An economic approach to study and optimize helium liquefier. (September 2020) - Mahmoudabadbozchelou, Mohammadamin; Larijani, Morteza Ardeshir; Afshin, Hossein
Highlights: Collins' Cycle which is the foundation of industrial plants is selected for this study. A computer code is developed to simulate the cycle based on the number of cooling stages. Relation between exergy efficiency and input parameters is functionalized using ANN. Genetic Algorithm is utilized to find the optimal working condition of the cycle. Collins' cycle with 4 expanders has the maximum economic profitability of 36M dollars. Increasing number of expanders from 2 to 4 leads to a 40% growth in economic profitability. 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.