-and-tube heat exchanger design is investigated.
The key problem for heat exchanger optimization design is to choose an appropriate objective function. In our work, the total dimensionless entransy dissipation (called as entransy dissipation number) is taken as the objective function, some geometric parameters of the heat exchanger and the outlet temperature of cold fluid are set to the design variables, the admissible pressure drop and requirements of heat exchanger design standard are selected as the constraint conditions, thus an optimization design problem for heat exchanger is formulated. The genetic algorithm is employed to solve the related optimization problems. The comparison between the initial and optimized design plans shows that the optimization process improves the exchanger effectiveness and in the same time reduces the pumping power significantly. In comparison with other optimization approaches, such as the traditional cost-minimization method, the single-objective heat exchanger optimization design method with the entransy dissipation number as the objective function demonstrates obvious advantages on improving the heat exchanger performance and reducing the irreversible loses.
However, there exists a drawback for the single-objective heat exchanger optimization design method with the total entransy dissipation number as the objective function, namely, the entransy dissipation induced by heat conduction under finite temperature difference is much larger than that caused by fluid friction in the heat exchange process with fluid as the heat transfer medium. Therefore, the single-objective heat exchanger optimization design method usually neglects the contribution of fluid friction to the entransy dissipation. In order to solve this problem, the entransy dissipation numbers related to the heat conduction and fluid frictions are set to two separate objective functions, a multi-objective optimization of heat exchanger design is proposed with the help of the genetic algorithm. By the analysis of the heat exchanger performance and the comparison with the results of single-objective optimization design, it is found that the multi-objective optimization of heat exchanger design is more advantageous.
换热器优化设计的关键问题是选择一个合适的优化目标函数。本文首先以无量纲化的总火积耗散(总火积耗散数)为目标函数,以换热器的一些几何参数和冷流体的出口温度为设计变量,以容许压降和换热器设计标准要求为约束条件,形成了换热器的优化设计问题,并应用遗传算法求解了相应的优化问题。通过比较优化前后的设计方案,发现通过优化设计,在提高换热器有效度的同时,明显减少了泵功的消耗。通过和其它换热器优化设计方法(譬如传统的最小成本法)对比,发现以总火积耗散数为目标函数的换热器优化设计方法在提高换热器性能和减少能量的损耗方面具有明显的优势。
但以总火积耗散数为目标函数的单目标换热器优化设计方法存在一定缺陷,即对于以液体为换热介质的换热器,有限温差导热引起的火积耗散远大于流动阻力引起的火积耗散,以二者的和作为目标函数进行单目标优化设计时很容易忽略流动阻力因素的影响。为了解决这一问题,本文以有限温差导热引起的火积耗散数和流体阻力引起的火积耗散数为两个独立的目标函数,应用多目标遗传算法构造了换热器的多目标优化设计方法。通过分析多目标优化过程中换热器性能参数的变化,以及对多目标和单目标优化结果之间的比较,我们发现换热器的多目标优化设计方法具有更大的优势。
Heat exchangers are widely applied in high energy consumption industries and are closely related to the energy saving, conversion, recovery as well as the exploitation of new energy sources. To improve the performance of heat exchanger and reduce the irreversible loses occurring in the heat exchange process by optimizing the heat exchanger design is one of important ways to increase the energy efficiency and is of great importance under the current situation that the energy shortage and environment deterioration becomes more and more severe. In the present work, the single-or multi-objective optimization of shell-and-tube heat exchanger design is investigated.
The key problem for heat exchanger optimization design is to choose an appropriate objective function. In our work, the total dimensionless entransy dissipation (called as entransy dissipation number) is taken as the objective function, some geometric parameters of the heat exchanger and the outlet temperature of cold fluid are set to the design variables, the admissible pressure drop and requirements of heat exchanger design standard are selected as the constraint conditions, thus an optimization design problem for heat exchanger is formulated. The genetic algorithm is employed to solve the related optimization problems. The comparison between the initial and optimized design plans shows that the optimization process improves the exchanger effectiveness and in the same time reduces the pumping power significantly. In comparison with other optimization approaches, such as the traditional cost-minimization method, the single-objective heat exchanger optimization design method with the entransy dissipation number as the objective function demonstrates obvious advantages on improving the heat exchanger performance and reducing the irreversible loses.
However, there exists a drawback for the single-objective heat exchanger optimization design method with the total entransy dissipation number as the objective function, namely, the entransy dissipation induced by heat conduction under finite temperature difference is much larger than that caused by fluid friction in the heat exchange process with fluid as the heat transfer medium. Therefore, the single-objective heat exchanger optimization design method usually neglects the contribution of fluid friction to the entransy dissipation. In order to solve this problem, the entransy dissipation numbers related to the heat conduction and fluid frictions are set to two separate objective functions, a multi-objective optimization of heat exchanger design is proposed with the help of the genetic algorithm. By the analysis of the heat exchanger performance and the comparison with the results of single-objective optimization design, it is found that the multi-objective optimization of heat exchanger design is more advantageous.
引文
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[2]Pletcher L S. Andrews M J. Technical/market assessment of heat exchanger technology for users of natural gas[M]. GRI Report GRI-94/0248,1994.
[3]史美中,王中铮.热交换热器原理与设计[M].南京：东南大学出版社,2003：40-93,272-275.
[4]Caputo Antonio C, Pelagagge Pacifico M, Salini Paolo. Heat exchanger design based on economic optimization[J]. Applied Thermal Engineering 2008;28(10):1151-1159.
[5]Akbarnia M, Amidpour M, Shadaram A. A new approach in pinch technology considering piping costs in total cost targeting for heat exchanger network [J]. Chemical Engineering Research and Design,2009,87:357-365.
[6]吴恩,牟福元.紧凑式换热器的技术经济分析[J].热处理技术与装备,2008,29(4)：1-4.
[7]Yilmaz M, Sara O N, Karsli S, Performance evaluation criteria for heat exchangers based on second law analysis [J]. Exergy, an International Journal.2001,1(4) 278～294.
[8]K.Muralikrishnaand U V.Shenoy.Heat exchangerdesign targers for minimum area and cost. Trans IchemE[J].2000,78(part A):161-167.
[9]陈维汉,一种考虑综合性能优化的换热器热设计方法,化工装备技术,2006,4(27),35-40.
[10]Wilde D J. A review of optimization theory [J]. Ind. Eng. Chem.,1965,57 (8),18-31.
[11]Giampietro Fabbrl.A genetic algorithm for fin profile optimization, Int. J. Hear Mass Transfer.1997.40(9),2165-2172.
[12]Xie G N, Sunden B, Wang Q W. Optimization of compact heat exchangers by a genetic algorithm[J].Applied Thermal Engineering,28,895-906.
[13]张丽娜,杨春信,王安良.应用遗传算法优化设计板翅式换热器[J].航空动力学报,2004,19(4)：530-535.
[14]谢公南,王秋旺.遗传算法在板翅式换热器尺寸优化中的应用[J].中国电机工程学报,2006,26(7)：53-57.
[15]吴志刚,丁国良,浦晖,龙慧芳.基于遗传算法的翅片管换热器管路优化方法[J].化工学报,2007,58(5)：1115-1120.
[16]Jiangfeng Guo, Mingtian Xu, Lin Cheng. The application of field synergy number in shell-and-tube heat exchanger optimization design[J]. Applied Energy 86 (2009) 2079-2087.
[17]刘云,徐伟福,赵伟,周昆颖.遗传算法在管箱式翅片管换热器优化设计中的应用[J].北京化工大学学报,2003,30(6)：8790.
[18]商建平,俞树荣.列管式换热器遗传算法的优化设计[J].兰州理工大学学报,2004,30(1)：63-66.
[19]崔永正,任禾盛,都桂梅.应用遗传算法优化设计紧凑式换热器[J].动力工程,2008,28(5)：739-743.
[20]于颖,李永生,关琦.板翅式换热器模糊优化设计[J].石油化工设备,2001,30(2)：20-22.
[21]Degroot S R, Mazur P. Thermodynamics of Irreversible Processes. Amsterdam[M]. North-Holland:North-Holland Publishing Company,1962:1-37.
[22]Bejan A. Entropy generation though heat and fluid flow[M].New York:Wiley, 1982:21-42,102-107.
[23]Grazzini C, Gori F. Entropy Parameters for Heat Exchanger Design [J]. Int. J. Heat Mass Transfer,1988,31(12):2547-255.
[24]Aceves Saborio S, Ranasinghe J, Reistad G M. An Extension to the Irreversibility Minimization Analysis Applied to Heat Exchangers [J]. Transactions of the ASME, Journaof Heat Transfer,1999,111:29-36.
[25]吴双应,李友荣,曾丹苓.换热管传热过程的熵产分析.重庆大学学报(自热科学版)[J].2001,24(2),92-95.
[26]Bejan A. Advanced Engineering Thermodynamics[M]. New York:Wiley,1988
[27]Hesselgreaves J E, Rationalisation of second law analysis of heat exchanger[J]. International Journal of Heat and Mass Transfer,2000,43:4189-4204.
[28]Shah.R.K,Skiepko.T.Entropy generation extrema and their relationship with heat exchanger effectiveness-number of transfer unit behavior for complex flow arrangements [J]. International Journal of Heat and Mass Transfer,2004,126(6): 994-1002.
[29]Zengyuan Guo,Hongye Zhu, Xingang Liang. Entransy-A physical quantity describing heat transfer ability [J]. International Journal of Heat and Mass Transfer, 2007,50:2545-2556.
[30]朱宏晔,陈泽敬,过增元.火积耗散极值原理的电热模拟实验研究[J].自然科学进展,2007,17(10)：1692-1698.
[31]陈群,任建勋.对流换热过程的广义热阻及其与火积耗散的关系[J].科学通报,2008,53(14)：1730—1736.
[32]许明田,程林,郭江峰.火积耗散理论在换热器设计中的应用[J].工程热物理学报,2009,30(12)：2090-2092.
[33]程新广,孟继安,过增元.导热优化中的最小传递势容耗散与最小熵产[J].工程热物理学报,2005,26(6)：1034—1036]
[34]柳雄斌,孟继安,过增元.换热器参数优化中的熵产极值和火积耗散极值[J].科学通报,2008,53(24)：3026—3029.
[35]郭江峰,程林,许明田.火积耗散数及其应用.科学通报[J].2009,54(19)：2998-3002.
[36]过增元,程新广,夏再忠.最小热量传递势容耗散原理及其在导热优化中的应用[J].科学通报,2003,1：21—25.
[37]Jiangfeng Guo, Lin Cheng, Mingtian Xu. Entransy dissipation number and its application to heat exchanger performance evaluation, Chinese Science Bulletin, 2009,54:2708-2713.
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