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首页> 外文学位 >ANALYSIS AND OPTIMIZATION OF HEAT INTEGRATED DISTILLATION SEQUENCES (HEURISTIC, EVOLUTIONARY).
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ANALYSIS AND OPTIMIZATION OF HEAT INTEGRATED DISTILLATION SEQUENCES (HEURISTIC, EVOLUTIONARY).

机译：热集成蒸馏序列（启发式，进化式）的分析和优化。

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This work proposes a heuristic-evolutionary method to optimize heat-integrated distillation sequences. The key to this method is the use of a quantitative measure which evaluates the Overall Difficulty of Separation for a separation problem (ODOS). ODOS is defined as ODOS = (Q/dt)/F where Q is the condenser duty in the column, dt is the temperature difference between the condenser and reboiler and F is a factor, proposed by Nadgir and Liu (1983), which reflects the balance between the top and bottom products. F is defined as F = Min (V/L, L/V) where V and L are respectively the amounts of the top and bottom products.; The ODOS, developed in this work, not only enabled selection of a good upper bound for the cost of the 'optimal' sequence, but allowed prediction of a band of 'good' sequences for the problems considered in this work. This quantitative measure was also successful in eliminating the non-competitive sequences from further consideration. The selection of a band of sequences enables the designer to choose the sequence for actual implementation from objectives other than economics, like ease of control, plant layout, etc. The method involves no intermediate evaluation of the candidate sequences, unlike traditional evolutionary methods.; This work has also confirmed the decomposition principle of Sophos et al (1981, 1982), which stated that the separation sequencing problem should be tackled first and then heat integration should be attempted for the 'good' sequences identified.; This method was tested by calculating the costs for each sequence with and without integration for seven of the nine examples considered in this work. For the other two examples, as well as for the first seven examples, values reported in the literature were used to assess this method.; This method has also been compared with the standard heuristic methods in the literature. This method compares very favorably with the literature methods in terms of locating a good initial sequence, identifying competitive sequences, eliminating non-competitive sequences and providing a quantitative measure for the competitiveness of a sequence.
机译：这项工作提出了一种启发式进化方法来优化热集成蒸馏序列。该方法的关键是使用定量方法来评估分离问题（ODOS）的总体分离难度。 ODOS的定义为ODOS =（Q / dt）/ F，其中Q是塔中的冷凝器负荷，dt是冷凝器和再沸器之间的温差，F是一个因数，由Nadgir和Liu（1983）提出，反映了顶部和底部产品之间的平衡。 F定义为F ＝ Min（V / L，L / V），其中V和L分别是上乘积和下乘积的量。在这项工作中开发的ODOS，不仅可以为“最佳”序列的成本选择一个好的上限，而且还可以为该工作中考虑的问题预测“好的”序列的范围。这种定量方法也成功地消除了非竞争性序列，无需进一步考虑。序列带的选择使设计人员能够从经济以外的目标（例如易于控制，工厂布局等）中选择要实际实施的序列。与传统的进化方法不同，该方法不涉及候选序列的中间评估。这项工作还证实了Sophos等人（1981，1982）的分解原理，该原理指出，应该先解决分离测序问题，然后再对鉴定出的“好”序列进行热整合。通过计算此工作中考虑的9个示例中的7个示例的每个序列在有无集成的情况下的成本来测试该方法。对于其他两个示例以及前七个示例，文献中报道的值用于评估该方法。该方法也已与文献中的标准启发式方法进行了比较。该方法在定位良好的初始序列，鉴定竞争序列，消除非竞争序列以及为序列竞争性提供定量度量方面，与文献方法相比非常有利。

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