中文摘要：

板翅式换热器的通道排列优劣直接影响换热器传热性能和结构的紧凑性等，因此通道排列的优化是设计中的重中之重。传统的板翅式换热器优化设计中，往往是基于一个最大负荷工况点进行通道排列设计，忽略了当工况点变化较大时通道排列对传热性能的影响。但操作工况常常随季节、原料和生产情况的变化而变化，使换热器常常在偏离设计工况点下运行，导致换热效率较低。板翅式换热器的通道排列方案随着流股数成指数增加，且现有的设计方法大多是基于经验确定的，这需要花费设计人员大量的时间对换热器进行不断改进，以使得换热器符合设计要求，同时达到较优的传热效果。针对上述设计不足，运用在变工况下板翅式换热器的通道排列柔性设计的方法，以通道排列累积热负荷最小均方差为目标函数，提出采用遗传算法优化多股流板翅式换热器的通道排列。具体步骤：11运用遗传算法获得各工况点下最优通道排列；2）利用柔性设计方法将以上获得的各工况下的最优通道排列整合成一个较优通道排列，使其在操作周期内以较优的状态工作；3）N用微调策略改进柔性设计通道排列，进一步降低累计热负荷均方差，得到最终的优化通道排列。最后对～个含一股热流体三股冷流体的板翅式换热器通道排列设计案例进行计算得出，采用本文的设计方法得到的最终通道排列在3个工况点下的累计热负荷均方差平均值为3632．48W，较文献值3660．72W低。而且该方法大大提高了设计速度，降低了设计人员的工作量，同时实现了板翅式换热器的柔性优化设计，使换热器能满足全年不同工况的操作要求，证明了该方法的有效性和优越性。

英文摘要：

Optimization of passage arrangement, which directly influence the heat transfer effect and the structure compactness of heat exchanger, is the core problem in the design of plate-fin heat exchanger. In the traditional plate-fin heat exchanger design, the passage arrangement is usually designed at a single maximum load operation point, which ignores the impact of heat transfer when the operation point changes very much. But in fact the operation conditions change along with seasons, raw materials and production circumstances, which usually lows the plate-fin heat exchanger＇s heat transfer when it works at these operation points. The number of the passage arrangement increases exponentially with the increase of fluid number in the plate-fin heat exchanger, so the passage arrangement is determined according to the experiential rule, which needs designers spend a lot of time in repeatedly improving the heat exchanger＇s passage arrangement to comply with the design requirements, and achieve superior heat transfer effect. To overcome this shortcoming, a novel flexible design method was presented in the paper based on flexible design of passage arrangement for multi-stream plate-fin heat exchanger in various conditions. The objective function was the minimum mean-square deviation of accumulative heat load of the passage arrangement, and genetic algorithm （GA） was adopted to attain the optimal passage arrangement. Specific steps： 1） GA was used to achieve the best passage arrangement at every operation point; 2） Flexible design was used to combine the different best passage arrangements to get flexible design passage arrangement which can worked well at all operation points; 3） Fine-tuning strategy was used to improve flexible design channel arrangement to get the final optimal passage arrangement by reducing the mean-square deviation of accumulative heat load. Finally an illustrative example was presented to demonstrate the validity and advantages of the proposed approach, the final passage arrangement?