Optimization design method of ultralow-temperature multi-load heat insulation support, support assembly and experiment research method

Abstract

The invention provides an optimal design method of an ultralow-temperature multi-load heat insulation support, a support assembly and an experimental research method, and relates to the field of large superfluid helium low-temperature distribution systems. Comprising the following steps: selecting thickness parameters of a casing pipe in each stage of temperature zone of a supporting assembly and a supporting panel as optimization design parameters to carry out parametric modeling, and introducing a stress maximum value and a heat leakage value as target values; and based on the thickness parameters of the cold shield sleeve and the supporting panel of each stage of temperature zone, taking a genetic algorithm as an optimization function, performing iterative calculation in combination with simulation software, obtaining the thickness parameters of the cold shield sleeve and the supporting panel under the optimal boundary, determining the heat leakage value and the maximum stress value of the supporting assembly according to the optimal boundary, and then processing the supporting assembly. By combining various simulation technical means and experimental research, the problems of poor performance of the support assembly, lack of process verification and the like caused by the adoption of a classic model are solved, and the rigidity and robustness of the large-scale superfluid helium transmission and distribution system are effectively optimized and improved.

Description

Technical Field

[0001] The present invention relates to the field of large-scale superfluid helium cryogenic distribution system, and in particular to an optimization design and experimental research method of a super-low temperature multi-load insulation support. Background Art

[0002] With the rapid development of large-scale superconducting accelerator technology, as a large-scale superfluid helium cryogenic system that cools the superconducting cavity of the superconducting accelerator and maintains the superconducting environment of the superconducting cavity, its distribution and transmission system requires strict control of external heat intrusion into the cold helium medium being transported, and is required to bear multi-physical field loads such as pipeline internal pressure, fluid-solid coupling, and large-span thermal stress to ensure the overall stiffness of the transportation system. For the distribution and transmission system, the insulation support is a core component. Each superconducting accelerator laboratory has developed and designed insulation support components and successfully used them in the research and development and construction of the cryogenic distribution system. In 2015, a laboratory published an accident report on the failure of the expansion joint in its distribution and transmission system, and pointed out that when considering the support design, it is necessary to consider the mechanical load after the pressure expansion joint is broken to avoid the failure of the support component, resulting in the failure of the cryogenic distribution system, and then leading to the failure of the refrigerator system. At present, the design and development of the insulation support in the large-scale superfluid helium cryogenic distribution system is still based on the classic model explored by foreign laboratories, combined with its own system layout for micro-adjustment, lacking the optimal method research that comprehensively considers the heat leakage and strength performance, and there is no relevant experimental research and data support. Summary of the invention

[0003] The present invention provides an optimization design method for an ultra-low temperature multi-load insulation support, which is used to solve the problem that the prior art lacks research on the optimal method for comprehensively considering heat leakage and strength performance, and there is no relevant experimental research and data support.

[0004] The present invention provides an optimization design method for an ultra-low temperature multi-load insulation support, comprising: Step S100, selecting the thickness of the casing of each temperature zone of the support assembly and the thickness parameters of the support panel as optimization design parameters for parameterized modeling, and introducing the maximum stress value and the heat leakage value as target values; Step S200, based on the thickness parameters of the casings in each temperature zone and the support panel, a genetic algorithm is used as an optimization function, and iterative calculation is performed in combination with simulation software to obtain the thickness parameters of the casings in each temperature zone and the support panel under the optimal boundary, and obtain the heat leakage value under the optimal boundary and the maximum stress value of the support assembly; Step S300, the support assembly is processed according to the thickness parameters of the casings in each temperature zone and the thickness parameters of the support panel under the obtained optimal boundary.

[0005] According to an optimization design method for ultra-low temperature multi-load insulation support provided by the present invention, step S200 comprises: Use MATLAB software as the host software to write the algorithm program of the genetic algorithm module; In the process of constructing the objective function, the thickness of the casing at each temperature zone and the thickness parameters of the support panel output by the parametric modeling are used as independent variables to perform parameter variables for optimization iteration; Taking the heat leakage value and the maximum stress of the support assembly as target values ​​for minimization optimization; The NSGA-II algorithm in the MATLAB software is retrieved, and the target value is analyzed according to the target function and the optimization simulation calculation is driven; ANSYS Workbench is used as a modeling and simulation calculation and solving platform. The independent variables selected by the genetic algorithm are parametrically modeled through Spaceclaim. After the model modeled by the SpaceClaim module is input into Steady-State Thermal, the calculation results are transmitted to Static Structural to complete the simulation calculation based on temperature analysis and comprehensive stress range, and the heat leakage value and the maximum stress value of the support component are obtained. The MATLAB software captures the calculation results of ANSYS Workbench and makes judgments, and finally gives the Pareto optimal frontier solution set.

[0006] According to an optimization design method for ultra-low temperature multi-load insulation support provided by the present invention, before the step of calling the NSGA-II algorithm in the MATLAB software to analyze the target value according to the objective function and drive the optimization simulation calculation, it also includes: A data transmission interface between the MATLAB software and the ANSYS Workbench is written in the MATLAB software to realize coupled simulation between the MATLAB software and the ANSYS Workbench.

[0007] According to an optimization design method for ultra-low temperature multi-load insulation support provided by the present invention, the genetic algorithm is the NSGA-II genetic algorithm, and the simulation software is the finite element simulation software.

[0008] The present invention also provides a support assembly, which is manufactured based on the optimization design method of the ultra-low temperature multi-load insulation support described in any one of the above items.

[0009] The present invention also provides an experimental research method for ultra-low temperature multi-load insulation support, comprising: Step S100a, during the process of processing the support component, a temperature sensor and a strain gauge are arranged to detect the support component; Step S200a, designing an experimental process based on the superfluid helium cryogenic distribution system used by the support assembly, using liquid helium and superfluid helium as experimental working fluids; Step S300a, connecting the experimental platform built based on the experimental process to the superfluid helium cryogenic system, and performing low-temperature testing according to the experimental process.

[0010] According to an experimental research method for ultra-low temperature multi-load insulation support provided by the present invention, step S100a includes: Based on the simulation calculation results, a strain gauge is arranged at a position where the stress of the support component is relatively large, and a temperature sensor is arranged near the strain gauge to obtain a strain-temperature response at the position where the strain gauge is arranged; When installing the strain gauge, the strain gauge is fixed by a processing tool, and the colloid bonding the strain gauge and the support assembly is cured by a constant temperature box to ensure the tightness between the strain gauge and the point to be measured; A metal cold shield is arranged around the temperature sensor to prevent the temperature sensor from generating measurement errors due to heat radiation.

[0011] According to an experimental research method for ultra-low temperature multi-load insulation support provided by the present invention, step S200a includes: A Wheatstone quarter bridge was used for strain acquisition; During the experiment, a slow cooling strategy was adopted to ensure that the support assembly could be fully cooled.

[0012] According to an experimental research method for ultra-low temperature multi-load insulation support provided by the present invention, the maximum cooling capacity provided by the superfluid helium low temperature distribution system is 1000W@4.5K.

[0013] According to an experimental research method for ultra-low temperature multi-load insulation support provided by the present invention, the output end of the temperature sensor and the output end of the strain gauge are both connected to a local industrial computer.

[0014] The optimization design method and experimental research method of the ultra-low temperature multi-load insulation support provided by the present invention select the thickness of the sleeves in each temperature zone of the support component and the thickness parameters of the support panel as the optimization design parameters for parametric modeling, construct the maximum stress value and the heat leakage value as the final optimization target, and use finite element simulation and NSGA-II genetic algorithm as optimization means to realize the coupling simulation of the MATLAB software and ANSYS Workbench. The method utilizes the high accuracy of finite element calculation and the multi-objective optimization characteristics of genetic algorithm to obtain the Pareto optimal frontier solution set and the optimal set of parameters to be optimized. By selecting the optimal model for prototype processing and designing the experimental research method, the closed loop of experimental verification is completed. The optimization design method and experimental research method of the ultra-low temperature multi-load insulation support provided by the present invention effectively consider the performance of the insulation support component under the multi-physical field boundary, provide the optimal support structure suitable for large-scale superfluid helium transmission and distribution system, and provide an experimental verification scheme and method. By combining a variety of simulation techniques and experimental research, the problems of poor support component performance and lack of process verification caused by the use of classical models were compensated, and the stiffness and robustness of the large-scale superfluid helium transport and distribution system were effectively optimized and improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 It is a schematic flow chart of the optimization design method of the ultra-low temperature multi-load insulation support provided by the present invention.

[0017] Figure 2 It is a schematic flow chart of the experimental research method of ultra-low temperature multi-load insulation support provided by the present invention.

[0018] Figure 3 It is a phase diagram of the pipeline constrained by the insulation support assembly provided by the present invention.

[0019] Figure 4 It is one of the structural schematic diagrams of the thermal insulation support assembly provided by the present invention.

[0020] Figure 5 This is the second structural schematic diagram of the thermal insulation support assembly provided by the present invention.

[0021] Figure 6 It is a schematic flow chart of a specific optimization design method for ultra-low temperature multi-load insulation support provided by the present invention.

[0022] Figure 7 It is the Pareto front solution set of the left and right structures of the thermal insulation support assembly provided by the present invention under the design working condition.

[0023] Figure 8 It is a principle diagram of an experiment using a 1 / 4 Wheatstone bridge provided by the present invention.

[0024] Fig. 9 It is a schematic diagram of the connection relationship between a large-scale superfluid helium cryogenic distribution system and an insulating support component experimental platform provided by the present invention.

[0025] Reference numerals: 6. Support panel; 7. Support assembly 75K cold screen return air duct perforation; 8. Support assembly outer cold screen welding ring; 9. Support assembly outer cold screen; 10. Support assembly inner cold screen; 11. Support assembly inner and outer cold screen welding rings; 12. 4.5K air supply duct casing cold screen welding ring; 13. 4.5K air supply duct casing cold screen; 14. 75K coupler return air duct casing cold screen; 15. 75K coupler return air duct casing cold screen welding ring; 16. 50K cold screen air supply duct casing cold screen; 17. 50K cold screen air supply duct casing cold screen welding ring; 18. 2K return air duct Casing cold shield; 19, 2K return air pipeline casing cold shield welding ring; 20, measured resistance strain gauge; 21, first fixed resistor; 22, adjustable resistor; 23, second fixed resistor; 24, replacement return air pipeline; 25, safety valve return air pipeline; 26, experimental platform interlayer vacuum pipeline; 27, 75K cold shield return air pipeline; 28, 50K cold shield air intake pipeline; 29, 4.5K supercritical helium gas delivery pipeline; 30, 2K return air pipeline; 31, 75K coupler return air pipeline; 32, first vacuum pump group; 33, vacuum plug valve; 34, second vacuum pump group; 35 , first temperature sensor; 36, second temperature sensor; 37, third temperature sensor; 38, fourth temperature sensor; 39, fifth temperature sensor; 40, vacuum connector assembly; 41, vacuum silicon; 42, first normal temperature valve; 43, first safety valve; 44, first bursting disc; 45, negative pressure protection integrated device; 46, second safety valve; 47, second bursting disc; 48, second normal temperature valve; 49, third normal temperature valve; 50, fourth normal temperature valve; 51, third safety valve; 52, third bursting disc; 53, fourth safety valve; 54, fourth bursting disc; 55, first Cryogenic valve; 56. One-way valve; 57. Mass flow meter; 58. Second cryogenic valve; 59. Third cryogenic valve; 60. Fourth cryogenic valve; 61. Helium pool; 62. Sixth temperature sensor; 63. 4.5K liquid helium level gauge; 64. 2K superfluid helium level gauge; 65. DC power heater; 66. Seventh temperature sensor; 67. Eighth temperature sensor; 68. Ninth temperature sensor; 69. Tenth temperature sensor; 70. Support assembly; 71. Experimental platform cold screen; 72. Experimental platform vacuum cover; 73. Eleventh temperature sensor group; 74. Fifth safety valve. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] In the description of the embodiments of the present invention, it should be noted that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limitations on the embodiments of the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0028] In the description of the embodiments of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific circumstances.

[0029] In the embodiments of the present invention, unless otherwise clearly specified and limited, the first feature being "above" or "below" the second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, the first feature being "above", "above" and "above" the second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0030] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0031] like Figure 1 As shown in the figure, the optimization design method of ultra-low temperature multi-load insulation support includes: Step S100, selecting the thickness of the casing of each temperature zone of the support assembly 70 and the thickness parameters of the support panel 6 as optimization design parameters for parameterized modeling, and introducing the maximum stress value and the heat leakage target value; Step S200, based on the thickness of the casing in each temperature zone and the thickness parameters of the support panel 6, the genetic algorithm is used as the optimization function, and the simulation software is combined to perform iterative calculations to obtain the thickness of the casing in each temperature zone and the thickness parameters of the support panel under the optimal boundary, and obtain the heat leakage value under the optimal boundary and the maximum stress of the support assembly 70; Specifically, the genetic algorithm is the NSGA-II genetic algorithm, and the simulation software is the finite element simulation software.

[0032] Step S300 , the support assembly 70 is processed according to the obtained thickness parameters of the casings in each temperature zone and the thickness parameters of the support panel under the optimal boundary.

[0033] The optimization design method and experimental research method of the ultra-low temperature multi-load insulation support provided by the present invention select the thickness of the sleeves in each temperature zone of the support assembly 70 and the thickness parameters of the support panel 6 as the optimization design parameters for parametric modeling, construct the maximum stress value and the heat leakage value as the final optimization target, and use finite element simulation and NSGA-II genetic algorithm as optimization means to realize the coupling simulation of the MATLAB software and ANSYS Workbench. The method uses the high accuracy of finite element calculation and the multi-objective optimization characteristics of genetic algorithm to obtain the Pareto optimal frontier solution set and the optimal set of parameters to be optimized. By selecting the optimal model for prototype processing and designing experimental research methods, a closed loop of experimental verification is completed. The optimization design method and experimental research method of the ultra-low temperature multi-load insulation support provided by the present invention effectively consider the performance of the insulation support assembly 70 under the multi-physical field boundary, provide the optimal support structure suitable for large-scale superfluid helium transmission and distribution systems, and provide experimental verification schemes and methods. By combining a variety of simulation techniques and experimental research, the problems of the lack of support component 70 performance and lack of process verification caused by the use of classical models are compensated, and the stiffness and robustness of the large-scale superfluid helium transmission and distribution system are effectively optimized and improved.

[0034] In one embodiment of the present invention, ANSYS Workbench is used as a modeling and subsequent simulation calculation and solving platform during the parametric modeling process, and the SpaceClaim module is used as the modeling software. For a typical thin-walled structural component such as the support component 70, a Shell unit is used instead of an entity, and the Shell unit is set in the later solver, and the parametric modeling interface is opened. The assignment of the Shell unit can be modified at any time to complete the parametric modeling.

[0035] It should be noted here that the thickness of the casing in each temperature zone includes the thickness of the outer cold screen 9 of the support assembly, the thickness of the inner cold screen 10 of the support assembly, the thickness of the 4.5K air supply pipe casing cold screen 13, the thickness of the 75K coupler return air pipe casing cold screen 14, the thickness of the 50K cold screen air supply pipe casing cold screen 16, and the thickness of the 2K return air pipe casing cold screen 18.

[0036] like Figure 3 and Figure 4 As shown, the outer cold shield welding ring 8 of the support assembly is connected to the pipeline, and the outer boundary of the outer cold shield welding ring 8 of the support assembly is 300K, one end of the inner cold shield 10 of the support assembly is provided with the inner and outer cold shield welding rings 11 of the support assembly, one end of the 4.5K air supply pipe casing cold shield 13 is provided with a 4.5K air supply pipe casing cold shield welding ring 12, and the thermal boundary is 4.5K, one end of the 75K coupler return air pipe casing cold shield 14 is provided with a 75K coupler return air pipe casing cold shield welding ring 15, and the thermal boundary is 75K, one end of the 50K cold shield air supply pipe casing cold shield 16 is provided with a 50K cold shield air supply pipe casing cold shield welding ring 17, and the thermal boundary is 50K, one end of the 2K return air pipe casing cold shield 18 is provided with a 2K return air pipe casing cold shield welding ring 19, and the thermal boundary is 2K, and the thermal boundary of the 75K cold shield return air pipe perforation 7 of the support assembly is 75K. The support assembly 70 is connected to five low-temperature pipes through the support assembly inner and outer cold shield welding rings 11, the 4.5K air supply pipe casing cold shield welding ring 12, the 75K coupler return air pipe casing cold shield welding ring 15, the 50K cold shield air supply pipe casing cold shield welding ring 17 and the 2K return air pipe casing cold shield welding ring 19.

[0037] Furthermore, there are three types of thermal resistance in the multi-channel pipeline of the superfluid helium cryogenic distribution system, namely, thermal conduction resistance, thermal radiation resistance and convection resistance. Indicates that thermal radiation resistance is The convection thermal resistance is expressed as Indicates that the total thermal resistance The relationship with the above three thermal resistances can be expressed by the following formula (1); (1); Thermal resistance It can be expressed by the following formula (2); (2); in, is the length of the heat flow path, is the cross-sectional area through which the heat flows, is the thermal conductivity of the material. From the above formula (2), it can be seen that the thermal resistance To maximize the value of and reduce During the design phase, Set to the maximum value required by the space and overall design. is the cross-sectional area of ​​the support assembly outer cold shield 9, the support assembly inner cold shield 10, the 4.5K air supply pipe casing cold shield 13, the 75K coupler return air pipe casing cold shield 14, the 50K cold shield air supply pipe casing cold shield 16 and the 2K return air pipe casing cold shield 18. It can be seen from the above formula (2) that to obtain the maximum , the pipe walls of the support component outer cold shield 9, the support component inner cold shield 10, the 4.5K air supply pipe casing cold shield 13, the 75K coupler return air pipe casing cold shield 14, the 50K cold shield air supply pipe casing cold shield 16 and the 2K return air pipe casing cold shield 18 need to be as thin as possible.

[0038] Cross-sectional area through which heat flows It can be expressed by the following formula (3); (3); in, The outer diameters of the support assembly outer cold shield 9, the support assembly inner cold shield 10, the 4.5K air supply pipe casing cold shield 13, the 75K coupler return air pipe casing cold shield 14, the 50K cold shield air supply pipe casing cold shield 16 and the 2K return air pipe casing cold shield 18, It is the inner diameter of the support component outer cold screen 9, the support component inner cold screen 10, the 4.5K air supply pipe casing cold screen 13, the 75K coupler return air pipe casing cold screen 14, the 50K cold screen air supply pipe casing cold screen 16 and the 2K return air pipe casing cold screen 18.

[0039] Thermal resistance It can be expressed by the following formula (4); (4); in, is the emissivity of the casing surface at each temperature zone of the support assembly 70, is the Boltzmann constant, is the absolute temperature of the outer surface of the two temperature zone casings that generate thermal radiation heat exchange. In the design process of the support assembly 70, multiple layers of insulation material are attached to the surface of the temperature zone casings of each level of the support assembly 70. It can be seen from the above formula (4) that as long as Small enough, It can be considered to be large enough to ignore thermal radiation. When the multi-channel pipelines of the low-temperature distribution system are working, the interior is in a high vacuum state, and the air molecules change from a continuous flow state to a molecular flow.

[0040] Convection thermal resistance It can be expressed by the following formula (5); (5); in, is the flow heat transfer coefficient. It can be seen from the above formula (5) that as long as Small enough that the thermal resistance It can be considered large enough to ignore heat convection.

[0041] Furthermore, the support assembly 70 bears the pipe gravity, thermal stress and some visible moments. The stress on the support assembly 70 can be expressed by formula (6); (6); It can be seen from the above formula (6) that the stress on the support assembly 70 is By external force and cross-sectional area Therefore, when designing the support assembly 70, it is necessary to increase the cross-sectional area as much as possible. , to reduce the stress on the support assembly 70 , ensuring the safety of the support assembly 70.

[0042] Furthermore, the support assembly outer cold shield welding ring 8, the support assembly inner and outer cold shield welding ring 11, the 4.5K air supply pipe casing cold shield welding ring 12, the 75K coupler return air pipe casing cold shield welding ring 15, the 50K cold shield air supply pipe casing cold shield welding ring 17 and the 2K return air pipe casing cold shield welding ring 19 will continuously transfer stress to the surrounding structures when connecting the corresponding low-temperature pipes and cold shields. The relevant dimensions have been set according to the existing process plan to dilute the stress gradient, avoid stress concentration, and destroy the stable structure of the support assembly 70.

[0043] Furthermore, the support panel 6 acts as a load-bearing and cold anchor. If the support panel 6 is too thick, the heat load of the 75K cold screen return air duct 27 will be increased. If it is too thin, it will not be able to withstand the loads from the cold screen welding ring 8 outside the support component, the cold screen welding rings 11 inside and outside the support component, the 4.5K air supply duct casing cold screen welding ring 12, the 75K coupler return air duct casing cold screen welding ring 15, the 50K cold screen supply air duct casing cold screen welding ring 17 and the 2K return air duct casing cold screen welding ring 19, thereby destroying the stable structure of the support component 70.

[0044] In one embodiment of the present invention, step S200 includes: Step S210, using MATLAB software as the host software to write the algorithm program of the genetic algorithm module; Step S220, in the process of constructing the objective function, the thickness parameters of the casings in each temperature zone and the thickness parameters of the support panel output by the parametric modeling are used as independent variables to perform parameter variables for optimization iteration; Step S230, taking the heat leakage value and the maximum stress of the support assembly as the target value of minimization optimization; Step S240, calling the NSGA-II algorithm in the MATLAB software to analyze the target value according to the objective function and drive the optimization simulation calculation; Step S250, using ANSYS Workbench as a modeling and simulation calculation platform, parametric modeling is performed on the independent variables selected by the genetic algorithm through Spaceclaim, and the model completed by the SpaceClaim module is input to Steady-State Thermal. The calculation result is transmitted to Static Structural to complete the simulation calculation based on temperature analysis and comprehensive stress range, and the heat leakage value and the maximum stress value of the support component are obtained; Step S260, MATLAB software captures the calculation results of ANSYS Workbench and makes judgments, and finally gives the Pareto optimal frontier solution set.

[0045] Furthermore, the thickness of the support assembly outer cold screen 9, the support assembly inner cold screen 10, the 4.5K air supply duct casing cold screen 13, the 75K coupler return air duct casing cold screen 14, the 50K cold screen air supply duct casing cold screen 16, the 2K return air duct casing cold screen 18, and the support panel 6 are taken as parameters to be optimized, and the maximum stress value and heat leakage value of the support assembly 70 are introduced as design target values.

[0046] Furthermore, if Figure 7 As shown, the key to the optimization design method of the ultra-low temperature multi-load insulation support is to introduce the NSGA-II genetic algorithm, iteratively calculate the optimization parameters, and determine the maximum stress of the support component 70 as the Pareto optimal frontier boundary of the target value of the minimization optimization.

[0047] Furthermore, if Figure 3 As shown, the heat leakage includes five parts, namely, the heat leakage generated by the 4.5K supercritical helium gas supply pipeline 29, the 50K cold shield air intake pipeline 28, the 75K cold shield air return pipeline 27, the 75K coupler air return pipeline 31, and the 2K air return pipeline 30, so the optimization objective functions are 6 in total.

[0048] Furthermore, if Figure 6 As shown, MATLAB software is used as the iteration platform of NSGA-II genetic algorithm, and ANSYS is used as the algorithm platform for multi-physics field calculation.

[0049] The basic idea of ​​NSGA-II genetic algorithm includes the following steps: First, randomly generate an initial population and calculate multiple objective function values ​​for each individual. Secondly, the population is non-dominated sorted according to the dominance relationship and divided into different levels (non-dominated frontier). Within each level, the diversity of the population is maintained by calculating the crowding distance. Next, a binary tournament selection method based on level and crowding distance is used to select individuals from the population for crossover and mutation operations to generate new individuals. The parent population and the child population are merged, and the merged population is re-sorted, and the first N individuals are selected as the new parent population. By repeating the steps of non-dominated sorting, crowding distance calculation, selection, crossover and mutation, and environmental selection until the termination condition (such as reaching the maximum number of generations or convergence conditions) is met, the Pareto Front is finally output as the result of multi-objective optimization. NSGA-II realizes the selection and balance of advantages and disadvantages in multi-objective optimization through the combination of non-dominated sorting and crowding distance, and ensures the diversity and distribution of the population.

[0050] The basic idea of ​​ANSYS for multi-physics field calculation is to perform parametric modeling on the parameters to be optimized, use the finite element method to iteratively calculate the parameterized model, and output the calculated maximum stress value and five heat leakage values ​​of the support component 70 to the interface code for NSGA-II driven iteration in MATLAB software, and generate the next generation of values ​​of the parameters to be optimized, which are then sent back to ANSYS for finite element calculation until the conditions of NSGA-II are met.

[0051] In one embodiment of the present invention, before calling the NSGA-II algorithm in the MATLAB software to analyze the target value according to the objective function and drive the optimization simulation calculation, it also includes: Write the data transfer interface between MATLAB software and ANSYS Workbench in MATLAB software to realize the coupled simulation between MATLAB software and ANSYS Workbench, so that MATLAB software can retrieve models or data from ANSYS Workbench.

[0052] The present invention further provides a support assembly 70, which is manufactured based on the optimization design method of the ultra-low temperature multi-load insulation support described in any of the above embodiments.

[0053] like Figure 2 As shown, the present invention also provides an experimental research method for ultra-low temperature multi-load insulation support, and the experimental research method for ultra-low temperature multi-load insulation support includes: Step S100a, during the process of processing the support assembly 70, a temperature sensor and a strain gauge are arranged to detect the support assembly 70; Step S200a, designing an experiment based on the superfluid helium cryogenic distribution system used by the support assembly 70, using liquid helium and superfluid helium as experimental working fluids; Step S300a, connecting the experimental platform built based on the experimental process to the superfluid helium cryogenic system, and performing low-temperature testing according to the experimental process.

[0054] In one embodiment of the present invention, step S100a includes: Step S110a, based on the simulation calculation results, a strain gauge is arranged at a position of the support assembly 70 where the stress is relatively large, and a temperature sensor is arranged near the strain gauge to obtain a strain-temperature response at the position where the strain gauge is arranged; Step S120a, when installing the strain gauge, use a processing tool to fix the strain gauge, and use a constant temperature box to cure the colloid bonding the strain gauge and the support assembly 70 to ensure the tightness between the strain gauge and the point to be measured; Step S130a, placing a metal cold shield around the temperature sensor to prevent the temperature sensor from generating measurement errors due to heat radiation.

[0055] In one embodiment of the present invention, step S200a includes: Step S210a, using a Wheatstone quarter bridge to collect strain; Step S220a: During the experiment, a slow cooling strategy is adopted to ensure that the support assembly 70 can be sufficiently cooled.

[0056] Furthermore, if Figure 8 As shown, a quarter Wheatstone bridge is used for the experiment, and the quarter bridge circuit includes a resistive strain gauge 20 to be measured, a first fixed resistor 21 , an adjustable resistor 22 and a second fixed resistor 23 .

[0057] Furthermore, the first fixed resistor 21, the adjustable resistor 22 and the second fixed resistor 23 constitute the acquisition part of the 1 / 4 bridge loop, which is packaged in a strain acquisition card and is powered by a computer's 3.3V built-in power supply.

[0058] Furthermore, the ANSYS calculation cloud diagram of the optimal support assembly 70 arranges strain gauges and temperature sensors at locations with greater stress to obtain a dynamic strain curve of the cooling process during the experiment.

[0059] In one embodiment of the present invention, a large-scale superfluid helium cryogenic distribution system currently in operation online is selected as the cold source parent system for experiments. The maximum cooling capacity provided by the superfluid helium cryogenic distribution system is 1000W@4.5K (150W@2K) to provide a stable low-temperature experimental environment.

[0060] In one embodiment of the present invention, the output end of the temperature sensor and the output end of the strain gauge are both connected to the local industrial computer. The temperature sensor and the strain gauge both use a built-in constant current power supply as the power output of the acquisition card, and a ground wire is laid to isolate electromagnetic interference.

[0061] Furthermore, relying on the process characteristics of the parent system, the experimental platform, experimental process and transfer scheme are designed. The support assembly 70 is encapsulated in a low-temperature distribution valve box for actual working environment. The 75K cold screen return air pipeline 27, the 50K cold screen air intake pipeline 28, the 4.5K supercritical helium gas delivery pipeline 29, the 2K return air pipeline 30, and the 75K coupler return air pipeline 31 are all connected to the upstream refrigerator system. The refrigerator system can provide the working pressure and temperature required by the above pipeline design. It is an existing commonly used refrigeration system and will not be described in detail here. Furthermore, if Figure 8 As shown, since a large number of temperature sensors, flow meters, heaters, liquid level meters, etc. are arranged, the above sensors cooperate with each other to provide a stable flow rate and obtain key parameters, providing high-precision experimental conditions for experimental research of the support assembly 70; Furthermore, by using LabView for experimental data acquisition, the measured resistive strain gauge and power supply After connecting to the strain acquisition card, adjust the value of the variable resistor so that The value of is 0. After the temperature drops, the measured resistance strain gauge begins to strain due to the external force. The value is not 0. At this time, the strain acquisition card will convert the voltage signal into a strain signal. In this embodiment, the strain gauge is triaxial, the angle between two adjacent gauges is 45°, and the strain signal in the 0° direction is , the strain signal in the 45° direction is , the strain signal in the 90° direction is After the background temperature error of the strain gauge itself is subtracted from the strain signals of the above three axes, the stress is calculated according to the von Mises fourth strength theory formula, that is, the following formula (7), to evaluate the mechanical properties of the support component.

[0062] (7); in, is Young's modulus, is Poisson's ratio, is the maximum principal stress.

[0063] like Fig. 9As shown, the experimental platform cold shield 71 , the vacuum silicon 41 , and the eleventh temperature sensor group 73 are all arranged inside the experimental platform vacuum cover 72 , and the sixth temperature sensor 62 is arranged in the helium pool 61 . The experimental platform interlayer vacuum evacuation pipeline 26 is connected to the experimental platform vacuum cover 72, the safety valve return air pipeline 25 is connected to the pipeline between the second cryogenic valve 58 and the tenth temperature sensor 69 through the first pipeline, and the first pipeline is provided with a first safety valve 43 and a first bursting disc 44; the safety valve return air pipeline 25 is connected to the helium pool 61 through the second pipeline, and the second pipeline is provided with a negative pressure protection integrated device 45, the second bursting disc 47 is connected to the negative pressure protection integrated device 45 through the fifth safety valve 74, and the second safety valve 46 is arranged inside the negative pressure protection integrated device 45; the safety valve return air pipeline 25 is connected to the pipeline between the ninth temperature sensor 68 and the mass flow meter 57 through the third pipeline, and the third pipeline is provided with a third safety valve 51 and a third bursting disc 52; the safety valve return air pipeline 25 is connected to the pipeline between the ninth temperature sensor 68 and the mass flow meter 57 through the fourth pipeline, and the fourth pipeline is provided with a fourth safety valve 53, a fourth bursting disc 54 and a one-way valve 56. The replacement return air pipeline 24 is connected to the first pipeline through the second safety valve 46, the replacement return air pipeline 24 is connected to the negative pressure protection integrated device 45 through the second normal temperature valve 48, the replacement return air pipeline 24 is connected to the second pipeline connecting pipe through the third normal temperature valve 49, and the replacement return air pipeline 24 is connected to the third pipeline through the fourth normal temperature valve 50.

[0064] For step S300a, the experimental platform built based on the experimental process is connected to the superfluid helium cryogenic system, and the cryogenic test is performed according to the experimental process. For ease of understanding, the specific steps of the experiment are described below.

[0065] (1) Cryogenic valves are provided between the 75K cold shield return air duct 27, the 50K cold shield air inlet duct 28, the 4.5K supercritical helium gas supply duct 29, the 2K return air duct 30, and the 75K coupler return air duct 31 and the upstream superfluid helium cryogenic system.

[0066] (2) The sensor signals are all led out to the atmosphere through the vacuum connector group 40, and then connected to the strain gauge and temperature sensor, and finally connected to the local industrial computer for collection. The 3.3V output voltage of the industrial computer is used as the power output of the acquisition card, and the 24V DC is used as the power input of the temperature sensor. Finally, a ground wire is laid to isolate electromagnetic interference.

[0067] (3) After closing all valves, open the vacuum plug valve 33 and the second vacuum pump group 34 on the interlayer vacuum pipe 26 of the experimental platform to prepare the environment in the test platform to a vacuum state, requiring the vacuum degree to be less than 10 -4 Pa.

[0068] (4) Maintain the low-temperature valves between the 75K cold shield return gas pipeline 27, the 50K cold shield air inlet pipeline 28, the 4.5K supercritical helium gas supply pipeline 29, the 2K return gas pipeline 30 and the 75K coupler return gas pipeline 31 and the upstream superfluid helium cryogenic system in a closed state, open the first vacuum pump group 32, the first normal temperature valve 42, the second normal temperature valve 48, the third normal temperature valve 49, the fourth normal temperature valve 50, the first cryogenic valve 55, the second cryogenic valve 58, the third cryogenic valve 59 and the fourth cryogenic valve 60, and evacuate the 75K cold shield return gas pipeline 27, the 50K cold shield air inlet pipeline 28, the 4.5K supercritical helium gas supply pipeline 29, the 2K return gas pipeline 30, the 75K coupler return gas pipeline 31 and their upper branches to below 100 Pa.

[0069] (5) Turn off the first vacuum pump group 32, open the cryogenic valve between the 75K cold shield return gas pipeline 27, the 2K return gas pipeline 30 and the upstream superfluid helium cryogenic system, and introduce helium into the 75K cold shield return gas pipeline 27, the 50K cold shield air inlet pipeline 28, the 4.5K supercritical helium gas supply pipeline 29, the 2K return gas pipeline 30, the 75K coupler return gas pipeline 31 and its upper branch to a slightly positive pressure state of about 1.1 bar. Let it stand for 10 minutes to complete an inner tube gas environment replacement.

[0070] (6) Repeat steps (4) and (5) for more than four times to ensure that the gas state inside the 75K cold screen return gas pipeline 27, the 50K cold screen air intake pipeline 28, the 4.5K supercritical helium gas supply pipeline 29, the 2K return gas pipeline 30, the 75K coupler return gas pipeline 31 and its upper branch is high-purity helium.

[0071] (7) Open the cryogenic valves between the 75K cold shield return air pipeline 27, the 50K cold shield inlet pipeline 28, the 4.5K supercritical helium gas supply pipeline 29, the 2K return air pipeline 30, the 75K coupler return air pipeline 31 and the upstream superfluid helium cryogenic system, and input low-temperature helium into the test platform to form a loop. More specifically, the 50K cold shield gas supply pipeline sleeve cold shield welding ring 17 and the 50K cold shield inlet pipeline 28 constitute the cold shield loop, the 4.5K supercritical helium gas supply pipeline 29 is the 4.5K supercritical helium gas supply loop, and the 2K return air pipeline 30 and the 75K coupler return air pipeline 31 constitute the return air loop of the 4.5K supercritical helium gas supply pipeline 29. More specifically, the 2K return air pipeline 30 can directly return to the refrigerator in the 4.5K mode. In the 2K mode, the helium in the 2K return air pipeline 30 is sent to the pressure reducing and cooling pump group to reduce the pressure inside the helium pool 61, so that the pressure inside the helium pool 61 is reduced to 3000Pa, and the liquid helium inside is converted into superfluid helium. The saturated helium of 2K will pass through the support assembly 70 from the 2K return air pipeline 30, monitor the temperature data of the fourth temperature sensor, and maintain its 2K environment to ensure that in the 2K mode, the five pipelines undertaken by the support assembly 70 are all in the designed working conditions.

[0072] (8) Monitor the mass flow meter 57, the first temperature sensor 35, the second temperature sensor 36, the third temperature sensor 37, the fourth temperature sensor 38, the fifth temperature sensor 39, the seventh temperature sensor 66, the eighth temperature sensor 67, the ninth temperature sensor 68, the tenth temperature sensor 69 and the temperature sensors on the support assembly 70 to ensure slow cooling and complete cooling of the support assembly 70. When the difference between the data of the mass flow meter 57, the first temperature sensor 35, the second temperature sensor 36, the third temperature sensor 37, the fourth temperature sensor 38, the fifth temperature sensor 39, the seventh temperature sensor 66, the eighth temperature sensor 67, the ninth temperature sensor 68, the tenth temperature sensor 69 and the temperature sensors on the support assembly 70 and the temperature sensor on the support assembly 70 remains unchanged, it is considered that the support assembly 70 has been completely cooled and has reached the final cooling state.

[0073] (9) Observe the readings of the 4.5K liquid helium level gauge 63 and the 2K superfluid helium level gauge 64. When the current data is too high, turn on the DC power heater 65 to maintain the liquid level inside the helium pool 61 so that it does not overflow the helium pool 61; (10) In the above steps, the experimental study of the support assembly 70 under the design conditions from normal temperature to the working state is completed. When the temperature drops, the signals of the strain gauge and the temperature sensor are recorded. After reaching the state described in step (9), it is maintained for a period of time to ensure the stability and validity of the data.

[0074] (11) After the test is completed, close the cryogenic valves between the 50K cold shield air intake pipe 28, the 4.5K supercritical helium gas delivery pipe 29 and the upstream superfluid helium cryogenic system, turn on the DC power heater 65, wait for the readings of the 4.5K liquid helium level gauge 63 and the 2K superfluid helium level gauge 64 to reach 0, and then turn off the DC power heater 65. At the same time, close the vacuum plug valve 33 and the second vacuum pump group 34, wait for the test platform to return to room temperature, and then close the cryogenic valves between the 75K cold shield return air pipe 27, the 2K return air pipe 30, the 75K coupler return air pipe 31 and the upstream superfluid helium cryogenic system.

[0075] The optimization design method and experimental research method of the ultra-low temperature multi-load insulation support provided by the present invention effectively consider the performance of the support assembly 70 under the multi-physical field boundary, provide the optimal support structure suitable for a large-scale superfluid helium transmission and distribution system, and provide an experimental verification scheme and method. By combining a variety of simulation technology means and experimental research, the problems of the lack of performance of the support assembly 70 and the lack of process verification caused by the use of classical models are compensated, and the stiffness and robustness of the large-scale superfluid helium transmission and distribution system are effectively optimized and improved.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An optimization design method for ultra-low temperature multi-load insulation support, characterized in that: include: Step S100, selecting the thickness of the casing of each temperature zone of the support assembly and the thickness parameters of the support panel as optimization design parameters for parameterized modeling, and introducing the maximum stress value and the heat leakage value as target values; Step S200, based on the thickness parameters of the casings in each temperature zone and the support panel, a genetic algorithm is used as an optimization function, and iterative calculation is performed in combination with simulation software to obtain the thickness parameters of the casings in each temperature zone and the support panel under the optimal boundary, and obtain the heat leakage value under the optimal boundary and the maximum stress value of the support assembly; Step S300, the support assembly is processed according to the thickness parameters of the casings in each temperature zone and the thickness parameters of the support panel under the obtained optimal boundary.

2. The optimization design method of ultra-low temperature multi-load insulation support according to claim 1 is characterized in that: The step S200 includes: Use MATLAB software as the host software to write the algorithm program of the genetic algorithm module; In the process of constructing the objective function, the thickness of the casing at each temperature zone and the thickness parameters of the support panel output by the parametric modeling are used as independent variables to perform parameter variables for optimization iteration; Taking the heat leakage value and the maximum stress of the support assembly as target values ​​for minimization optimization; The NSGA-II algorithm in the MATLAB software is retrieved, the target value is analyzed according to the objective function, and the optimization simulation calculation is driven; ANSYS Workbench is used as a modeling and simulation calculation platform. The independent variables selected by the genetic algorithm are parametrically modeled through Spaceclaim. After the model built by the SpaceClaim module is input into Steady-State Thermal, the calculation results are transmitted to Static Structural to complete the simulation calculation based on temperature analysis and comprehensive stress range, and the heat leakage value and the maximum stress value of the support component are obtained. The MATLAB software captures the calculation results of ANSYS Workbench and makes judgments, and finally gives the Pareto optimal frontier solution set.

3. The optimization design method of ultra-low temperature multi-load insulation support according to claim 2 is characterized in that: Before calling the NSGA-II algorithm in the MATLAB software to analyze the target value according to the objective function and drive the optimization simulation calculation, the method further includes: A data transmission interface between the MATLAB software and the ANSYS Workbench is written in the MATLAB software to realize coupled simulation between the MATLAB software and the ANSYS Workbench.

4. The optimization design method of ultra-low temperature multi-load insulation support according to claim 1 is characterized in that: The genetic algorithm is NSGA-II genetic algorithm, and the simulation software is finite element simulation software.

5. A support assembly, characterized in that: The support assembly is manufactured based on the optimization design method of the ultra-low temperature multi-load insulation support described in any one of claims 1 to 4.

6. An experimental research method for ultra-low temperature multi-load insulation support, characterized in that: include: Step S100a, during the process of processing the support component, a temperature sensor and a strain gauge are arranged to conduct an experiment on the support component; Step S200a, designing an experimental process based on the superfluid helium cryogenic distribution system used by the support assembly and using liquid helium and superfluid helium as experimental working fluids; Step S300a, connecting the experimental platform built based on the experimental process to the superfluid helium cryogenic system, and performing low-temperature testing according to the experimental process.

7. The experimental research method of ultra-low temperature multi-load insulation support according to claim 6 is characterized in that: The step S100a comprises: Based on the simulation calculation results, a strain gauge is arranged at a position where the stress of the support component is relatively large, and a temperature sensor is arranged near the strain gauge to obtain a strain-temperature response at the position where the strain gauge is arranged; When installing the strain gauge, the strain gauge is fixed by a processing tool, and the colloid bonding the strain gauge and the support assembly is cured by a constant temperature box to ensure the tightness between the strain gauge and the point to be measured; A metal cold shield is arranged around the temperature sensor to prevent the temperature sensor from generating measurement errors due to heat radiation.

8. The experimental research method of ultra-low temperature multi-load insulation support according to claim 6 is characterized in that: The step S200a comprises: A Wheatstone quarter bridge was used for strain acquisition; During the experiment, a slow cooling strategy was adopted to ensure that the support assembly could be fully cooled.

9. The experimental research method of ultra-low temperature multi-load insulation support according to claim 6 is characterized in that: The superfluid helium cryogenic distribution system can provide a maximum cooling capacity of 1000W@4.5K.

10. The experimental research method of ultra-low temperature multi-load insulation support according to claim 6, characterized in that: The output end of the temperature sensor and the output end of the strain gauge are both connected to a local industrial computer.

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