摘要
为简化大型氦液化流程的优化过程,采用遗传算法,以液化率为目标,针对带液氮预冷的柯林斯(Collins)氦液化循环进行了优化。优化结果表明,利用遗传算法(GA)可以在给定的优化参数的范围内进行全局寻优,证明了遗传算法在流程设计过程中具有重要的预优化作用。此外还得出了换热器最小允许温差与液化率的关系曲线。
In order to simplify the optimization and analysis of the large helium liquefaction cycle,genetic algorithm（ GA） was adopted in characteristics optimization Collins helium liquefaction cycle with nitrogen pre-cooling,the global solution was searched given parameter to get the maximum liquefaction rate. GA is proved to be applicable for optimization of the cryogenic process. The relation curve of liguefaction rate and temperature difference in heat exchanger hot end was plotted,which shows a decreased liguefaction rate with increasing the temperature difference.
出处
《低温工程》
CAS
CSCD
北大核心
2015年第6期21-25,共5页
Cryogenics
关键词
氦液化
遗传算法
经济效益
process optimization
genetic algorithm
economic benefits
