HYSYS中recycle模块质量不守恒
各位炮友，大家好！我在做一个工艺流程模拟时发现recycle模块进出物料质量不守恒，请问高手们都是怎么设置recycle模块，使之守恒的？非常着急，在线等，谢谢大家了！data:image/png;base64,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**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**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**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
谢谢各位炮友的关注，我自已研究出解决方案了。在R模块的Parameters中Sensitivities项，先通过比较粗略（软件默认的是10）的收敛后，再将该数值调小，直至满足自己的精度要求为止。 gaoxuejian2006 发表于 2016-5-7 11:15
谢谢各位炮友的关注，我自已研究出解决方案了。在R模块的Parameters中Sensitivities项，先通过比较粗略（软 ...
您好，我想问一下，我也出现了差不多的问题，就是加了循环之后，相应物流线上的带功率的模型的热负荷都增大了好多，怎么解决啊
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