Abstract Gas liquefaction is one of the main applications of cryogenics science. Due to the unique properties of Helium, it can be used for several important applications. Therefore, appropriate and applicable analysis should be used to investigate and optimize the Helium liquefaction cycles. In the current study, the focus will be identifying the optimal point of the Collins’ cycle by performing energy and exergy analysis based on economic criterion. In order to simulate the cycle, a computer code is developed. Firstly, sensitivity analysis of different parameters affecting exergy efficiency and liquid fraction of the cycle has been done. Secondly, Artificial Neural Network and Genetic Algorithm is used to reach the optimal point of the cycle. The results indicate that a Collins’ cycle with 4 stages of pre-cooling in the cold-box section has the maximum exergy efficiency of 40.32%, maximum liquid fraction of 9.98%, and maximum economic profitability of 36 million dollars. These values are 60%, 50% and 40% greater compared to a Collins’ cycle with 2 stages of pre-cooling.

中文翻译：

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研究和优化氦气液化器的经济方法

摘要 气体液化是低温科学的主要应用之一。由于氦气的独特特性，它可用于多种重要应用。因此，应使用适当和适用的分析来调查和优化氦液化循环。在当前的研究中，重点将是通过基于经济标准进行能量和火用分析来确定柯林斯循环的最佳点。为了模拟循环，开发了计算机代码。首先，对影响火用效率和循环液体分数的不同参数进行了敏感性分析。其次，利用人工神经网络和遗传算法达到循环的最佳点。结果表明，在冷箱段采用4级预冷的柯林斯循环的最大火用效率为40.32%，最大液体分数为9.98%，最大经济利润为3600万美元。与具有 2 个预冷阶段的柯林斯循环相比，这些值分别高出 60%、50% 和 40%。