【作者】 肖武；

【导师】 姚平经；

【作者基本信息】 大连理工大学 ， 化学工程， 2006， 博士

【摘要】 与双流股换热器相比,多流股换热器以其高效率、结构紧凑及投资低在气体加工和石油化工等过程工业中有着广泛的应用。但是以往人们把大部分精力用于传统的双流股换热器网络综合的研究,而有关多流股换热器网络综合问题的研究目前仍然很有限,尤其是对于工业大规模多流股换热器网络。本文在德国科学研究会项目(DFG)的资助下进行了多流股换热器网络综合方法的研究,主要的进展有以下几个方面: 1)提出了产生初始的近优可行解的有效方法。基于传热过程等有效能损失分布原则的热力学原理提出了一种新的确定流股传热温差贡献值的方法,从而确定流股的虚拟温度—有效温位,在温-焓(T-H)图上构造组合曲线,在分割的焓间隔内进行流股垂直匹配,能够得到合理的网络,原则上实现了有效温位的流股逆流换热,能以很高的概率获得热力学和经济上近优的网络作为初始可行解和进化过程中的逐次优化解。 2)建立了一个新的有效的多流股换热器网络综合数学模型。基于流股有效温位和在T-H图上的垂直匹配法,建立了多流股换热器网络综合NLP数学模型。该模型以流股的传热温差贡献值为网络综合的决策变量,明显地降低了问题的维数,而且不含有0-1变量,采用T-H图上的垂直匹配法解决了复杂的约束问题,进化过程中的解均可行,这一新的换热网络综合模型显著地降低了求解大规模多流股换热器网络综合的复杂性。而且此模型也可以用于求解具有不同传热膜系数和不同换热器材质的网络。 3)大规模多流股换热器网络综合问题的求解。提出了多流股换热器网络初始近优可行解的产生方法,设计了用于多流股换热器网络综合问题的交叉算子、变异算子、保留父代良好信息的OCX算子、多样性保持EC算子,引入了多种群进化机制,提高了遗传算法的搜索能力和计算效率。最后,基于多流股换热网络综合NLP模型,采用改进的遗传/模拟退火算法求解100对100流股分支的大规模多流股换热器网络综合问题,能够得到优化解。更多还原

【Abstract】 Multi-stream heat exchangers are widely used in process industries such as gas processing and petrochemical industries to exchange heat energy among more than two streams because of their higher efficiency, more compact structure and lower cost compare with two-stream heat exchangers. In the last few decades, much research work focused on conventional two-stream heat exchanger networks, while investigation on synthesis of multi-stream heat exchanger network (MSHEN), especially large scale MSHEN, is limited due to its complexity. In this thesis, the studies on synthesis methods of MSHEN are supported by German Research Council Foundation (DFG), and main research improvements are as follows:(1) Bring forward an effective method of generating initial near optimum feasible solution. A new calculation method for stream heat transfer temperature difference contribution value is proposed based on the thermodynamic principle of equal exergy loss distribution. Thereby, stream pseudo-temperature, that is, the stream effective temperature level, is determined, and composite curves are constructed on the T-H diagram, a reasonable feasible network structure is attained by vertical match in enthalpy intervals. In principle countercurrent heat exchange in network is achieved based on the stream effective temperature level, so probability of attainment of near optimum feasible solutions is high and these solutions are original feasible solutions and ordinal optimal solutions in evolution.(2) A new and effective mathematical model is presented for synthesizing MSHEN. A NLP model of MSHEN synthesis is proposed based on the stream effective temperature level. The decision variables of network synthesis in the model are stream heat transfer temperature difference contribution values, hence the number of dimensions is evidently reduced. Moreover, no binary variables exist in the model, the vertical match approach on the T-H diagram can deal with complex constraints and assure all solutions in evolution procedure feasible, so large scale MSHEN synthesis problem complexity is remarkably reduced by using the new NLP model. Furthermore, the model can also be used to solve heat exchanger network problems with unequal heat transfer film coefficients and different construction materials.(3) The problem of large scale MSHEN synthesis is solved. Some improvements of GA(genetic algorithm) are made, for example, design of crossover and mutation operators for synthesizing MSHEN, OCX operator for preserving good paternal information and EC operator for holding the diversities of population individuals. Moreover, the idea of parallel algorithm is introduced to advance the search capability and calculation efficiency of GA. Finally, improved GA/SA is successfully used to solve a large scale MSHEN synthesisproblem including 100*100 splitting streams, and the optimal solution can be attained.更多还原