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Procedure for determining the number of thermal diffusion columns in square cascade for separation of Ne stable isotopes

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Abstract

The thermal diffusion column represents one method of separating stable isotopes. This method is advantageous for small-scale operations because of the simplicity of the apparatus and small inventory, especially in gas-phase operations. Consequently, it has attracted attention for its applicability in tritium and noble gas separation systems. In this study, the R cascade was used to design and determine the number of columns. A square cascade was adopted for the final design because of its flexibility, and calculations were performed to separate 20Ne and 22Ne isotopes. All the R cascades that enriched the Ne isotopes by more than 99% were investigated, the number of columns was determined, and the square cascade parameters were optimized using the specified columns. Additionally, a calculation code “RSQ_CASCADE” was developed. A unit separation factor of three was considered, and the number of studied stages ranged from 10 to 20. The results showed that the column separation power, relative total flow rate, and required number of columns were linearly related to the number of stages. The separation power and relative total flow decreased and the number of columns increased as the stage number increased. Therefore, a cascade of 85 columns is recommended to separate the stable Ne isotopes. These calculations yielded a 17-stage square cascade with five columns in each stage. By changing the stage cut, feed point, and cascade feed flow rate, the best parameters for the square cascade were determined according to the cascade and column separation powers. As the column separation power had a maximum value in cascade feed 50, it was selected for separating Ne isotopes.

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Correspondence to Fatemeh Mansourzadeh.

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Mansourzadeh, F., Shadman, M.M., Sabet, J.K. et al. Procedure for determining the number of thermal diffusion columns in square cascade for separation of Ne stable isotopes. NUCL SCI TECH 34, 68 (2023). https://doi.org/10.1007/s41365-023-01217-z

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  • DOI: https://doi.org/10.1007/s41365-023-01217-z

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