阅读说明：本技术 一种液氦储罐复合变密度多层绝热结构变密度优化方法 (Variable density optimization method for composite variable density multi-layer heat insulation structure of liquid helium storage tank ) 是由 李长俊 张财功 贾文龙 吴瑕 蒲兼林 王静 于 2020-12-29 设计创作，主要内容包括：本发明专利公开了一种液氦储罐复合变密度多层绝热结构变密度优化方法,该方法考虑了间隔物的增加对多层绝热层间残余气体导热及固体导热产生影响,残余气体导热量随间隔物的增加而增加,固体导热量随间隔物的增加而减小。因此,该计算方法综合两这方面变化规律,建立复合变密度多层绝热结构的层密度优化方法。对复合多层绝热层内每个添加间隔物的位置逐层优化,并不断增加间隔物数量,直至总热流密度达到最小值,该最小值对应的间隔物数量即为该层的最佳间隔物刷量,并采用同样的方法对其余各层进行优化。通过优化,实现了液氦储罐复合变密度多层绝热结构的优化配置,进一步提高了液氦储罐的保冷性能,减小了液氦的蒸发损耗。(The invention discloses a variable density optimization method for a composite variable density multilayer heat insulation structure of a liquid helium storage tank, which considers the influence of the increase of spacers on the heat conduction of residual gas and solid between multiple heat insulation layers, wherein the heat conduction of the residual gas is increased along with the increase of the spacers, and the heat conduction of the solid is decreased along with the increase of the spacers. Therefore, the calculation method integrates the two change laws to establish a layer density optimization method of the composite variable density multi-layer heat insulation structure. Optimizing the position of each added spacer in the composite multilayer heat insulation layer by layer, continuously increasing the number of the spacers until the total heat flow density reaches the minimum value, wherein the number of the spacers corresponding to the minimum value is the optimal spacer brushing amount of the layer, and optimizing the rest layers by adopting the same method. Through optimization, the optimized configuration of the composite variable-density multilayer heat-insulating structure of the liquid helium storage tank is realized, the cold insulation performance of the liquid helium storage tank is further improved, and the evaporation loss of liquid helium is reduced.)

1. A variable density optimization method for a composite variable density multi-layer heat insulation structure of a liquid helium storage tank is characterized by comprising the following steps: the optimization method considers the influence of the increase of the spacers on the residual gas heat conduction and the solid heat conduction between the multiple layers of heat insulation layers, wherein the residual gas heat conduction quantity is increased along with the increase of the spacers, and the solid heat conduction quantity is reduced along with the increase of the spacers; the calculation method integrates two change rules and establishes a variable density optimization method of the composite variable density multilayer heat insulation structure, and the calculation process comprises the following steps:

1) establishing dimensionless pressure coefficients p (i, n):

on the basis of a pressure distribution equation of the multilayer heat insulating layer under a stable condition, carrying out degradation, discretization, recursion and the like on the multilayer heat insulating layer, and defining a binary pressure distribution function p (i, n) which is represented by the following formula:

wherein p is₀Representing the pressure of the vacuum system without the insulating layer; d represents a diffusion coefficient; δ represents the adiabatic layer thickness; omega₀Expressing the air release amount of the heat insulating layer per unit volume; f represents the area of the heat-insulating outer layer; s represents the air extraction speed; i represents a layer position; n represents an increased number of spacers; n represents the total number of radiation screens in the thermal insulation layer;

when the spacers (n ═ 1) are not added much between the radiation screens, i.e., the layer density optimizes the binary pressure distribution function at the initial moment, represented by the following formula:

carrying out non-dimensionalization on the binary pressure distribution function, defining a non-dimensional pressure coefficient p (i, n), and calculating according to the following formula:

2) initial binary pressure distribution function parameter fitting:

carrying out inverse calculation on unknown parameters in the initial binary pressure distribution function p (i, 1) by adopting experimental values; in order to improve the fitting precision, the pressure distribution curve is segmented according to the change rule of the pressure distribution curve, the pressure distribution curve is divided into 3 segments, different quadratic curves are adopted for fitting different intervals, different functions are obtained in different intervals, and therefore the fitting precision is improved, and the pressure distribution curve fitting method is calculated according to the following formula:

3) and (3) variable density optimization:

considering the influence of the addition of the spacers on solid heat conduction, after n spacers are added, the solid heat conduction thermal resistance between the adjacent radiation screens is increased by n times, namely the heat flow density and the heat conduction coefficient after the n spacers are added are calculated according to the following formula:

wherein q is_s-condRepresents the total heat flux density; c represents an empirical constant, and is taken as 0.008; δ represents the relative density of the spacer material relative to the solid material; Δ x represents the actual thickness of the spacer between the radiation layersDegree; k represents the thermal conductivity of the spacer material;

considering the influence of the addition of the spacers on the heat conduction of the residual gas to obtain a density optimization model of the variable-density multilayer heat insulation structure layer, calculating the total heat flow density after the spacers are added, and calculating according to the following formula:

2. a variable density optimization method for a composite variable density multi-layer heat insulation structure of a liquid helium storage tank is characterized by comprising the following steps: the calculation method of claim 1 is adopted to optimize the position of each added spacer in the composite multilayer heat insulation layer in sequence, each time, one spacer layer is added, the number of spacers is continuously increased until the comprehensive heat flow density reaches the minimum value, the number of spacers corresponding to the minimum value is the optimal spacer brushing amount of the layer, and the other layers are optimized by adopting the same method.

Technical Field

The invention relates to a variable density optimization method for a composite variable density multilayer heat insulation structure of a liquid helium storage tank, and belongs to the technical field of low-temperature liquid passive heat protection.

Background

Helium is a monatomic inert gas, colorless, tasteless, non-toxic, and the lowest critical temperature substance currently found in humans. The liquid helium has extremely low critical temperature, high-efficiency convection heat transfer characteristic and high quantum mechanical zero energy, so that the liquid helium plays an irreplaceable role in the fields of space exploration, war industry, refrigeration, medical treatment, semiconductor and magnet production, superconducting experiments, photoelectron product production and the like. At present, helium is transported mainly in liquid phase, but the extremely low temperature of liquid helium presents a great challenge to the thermal protection requirements of liquid helium storage tanks. The cold insulation of the liquid helium storage tank requires a heat insulation structure having excellent heat insulation performance, and the current heat insulation structure mainly has a vacuum multilayer heat insulation, a variable density multilayer heat insulation, a gas cooling screen heat insulation, and the like. However, the problem of large heat leakage of the liquid helium storage tank still exists when a single heat insulation structure is adopted, and the liquid helium is expensive, so how to improve the cold insulation performance of the storage tank by the liquid helium becomes a problem which needs to be paid attention for a long time. In recent years, with the further development of low-temperature thermal insulation technology, composite multilayer thermal insulation and composite variable-density multilayer thermal insulation technology, in which two or three kinds of low-temperature thermal insulation technologies are combined, has become a hot spot in research in the field under the large trend of combined application of multiple methods. The composite multilayer insulation is obtained by installing a foam heat insulation layer on the inner side of the vacuum multilayer insulation, and the essence of the composite multilayer insulation is the combined application of the vacuum multilayer insulation and the common accumulation insulation. The composite variable density multilayer thermal insulation is obtained by performing variable density optimization on the basis of a composite multilayer thermal insulation technology, and the basic principle is to reduce the layer density near a cold boundary to reduce the solid heat conduction heat flow density near the cold boundary and increase the layer density near a hot boundary to reduce the radiation heat transfer near the hot boundary, so that the heat leakage of the liquid helium storage tank is reduced, and the evaporation loss of the liquid helium is reduced. According to the existing research results, in the two heat insulation structures, the introduction of the foam heat insulation layer and the optimization of the variable density can improve the heat insulation performance of the low-temperature storage tank.

However, the following problems exist in the prior art of optimizing the variable density of the composite variable density multilayer insulation structure of the liquid helium tank. Firstly, the current research on the variable density optimization of the multilayer heat insulation is mainly carried out around the multilayer heat insulation structure, and the research on the composite variable density multilayer heat insulation structure is not available at present; secondly, the research on the variable density optimization of the composite variable density multilayer heat insulation structure of the liquid helium storage tank is few, and the research on the variable density optimization mainly surrounds the liquid hydrogen storage tank and the liquid nitrogen storage tank. Liquid helium is the lowest liquid in temperature level at present, the critical temperature is as low as 5.15K, the boiling point is as low as 4.2K, the critical temperature is much lower than low-temperature liquids such as LNG and liquid nitrogen, even lower than liquid hydrogen, the liquid helium storage tank has the highest sensitivity to environmental heat leakage, and evaporation loss and storage and transportation safety problems caused by heat leakage are the most serious, so that the demand of carrying out variable density optimization research on composite multilayer heat insulation of the liquid helium storage tank is urgent, but at present, there is almost no literature report on variable density optimization research of the liquid helium storage tank. Thirdly, the existing variable density optimization research mainly adopts an orthogonal experiment method or artificially sets variable density optimization termination conditions, so that the variable density optimization result is not optimal, namely the thermal insulation performance of the storage tank can be further improved. Therefore, it is very important to develop the research of the composite variable density multilayer adiabatic variable density optimization method of the liquid helium storage tank.

Disclosure of Invention

In view of the above-mentioned problems, the present invention is directed to: under the condition of meeting the national relevant standards, the variable density optimization method for the composite variable density multilayer heat insulation structure of the liquid helium storage tank is provided, the number of spacers near a cold boundary and a hot boundary can be optimized, the variable density optimization of the composite variable density multilayer heat insulation structure of the liquid helium storage tank is realized, and the purposes of improving the heat insulation performance of the liquid helium storage tank and reducing the evaporation loss of liquid helium are achieved.

In order to achieve the purpose, the invention provides a variable density optimization method of a composite variable density multilayer insulation structure of a liquid helium storage tank, which is based on a thermodynamic method and has the following optimization ideas: firstly, assuming that 1 layer of spacing material is configured between the adjacent radiation screens, then starting from the first layer of spacing layer, adding the rest spacing material between the two adjacent radiation screens one by one, adding one layer of spacing material between the two adjacent radiation screens each time, and calculating the heat flow density after adding the new layer of spacing material. As the spacing material between the two radiation screens increases, the solid heat conduction heat flow density will gradually decrease. However, when the spacer material is excessively increased at the position, the increase of the outgassing amount of the spacer material reduces the vacuum degree between the adjacent radiation screens at the position, so that the residual gas heat conduction is increased, therefore, in the process of increasing the spacer material, the comprehensive heat flow density is influenced by the solid heat conduction of the spacer and the residual gas heat conduction, for each spacer layer, the comprehensive heat flow density has a minimum value relative to the curve of the number of the spacer material, the number of the spacer material corresponding to the minimum value is the optimal number of the spacer at the position, and the composite variable density multilayer heat insulation structure can be obtained by optimizing the rest layers by the same method. The method provided by the invention is suitable for variable density optimization of a composite variable density multilayer heat insulation structure of a liquid helium storage tank, and comprises the following specific processes:

1) setting basic parameters

Setting cold boundary conditions and hot boundary conditions, setting materials of a radiation screen, a spacer and a foam layer of the composite multi-layer heat insulation structure, and assuming initial temperature linearization.

2) Calculation of temperature distribution

And (3) adding a spacer to the spacing layer, performing iterative calculation, calculating the interlayer heat transfer resistance after the spacer is added, and calculating new temperature distribution by using the heat resistance until the temperature distribution calculation result meets the convergence condition.

3) Establishing dimensionless pressure coefficient p (i, n)

And establishing a pressure distribution equation of the multilayer heat insulating layer under the stable condition, wherein the pressure distribution equation is shown as the following formula.

Wherein p is₀Denotes the pressure, Pa, of the vacuum system without the insulating layer; d represents a diffusion coefficient; δ represents the adiabatic layer thickness, m; omega₀Expressing the air release amount of the heat insulating layer per unit volume; f represents the area of the heat-insulating outer layer, m²(ii) a S represents the pumping speed.

The pressure distribution equation of the multilayer heat insulation layer is processed by a mathematical method such as degradation and discretization, and a binary pressure distribution function p (i, n) is defined and is represented by the following formula.

Wherein i denotes the layer position, N denotes the increased number of spacers, N denotes the total number of radiation screens in the thermal insulation layer,

when the number of spacers (n ═ 1) is not increased between the radiation screens, that is, the variable density optimizes the binary pressure distribution function at the initial moment, which is expressed by the following formula.

And performing recursive processing on the binary pressure distribution function, and representing the binary pressure distribution function by using the binary pressure distribution function at the initial moment as shown in the following formula.

The binary pressure distribution function is represented by the following formula without dimensionalization.

The dimensionless pressure coefficient p (i, n) is defined as shown below.

4) Initial binary pressure distribution function parameter fitting

For the unknown parameters in the initial binary pressure distribution function p (i, 1), the experimental values are used for back calculation. In order to improve the fitting precision, segmentation is performed according to the change rule of the pressure distribution curve, different quadratic curves are adopted for fitting different intervals, different functions are obtained in different intervals, and therefore the fitting precision is improved as shown in the following formula.

5) Establishing a variable density optimization model

Considering the influence of the addition of the spacers on solid heat conduction, after n spacers are added, the solid heat conduction thermal resistance between the adjacent radiation screens is increased by n times, namely the heat flow density and the heat conduction coefficient after the n spacers are added are shown as the following formula.

Wherein q is_s-condRepresents the total heat flow density, C represents an empirical constant, taken at 0.008; δ represents the relative density of the spacer material relative to the solid material; Δ x represents the actual thickness of the spacer between the radiating layers, m; k represents the thermal conductivity of the spacer material, W/(m)²·K)；

And (3) considering the influence of the addition of the spacer on the heat conduction of the residual gas to obtain a density optimization model of the variable-density multilayer heat insulation structure layer, and calculating the total heat flow density after the spacer is added, as shown in the following formula.

Wherein q is_totDenotes the total heat flow density, q_radDenotes radiant heat flux density, q_g-condRepresents the total heat flux density, and sigma represents the Stephan-Boltsman constant, which is 5.675X 10^-8W/(m²·K⁴)；T_iRepresents the temperature of the higher temperature radiation screen, K; t is_i-1Represents the temperature of the lower temperature radiation screen, K; epsilon_iIndicating the emissivity of the radiant screen at a higher temperature; epsilon_i-1Indicating the emissivity of the lower temperature radiation screen; p represents the gas pressure (vacuum) between adjacent radiation screens, Pa; α represents a thermal adaptation coefficient, and α is 0.9 for air; r represents a gas constant of 8.314J/(mol.K); m represents the molar mass of the gas, g/mol; t represents the temperature of the surface of the reflecting layer, K; gamma ═ c_p/c_v，c_pRepresents the isobaric specific heat capacity, J/(kg. K); c. C_vRepresents the equivalent heat capacity, J/(kg. K).

c_p、c_tThe temperature and pressure correction coefficients are expressed respectively and calculated by the following formula.

6) Determination of the number of the most probable spacers

And after the spacers are added to each layer in sequence, the number of the spacers corresponding to the minimum value of the heat flow density curve is the optimal number of the spacers.

The technical idea adopted by the invention is as follows:

considering that the increase of the spacers has influence on the residual gas heat conduction and the solid heat conduction between the multilayer heat insulation layers, from the two aspects, a variable density optimization model of the composite variable density multilayer heat insulation mechanism is established, so that the variable density arrangement with the layer density changing continuously can be calculated.

The invention has the beneficial effects that:

the composite variable-density multilayer heat-insulation variable-density optimization method for the liquid helium storage tank realizes the optimization of variable density, ensures the rationality of an optimization result and further improves the cold insulation performance of the liquid helium storage tank with the composite variable-density multilayer heat-insulation structure compared with a manually set variable-density configuration and orthogonal experiment optimization method.

Drawings

FIG. 1 is a model diagram of a method for optimizing the composite variable-density multi-layer insulation structure of a liquid helium storage tank in variable density;

FIG. 2 is a flow chart of the calculation of the variable density optimization method of the composite variable density multi-layer heat insulation structure of the liquid helium storage tank;

FIG. 3 is a calculated optimal number of spacers between 1-6 layers of radiant screens according to the present invention;

FIG. 4 is a calculated optimal number of spacers between 7-12 layers of radiant screens according to the present invention;

FIG. 5 is a calculated optimal number of spacers between 13-18 layers of radiant screens according to the present invention;

FIG. 6 is a calculated optimal number of spacers between the 19-24 layers of radiant screens of the present invention;

FIG. 7 is a calculated optimal number of spacers between 25-30 layers of radiant screens according to the present invention;

FIG. 8 is a calculated optimal number of spacers between 31-36 layers of radiant screens according to the present invention;

FIG. 9 is a calculated optimal number of spacers between 37-40 layers of radiant screens according to the present invention;

figure 10 is a calculated continuous variable density spacer material distribution of the present invention.

Detailed Description

The technical solution of the present invention will be further described in detail with reference to the accompanying drawings: as shown in fig. 1, a method for optimizing the composite variable density multilayer insulation structure of a liquid helium storage tank by varying the density takes a composite variable density multilayer insulation structure of 41 layers of radiation screens as an example, and calculates the optimal number of spacers layer by layer, which mainly includes the following calculation steps:

1) setting boundary conditions, wherein the cold boundary temperature is 4.2K, the hot boundary temperature is 300K, assuming that the internal initial temperature of the multilayer material is linearly distributed, the radiation screen adopts aluminum foil, the spacer adopts polyester net, the thickness of the multilayer material is 0.315m, and the thickness of the Foam layer is 0.0355 m.

2) For the unknown parameters in the initial binary pressure distribution function p (i, 1) in the optimization model, the experimental values are used for back calculation. In order to improve the fitting precision, the pressure distribution curve is divided into 3 sections according to the change rule of the pressure distribution curve, different quadratic curves are adopted for fitting different intervals, different functions are obtained in different intervals, and therefore the fitting precision is improved as shown in the following formula.

3) And (3) adding a spacer, increasing the spacers layer by layer one at a time, calculating the heat transfer resistance between layers, and calculating new temperature distribution according to the heat transfer resistance until the error of the calculation results of two adjacent times is less than 0.0001K.

4) The corresponding binary pressure distribution function p (i, n) is calculated as in equation (2).

And (4) calculating a binary pressure distribution function at the initial moment of optimizing the layer density according to the formula (3).

And (5) calculating a dimensionless pressure coefficient p (i, n) according to the formula (6).

4) Calculating the total heat flow after adding the spacer layer by layer

The total heat flow of each layer after adding spacers was calculated according to equations (9) and (10).

5) With the increase of the interlayer spacers, the residual gas heat conduction and the solid heat conduction are changed, so that the total heat flow density is changed in a rule that the total heat flow density is firstly reduced and then increased along with the increase of the interlayer spacers, whether the total heat flow reaches a minimum value or not is judged, if the total heat flow reaches the minimum value, the number of the spacers corresponding to the minimum value is the optimal number of the spacers of the layer, if the total heat flow does not reach the minimum value, the spacers are continuously increased, and the recalculation is started from the step.

Fig. 3 shows the calculation results of the optimal number of spacers between the radiation screens of 1-6 layers, and it can be seen that the optimal number of spacers of the first layer is 18 layers and the optimal number of spacers of the second layer is 15 layers. The same method is used to calculate the optimal number of spacers for the other layers, as shown in fig. 4-9.

And finally, calculating to obtain the optimal number of the spacers of each layer, wherein the number of the spacers is gradually reduced and the layer density is gradually increased from inside to outside. As shown in fig. 10.

Therefore, the optimization of variable density is realized, the composite variable density multilayer heat insulation structure of the liquid helium storage tank is obtained, after the optimization of variable density, the heat leakage of the liquid helium storage tank is reduced compared with that before the optimization, and the cold insulation performance is improved.