A prediction method, system, device and medium for non-gray gas radiative heat transfer based on the Monte Carlo method

Abstract

A prediction method, system, device and medium for non-gray gas radiative heat transfer based on the Monte Carlo method. The method is as follows: First, assume the temperature field data of the computational domain cells. Then, use the HITRAN database to obtain the average Planck absorption coefficient and emissivity of the gas, and use the Monte Carlo method to calculate the radiative transfer factor RD of the surface cells and volume cells in the region i,j , and finally list a system of linear equations to solve for the temperature distribution of the computational domain; determine whether the temperature is within the tolerance range. If the tolerance requirement is met, the program ends. Otherwise, restore the temperature field of the computational domain, update the temperature of the computational domain, and solve again; its system, device and medium can predict non-gray gas radiative heat transfer based on the Monte Carlo method; the present invention analyzes the line spectral absorption coefficient of polyatomic gases and combines non-gray medium radiative parameters such as wavelength, emissivity, and average Planck absorption coefficient with the traditional Monte Carlo method to solve the radiative transfer factor RD between cells i,j , gradually correct the numerical value of the computational domain temperature to achieve the heat balance of the system, so as to realize the calculation of the thermal radiation heat transfer between non-gray gases in the computational domain; it has the advantages of good flexibility, high prediction accuracy and wide application range.

Description

Technical Field

[0001] The present invention relates to the technical field of radiative heat transfer simulation calculation of participating media, and particularly to a non-gray gas radiative heat transfer prediction method, system, device and medium based on the Monte Carlo method. Background Technique

[0002] Radiative heat transfer, conductive heat transfer and convective heat transfer are the basic ways of heat transfer, and are widely used in combustion, remote sensing, solar energy and rocket propulsion. Radiative heat transfer accounts for about 90% in these processes. Especially in a vacuum environment, radiative heat transfer is even more important. Therefore, it is more important to accurately calculate the radiative heat transfer problem.

[0003] Common gases such as methane, water vapor, ozone, carbon dioxide, etc. belong to polyatomic gases. When such polyatomic gases appear in heat transfer situations, the radiative heat transfer between the gas and the solid needs to be considered. Especially in the aerospace field, the fuel combustion products contain a certain concentration of water vapor and carbon dioxide. At this time, the calculation of gas radiative heat transfer is particularly important in engineering.

[0004] The characteristics of gas radiative heat transfer are mainly related to radiative energy, spatial coordinates, spatial orientation and wavelength. Traditional calculation methods usually discretely solve the continuous physical quantities of space and time of the research object in the calculation domain. Currently, common radiative heat transfer equation models are: Monte Carlo method, zonal method, diffusion approximation method, heat flux method, discrete transfer method, finite volume method, ray tracing-node analysis method. These radiative heat transfer equation models are usually based on the following three assumptions: 1. Assume that the object surface, medium and particles are gray bodies; 2. Use equivalent parameters to replace the radiative property parameters that vary with wavelength; 3. Use an approximate band method. The above methods are only for participating media as gray bodies, and have great limitations for the radiative heat transfer calculation of non-gray media where the radiative parameters vary with wavelength, pressure and temperature. Summary of the Invention

[0005] To overcome the above technical problems existing in the prior art, the present invention provides a non-gray gas radiative heat transfer prediction method, system, device and medium based on the Monte Carlo method, which includes mesh division methods and mesh parameter acquisition for any calculation domain; obtaining radiative line spectrum parameters of polyatomic gases; calculating the radiative transfer factor between units by the Monte Carlo method, and fully considering the variable property characteristics of non-gray gases during the calculation process, using the blackbody radiation distribution cumulative function at a certain temperature as the only condition for determining the emission wavelength of the light beam, and being able to accurately combine the spectral average Planck absorption coefficient of polyatomic gases during light beam tracing; solving the matrix equation according to the radiative transfer factor by the iteration method based on the principle of energy conservation to obtain the temperature of each unit; the present invention can solve the radiative heat transfer problem of non-gray media where the radiative parameters vary with temperature, pressure and wavelength.

[0006] To achieve the above object, the technical solution of the present invention is:

[0007] A prediction method for radiative heat transfer of non-gray gases based on the Monte Carlo method, specifically including the following steps:

[0008] S1: After dividing the computational domain into a modeling grid, obtain the surface grid or volume grid parameters of the custom computational region; including the element numbers, boundary coordinates, and element center coordinates of the surface grid or volume grid;

[0009] S2: Calculate the surface equation of the surface grid or the surface equation that envelopes all surfaces in the volume grid according to the boundary coordinates of the surface grid or volume grid;

[0010] S3: Initially assume the temperature T of the unknown surface elements and volume elements in the computational domain i ;

[0011] S4: Obtain the temperatures of the unknown elements in the computational domain based on the known boundary condition temperatures, and determine the wavelength range [λ1 - λ2] of 99% of the energy radiation energy from the blackbody radiation function and Wien displacement law.

[0012]

[0013] λT = 2.8976×10 -3 m·K

[0014] S5: Assume the wavelength interval is [λ1 - λ2], divide the wavelength interval into n (n > 1000) equal parts, and calculate the share of the cumulative radiation energy of each equal part in the blackbody radiation energy;

[0015] S6: Obtain the multi-atomic gas radiation line spectrum parameter data packet from the HITRAN database, process the hot line data in the multi-atomic gas data packet, and select the microwave band in S5 Select the microwave band according to the temperature assumed in S3 The average Planck absorption coefficient k within the range λ,i is used to replace the absorption coefficient with the central wavelength of η λ,i ;

[0016]

[0017] In the formula: —Spectral absorption coefficient at the center of the band, m -1 ; k λ,i —Average Planck absorption coefficient, m-1; T—Temperature, K; η—Wavelength, cm-1; σ—Blackbody radiation constant, 5.6703×10 -8 W / (m 2 ·K 4 );e bη —Blackbody emissive power, W / (m 2 ·μm);

[0018] S7: Solve for the average ray length of the computational domain based on the boundary of the computational domain;

[0019]

[0020] S8: Calculate the emissivity of polyatomic gases at the temperature assumed in S3 using difference calculation;

[0021] ε g = f(T g , ps)

[0022] In the formula: ε g — Emissivity, T g — Gas temperature, K, p — Pressure, atm, s — Average ray length, m;

[0023] S9: Compile the Monte Carlo algorithm for the computational domain;

[0024] S9-1: During the beam emission process, the number of rays emitted in the microwave band at different temperatures T is different. According to the share of the radiation energy emitted by the beam method in the microwave band determined in step S5-2 in the blackbody radiation energy, a random number P is randomly generated to determine the microwave band Δη where the beam is located, and the wavelength η i of the emitted beam is obtained; λ,i ;

[0025] S9-2: Start emitting the beam on the surface element or volume element with known temperature or heat flux density. First, determine the surface element where the beam is emitted. Let [x i,max , x i,min , [y i,max , y i,min , and [z i,max , z i,min belong to the surface element where the emission point is located at (x0, y0, z0). The emission point probability model is

[0026]

[0027] S9-3: Determine the zenith angle and azimuth angle of the beam emission. The beam is diffusely reflected on the surface element in the cavity. The zenith angle θ and azimuth angle ψ of the beam emission direction are determined by the following formula:

[0028]

[0029] S9-4: Determine the direction vector of the beam emission. The emission direction of the beam in the rectangular coordinate system is:

[0030]

[0031] S9-5: Determine the linear equation of the light beam according to step S9-4, solve the intersection points of the linear equation of the light beam and the equations of adjacent surface elements, and determine whether the intersection points belong to the boundary surface elements or the volume elements. If the area of the region formed by the coordinates of the intersection point and the boundary surface element where it is located is equal to the area of the surface element, it is considered that the intersection point is within the boundary surface element. If the volume of the region formed by the vertex coordinates of the intersection point and the volume element is equal to the volume element, it is considered that the intersection point intersects with the volume element;

[0032] S9-5-1: If it is determined that the light beam intersects with the volume element after judgment, obtain the wavelength η of the light beam through step S1 λ,i of the average Planck coefficient to k λ,i , calculate the distance L passing through the volume element and the energy share absorbed by the volume element. The remaining energy of the light beam after traveling the distance L can be calculated by the Bouger-Lamber law:

[0033] E'0 = E0exp(-LK abs (λ))

[0034] The energy absorbed by the volume element from the light beam is:

[0035] E0[1 - exp(-LK abs (λ))]

[0036] When the remaining energy of the energy beam emitted by the micro-element segment i gradually decreases after multiple reflections or scatterings, and when the ratio of the remaining energy to the emitted energy satisfies E'0 < 0.0001%E0, it is considered that the light beam tracking stops;

[0037] S9-5-2: If it is determined that the light beam intersects with the boundary surface element after judgment, the distance between the intersection points of two adjacent elements is L. Generate a random number P to determine whether it is reflected by the surface element or absorbed by the surface element. If it is absorbed, return to S9-1 to re-emit the light beam. If it is reflected, the intersection point is (x', y', z'), and return to S9-5 to re-determine the zenith angle and azimuth angle of the diffuse reflection;

[0038]

[0039] S9-5-3: If there is no intersection solution between the light beam equation and all the surface element equations, it is considered that the light beam escapes from the calculation domain;

[0040] S9-6: Return to S9-2 to re-determine the surface element or volume element that emits the light beam within the calculation domain;

[0041] S9-6-1: Repeat steps S9-2 to S9-5-3 until the specified number of light beams are emitted;

[0042] S10: The radiation transfer factor RD of the boundary surface element and the volume element is calculated from the steps of S9 i,j ;

[0043] S11: Solve by listing the energy equation matrix from the known boundary temperature or heat flux density. For the calculation domain with n surface elements and s volume elements, the energy emitted by any element is equal to the sum of the energy radiated to it by other elements. Then the energy equation is as follows:

[0044]

[0045]

[0046] ε—Thermal emissivity of the surface element; S—Area / m 2 ; σ—Stefan-Boltzmann constant, 5.67×10 -8 W·m -2 ·K -4 ; k—Planck mean absorption coefficient of the volume element, m -1 ; V—Volume / m 3 ;

[0047] S12: Obtain the preliminary temperature values of the unknown elements in the calculation domain from step S11, and then return to S4 to execute steps S4, S5, S6, S7, S8, S9, S10, S11 until the temperatures of the unknown elements obtained by two solutions satisfy |T i -T j | < 0.00001 to stop the calculation.

[0048] In the described light beam emission process, it carries the wavelength η λ,i , gas emissivity ε g (T g , ps), and the average Planck absorption coefficient k λ,i .

[0049] In step S8, the gas emissivity ε g (T g , ps) and in step S6, the Planck mean absorption coefficient k λ,i are iteratively updated with the temperature T i .

[0050] A prediction system for a non-gray gas radiative heat transfer prediction method based on the Monte Carlo method, including:

[0051] A data storage module for storing the line spectrum parameter data of the gases in the HITRAN database;

[0052] A radiation transfer factor RD i,j calculation module for calculating the radiation transfer factor RD of each surface element and volume element in the calculation domain i,j；

[0053] A post-processing module for solving the energy balance equation to obtain the heat flux density of each surface element and volume element.

[0054] A prediction device for a non-gray gas radiative heat transfer prediction method based on the Monte Carlo method, comprising:

[0055] A memory for storing a computer program;

[0056] A processor for implementing the non-gray gas radiative heat transfer prediction method described in steps S1 to S9 when executing the computer program.

[0057] Furthermore, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it can predict the radiative heat transfer of non-gray gases based on the Monte Carlo method.

[0058] Compared with the prior art, the present invention has the following advantages:

[0059] 1. Mesh generation method and mesh parameter acquisition for any computational domain; the mesh generation method and mesh parameter acquisition for any computational domain have good flexibility; using the HITRAN database to obtain the radiative line spectrum parameters of polyatomic gases, with high accuracy; by programming the Monte Carlo method, the variable physical property characteristics of non-gray gases are fully considered during the calculation of the radiative transfer factor between computational cells, and the blackbody radiation distribution cumulative function at a certain temperature is used as the only condition to determine the emission wavelength of the light beam, and the spectral average Planck absorption coefficient of polyatomic gases can be accurately combined during the light beam tracing; by using an iterative method to solve the matrix equation according to the radiative transfer factor based on the principle of energy conservation to obtain the temperature of each cell, the result has high accuracy.

[0060] 2. The present invention directly introduces the radiative property parameters (emissivity, absorption coefficient, wavelength) of non-gray media into the Monte Carlo method, making the wavelength of the emitted light beam correspond one-to-one with the absorption coefficient of non-gray media, accurately describing the selective absorption characteristics of non-gray media, and completing the light beam tracing to obtain the radiative transfer factor RD between each cell in the computational domain j,i , solving the problem that the traditional radiative heat transfer model is only applicable to gray media and is not applicable to non-gray media whose emissivity and absorption coefficient vary with wavelength, pressure, and temperature; it can be widely applied to heat transfer research in technical fields such as combustion, remote sensing, solar energy, and rocket propulsion. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0062] Figure 1Schematic diagram of the two-dimensional rectangular calculation domain of the embodiment of the present invention.

[0063] Figure 2 Flowchart of the prediction method of the present invention.

[0064] Figure 3 Cumulative distribution function graph of the beam emission wavelength determination of the present invention.

[0065] Figure 4 Prediction result graph of the embodiment of the present invention. Specific embodiments

[0066] The following will describe the specific embodiments of the present disclosure in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for the purpose of illustration and explanation of the present disclosure, and are not intended to limit the present disclosure.

[0067] A prediction method for non-gray gas radiative heat transfer based on the Monte Carlo method according to the present invention proposes a heat transfer calculation method that combines the spectral absorption coefficient, emissivity, and selective absorption characteristics of polyatomic gases with the traditional Monte Carlo method in view of the non-gray characteristics of polyatomic gases, providing a more accurate and reliable calculation method for the radiative heat transfer of non-gray media.

[0068] The schematic diagram of the two-dimensional rectangular calculation domain of the embodiment of the present invention is as Figure 1 shown. The two-dimensional rectangular calculation region of 1m x 0.5m is filled with carbon dioxide gas with a concentration of 0.1 and a temperature of 1000K. The total pressure in the calculation domain is 1 atm. Only radiative heat transfer is considered and fluid flow is not considered during the calculation process. The calculation domain uses a grid of 21 x 21, and the cell center is used as the data storage point to solve the divergence of the wall heat flux density.

[0069] As Figure 2 shown, a prediction method for non-gray gas radiative heat transfer based on the Monte Carlo method according to the present invention includes the following steps:

[0070] S1: After modeling and mesh generation using Gambit 2.1, import into Fluent 6.3 to obtain the surface mesh or volume mesh parameters of the calculation region. The UDF function is as follows.

[0071] S2: Calculate the surface equation of the surface mesh or the surface equation that envelopes all surfaces in the volume mesh according to the boundary coordinates of the surface mesh or volume mesh;

[0072] S3: Initially assume the temperature T of the unknown surface elements and volume elements in the calculation domain i ;

[0073] S4: Determine the blackbody radiation λT range according to the initial boundary temperature, where the wavelength range [λ1 - λ2] can contain 99% of the energy radiation;

[0074]

[0075] λT = 2.8976×10 -3 m·K

[0076] S5: If the wavelength range is [λ1 - λ2], divide the wavelength range into n (n > 1000) equal parts, and calculate the cumulative distribution function of the microwave band as shown in Figure 3;

[0077] S6: Select the HITRAN database provided by the Phillips Geophysics Laboratory of the United States Air Force as the source of the spectral line parameters of polyatomic gases. Process the hotline data in the polyatomic gas data packet, and select the microwave band in S5 Select the microwave band according to the assumed temperature in S3 The average Planck absorption coefficient k within the range is used to λ,i replace the absorption coefficient with the central wavelength of η λ,i ;

[0078]

[0079] In the formula: —Spectral absorption coefficient at the center of the band, m -1 ; k λ,i —Average Planck absorption coefficient, m-1; T—Temperature, K; η—Wavelength, cm-1; σ—Blackbody radiation constant, 5.6703×10 -8 W / (m 2 ·K 4 ); e bη —Blackbody emissive power, W / (m 2 ·μm).

[0080] S7: Obtain the average ray length of the calculation region according to the boundary of the calculation domain;

[0081]

[0082] In the formula: S—Average ray length, m; V—Volume of the calculation domain, m 3 ; A—Area of the calculation domain, m 2 .

[0083] S8: Calculate the emissivity of polyatomic gases at the temperature assumed in S3 using interpolation;

[0084] ε g = f(T g , ps)

[0085] In the formula: ε g —Emissivity, T g —Gas temperature, K, p—Pressure, atm, s—Average ray length, m.

[0086] S9: Write the Monte Carlo algorithm for the calculation domain;

[0087] S9-1: During the beam emission process, since the number of light rays emitted in the microwave band at different temperatures T is different, and step S5-2 has determined the share of the radiation energy emitted by the beam method in the microwave band in the blackbody radiation energy, randomly generate a random number P to determine the microwave band Δη where the beam is located , and then the wavelength η of the emitted beam is determined i ; λ,i ;

[0088] S9-2: Start emitting the beam on the boundary surface element or volume element with known temperature or heat flux density. First, determine the surface element where the beam is emitted. Let [x i,max , x i,min , [y i,max , y i,min and [z i,max, z i,min belong to the surface element where the emission point is located at (x0, y0, z0). The emission point probability model is

[0089]

[0090] S9-3: Determine the zenith angle and azimuth angle of the beam emission. The beam is diffusely reflected on the cavity surface element. The zenith angle θ and azimuth angle ψ of the beam emission direction are determined by the following formula:

[0091]

[0092] S9-4: Determine the direction vector of the beam emission. The emission direction of the beam in the rectangular coordinate system is:

[0093]

[0094] S9-5: According to step S9-4, determine the straight-line equation of the beam, solve the intersection point of the straight-line equation of the beam and the equation of the adjacent surface element, and determine whether the intersection point belongs to the boundary surface element or the volume element. If the area of the region formed by the intersection point and the 4 coordinates of the boundary surface element where it is located is equal to the area of the surface element, it is considered that the intersection point is within the boundary surface element. If the volume of the region formed by the intersection point and the 8 vertex coordinates of the volume element is equal to the volume of the volume element, it is considered that the intersection point intersects with the volume element;

[0095] S9-5-1: If it is determined that the beam intersects with the volume element after judgment, obtain the average Planck coefficient k λ,i of the beam wavelength η through step S1 λ,i , calculate the distance L passing through the volume element and the energy share absorbed by the volume element. The remaining energy of the beam after passing through the distance L can be calculated by the Bouger-Lamber law:

[0096] E'0 = E0exp(-LK abs (λ))

[0097] The energy absorbed by the volume element from the light beam is:

[0098] E0[1 - exp(-LK abs (λ))]

[0099] When the remaining energy of the energy beam emitted by the micro - element segment i gradually decreases after multiple reflections or scatterings, and when the ratio of the remaining energy to the emitted energy satisfies E'0 < 0.0001%E0, the light beam tracking is considered to stop.

[0100] S9 - 5 - 2: If it is determined that the beam intersects with the boundary - face element, and the distance between the intersection points of two adjacent elements is L, generate a random number P to determine whether it is reflected by the face element or absorbed by the face element. If it is absorbed, return to S9 - 1 to re - emit the light beam. If it is reflected, assume the intersection point is (x', y', z'), and return to S9 - 5 to determine the new zenith angle and azimuth angle;

[0101]

[0102] S9 - 5 - 3: If the light beam does not intersect with the computational domain, it escapes from the computational domain.

[0103] S9 - 6: Return to S9 - 2 to determine the light beam emitted by the volume element within the computational domain;

[0104] S9 - 6 - 1: Repeat the steps from S9 - 2 to S9 - 5 - 3.

[0105] S10: Obtain the radiation transfer factor R of the computational domain through the calculation in step S9 i,j ;

[0106] S11: List the energy - equation matrix from the known boundary temperature or heat - flux density and solve it. For n face elements and s volume elements within the computational domain, the energy emitted by any element is equal to the sum of the energy radiated to it by other elements:

[0107]

[0108]

[0109] ε—the thermal emissivity of the surface element; S—the area / m 2 ; σ—the Stefan - Boltzmann constant, 5.67×10 -8 W·m -2 ·K -4 ; k—the Planck mean absorption coefficient of the volume element, m -1 ; V—the volume / m 3 ;

[0110] S12: Obtain the preliminary temperature value of the computational domain from step S11, and then return to S4 to execute steps S4, S5, S6, S7, S8, S9, S10, and S11 until the two solutions satisfy |T i -T j | < 0.00001 to stop the calculation;

[0111] According to the divergence of the heat flux density of 84 cells on the calculation wall, draw the boundary heat flux density divergence diagram as Figure 4 shown.

[0112] The traditional radiative heat transfer model is applicable to the calculation of radiative heat transfer between gray bodies and cannot accurately solve the problem of radiative heat transfer of non-gray polyatomic gases. The present invention is applicable to solving the problem of radiative heat transfer of non-gray polyatomic gases. By using the HITRAN database, the spectral absorption coefficient of non-gray polyatomic gases is accurately obtained, the average Planck absorption coefficient is obtained by integrating and averaging in the microwave band, the wavelength of the emitted light beam is obtained by combining the unit temperature parameters, and the above parameters are introduced into the Monte Carlo method to obtain the radiative transfer factor RD i,j between units. Finally, the temperatures of other units are solved using the law of conservation of energy. The entire calculation is carried out iteratively. In each iterative step calculation, the emissivity of the polyatomic gas, the wavelength of the light beam, and the average Planck coefficient of the polyatomic gas for the light beam of this wavelength are known quantities, and the temperature and heat flux can be solved and analyzed using the existing thermal radiation boundary conditions.

[0113] In the embodiment of the present invention, by selecting a 1m x 0.5m two-dimensional rectangle filled with carbon dioxide gas with a concentration of 0.1 and a temperature of 1000K as the computational domain, the surface grid or volume grid parameters of the computational region are obtained using Gambit 2.1 and Fluent 6.3; the radiative line spectrum parameters of carbon dioxide gas are obtained from the HITRAN database; the radiative transfer factor RD i,j between units is obtained through the Monte Carlo algorithm; finally, the heat flux density of the rectangular wall is obtained by solving the matrix equation.

[0114] The preferred embodiments of the present disclosure have been described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0115] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the present disclosure does not separately describe various possible combination methods. In addition, any combination can be made between various different embodiments of the present disclosure as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

Claims

1. A prediction method for radiative heat transfer of non-gray gas based on Monte Carlo method, characterized in that: It includes the following steps: S1: After performing modeling grid division on the computational domain, obtain the surface grid or volume grid parameters of the custom computational region, including the element numbers, boundary coordinates, and element center coordinates of the surface grid or volume grid. S2: Calculate the surface equation of the surface grid or the surface equation enclosing all surfaces in the volume grid according to the boundary coordinates of the surface grid or volume grid. S3: Initially calculate the temperature T of the unknown surface elements and volume elements within the computational domain i ; S4: Solve for the temperatures of the unknown elements in the computational domain based on the initial known boundary condition temperatures, and determine the wavelength range of 99% of the energy radiation according to the blackbody radiation function and Wien's displacement law ; S5: Assume the wavelength range is , divide the wavelength range into n equal parts, where n > 1000, and calculate the share of the cumulative radiation energy of each equal part in the blackbody radiation energy; S6: Obtain the spectral parameter data packet of polyatomic gases from the HITRAN database, process the hot line data in the polyatomic gas data packet, and select the microwave band in S5 , and select the average Planck absorption coefficient within the microwave band according to the assumed temperature in S3 to replace the absorption coefficient with a central wavelength of ; In the formula: —Spectral absorption coefficient at the center of the band, m -1 ; —Average Planck absorption coefficient, m -1 ; T—Temperature, K; —Wavelength, cm -1 ; —Blackbody radiation constant, 5.6703 ; —Blackbody emissive power, ; S7: Solve the average ray length of the computational domain according to the computational domain boundary. S8: Use interpolation to calculate the emissivity of the polyatomic gas at the temperature assumed in S3. In the formula: — Emissivity — Gas temperature, K — Pressure, atm, s — Mean beam length, m S9: Write the Monte Carlo algorithm for the computational domain. S10: The radiation transfer factors RD of the boundary surface elements and volume elements are obtained by solving the Monte Carlo algorithm written by S9 i,j ; S11: List the energy equation matrix from the known boundary temperature or heat flux density for solution. For the case where there are n surface elements and s volume elements in the computational domain, the energy emitted by any element is equal to the sum of the energy radiated to it by other elements. Then the energy equation is: ε—Thermal emissivity of the surface element; S—Area / m 2 ; σ—Blackbody radiation constant, ; k—Planck mean absorption coefficient of the volume element, m -1 ; V—Volume / m 3 ; S12: Obtain the preliminary temperature values of the unknown cells in the computational domain from step S11, and then return to S4 to execute steps S4, S5, S6, S7, S8, S9, S10, S11 until the temperatures of the unknown cells are solved twice to satisfy Stop the calculation.

2. The non-gray gas radiative heat transfer prediction method based on the Monte Carlo method according to claim 1, wherein: The specific method of step S9 is as follows: S9-1: During the beam emission process, the number of light rays emitted in the microwave band at different temperatures T is different. According to the share of the radiation energy emitted by the beam method in different microwave bands determined in step S5-2, a random number P is randomly generated to determine the microwave band where the beam is located to obtain the wavelength of the emitted beam ; ; S9-2: Start emitting a light beam on the surface or volume element with a known temperature or heat flux density. First, determine the surface element where the light beam is emitted, and let , and belong to the surface element where the emission point is located at (x0, y0, z0), and the emission point probability model is S9-3: Determine the zenith angle and azimuth angle of the beam emission. The beam is diffusely reflected on the inner surface unit of the cavity, and the zenith angle of the beam emission direction and the azimuth angle are determined by the following formula: S9-4: Determine the direction vector of the beam emission. In a rectangular coordinate system, the emission direction of the beam is: S9-5: According to step S9-4, determine the straight-line equation of the beam, solve the intersection point of the straight-line equation of the beam and the equation of the adjacent surface element, and determine whether the intersection point belongs to the boundary surface element or the volume element. If the area of the region formed by the coordinates of the intersection point and the boundary surface element where it is located is equal to the area of the surface element, it is considered that the intersection point is within the boundary surface element. If the volume of the region formed by the vertex coordinates of the intersection point and the volume element is equal to the volume element, it is considered that the intersection point intersects with the volume element. S9-5-1: If it is determined that there is an intersection with the volume element, obtain the beam wavelength through step S1 to calculate the average Planck coefficient , calculate the distance L passing through the volume element and the energy fraction absorbed by the volume element. The remaining energy of the beam after traveling the distance L can be calculated by the Bouger-Lamber law: The energy absorbed by the volume element from the beam is: When the remaining energy of the energy beam emitted by the infinitesimal segment i gradually decreases after multiple reflections or scatterings, and when the ratio of the remaining energy to the emitted energy satisfies , the beam tracking is considered to stop. S9-5-2: If it is determined that the intersection with the boundary surface element occurs and the distance between the intersection points of two adjacent elements is L, a random number P is generated to determine whether to be reflected by the surface element or absorbed by the surface element. If absorbed, return to step S9-1 to re-emit the light beam. If reflected, the intersection point is , return to step S9-5 to re-determine the zenith angle and azimuth angle of the diffuse reflection; S9-5-3: If there is no intersection solution between the beam equation and all surface element equations, it is considered to escape from the computational domain. S9-6: Return to step S9-2 to re-determine the beam emission from the surface elements or volume elements within the computational domain. S9-6-1: Repeat steps S9-2 to S9-5-3 until the specified number of beams is emitted.

3. The non-grey gas radiative heat transfer prediction method based on the Monte Carlo method according to claim 2, characterized in that: The beam emission process carries a wavelength , gas emissivity , and average Planck absorption coefficient .

4. A method for predicting non-gray gas radiation heat transfer based on the Monte Carlo method according to claim 1, characterized in that: The gas emissivity in step S8 and the Planck mean absorption coefficient in step S6 are iteratively updated with the temperature T i ​ 5. A prediction system for the non-gray gas radiation heat transfer prediction method according to any one of claims 1 to 4, including: A data storage module for storing the line spectrum parameter data of the gases in the HITRAN database. Radiative transfer factor RD i,j Calculation module for calculating the radiative transfer factor RD of each surface element and volume element within the calculation domain i,j； A post-processing module for solving the energy balance equation to obtain the heat flux density of each surface element and volume element.

6. A prediction device for the non-gray gas radiation heat transfer prediction method according to any one of claims 1 to 4, including: A memory for storing computer programs. A processor for implementing the non-gray gas radiation heat transfer prediction method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium storing a computer program, which can predict non-gray gas radiation heat transfer based on the non-gray gas radiation heat transfer prediction method according to any one of claims 1 to 4 when the computer program is executed by a processor.

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