Method for calculating heat conductivity coefficient of aerogel composite material

Abstract

The invention provides a method for calculating the heat conductivity coefficient of an aerogel composite material, and relates to the field of aerogel composites.The method for calculating the heat conductivity coefficient of the aerogel composite material builds an objective function model through cyclic nesting and collaborative parallelization and specifically comprises the steps of A, input parameter obtaining, B, four-stage model building, C, three-stage model building, D, two-stage model building and E, first-stage model building. And F, constructing an objective function. According to the method, the optimal volume ratio and the optimal diameter of the basalt fiber in the composite material can be rapidly and accurately determined, guidance is provided for research, development and design of the fiber reinforced aerogel composite material, and the thermal insulation performance of the basalt fiber aerogel composite material is optimal on the premise that the mechanical property of the basalt fiber aerogel composite material is balanced.

Description

Technical Field

[0001] The invention relates to the technical field of aerogel composite materials, and in particular to a method for calculating thermal conductivity of an aerogel composite material. Background Art

[0002] Silicon-based aerogel is an ideal thermal insulation material with high porosity, high specific surface area, extremely low density and ultra-low thermal conductivity, which is formed by the aggregation of amorphous silicon-based nanoparticles in space. However, the extremely high porosity also leads to low toughness and mechanical strength of aerogel, which in turn limits its application and promotion in the field of thermal insulation. In order to improve the mechanical properties of aerogel materials, fiber skeletons are currently usually selected as their mechanical performance reinforcement. On the other hand, silicon-based aerogel has a low extinction coefficient at high temperatures, and accordingly, its emissivity increases sharply with increasing temperature, resulting in reduced thermal insulation performance under high temperature conditions. In order to improve the high-temperature thermal insulation performance of aerogel, basalt fibers are usually used as sunshades to enhance the infrared radiation scattering and absorption of aerogels under high temperature environments. According to research, ultrafine basalt fibers have the following advantages over other fiber bodies when applied to aerogel materials: first, they have higher thermal stability, with a thermal stability of more than 650°C; second, they have higher single-filament mechanical strength, with a mechanical strength 30% higher than that of glass fibers; third, they have a higher creep rupture limit; and fourth, they have higher corrosion resistance. Therefore, basalt fiber aerogel composites have great application prospects in the fields of thermal insulation and heat insulation.

[0003] In basalt fiber aerogel composite materials, the greater the density of the fiber reinforcement phase, the better the mechanical properties of the composite material, but it will lead to an increase in the thermal conductivity of the solid phase; while the density is too small, the mechanical properties of the composite material are difficult to meet the use requirements. At the same time, when the diameter of the fiber reinforcement phase is larger, the strength of the aerogel support skeleton formed is higher and the mechanical properties of the composite material are better, but it will lead to enhanced high-temperature thermal conductivity and aerogel "ashing" phenomenon; while if the diameter is too small, although it can also improve the scattering and absorption capacity of near-infrared light at high temperatures, it is easy to generate static electricity during the preparation process, resulting in problems such as aggregation of short-cut fibers and poor dispersion, which ultimately leads to reduced thermal insulation performance of the composite material. Therefore, it is necessary to determine the optimal volume ratio and optimal diameter size of basalt fiber in the composite material, so as to balance the relationship between mechanical properties and thermal conductivity, and avoid the problems of poor high-temperature thermal conductivity, "ashing", agglomeration, poor dispersion, etc. of basalt fiber reinforced aerogel composite materials; while the existing technology mainly obtains the optimal volume ratio and optimal diameter size through a large amount of test data combined with practical experience. This method has the problems of long design cycle, large amount of manpower and material resources, high requirements for R&D personnel, numerous calculation errors and large cumulative errors, and cannot obtain the optimal volume ratio and optimal diameter size of basalt fiber in the composite material in real time, quickly and accurately. Summary of the invention

[0004] In view of the problems existing in the above prior art, the purpose of the present invention is to provide a method for calculating the thermal conductivity of an aerogel composite material, which can quickly and accurately determine the optimal volume proportion and optimal diameter size of basalt fiber in the composite material, thereby providing effective guidance for the design of basalt fiber reinforced aerogel composite materials, and optimizing the thermal insulation performance of the basalt fiber aerogel composite material while balancing the mechanical properties of the basalt fiber aerogel composite material.

[0005] The purpose of the present invention is achieved through the following technical solutions: A method for calculating the thermal conductivity of aerogel composite materials is proposed. The objective function model is constructed by loop nesting and collaborative parallel development. Specifically, Step A, obtaining input parameters: including silica-based aerogel parameters, nanopore structure parameters, environmental parameters and basalt fiber parameters; Step B, four-level model establishment: based on the input parameters, establish the contact properties and size parameter calculation models of nanoparticles in the silicon-based skeleton, the surface area and volume boundary calculation model of the free movement of gas molecules in the skeleton cavity, and the basalt fiber extinction coefficient distribution calculation model with the incident angle; Step C, three-level model establishment: embed the four-level models as subroutines respectively to construct three-level models with single-layer nesting; Step D, secondary model establishment: embed each third-level model as a subroutine to construct each secondary model with double-layer nesting; Step E, first-level model establishment: each second-level model is used as a subroutine and coupled respectively to construct each first-level model with three layers of nesting; Step F, objective function construction: All primary models are coupled as subroutines to construct an objective function of the thermal insulation performance of the composite material with four nested layers.

[0006] Based on further optimization of the above scheme, the silicon-based aerogel parameters include porosity, specific surface area, density, extinction coefficient distribution with wavelength, etc., the nanopore structure parameters include internal characteristics of normal distribution or skewed distribution of pore size, environmental parameters include temperature, pressure, air specific heat, etc., and basalt fiber parameters include the distribution of complex refractive index of basalt material with wavelength; the input parameters are obtained by consulting materials and experimental experience data.

[0007] Based on the further optimization of the above scheme, the method for constructing the calculation model of the contact properties and size parameters of nanoparticles in the silicon-based skeleton is specifically as follows: Firstly, a cubic array aerogel skeleton model formed by regular cubic nanosphere particles was constructed, in which the diameter of the nanosphere particles, the contact length between two adjacent sphere particles, and the side length of the cubic array unit were the unknown parameters. Then, based on the measured aerogel porosity, specific surface area and target thermal conductivity, the contact state and size parameters of the particles in the cubic array aerogel skeleton were determined using the equal volume method and equal area method.

[0008] Based on further optimization of the above scheme, the calculation model of the surface area and volume boundary of the free movement of the gas molecular skeleton cavity is: using the molecular collision theory in a confined space, the surface area boundary and volume boundary of a single gas molecule in the aerogel cavity when it moves freely in the cavity and when the aerogel cubic nanosphere particles collide with the remaining gas molecules are analyzed.

[0009] Based on further optimization of the above scheme, the calculation model of the basalt fiber extinction coefficient distribution with incident angle is: using the relationship between the extinction coefficient and the absorption coefficient and the scattering coefficient in the photoelectric characteristics, the extinction coefficient distributed with wavelength and incident angle required for calculating the basalt fiber radiation coefficient is determined.

[0010] Based on the further optimization of the above scheme, the three-level model includes a contact thermal resistance calculation model between silicon-based nanoparticles, a gas molecule number distribution model and a mean free path model in the skeleton cavity, an average extinction coefficient model of basalt fibers, and an average extinction coefficient model of silicon-based aerogels; wherein, the contact thermal resistance calculation model between silicon-based nanoparticles is nested with the contact properties and size parameter calculation model of nanoparticles in the silicon-based skeleton as a subroutine, and the relationship between the contact thermal resistance of nanosphere particles in the silicon-based skeleton and the particle contact state, particle surface roughness, and lattice defects is determined through the thermal boundary layer theory; the gas molecule number distribution model and the mean free path model in the skeleton cavity are nested with the surface area and volume boundary calculation model for the free movement of gas molecules in the skeleton cavity as a subroutine, and the gas molecule number distribution and the mean free path of the gas molecules that can move freely in the silicon-based skeleton cavity are determined according to the gas molecule dynamics theory; the average extinction coefficient model of basalt fibers and the average extinction coefficient model of silicon-based aerogels are both nested with the calculation model of the extinction coefficient distribution of basalt fibers with the incident angle as a subroutine, and the average extinction coefficients of basalt fibers and silicon-based aerogels are respectively determined through the radiation heat transfer equation.

[0011] Based on the further optimization of the above scheme, the radiation heat transfer equation adopts the Rosseland approximation method:

[0012] In the formula, represents the composite-specific Rosseland average extinction coefficient; w f and w a represent the mass fractions of basalt fiber and silica-based aerogel in the composite material, respectively; , represent the specific Rosseland average extinction coefficients of basalt fiber and silica-based aerogel, respectively;

[0013] Where: , represent the average emissivity and spectral emissivity of a black body, respectively; Represents the spectral extinction coefficient of the material, which can be obtained through experimental testing of aerogel infrared spectral transmittance according to Beer's law:

[0014] Where: L and represent the thickness of the silicon-based aerogel and the infrared spectral transmittance through the silicon-based aerogel, respectively. Represents the density of silica-based aerogel.

[0015] Based on the further optimization of the above scheme, the secondary model includes a silicon-based skeleton thermal conductivity prediction model, a skeleton cavity gas phase thermal conductivity model, a basalt fiber radiation coefficient model and a silicon-based aerogel radiation coefficient model; wherein, the silicon-based skeleton thermal conductivity prediction model is nested with the contact thermal resistance calculation model between silicon-based nanoparticles as a subroutine, and the classical heat conduction theory is used to determine the prediction of the thermal conductivity of the silicon-based skeleton with respect to the contact thermal resistance of silicon-based nanoparticles; the skeleton cavity gas phase thermal conductivity model is nested with the skeleton cavity gas molecule number distribution model and the mean free path model as subroutines, and based on the thermal motion theory of gas molecules, the prediction of the thermal conductivity of the pores in the silicon-based skeleton cavity with respect to the gas mean free path is determined, see Kaganer model; The basalt fiber radiation coefficient model and the silicon-based aerogel radiation coefficient model are nested with the average extinction coefficient model of basalt fiber and the average extinction coefficient model of silicon-based aerogel as subroutines, respectively. Based on the Rosseland approximation method, the radiation coefficient prediction of basalt fiber and the radiation coefficient of silicon-based skeleton are determined respectively.

[0016] Based on the further optimization of the above scheme, the Kaganer model is specifically:

[0017] Where: It represents the thermal conductivity of the cavity formed by the nano-void structure in the silica-based aerogel; represents the viscosity of the gas in the nanovoids, which is obtained by multiplying the gas density in the silicon-based aerogel by the mean free path of the gas in the silicon-based skeleton cavity. for:

[0018] Where:k B represents the Boltzmann constant; T Indicates temperature; d represents the diameter of the nanosphere particles in the skeleton model; p Indicates environmental pressure.

[0019] Based on further optimization of the above scheme, the radiation coefficient of the basalt fiber for:

[0020] Where: represents the composite extinction coefficient of the cylindrical fiber,

[0021] Where: f v represents the volume fraction of basalt fiber in the composite material; represents the incident angle of the incident light wave with the columnar basalt fiber; d f represents the fiber diameter; Q ext represents the extinction efficiency, which is characterized as a function of the complex refractive index of basalt fiber according to the anomalous scattering estimation method ADT and Rayleigh-Debye light scattering theory; Emissivity of silica-based aerogels for:

[0022] Based on the extinction coefficient distribution of the dry aerogel spectrum measured by Lawrence Berkeley, the extinction coefficient of the aerogel is calculated by integrating within the band. .

[0023] Based on further optimization of the above scheme, the primary model includes a comprehensive thermal conductivity prediction model for aerogel composite materials and a radiation coefficient prediction model for aerogel composite materials; wherein the comprehensive thermal conductivity prediction model for aerogel composite materials is based on the heat transfer coupling theory of different phases in a confined space, coupling the silicon-based skeleton thermal conductivity prediction model with the gas phase thermal conductivity model in the skeleton cavity; the radiation coefficient prediction model for aerogel composite materials is based on the heat transfer coupling theory of different phases in a confined space, coupling the basalt fiber radiation coefficient model with the silicon-based aerogel radiation coefficient model.

[0024] The following are the effects of the technical solution of the present invention: The present application is based on the construction of various sub-function models of basalt fiber phase and silicon-based aerogel box, and utilizes the loop nesting and collaborative parallel layered stacking method of each sub-function model to construct an objective function of the thermal insulation performance of the composite material that couples each sub-function, and builds a mapping relationship between material parameters and thermal insulation performance, which is used to predict the thermal insulation performance of basalt fiber aerogel composite materials, and can timely, quickly, efficiently and accurately determine the optimal volume ratio and optimal diameter size of basalt fiber in the composite material, thereby providing guidance for the research of fiber-reinforced aerogels, effectively reducing the time and materials consumed in the selection test and matching test of fiber-reinforced aerogels, thereby improving R&D efficiency and reducing R&D costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 Schematic diagram of the cubic array model of the aerogel skeleton in Example 1 of the present invention.

[0026] Figure 2 This is a schematic diagram of the structure of the fiber phase in Example 1 of the present invention.

[0027] Figure 3 This is a flow chart of constructing the objective function in Example 1 of the present invention.

[0028] Figure 4 This is a schematic diagram of operations in Example 2 of the present invention.

[0029] Figure 5 Schematic diagram of the grid matrix in Example 2 of the present invention.

[0030] Figure 6 Schematic diagram of the thermal insulation performance grid matrix in Example 3 of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0032] Embodiment 1: A method for calculating the thermal conductivity of aerogel composite materials is proposed. The objective function model is constructed by loop nesting and collaborative parallel development. Specifically, Step A, obtaining input parameters: including silicon-based aerogel parameters: porosity, specific surface area, density, extinction coefficient distribution with wavelength, etc.; nanopore structure parameters: including internal characteristics of normal distribution or skewed distribution of pore size; environmental parameters: temperature, pressure, air specific heat, etc.; basalt fiber parameters: including the distribution of complex refractive index of basalt material with wavelength; various input parameters are obtained by consulting materials and experimental experience data.

[0033] Step B, four-level model establishment: based on the input parameters, establish the contact properties and size parameter calculation models of nanoparticles in the silicon-based skeleton, the surface area and volume boundary calculation model of the free movement of gas molecules in the skeleton cavity, and the basalt fiber extinction coefficient distribution calculation model with the incident angle; The calculation model of contact properties and size parameters of nanoparticles in the silicon-based skeleton is mainly based on the input of silicon-based aerogel parameters and environmental parameters. The specific construction method is as follows: Firstly, a cubic array aerogel skeleton model formed by regular cubic nanosphere particles was constructed, in which the diameter of the nanosphere particles, the contact length between two adjacent sphere particles, and the side length of the cubic array unit were the unknown parameters. Then, based on the measured aerogel porosity, specific surface area and target thermal conductivity, the contact state and size parameters of the particles in the cubic array aerogel skeleton were determined using the equal volume method and equal area method.

[0034] The calculation model of the surface area and volume boundary of the free movement of gas molecular skeleton cavity is mainly based on the input of environmental parameters and nanopore structure parameters. Specifically, the molecular collision theory in a confined space is used to analyze the surface area boundary and volume boundary of a single gas molecule in the aerogel cavity when it moves freely in the cavity and when the aerogel cubic nanosphere particles collide with the remaining gas molecules.

[0035] The calculation model of basalt fiber extinction coefficient distribution with incident angle is mainly based on the input of basalt fiber parameters. Specifically, the relationship between the extinction coefficient and the absorption coefficient and scattering coefficient in the photoelectric characteristics is used to determine the extinction coefficient distributed with wavelength and incident angle required for the calculation of basalt fiber radiation coefficient.

[0036] Step C, three-level model establishment: embed the four-level models as subroutines respectively to construct three-level models with single-layer nesting; the three-level models include a contact thermal resistance calculation model between silicon-based nanoparticles, a gas molecule number distribution model and a mean free path model in the skeleton cavity, an average extinction coefficient model of basalt fibers, and an average extinction coefficient model of silicon-based aerogels; Among them, the contact thermal resistance calculation model between silicon-based nanoparticles is nested with the contact properties and size parameter calculation model of nanoparticles in the silicon-based skeleton as a subroutine. Through the thermal boundary layer theory, the relationship between the contact thermal resistance of nanosphere particles in the silicon-based skeleton and the particle contact state, particle surface roughness and lattice defects is determined.

[0037] The gas molecule number distribution model and mean free path model in the skeleton cavity use the surface area and volume boundary calculation model of the free movement of gas molecules in the skeleton cavity as a subroutine nesting, and according to the gas molecular dynamics theory, determine the gas molecule number distribution and mean free path of the gas molecules that can move freely in the silicon-based skeleton cavity; The average extinction coefficient model of basalt fiber and the average extinction coefficient model of silicon-based aerogel are both based on the calculation model of the extinction coefficient distribution of basalt fiber with incident angle as a nested subroutine, and the average extinction coefficients of basalt fiber and silicon-based aerogel are determined respectively through the radiation heat transfer equation.

[0038] The radiation heat transfer equation uses the Rosseland approximation method:

[0039] In the formula, represents the composite-specific Rosseland average extinction coefficient; w f and w a represent the mass fractions of basalt fiber and silica-based aerogel in the composite material, respectively; , represent the specific Rosseland average extinction coefficients of basalt fiber and silica-based aerogel, respectively;

[0040] Where: , represent the average emissivity and spectral emissivity of a black body, respectively; Represents the spectral extinction coefficient of the material, which can be obtained through experimental testing of aerogel infrared spectral transmittance according to Beer's law:

[0041] Where: L and represent the thickness of the silicon-based aerogel and the infrared spectral transmittance through the silicon-based aerogel, respectively. Represents the density of silica-based aerogel.

[0042] Step D, secondary model establishment: embed each third-level model as a subroutine to construct each secondary model with double-layer nesting; the secondary model includes a silicon-based skeleton thermal conductivity prediction model, a skeleton cavity gas phase thermal conductivity model, a basalt fiber radiation coefficient model and a silicon-based aerogel radiation coefficient model; Among them, the thermal conductivity prediction model of the silicon-based skeleton is nested with the contact thermal resistance calculation model between silicon-based nanoparticles as a subroutine, and the classical heat conduction theory (the common heat conduction theory in this field can be used) is used to determine the thermal conductivity of the silicon-based skeleton with respect to the prediction of the contact thermal resistance of the silicon-based nanoparticles.

[0043] The gas phase thermal conductivity model in the skeleton cavity uses the gas molecule number distribution model and the mean free path model in the skeleton cavity as subroutines. Based on the thermal motion theory of gas molecules, the prediction of the thermal conductivity of the pores in the silicon-based skeleton cavity with respect to the mean free path of the gas is determined, see the Kaganer model:

[0044] Where: Indicates the thermal conductivity of the cavity formed by the nano-void structure in the silica-based aerogel, that is, the gas phase thermal conductivity of the silica-based aerogel k s ; represents the viscosity of the gas in the nanovoids, which is obtained by multiplying the gas density in the silicon-based aerogel by the mean free path of the gas in the silicon-based skeleton cavity. for:

[0045] Where: k B represents the Boltzmann constant; T Indicates temperature; d represents the diameter of the nanosphere particles in the skeleton model; p Indicates environmental pressure; in:

[0046] In the formula, k s0 Represents the thermal conductivity of a single silica nanosphere particle; R c Represents the contact thermal resistance between two adjacent silica nanosphere particles; H Represents the center distance between two adjacent nanosphere particles.

[0047] The basalt fiber radiation coefficient model and the silicon-based aerogel radiation coefficient model respectively use the average extinction coefficient model of basalt fiber and the average extinction coefficient model of silicon-based aerogel as subroutines to nest, and based on the Rosseland approximation method, the radiation coefficient prediction of basalt fiber and the radiation coefficient of silicon-based skeleton are determined respectively; Emissivity of basalt fiber for:

[0048] Where: represents the composite extinction coefficient of the cylindrical fiber,

[0049] Where: f v represents the volume fraction of basalt fiber in the composite material; represents the incident angle of the incident light wave with the columnar basalt fiber (see Figure 2 shown); d frepresents the fiber diameter; Q ext represents the extinction efficiency, which is characterized as a function of the complex refractive index of basalt fiber according to the anomalous scattering estimation method ADT and Rayleigh-Debye light scattering theory; Emissivity of silica-based aerogels for:

[0050] Based on the extinction coefficient distribution of the dry aerogel spectrum measured by Lawrence Berkeley, the extinction coefficient of the aerogel is calculated by integrating within the band. .

[0051] Step E, first-level model establishment: each second-level model is used as a subroutine and coupled respectively to construct each first-level model with three layers of nesting; the first-level model includes a comprehensive thermal conductivity prediction model of aerogel composite materials and a radiation coefficient prediction model of aerogel composite materials; wherein, the comprehensive thermal conductivity prediction model of aerogel composite materials is based on the heat transfer coupling theory of different phases in a confined space, coupling the thermal conductivity prediction model of silicon-based skeleton and the thermal conductivity model of gas phase in the skeleton cavity; the radiation coefficient prediction model of aerogel composite materials is based on the heat transfer coupling theory of different phases in a confined space, coupling the basalt fiber radiation coefficient model and the silicon-based aerogel radiation coefficient model.

[0052] The coupled silicon-based skeleton thermal conductivity prediction model and the skeleton cavity gas phase thermal conductivity model are shown below (the coupled basalt fiber radiation coefficient model and the silicon-based aerogel radiation coefficient model are the same). The thermal conductivity of this model is k a Including the thermal conductivity of the solid skeleton k g Thermal conductivity of gas phase k s , specifically:

[0053] Where: N Represents the number of nanosphere particles on each edge of the skeleton model; d represents the diameter of the nanosphere particles in the skeleton model; H Represents the center distance between two adjacent nanosphere particles;

[0054] Where: a represents the contact length between two adjacent nanosphere particles; in:

[0055] Where: Specific heat capacity at constant pressure cpg and specific heat at constant volume c vg ratio; p Indicates environmental pressure; k B represents the Boltzmann constant; T Indicates temperature; m g Indicates the molecular mass of gas; S represents the specific surface area of ​​the aerogel matrix; represents the density of the aerogel matrix; represents the porosity of the aerogel matrix; d g Represents the diameter of gas molecules; N A represents Avogadro's constant.

[0056] Step F, objective function construction: All first-level models are coupled as subroutines (such as Figure 3 As shown in Figure 3, the objective function of thermal insulation performance of a four-layer nested composite material is constructed.

[0057] Embodiment 2: As another preferred embodiment of the present application, when calculating the comprehensive thermal conductivity and comprehensive radiation coefficient of basalt fiber aerogel based on the theoretical model in Example 1, especially when calculating the comprehensive radiation coefficient, a large number of integral calculations are involved, such as: extinction efficiency Q ext , extinction coefficient It is necessary to use numerical integration to carry out the calculation, and in order to ensure the accuracy of the numerical calculation results, it is also necessary to use smaller discrete steps, such as: the angle of incidence The discrete step length in the range of 0° to 90° can be set to 0.01°, or even smaller than 0.005°, or the discrete value in the range of fiber diameter 2 to 12 μm can be set to 0.01 μm; if iteration is performed through this discrete step length, thousands of iterations are required, and the parameter iteration after compounding the discrete step lengths may even reach millions of times; therefore, based on the scheme in Example 1, when numerically integrating and calculating the spectral extinction coefficient corresponding to each wavelength within a certain wavelength range, in order to improve the computational efficiency and reduce the computing power consumption, the parallel pool method is adopted in this embodiment to divide the independent iteration tasks in the numerical integration calculation into multiple parallel processes of each parallel pool for independent calculation (such as Figure 4 The calculation results are then combined.

[0058] Specifically in this embodiment, for tens of thousands of basalt fiber diameter and volume percentage combinations, sequential calculations will occupy a large amount of computing resources and consume a lot of time; considering that the algorithm flow of each fiber parameter combination in calculating its corresponding thermal insulation performance objective function value is consistent, it is decided to generate a grid matrix based on the fiber diameter sequence and the fiber volume percentage sequence, and use the matrix to represent all fiber variable combinations that need to be traversed when calculating thermal insulation performance. Figure 5 As shown: the basalt fiber parameter grid matrix is ​​input as a parameter into the thermal insulation performance objective function model established in Example 1 to carry out matrix calculation, where d f represents the diameter of basalt fiber, υ represents the volume proportion of basalt fiber in the composite material, K It indicates the comprehensive thermal insulation performance index of composite materials.

[0059] Embodiment 3: As another preferred embodiment of the present application, in the above-mentioned fiber diameter and fiber volume percentage grid matrixing process based on the parallel pool + matrix method, the calculation time is proportional to the product of the discrete resolution of the fiber diameter and the discrete resolution of the fiber volume percentage. In order to increase the resolution of the calculation result by one order of magnitude, the calculation time will often increase by at least two orders of magnitude; therefore, there is a contradictory relationship between the high-resolution value of basalt fiber parameters and the reduction of computing resources and computing time.

[0060] In order to solve the above-mentioned contradictory relationship, based on the method of the above-mentioned embodiment 2, a larger range of basalt fiber diameters and a larger range of fiber volume percentages are firstly grid-matrixed using a higher discrete resolution, and a parallel pool + matrix method is adopted, that is, independent parallel operations of integral numerical operations and basalt fiber parameter matrix operations, to quickly determine the rough distribution state of the thermal insulation performance of the composite material corresponding to the basalt fiber parameter variables in a large range, see Figure 6 shown.

[0061] Then, based on the rough thermal insulation performance distribution grid matrix of basalt fiber aerogel composite materials under a larger range of fiber parameters (diameter, volume percentage), the fiber parameter boundary ranges where multiple local optimal solutions of the thermal insulation performance of the composite materials are located are determined, and these fiber parameter local boundary ranges are extracted.

[0062] Finally, based on the local boundary ranges of the extracted basalt fiber parameters, the globally optimal high-resolution basalt fiber parameter values ​​are further explored. In this embodiment, the fmincon solver provided by matlab is used to handle the optimization problem of nonlinear constraints, and the high-resolution optimal fiber parameter solution is searched within the reduced local boundary range, thereby solving the problem of multivariable nonlinear optimization with constraints and the problem that the method of directly solving the optimal parameter value (i.e., determining the optimal parameter value by solving the zero value of the first-order derivative of the objective function) is difficult to develop due to the complexity of the function.

Claims

1. A method for calculating thermal conductivity of an aerogel composite material, characterized in that: The objective function model is constructed by loop nesting and collaborative parallel development, specifically: Step A, obtaining input parameters: including silica-based aerogel parameters, nanopore structure parameters, environmental parameters and basalt fiber parameters; Step B, four-level model establishment: based on the input parameters, establish the contact properties and size parameter calculation models of nanoparticles in the silicon-based skeleton, the surface area and volume boundary calculation model of the free movement of gas molecules in the skeleton cavity, and the basalt fiber extinction coefficient distribution calculation model with the incident angle; Step C, three-level model establishment: embed the four-level models as subroutines respectively to construct three-level models with single-layer nesting; Step D, secondary model establishment: embed each third-level model as a subroutine to construct each secondary model with double-layer nesting; Step E, first-level model establishment: each second-level model is used as a subroutine and coupled respectively to construct each first-level model with three layers of nesting; Step F, objective function construction: All primary models are coupled as subroutines to construct an objective function of the thermal insulation performance of the composite material with four nested layers.

2. The method for calculating thermal conductivity of an aerogel composite material according to claim 1, characterized in that: The silicon-based aerogel parameters include porosity, specific surface area, density, extinction coefficient distribution with wavelength, etc., the nanopore structure parameters include internal characteristics of normal distribution or skewed distribution of pore size, environmental parameters include temperature, pressure, air specific heat, etc., and basalt fiber parameters include the distribution of complex refractive index of basalt material with wavelength; the input parameters are obtained by consulting materials and experimental experience data.

3. A method for calculating thermal conductivity of an aerogel composite material according to claim 1 or 2, characterized in that: The method for constructing the calculation model of contact properties and size parameters of nanoparticles in the silicon-based skeleton is specifically as follows: Firstly, a cubic array aerogel skeleton model formed by regular cubic nanosphere particles was constructed, in which the diameter of the nanosphere particles, the contact length between two adjacent sphere particles, and the side length of the cubic array unit were unknown parameters. Then, based on the measured aerogel porosity, specific surface area and target thermal conductivity, the contact state and size parameters of the particles in the cubic array aerogel skeleton were determined using the equal volume method and equal area method.

4. A method for calculating thermal conductivity of an aerogel composite material according to any one of claims 1 to 3, characterized in that: The calculation model of the surface area and volume boundary of the free movement of the gas molecular skeleton cavity is as follows: using the molecular collision theory in a confined space, the surface area boundary and volume boundary of a single gas molecule in the aerogel cavity when it moves freely in the cavity and when the aerogel cubic nanosphere particles collide with the remaining gas molecules are analyzed.

5. A method for calculating thermal conductivity of an aerogel composite material according to any one of claims 1 to 3, characterized in that: The calculation model of the basalt fiber extinction coefficient distribution with incident angle is: using the relationship between the extinction coefficient and the absorption coefficient and the scattering coefficient in the photoelectric characteristics, the extinction coefficient distributed with wavelength and incident angle required for calculating the basalt fiber radiation coefficient is determined.

6. The method for calculating thermal conductivity of an aerogel composite material according to claim 5, characterized in that: The three-level model includes a contact thermal resistance calculation model between silicon-based nanoparticles, a gas molecule number distribution model and a mean free path model in a skeleton cavity, an average extinction coefficient model of basalt fibers, and an average extinction coefficient model of silicon-based aerogels; wherein the contact thermal resistance calculation model between silicon-based nanoparticles is nested with a nanoparticle contact property and size parameter calculation model in a silicon-based skeleton as a subroutine, and the relationship between the contact thermal resistance of nanosphere particles in the silicon-based skeleton and the particle contact state, particle surface roughness, and lattice defects is determined through the thermal boundary layer theory; the gas molecule number distribution model and the mean free path model in the skeleton cavity are nested with a surface area and volume boundary calculation model for free movement of gas molecules in the skeleton cavity as a subroutine, and the gas molecule number distribution and the mean free path of gas molecules that can move freely in the silicon-based skeleton cavity are determined according to the gas molecule dynamics theory; the average extinction coefficient model of basalt fibers and the average extinction coefficient model of silicon-based aerogels are both nested with a basalt fiber extinction coefficient distribution calculation model with incident angle as a subroutine, and the average extinction coefficients of basalt fibers and silicon-based aerogels are respectively determined through the radiation heat transfer equation.

7. The method for calculating thermal conductivity of an aerogel composite material according to claim 6, characterized in that: The secondary model includes a silicon-based skeleton thermal conductivity prediction model, a skeleton cavity gas phase thermal conductivity model, a basalt fiber radiation coefficient model and a silicon-based aerogel radiation coefficient model; wherein, the silicon-based skeleton thermal conductivity prediction model uses the contact thermal resistance calculation model between silicon-based nanoparticles as a subroutine nesting, and uses the classical heat conduction theory to determine the thermal conductivity of the silicon-based skeleton with respect to the prediction of the contact thermal resistance of silicon-based nanoparticles; the skeleton cavity gas phase thermal conductivity model uses the skeleton cavity gas molecule number distribution model and the mean free path model as subroutine nesting, and based on the thermal motion theory of gas molecules, determines the prediction of the thermal conductivity of the pores in the silicon-based skeleton cavity with respect to the gas mean free path. The basalt fiber radiation coefficient model and the silicon-based aerogel radiation coefficient model are nested with the average extinction coefficient model of basalt fiber and the average extinction coefficient model of silicon-based aerogel as subroutines, respectively. Based on the Rosseland approximation method, the radiation coefficient prediction of basalt fiber and the radiation coefficient of silicon-based skeleton are determined respectively.

8. The method for calculating thermal conductivity of an aerogel composite material according to claim 7, characterized in that: The primary model includes a comprehensive thermal conductivity prediction model for aerogel composite materials and a radiation coefficient prediction model for aerogel composite materials; wherein the comprehensive thermal conductivity prediction model for aerogel composite materials is based on the heat transfer coupling theory of different phases in a confined space, coupling the silicon-based skeleton thermal conductivity prediction model with the gas phase thermal conductivity model in the skeleton cavity; the radiation coefficient prediction model for aerogel composite materials is based on the heat transfer coupling theory of different phases in a confined space, coupling the basalt fiber radiation coefficient model with the silicon-based aerogel radiation coefficient model.

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