BibTeX
@ARTICLE{
         Shi2024Cmo,
       author = "Min Shi and Tongqiang Shi and Lei Shi and Zhengrong Ouyang and Junjie Li",
       title = "Constrained multi-objective optimization of helium liquefaction cycle",
       journal = "Thermal Science",
       doi = "10.2298/TSCI230626278S",
       url = "https://doi.org/10.2298/TSCI230626278S",
       year = "2024",
       publisher = "Vin\v{c}a Institute of Nuclear Sciences, Belgrade",
       volume = "28",
       number = "4",
       pages = "2777--2790",
       abstract = "The helium cryo-plant is an indispensable subsystem for the application of low
         temperature superconductors in large-scale scientific facilities. However, it is important to note
         that the cryo-plant requires stable operation and consumes a substantial amount of electrical power
         for its operation. Additionally, the construction of the cryo-plant incurs significant economic
         costs. To achieve the necessary cooling capacity while reducing power consumption and ensuring
         stability and economic feasibility, constrained multi-objective optimization is performed using the
         interior point method in this work. The Collins cycle, which uses liquid nitrogen precooling, is
         selected as the representative helium liquefaction cycle for optimization. The discharge pressure of
         the compressor, flow ratio of turbines, and effectiveness of heat exchangers are taken as decision
         parameters. Two objective parameters, cycle exergy efficiency, $\eta_{ex,cycle}$, and
         liquefaction rate, $\dot{m}_L$, are chosen, and the wheel tip speed of turbines and UA of heat
         exchangers are selected as stability and economic cost constraints, respectively. The technique for
         order of preference by similarity to the ideal solution (TOPSIS) is utilized to select the final
         optimal solution from the Pareto frontier of constrained multi-objective optimization. Compared to
         the constrained optimization of $\eta_{ex,cycle}$, the TOPSIS result increases the
         $\dot{m}_L$ by 23.674\%, but there is an 8.162\% reduction in $\eta_{ex,cycle}$.
         Similarly, compared to the constrained optimization of $\dot{m}_L$, the TOPSIS result increases
         the $\eta_{ex,cycle}$ by 57.333\%, but a 10.821\% reduction in $\dot{m}_L$ is
         observed. This approach enables the design of helium cryo-plants with considerations for cooling
         capacity, exergy efficiency, economic cost, and stability. Furthermore, the wheel tip speed and UA
         of heat exchangers of the solutions in the Pareto frontier are also studied.",
       ad_area = "Chemistry",
       ad_tools = "ADiMat"
}