肖武

个人信息Personal Information

副教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:化工学院

学科:化学工程

办公地点:大连理工大学西部校区化工实验楼D-405

联系方式:wuxiao@dlut.edu.cn

电子邮箱:wuxiao@dlut.edu.cn

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A new and efficient NLP formulation for synthesizing large scale multi-stream heat exchanger networks

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论文类型:期刊论文

发表时间:2006-07-01

发表刊物:JOURNAL OF THE CHINESE INSTITUTE OF CHEMICAL ENGINEERS

收录刊物:SCIE、EI

卷号:37

期号:4

页面范围:383-394

ISSN号:0368-1653

关键字:stream heat transfer temperature difference contribution; pseudo-temperature; multi-stream heat exchanger network; nonlinear programming; genetic/simulated annealing algorithm

摘要:The heat exchanger network (HEN) synthesis. problem is generally formulated as a mixed integer nonlinear programming (MINLP) by using the concept of HEN superstructures. Although these MINLP formulations can be used to solve the HEN synthesis problem, the size of the problem of their application is restrained because of their complexity. In this study, a new nonlinear programming (NLP) formulation of the simultaneous model for multi-stream heat exchanger network (MSHEN) synthesis is proposed based on stream pseudo-temperature. This formulation can be used to solve MSHEN synthesis problem with temperature enthalpy (T-H) diagram method based on optimal stream heat transfer temperature difference contributions using genetic/simulated annealing algorithm (GA/SA). A significant reduction on the size and complexity of the problem is achieved by the NLP formulation. Large scale MSHEN synthesis problem with unequal heat transfer film coefficients and different construction materials can be solved using the NLP formulation. The performance and efficiency of the NLP formulation and algorithm are demonstrated through two examples.