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Abstract <p>In this paper, an estimated method for determining the cooling capacity of a closed-type nitrogen-helium cryostat is proposed. This problem is solved as a problem of finding the extremum of the calculated values of the heat flow from each stage in each time block under consideration, while minimizing the root-mean-square error between the expected dynamics of the cooling of the stages over the time period under consideration and the calculated dynamics of the cooling. To do this, it is first necessary to solve the “direct” problem of heat transfer of the structure, then find the optimum from the chosen regularization method, iteratively refining the parameters under study. The method of conjugate directions was chosen as the optimization method, as the most accurate method of the first order of convergence. And as a regularization method to overcome the incorrectness in the source data, the iterative regularization method was chosen, where the regularizing parameter is the iteration number.</p>

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Theoretical Determination of the Cold Capacity of the Nitrogen and Helium Stages of a Cyclic Cryostat

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • N. O. Borshchev

摘要

Abstract

In this paper, an estimated method for determining the cooling capacity of a closed-type nitrogen-helium cryostat is proposed. This problem is solved as a problem of finding the extremum of the calculated values of the heat flow from each stage in each time block under consideration, while minimizing the root-mean-square error between the expected dynamics of the cooling of the stages over the time period under consideration and the calculated dynamics of the cooling. To do this, it is first necessary to solve the “direct” problem of heat transfer of the structure, then find the optimum from the chosen regularization method, iteratively refining the parameters under study. The method of conjugate directions was chosen as the optimization method, as the most accurate method of the first order of convergence. And as a regularization method to overcome the incorrectness in the source data, the iterative regularization method was chosen, where the regularizing parameter is the iteration number.