Method, system, storage medium and device for measuring radiation transmission characteristics of high temperature gas

Abstract

The present invention belongs to the field of target characteristics and thermal radiation technology, and discloses a method, system, storage medium and device for measuring the radiation transfer characteristics of high-temperature gas. The method for measuring the radiation transfer characteristics of high-temperature gas includes: (1) obtaining accurate gas radiation characteristic parameters; establishing a multi-width spectral band K distribution model; (2) calculating optimized gas radiation characteristic parameters; (3) establishing an optimized gas radiation characteristic parameter database; (4) accurately predicting the gas radiation transfer characteristic parameters under given conditions; (5) calculating the emission intensity of radiation transmission. The present invention optimizes the solution of the radiation transmission equation by establishing an accurate and efficient radiation characteristic parameter calculation model and accurately predicting the radiation transmission characteristic parameters, avoiding the problem that the traditional spectral band model cannot take into account both accuracy and efficiency when calculating radiation transmission, and provides a new idea for the calculation of the radiation transmission characteristics of high-temperature gas.

Description

Technical Field

[0001] The present invention belongs to the technical field of target characteristics and thermal radiation, and in particular, relates to a method, system, storage medium and equipment for measuring the radiation transmission characteristics of high-temperature gas. Background Art

[0002] At present, radiation heat transfer plays a dominant role in high-temperature flow fields. Rapid and reliable measurement or calculation of radiation transfer characteristics of radiation sources is a prerequisite for thermal performance analysis and target detection. The calculation of radiation transfer characteristics mainly involves three aspects: accurate gas radiation spectrum data, efficient radiation characteristic calculation model and accurate multi-dimensional space radiation transfer equation solution method. Due to the huge number of gas radiation spectrum lines and complex environmental background conditions, the difficulty of calculation is greatly increased, which seriously affects the reliability and efficiency of spectral measurement.

[0003] At present, the calculation of the radiation transfer characteristics of high-temperature gases mainly revolves around two aspects: first, in view of the complexity of radiation characteristic parameters, research on the calculation methods and models of radiation characteristic parameters is carried out, and an accurate and efficient radiation characteristic parameter database is established through distributed processing of complex radiation characteristic parameters; second, in view of the prediction problem of actual radiation transfer characteristic parameters, research on prediction algorithms of radiation transfer characteristic parameters is carried out, and the solution of radiation transfer equations is simplified through accurate prediction of radiation transfer characteristic parameters of non-gray media.

[0004] At present, the calculation models of gas radiation characteristic parameters are mainly divided into three categories: overall model, spectral band model and line-by-line model. After years of development, the above models have been relatively perfect. High-temperature gas radiation itself has the complex characteristics of multi-physical field coupling. The overall model only considers the overall situation of radiation, ignoring the spectral details, resulting in large errors; the spectral band model improves the calculation efficiency by sacrificing accuracy, but there is still a lot of room for optimization in the calculation of the full spectrum; the line-by-line model has the highest calculation accuracy, but it involves a huge number of spectral lines, which increases the difficulty of solving. For spectral calculations of complex radiation sources, it is necessary to obtain as much and accurate information as possible, while also requiring speed and low complexity. Conventional calculation models are difficult to balance accuracy and efficiency in the full spectrum.

[0005] The existing prediction algorithms for the radiation transfer characteristic parameters of non-gray media mainly include data fitting, formula correction and proxy model. The data fitting method is mostly used to solve the radiation transfer characteristic parameters of characteristic spectrum bands. However, it takes a long time to calculate the fitting coefficients in the full spectrum range. Formula correction is a table lookup calculation based on the radiation characteristic parameter database. Different correction methods have different errors and efficiencies. The proxy model is limited by the model's nonlinear ability, learning ability and model structure, and it is often difficult to explain the calculation results.

[0006] Through the above analysis, the problems and defects of the existing technology are as follows: when calculating the spectral radiation characteristics of complex radiation sources, conventional methods cannot be directly applied. It is necessary to develop accurate and efficient high-temperature gas radiation characteristic parameter calculation models and radiation transfer characteristic parameter prediction optimization algorithms in the full spectral range to achieve efficient and accurate solutions to the radiation transfer equation.

[0007] The difficulty in solving the above problems and defects is that the calculation premise requires the detailed spectral line information of gas molecules, such as transition frequency, spectral line intensity, spectral line half-width, spectral line initial and final state energy levels, spectral line energy level degeneracy, etc. The amount of data for these parameters is very large. For molecular spectra, there are often tens of thousands of spectral lines, so the solution is very time-consuming. The various methods currently developed are approximations of gas characteristics within a certain spectral interval at different levels, and it is often difficult to take into account the dual effects of accuracy and efficiency.

[0008] The significance of solving the above problems and defects is that the method proposed by the present invention improves the problem that the traditional method is difficult to balance accuracy and efficiency, and the prediction parameters retain the detailed information of the spectrum line, which is easy to couple with the solution of the radiation transfer equation. This method is applicable to many fields such as heat transfer calculation of high-temperature combustion chambers, thermal protection and detection and identification of hypersonic targets, optical analysis and diagnosis, etc., and has important commercial and scientific value. Summary of the invention

[0009] In view of the problems existing in the prior art, the present invention provides a method, system, storage medium and device for measuring the radiation transmission characteristics of high-temperature gas.

[0010] The present invention is implemented as follows: a method for measuring the radiation transmission characteristics of a high-temperature gas, the method comprising: obtaining accurate gas radiation characteristic parameters; establishing a multi-width spectral band K distribution model; calculating optimized gas radiation characteristic parameters; establishing an optimized gas radiation characteristic parameter database; accurately predicting the gas radiation characteristic parameters under given conditions; calculating the emission intensity of radiation transmission; optimizing the solution of the radiation transmission equation by establishing a radiation characteristic parameter calculation model and accurately predicting the radiation transmission characteristic parameters,

[0011] Furthermore, the method for measuring the radiation transmission characteristics of high temperature gas comprises the following steps:

[0012] The first step is to obtain accurate gas radiation characteristic parameter spectrum: input ambient temperature T, pressure P, gas mole fraction Mf, gas molecular spectrum center wave number σ, line intensity S in the spectrum database σ , transition lower state energy E l , air broadening temperature dependence index N t 、Air widening half width L env and self-widening half width L selfAccording to the principle that Doppler broadening and Lorentz broadening are independent of each other, the Voigt line shape is used to determine the spectral line intensity S under non-standard conditions. σ (P, T) and line function F(σ-σ0), using the line-by-line integration model, calculate the exact absorption coefficient spectrum k(σ) after superposition;

[0013] The second step is to calculate the trend of the spectrum line of the precise gas radiation characteristic parameters: input the precise absorption coefficient spectrum line k(σ), the narrow band width Δσ, and calculate the fitting slope k'(σ) of the spectrum line at the wave number σ by the three-point derivation method;

[0014] The third step is to establish a multi-width spectral band K distribution model: input the precise absorption coefficient spectrum line k(σ), the spectrum line fitting slope k'(σ), the optimal slope critical value k'0, and the spectral band division bandwidth range Δσ min -Δσ max , establish a multi-width band K distribution model, and calculate the absorption coefficient spectrum line K(σ) under the optimal slope critical value k'0;

[0015] Step 4: Establish an optimized gas radiation characteristic parameter database: Input the ambient temperature range T1~T n , pressure range P1~P n , gas mole fraction distribution Mf1~Mf n Repeat the first step to the third step to establish different gradient temperatures T i , pressure P i , mole fraction Mf i The optimized absorption coefficient database K Ti,Pi,Mfi (σ);

[0016] Step 5: Calculate the gas radiation transmission characteristics based on the optimized radiation characteristic parameter database: Based on the optimized absorption coefficient database, the absorption coefficient K under given conditions is predicted by a three-dimensional linear interpolation algorithm. T*,P*,Mf* (σ); solve the radiation transfer equation and calculate the gas radiation emission intensity I(σ) along the LOS direction in the flow field by the apparent ray method (LOS).

[0017] Furthermore, the first step of obtaining accurate gas radiation characteristic parameter spectrum includes the following steps:

[0018] (1) Calculate the spectral line intensity S under non-standard conditions σ (P,T): Input pressure P0, temperature T0, line intensity S under standard conditions σ (P0, T0), flow field temperature T, pressure P, total partition function Q(T), transition low state energy E l , Planck constant h, speed of light c, Boltzmann constant k, obtain the intensity S of the spectral line at wave number σ σ (P,T);

[0019] (2) Calculate the broadening line function F(σ-σ0) of the spectral line with the central wave number σ0 at the wave number σ: Input the half-height width W of the spectral line of Doppler broadening, Lorentz broadening and Voigt line type d , W l and W v According to the principle that Doppler broadening and Lorentz broadening are independent of each other, the Voigt line shape function F(σ-σ0) is calculated by approximation;

[0020] (3) Calculate the precise gas absorption coefficient k of a single gas using the line-by-line integration model j (σ): Input spectral line intensity S under non-standard conditions σ (P, T) and linear function F(σ-σ0); superimpose the contribution of all absorption lines at wave number σ one by one to obtain the accurate gas absorption coefficient line k j (σ), j represents the type of gas;

[0021] (4) Calculate the exact absorption coefficient spectrum k(σ) of the mixed gas: For the mixed gas, combine (1) and (2) to obtain the exact absorption coefficient spectrum k of the single gas j: j (σ), and superimpose the contributions of all gas absorption lines at wave number σ one by one to obtain the precise absorption coefficient spectrum k(σ) of the mixed gas.

[0022] Furthermore, the second step of statistically accurately determining the gas radiation characteristic parameter spectrum trend comprises the following steps:

[0023] (1) Calculate the average absorption coefficient of the absorption coefficient spectrum at wave number σ Input the unit bandwidth Δσ, divide the spectrum line into multiple small narrow bands along the wave number σ direction with Δσ as the unit, take a single small narrow band as the minimum calculation unit, and calculate the average absorption coefficient at the center wave number σ

[0024] (2) Calculate the fitting slope k'(σ) of the absorption coefficient spectrum at wave number σ: Input the bandwidth Δσ, center wave number σ and average absorption coefficient of all small narrow bands Take the central wave number σ i The wave number σ of the adjacent i-1 , σ i+1 , the average absorption coefficient is k(σ i-1 ), k(σ i ), k(σ i+1 ), perform three-point derivation, and obtain the spectrum line at wave number σ i The fitting slope k'(σ i ), calculate the fitting slope k' of the spectrum line at all wave numbers σ in turn σ .

[0025] Further, the third step of establishing a multi-width spectral band K distribution model comprises the following steps:

[0026] (1) Calculate the optimal slope critical value k'0: Input the accurate gas absorption coefficient spectrum k(σ), slope critical value sample range k' min -k' max ; For each sample point k' i The gas absorption coefficient K is obtained by the multi-width band K distribution model i (σ), the modeling method of the multi-width band K distribution model is given in (2);

[0027] Use k(σ) to calculate the total transmittance τ at the transmission distance L, and count the program time t, and calculate the total transmittance τ and radiation intensity I based on k(σ) L The (σ) method is given in (4);

[0028] The total transmittance τ at the transmission distance L is calculated using Ki(σ) i and time t i , calculate the total transmittance τ and radiation intensity I based on K(σ) L The (σ) method is given in (5);

[0029] Statistics at sample point k' i The error ratio E of the two calculation results is i and time consumption ratio T i , the formula is as follows:

[0030] E i =|τ i -τ| / τ<E line ;

[0031] T i =(tt i ) / t>T line ;

[0032] Where E line is the maximum allowable error ratio, T line In order to improve the minimum time consumption ratio, the sample points that do not meet the conditions are discarded;

[0033] By using the data normalization method, the system performance P of each sample point is calculated. i :

[0034]

[0035] Count all sample point results so that the system performance P i The largest sample point k' i That is the optimal slope critical value k'0;

[0036] (2) Establish a multi-width spectral band K distribution model: input the accurate gas absorption coefficient spectrum line k(σ), the spectrum line fitting slope k'(σ), the slope critical value k'0, and the spectral band division bandwidth range Δσ min -Δσ max ; Along the direction of increasing wave number σ, the spectrum line k(σ) is divided into the spectrum segment Mi where the spectrum line fitting slope k'(σ) is less than the slope critical value k'0, and the spectrum segment Ma where the spectrum line fitting slope k'(σ) is greater than the slope critical value k'0;

[0037] For each Mi spectrum segment, the minimum bandwidth Δσ is divided according to the spectrum band min Divided into MMi small spectral bands; for each small spectral band, the K distribution method is used to obtain the spectral band center wave number σ Mi The absorption coefficient K Mi (σ Mi ), the K distribution method is given in (3);

[0038] For each Ma spectral band, the spectral band width Δσ is divided into the number of Divide into MMa large spectral bands; for each large spectral band, use the K distribution method to obtain the spectral band center wave number σ Ma The absorption coefficient K Ma (σ Ma );

[0039] Count the central wavenumbers and absorption coefficients of all spectral bands to obtain the optimized absorption coefficient spectrum line K(σ);

[0040] (3) Calculate the gas radiation characteristic parameter K using the spectral band K distribution method K (σ K ): Input the accurate gas absorption coefficient spectrum line k(σ) and wave number σ within the spectral band Δσ; introduce the Dirac-delta function δ(k), calculate its probability density function f(k) and cumulative distribution function g(k) for k(σ); use the Gauss-Lobatto 7-point integration method to obtain the 7 corresponding value points g in g(k) j A set of gas absorption coefficients K K (σ K ):K1-K7;

[0041] (4) Calculate the total transmittance τ and radiation intensity I based on k(σ) L (σ): Input the accurate gas absorption coefficient spectrum line k(σ) and wave number σ, and use k(σ) to calculate the radiation intensity I at the transmission distance L L (σ) and total transmittance τ;

[0042] (5) Calculate the total transmittance τ and radiation intensity I based on K(σ) L(σ): Input gas absorption coefficient K(σ): K1-K7, wave number σ; 7 weight parameters ω corresponding to Gauss-Lobatto 7-point integral j , the total transmittance τ is expressed as:

[0043]

[0044] Where i represents the i-th spectral band, N represents the number of all spectral bands; Kj K(σ) represents the j-th absorption coefficient Kj at wave number σ; Δσ represents the spectral band width at the center wave number σ;

[0045] For each wide spectral band, the spectral band width Δσ is divided into multiple small narrow bands with a width of Δσ0, the blackbody radiation intensity of each small narrow band is calculated, and the average blackbody radiation intensity I is taken. b (σ), the expression is:

[0046]

[0047] Furthermore, the fourth step of establishing an optimized gas radiation characteristic parameter database includes the following steps: inputting flow field data. Determining the database temperature, pressure, and mole fraction gradient according to the distribution of flow field temperature, pressure, and gas mole fraction, repeating the first step to the third step to establish different temperature T i , pressure P i , mole fraction Mf i Database of gas absorption coefficients optimized under gradient.

[0048] Furthermore, the fifth step of using the three-dimensional linear interpolation algorithm to predict the gas absorption coefficient spectrum under given conditions includes the following steps:

[0049] (1) Obtaining gas radiation characteristic parameter database data K(σ): Input flow field temperature T*, pressure P*, and mole fraction Mf*. Based on the temperature T, pressure P, and mole fraction Mf data points in the optimized gas absorption coefficient database, select the data points T1 and T2, P1 and P2, Mf1 and Mf2 in the database that are close to T*, P*, and Mf*, respectively. Take the eight gas absorption coefficients K in the database where T = T1 and T2, P = P1 and P2, and Mf = Mf1 and Mf2. Ti,Pi,Mfi (σ), i = 1-8;

[0050] (2) Predict the absorption coefficient spectrum K(σ) under given conditions: Input flow field temperature T*, pressure P*, mole fraction Mf*, database data points T1, T2, P1, P2, Mf1, Mf2, gas absorption coefficient K Ti,Pi,Mfi (σ), i = 1-8; predict the gas absorption coefficient spectrum K under given conditions through a three-dimensional linear interpolation algorithm T*,P*,Mf* (σ);

[0051] The fifth step of calculating the radiation emission intensity along the LOS direction in the flow field includes the following steps:

[0052] (1) Obtain the environmental variable Data in the flow field by using the LOS method: the flow field medium on the transmission path is divided into N layers, each layer is regarded as an isothermal and uniform medium, and the mean value of each flow field parameter in each layer is taken as Data1-DataN;

[0053] (2) Solve the radiation transfer equation: Input the absorption coefficient k(σ) at the σ wave number, and the radiation intensity I at the σ wave number in a specific direction σ , the blackbody radiation intensity I at the wave number σ in a specific direction bσ Ignoring scattering, the radiation transfer equation of the gas can be transformed by integrating to obtain the radiation intensity I of a ray along the LOS direction passing through the nth layer of flow field. n (σ);

[0054] (3) Calculate the radiation emission intensity I(σ): Starting from the wall, based on the flow field data and the radiation transfer recursion formula, calculate the radiation intensity I of the light passing through the nth layer layer by layer n (σ), and finally the radiation emission intensity I is obtained N (σ). According to the 7 weight parameters corresponding to the Gauss-Lobatto 7-point integral, the average radiation emission intensity I(σ) is obtained.

[0055] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for measuring the radiation transfer characteristics of high-temperature gas.

[0056] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the method for measuring the radiation transfer characteristics of high-temperature gas.

[0057] Another object of the present invention is to provide a high temperature gas radiation transfer characteristic measurement system for implementing the high temperature gas radiation transfer characteristic measurement method, the high temperature gas radiation transfer characteristic measurement system comprising:

[0058] Distribution model building module, used to obtain accurate gas radiation characteristic parameters; establish multi-width spectral band K distribution model;

[0059] Parameter calculation module, used to calculate optimized gas radiation characteristic parameters;

[0060] A database establishment module is used to establish an optimized gas radiation characteristic parameter database;

[0061] Gas radiation characteristic parameter prediction module, used to accurately predict the gas absorption coefficient under given conditions;

[0062] The emission intensity calculation module is used to calculate the emission intensity of radiation transmission.

[0063] Combining all the above technical solutions, the advantages and positive effects of the present invention are as follows: The present invention is applicable to the optimization method for calculating the radiation transfer characteristics of gases in high-temperature flow fields, characterized in that a high-temperature gas multi-width band K distribution model and a radiation transfer characteristic parameter prediction algorithm are designed, which improves the problem that traditional methods cannot take into account both calculation accuracy and efficiency. This method can realize high-reliability and high-efficiency calculation of gas radiation transfer characteristics in high-temperature flow fields, and can be used in multiple fields such as heat transfer calculation of high-temperature combustion chambers, thermal protection and detection and identification of hypersonic targets, optical analysis and diagnosis, etc., and has important scientific and commercial value.

[0064] In order to calculate the radiation characteristic parameters of high-temperature gases, the present invention provides a multi-width spectral band K distribution model modeling method to establish an efficient and reliable radiation characteristic parameter database under different conditions. The model calculates the radiation characteristic parameters and retains the detailed information of the spectral line such as spatial position, radiation intensity, wavelength, etc., which can be combined with the solution of any radiation transfer equation. The model can adjust the spectral band and bandwidth division range as needed, and is suitable for the calculation of radiation transfer characteristics within the characteristic spectrum and full spectrum range with different resolution requirements.

[0065] For given environmental conditions, the present invention proposes a radiation transfer characteristic parameter prediction algorithm, which flexibly predicts the radiation transfer characteristic parameters under given conditions based on database data. In high-temperature flow fields, high-reliability and high-efficiency gas radiation transfer characteristic calculations can be achieved, which improves calculation efficiency and ensures calculation accuracy. The calculation results can lay a data foundation for subsequent thermal performance analysis and target detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a flow chart of a method for measuring radiation transmission characteristics of high temperature gas provided in an embodiment of the present invention.

[0067] Figure 2 is a schematic structural diagram of a high-temperature gas radiation transmission characteristic measurement system provided by an embodiment of the present invention;

[0068] Figure 2 In: 1. Distribution model establishment module; 2. Parameter calculation module; 3. Database establishment module; 4. Gas radiation characteristic parameter prediction module; 5. Emission intensity calculation module.

[0069] Figure 3 It is a flow chart for implementing a method for measuring radiation transmission characteristics of high temperature gas provided in an embodiment of the present invention.

[0070] Figure 4 This is a diagram of the modeling method of the multi-width spectral band K distribution model in the present invention.

[0071] Figure 5 It is the accurate absorption coefficient spectrum of CO2 gas under given conditions obtained by the present invention.

[0072] Figure 6 It is a relationship diagram between the optimal slope critical value and temperature of CO2 gas under given conditions obtained by the present invention.

[0073] Figure 7 It is a relationship diagram between the optimal slope critical value and pressure of CO2 gas under given conditions obtained by the present invention.

[0074] Figure 8 It is a relationship diagram between the optimal slope critical value and the molar fraction of CO2 gas under given conditions obtained by the present invention.

[0075] Fig. 9 This is a diagram of the radiation emission intensity of the high-temperature mixed gas obtained by the present invention.

[0076] Fig.10 It is a gas radiation emission intensity diagram on a LOS line in a rocket plume obtained by the present invention.

[0077] Fig.11 This is a diagram showing the influence of the bandwidth range obtained in the present invention on the calculation efficiency and error of the multi-width spectral band K distribution model. DETAILED DESCRIPTION

[0078] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0079] In view of the problems existing in the prior art, the present invention provides a method, system, storage medium and device for measuring the radiation transmission characteristics of high-temperature gas. The present invention is described in detail below with reference to the accompanying drawings.

[0080] like Figure 1 As shown, the method for measuring the radiation transmission characteristics of high temperature gas provided by the present invention comprises the following steps:

[0081] S101: Obtain accurate gas radiation characteristic parameters; establish a multi-width band K distribution model;

[0082] S102: Calculate optimized gas radiation characteristic parameters;

[0083] S103: Establishing an optimized gas radiation characteristic parameter database;

[0084] S104: Accurately predict the gas radiation characteristic parameters of the gas under given conditions;

[0085] S105: Calculate the emission intensity of the radiation transmission.

[0086] The method for measuring the radiation transmission characteristics of high-temperature gas provided by the present invention can also be implemented by other steps by ordinary technicians in the industry. Figure 1 The method for measuring the radiation transmission characteristics of high-temperature gas provided by the present invention is only a specific embodiment.

[0087] like Figure 2 As shown, the high temperature gas radiation transmission characteristic measurement system provided by the present invention comprises:

[0088] Distribution model building module 1 is used to obtain accurate gas radiation characteristic parameters; establish a multi-width spectrum band K distribution model;

[0089] Parameter calculation module 2, used for calculating optimized gas radiation characteristic parameters;

[0090] Database establishment module 3, used to establish an optimized gas radiation characteristic parameter database;

[0091] Gas radiation characteristic parameter prediction module 4 is used to accurately predict the gas absorption coefficient under given conditions;

[0092] The emission intensity calculation module 5 is used to calculate the emission intensity of the radiation transmission.

[0093] The technical solution of the present invention is further described below in conjunction with specific embodiments.

[0094] Example 1

[0095] At present, relevant research on high-resolution spectral databases and radiation characteristic parameter calculation models for common types of gases already exists. However, with the development of aerospace technology, due to the complexity of the spatial background of radiation sources, it is necessary to obtain as much and accurate information as possible. At the same time, electronic countermeasures require speed and low complexity. Conventional models are difficult to balance accuracy and efficiency in the full spectrum. The present invention studies and discusses the optimization method for calculating the radiation transfer characteristics of high-temperature gases. The present invention aims to establish a multi-width band K distribution model, optimize the gas radiation characteristic parameter database, and realize flexible and accurate prediction of the radiation transfer characteristic parameters through a three-dimensional linear interpolation algorithm, thereby optimizing the calculation of the radiation transfer characteristics of high-temperature gases. The gas radiation characteristic parameters include absorption coefficient, emission coefficient, transmittance, etc., which can all be used for the calculation of radiation transmission. The present invention only takes the absorption coefficient as an example to calculate the radiation transmission.

[0096] like Figure 3As shown, the present invention is an optimized method for calculating the radiation transmission characteristics of high temperature gas, and the optimization algorithm includes the following steps:

[0097] Step 1: Obtain accurate gas radiation characteristic parameters (absorption coefficient) spectrum: input ambient temperature T, pressure P, gas mole fraction Mf, gas molecular spectrum center wave number σ, line intensity S in the spectrum database σ , transition lower state energy E l , air broadening temperature dependence index N t 、Air widening half width L env and self-widening half width L self According to the principle that Doppler broadening and Lorentz broadening are independent of each other, the Voigt line type is used to determine the spectral line intensity S under non-standard conditions. σ (P, T) and line function F(σ-σ0), and use the line-by-line integration model to calculate the exact absorption coefficient spectrum line k(σ) after superposition.

[0098] The present invention adopts a line-by-line integration model to perform superposition calculations on all absorption lines within the full spectral range, thereby obtaining an accurate gas absorption coefficient, which provides a basis for subsequent algorithm verification reliability and efficiency.

[0099] Step 2: Statistically calculate the trend of the gas radiation characteristic parameter spectrum line: input the precise absorption coefficient spectrum line k(σ), the narrow band width Δσ, and calculate the fitting slope k'(σ) of the spectrum line at the wave number σ through the three-point derivation method.

[0100] The present invention uses a three-point derivation method to perform statistics on the fitting slope of the spectrum line at the wave number σ, determines the precise gas absorption coefficient spectrum line trend, and provides a basis for subsequent spectrum segment division.

[0101] Step 3: Establish a multi-width spectral band K distribution model: input the precise absorption coefficient spectrum line k(σ), the spectrum line fitting slope k'(σ), the optimal slope critical value k'0, and the spectral band division bandwidth range Δσ min -Δσ max A multi-width band K distribution model is established, and the absorption coefficient spectrum line K(σ) under the optimal slope critical value k'0 is calculated.

[0102] The present invention optimizes the precise gas absorption coefficient data by establishing a multi-width spectral band K distribution model. Compared with the existing high-temperature gas radiation characteristic parameter calculation model, the calculation results of the multi-width spectral band K distribution model can improve the calculation efficiency while ensuring accuracy. It is also suitable for the optimization of the calculation of radiation transfer characteristics in the full spectrum, and is more in line with the actual situation of the analysis of the radiation transfer characteristics of the radiation source.

[0103] Step 4: Establish an optimized gas radiation characteristic parameter database: Input the ambient temperature range T1~T n , pressure range P1~Pn , gas mole fraction distribution Mf1~Mf n Repeat S1 to S3 to establish different gradient temperatures T i , pressure P i , mole fraction Mf i The optimized absorption coefficient database K Ti,Pi,Mfi (σ).

[0104] The present invention divides the data points into different gradients by analyzing the distribution of ambient temperature, pressure and mole fraction, and establishes an optimized gas radiation characteristic parameter database using a multi-width spectral band K distribution model, providing a data basis for subsequent radiation transmission characteristic calculations.

[0105] Step 5: Calculate the gas radiation transmission characteristics based on the optimized radiation characteristic parameter database: Based on the optimized absorption coefficient database, the absorption coefficient K under given conditions is predicted by a three-dimensional linear interpolation algorithm. T,P,Mf The radiation transfer equation is solved, and the gas radiation emission intensity I(σ) along the LOS direction in the flow field is calculated by the apparent ray method (LOS).

[0106] The present invention provides a flexible and accurate gas radiation transmission characteristic parameter prediction algorithm. The gas absorption coefficient under given conditions is predicted through a three-dimensional linear interpolation algorithm. The radiation transmission equation is solved based on the predicted gas absorption coefficient to obtain the radiation emission intensity, providing a data basis for subsequent thermal performance analysis and target detection.

[0107] The present invention provides a radiation characteristic parameter calculation model and a radiation transmission characteristic parameter prediction algorithm for optimizing the calculation of gas radiation transmission characteristics. The modeling method is as follows: Figure 4 As shown. By judging the trend of the precise gas radiation characteristic parameter spectrum line, a multi-width spectral band K distribution model is established, the gas radiation characteristic parameter data is optimized, and a gas radiation characteristic parameter database under different gradient temperatures, pressures, and mole fractions is established. Based on the database, a three-dimensional linear interpolation algorithm is used to flexibly and accurately predict the radiation transfer characteristic parameters under given conditions, thereby optimizing the solution of the radiation transfer equation, improving the calculation efficiency while ensuring the calculation accuracy, and obtaining the radiation emission intensity, providing a data basis for subsequent thermal performance analysis and target detection.

[0108] Example 2

[0109] The method for calculating the optimized high-temperature gas radiation transmission characteristics of the present invention is the same as that in Example 1. The first step of obtaining an accurate gas radiation characteristic parameter (absorption coefficient) spectrum line includes the following steps:

[0110] 2.1) Calculate the spectral line intensity S under non-standard conditions σ(P,T): The intensity S of the spectral line at wave number σ for temperature T and pressure P σ (P,T) can be expressed as:

[0111]

[0112] Among them, the pressure under standard conditions is P0 = 1.01325×10 5 Pa, temperature T0 = 296K; Planck constant h = 6.63 × 10 -34 J·s, speed of light c = 3×10 8 m / s, Boltzmann constant k = 1.3806505 × 10 -23 J / K;S σ (P0,T0) is the line intensity under standard conditions, unit: cm -2 The spectral databases HITRAN, HITEMP and CDSD provide the line intensity S of a single molecule at wave number σ. σ,M (P0, T0), unit: cm -1 / (molecule·cm -2 ), where S σ (P0,T0)=N L ·S σ,M (P0, T0), the number of molecules per unit volume under standard conditions N L =2.479×10 19 molecule cm -3 ; Q(T) is the total partition function, E l It is the low state energy of transition and can be obtained by querying the spectral database.

[0113] 2.2) Calculate the broadening line function F(σ-σ0) of the spectral line with the central wave number σ0 at the wave number σ: According to the independent characteristics of Doppler broadening and Lorentz broadening, the Voigt line shape approximation is used to calculate the broadening line function F(σ-σ0), and the expression is as follows:

[0114]

[0115]

[0116] Among them, W d , W l , W v are the half-width of the spectral line of Doppler broadening, Lorentz broadening and Voigt line type, respectively, and the expressions are as follows:

[0117]

[0118]

[0119] W v =W l ×0.5346+(W l 2 ×0.2166+W d 2 ) 1 / 2 (6)

[0120] m is the molecular mass; N t is the temperature dependence index of air broadening, L env The half width of air is L self is the self-broadening half-width, which can be obtained by querying the spectral database.

[0121] 2.3) Calculate the exact gas absorption coefficient k of a single gas using the line-by-line integration model j (σ): Input spectral line intensity S under non-standard conditions σ (P, T) and linear function F(σ-σ0). The contribution of all absorption lines at wave number σ is superimposed one by one to obtain the accurate gas absorption coefficient line k j (σ):

[0122]

[0123] Where i represents the i-th absorption line, and j represents the type of gas. The precise absorption coefficient line k of pure CO2 gas at 4000K and 1 standard atmospheric pressure is simulated. CO2 (σ) Figure 3 shown.

[0124] 2.4) Calculate the accurate absorption coefficient spectrum k(σ) of the mixed gas: For the mixed gas, repeat 2.1) and 2.2) to obtain the accurate absorption coefficient spectrum k of the single gas j j (σ), and superimpose the contribution of all gas absorption lines at wave number σ one by one to obtain the precise absorption coefficient line k(σ) of the mixed gas:

[0125]

[0126] Example 3

[0127] The method for calculating the optimized high-temperature gas radiation transmission characteristics of the present invention is the same as that of Embodiment 1-Embodiment 2. The second step of calculating the statistically accurate gas radiation characteristic parameter spectrum trend includes the following steps:

[0128] 3.1) Calculate the average absorption coefficient of the absorption coefficient spectrum at wave number σ Input the accurate gas absorption coefficient spectral line k(σ) and unit bandwidth Δσ, generally 0.5-2cm -1 The present invention takes 1cm -1The spectrum is divided into multiple small narrow bands along the wave number σ direction in units of Δσ, and a single small narrow band is used as the minimum calculation unit. The average absorption coefficient at the center wave number σ is The calculation formula is as follows:

[0129]

[0130] 3.2) Calculate the fitting slope k'(σ) of the absorption coefficient spectrum at wave number σ: Input the bandwidth Δσ, center wave number σ and average absorption coefficient of all small narrow bands Take the central wave number σ i The wave number σ of the adjacent i-1 , σ i+1 , the average absorption coefficient is k(σ i ), k(σ i-1 ), k(σ i+1 ), perform three-point derivation:

[0131]

[0132]

[0133]

[0134] Get the spectrum line at wave number σ i The fitting slope k'(σ i ). Calculate the fitting slope k'(σ) of the spectrum line at all wave numbers σ in sequence.

[0135] Example 4

[0136] The method for calculating the radiation transmission characteristics of high-temperature gas optimized by the present invention is the same as that of Examples 1 to 3. The third step of establishing a multi-width band K distribution model includes the following steps:

[0137] 4.1) Calculate the optimal slope critical value k'0: Input the accurate gas absorption coefficient spectrum k(σ), slope critical value sample range k' min -k' max , the present invention takes k' min =10 -7 , k' max =0.5. For each sample point k' i The gas absorption coefficient K is obtained by the multi-width band K distribution model i (σ), the modeling method of the multi-width spectral band K distribution model is given in 4.2).

[0138] Use k(σ) to calculate the total transmittance τ at the transmission distance L, and count the program time t, and calculate the total transmittance τ and radiation intensity I based on k(σ) L The process of (σ) is given in 4.4).

[0139] Using K i (σ) Calculate the total transmittance τ at the transmission distance L i and time t i , calculate the total transmittance τ and radiation intensity I based on K(σ) L The process of (σ) is given in 4.5).

[0140] Statistics at sample point k' i The error ratio E of the two calculation results is i and time consumption ratio T i , the formula is as follows:

[0141] E i =|τ i -τ| / τ<E line (13)

[0142] T i =(tt i ) / t>T line (14)

[0143] Where E line is the maximum allowable error ratio, T line In order to improve the minimum time consumption ratio, the present invention takes E line =5%, T line =90%, discarding sample points that do not meet the conditions.

[0144] Statistical error ratio range E of all sample points min -E max And the time ratio range T min -T max Through the data standardization method, in order to simplify the calculation, the present invention defines the error ratio and time consumption ratio weights as 0.5, and calculates the system performance P of each sample point i :

[0145]

[0146] Count all sample point results so that the system performance P i The largest sample point k' i This is the optimal slope critical value k'0.

[0147] The relationship between the optimal slope critical value and temperature of pure CO2 gas under 1 standard atmospheric pressure is as follows: Figure 6 As shown in the figure, the relationship between the optimal slope critical value and pressure of pure CO2 gas at 4000K is as follows Figure 7 As shown in the figure, the relationship between the optimal slope critical value and mole fraction of CO2 gas at 4000K and 1 standard atmospheric pressure is as follows: Figure 8 shown.

[0148] 4.2) Establish a multi-width spectral band K distribution model: input the accurate gas absorption coefficient spectrum line k(σ), the spectrum line fitting slope k'(σ), the slope critical value k'0, and the minimum bandwidth Δσ of the spectral band division min , maximum bandwidth Δσ max , the present invention takes Δσ min =25cm -1 , Δσ max =100cm -1 , N = 5. Along the direction of increasing wave number σ, the spectrum line k(σ) is divided into the spectrum segment Mi where the spectrum line fitting slope k'(σ) is less than the slope critical value k'0, and the spectrum segment Ma where the spectrum line fitting slope k'(σ) is greater than the slope critical value k'0.

[0149] For each Mi spectrum segment, the minimum bandwidth Δσ is divided according to the spectrum band min Divided into MMi small spectral bands; for each small spectral band, the K distribution method is used to obtain the spectral band center wave number σ Mi The absorption coefficient K Mi (σ Mi ), the K distribution method is given in 4.3).

[0150] For each Ma spectral band, the spectral band width Δσ is divided into the number of The K distribution method is used to obtain the center wave number σ of each large spectral band. Ma The absorption coefficient K Ma (σ Ma ).

[0151] The center wavenumbers and absorption coefficients of all spectral bands are counted to obtain the optimized absorption coefficient spectrum line K(σ).

[0152] 4.3) Calculate the gas radiation characteristic parameter K using the spectral band K distribution method K (σ K ): Input the accurate gas absorption coefficient line k(σ), wave number σ, center wave number σ within the spectral band Δσ K . Introduce the Dirac-delta function δ(k):

[0153]

[0154] For k(σ), its probability density function f(k) and cumulative distribution function g(k) can be expressed as:

[0155]

[0156]

[0157] in

[0158] Using the Gauss-Lobatto 7-point integration method, we get the 7 corresponding value points g in g(k): j A set of gas absorption coefficients K K (σ K ):K1-K7.

[0159] 4.4) Calculate the total transmittance τ and radiation intensity I based on k(σ) L (σ): Input the accurate gas absorption coefficient spectrum line k(σ) and wave number σ, and use k(σ) to calculate the radiation intensity I at the transmission distance L L (σ) and total transmittance τ formula are as follows:

[0160] I L (σ)=I0(σ)·exp(-k(σ)·L) (19)

[0161]

[0162] Where I0(σ) is the black body radiation intensity I b (σ), the calculation formula is as follows:

[0163]

[0164] The first radiation constant c1 = 2πhc 2 =3.74177×10 -16 W·m 2 , the second radiation constant c2=hc / k=1.43879×10 -2 m.K.

[0165] 4.5) Calculate the total transmittance τ and radiation intensity I based on K(σ) L (σ): Input gas absorption coefficient K(σ): K1-K7, wave number σ. According to the 7 weight parameters ω corresponding to the Gauss-Lobatto 7-point integral j , the total transmittance τ is expressed as:

[0166]

[0167] Where i represents the i-th spectral band, N represents the number of all spectral bands; Kj K(σ) represents the j-th absorption coefficient Kj at wave number σ; Δσ represents the spectral band width at the central wave number σ.

[0168] For each wide spectral band, the spectral band width Δσ is evenly divided into multiple small narrow bands with a width of Δσ0. The present invention defines Δσ0=5cm -1 , calculate the blackbody radiation intensity of each small narrow band and take the average blackbody radiation intensity I b(σ), the expression is:

[0169]

[0170] Example 5

[0171] The method for calculating the optimized high-temperature gas radiation transmission characteristics of the present invention is the same as that of Examples 1 to 4. The fourth step of establishing an optimized gas radiation characteristic parameter database includes the following steps:

[0172] 5.1) Database gradient division: The present invention takes the flow field data of the HTV2 aircraft at an altitude of H = 30-70km, a Mach number of M = 10-25, and an angle of attack of α = 0-20°. The temperature range of the database is set to 300-15000K, the gradient is 200K, and the data is divided into 74 data points at equal intervals, and the pressure range is 0-30000Pa, the gradient is 1000Pa, and the data is divided into 31 data points at equal intervals. For different gases, the mole fraction gradient division is also different.

[0173] The mole fraction of CO2 and CO is 10 -7 -10 -2 The data is divided into 6 data points in 10 -2 The range of -1 is divided into 10 data points with a 0.1 interval. The H2O mole fraction is divided into 4 data points at 0.1, 0.25, 0.4, and 0.6.

[0174] 5.2) Repeat S1 to S3 for each data point to establish an optimized gas absorption coefficient database.

[0175] Example 6

[0176] The method for calculating the radiation transmission characteristics of high-temperature gas optimized by the present invention is the same as that of Examples 1 to 5. The three-dimensional linear interpolation algorithm described in the fifth step predicts the gas absorption coefficient spectrum under given conditions, and includes the following steps:

[0177] 6.1) Obtain gas radiation characteristic parameter database data K(σ): Input flow field temperature T*, pressure P*, mole fraction Mf*, based on the temperature T, pressure P, mole fraction Mf data points in the optimized gas absorption coefficient database, select the temperature T1 and T2 near T*, the pressure P1 and P2 near P*, the mole fraction Mf1 and Mf2 near Mf* in the database, and take the 8 gas absorption coefficients K in the database with T=T1 and T2, P=P1 and P2, Mf=Mf1 and Mf2 Ti,Pi,Mfi (σ), i=1-8.

[0178] 6.2) Predict the absorption coefficient spectrum K(σ) under given conditions: Input flow field temperature T*, pressure P*, mole fraction Mf*, database data points T1, T2, P1, P2, Mf1, Mf2, gas absorption coefficient K Ti,Pi,Mfi (σ), i = 1-8. The gas absorption coefficient spectrum K under given conditions is predicted by a three-dimensional linear interpolation algorithm. T*,P*,Mf* (σ). The three-dimensional linear interpolation formula is as follows:

[0179] T d =(T * -T1) / (T2-T1) (24)

[0180] P d =(P * -P1) / (P2-P1) (25)

[0181] Mf d =(Mf * -Mf1) / (Mf2-Mf1) (26)

[0182]

[0183] Example 7

[0184] The method for calculating the radiation transmission characteristics of high-temperature gas optimized by the present invention is the same as that of Examples 1 to 6. The fifth step of calculating the radiation emission intensity along the LOS direction in the flow field includes the following steps:

[0185] 7.1) Obtaining environmental variables Data in the flow field by LOS method: Divide the flow field medium on the transmission path into N layers. For the convenience of calculation, the present invention takes an outgoing ray in the vertical wall direction of the HTV2 plume and divides it into 10 layers. Each layer is regarded as an isothermal and uniform medium. The mean value of each parameter of each layer of the flow field is expressed as Data1-Data10. Data1 is as follows Fig. 9 shown.

[0186] 7.2) Solve the radiation transfer equation: Ignoring scattering, the radiation transfer equation of gas can be expressed as:

[0187]

[0188] Where K(σ) is the absorption coefficient at the σ wave number; I σ is the radiation intensity at the wave number σ in a specific direction, s is the incident surface element of the light; I bσ is the blackbody radiation intensity at the σ wave number in a specific direction.

[0189] By performing an integral transformation on the equation, we can obtain the one-dimensional radiation transfer recursion formula along the LOS direction:

[0190]

[0191] Where n represents the nth layer in the flow field, and L is the distance between two layers; the parameter calculation is given in 4.4) and 4.5).

[0192] 7.3) Calculate the radiation emission intensity I(σ): Starting from the wall, based on the flow field data of 7.1) and the radiation transfer recursion formula of 7.2), calculate the radiation intensity of the light passing through the nth layer layer by layer, and finally get the radiation emission intensity I N (σ). According to the 7 weight parameters corresponding to the Gauss-Lobatto 7-point integral, the expression of the average radiation emission intensity I(σ) is:

[0193]

[0194] The technical effects of the present invention are described in detail below through simulation.

[0195] 1. Simulation conditions:

[0196] The emission spectrum in the rocket thruster plume was detected using a spectrometer TN6500. The thickness of the high-temperature flow field was 10 cm, the temperature was T = 2200 K, the pressure was 40 atm, the mole fractions of the mixed gases were 22.3% H2O, 9.2% CO2 and 8.6% CO, and the spectral database used was HITRAN.

[0197] 2. Simulation results and analysis:

[0198] Fig.10 This is a diagram of the gas radiation emission intensity on a LOS line in a rocket plume obtained by the present invention. The horizontal axis of Figure 10 represents the wave number, and the vertical axis represents the radiation intensity. The radiation transmission emission intensity of the mixed gas in the high-temperature flow field is calculated using the method proposed in this patent. The results are as follows: Fig.10 As shown. It can be seen that the predicted results are basically consistent with the measured results. At 3.5-4.0μm, the predicted results are slightly lower than the measured results, considering that the scattering is ignored in the calculation. Combined with the simulation results, it can be seen that the method of the present invention can well predict the high-temperature gas radiation emission intensity, providing a data basis for the subsequent radiation transmission characteristics analysis.

[0199] Fig.11 This is a graph showing the influence of the bandwidth range obtained by the present invention on the calculation efficiency and error of the multi-width spectral band K distribution model. Fig.11 The horizontal axis represents the bandwidth range of the spectrum band division, the vertical axis a represents the error ratio, and the vertical axis b represents the improved efficiency. Fig.11 Able to obtain a bandwidth of 300cm -1The error of the prediction results of the present invention is within 5% compared with the traditional line-by-line integration results, and the efficiency is improved by about 30% compared with the results of the traditional spectral band K distribution model. The traditional spectral band K distribution model is difficult to ensure the improvement of accuracy and efficiency in the full spectrum when measuring the radiation source. The multi-width spectral band K distribution model of the present invention can effectively solve this problem and lay the foundation for subsequent research on radiation transmission characteristics analysis.

[0200] In short, the present invention discloses an optimized method for calculating the radiation transfer characteristics of high-temperature gases. It mainly targets complex radiation sources and proposes a radiation transfer characteristics calculation optimization method that takes into account both accuracy and efficiency within the full spectrum. The implementation process is as follows: obtaining accurate gas radiation characteristic parameters; establishing a multi-width spectral band K distribution model; calculating optimized gas radiation characteristic parameters; establishing an optimized gas radiation characteristic parameter database; accurately predicting gas radiation characteristic parameters under given conditions; and calculating the emission intensity of radiation transmission. The present invention optimizes the solution of the radiation transmission equation by establishing an accurate and efficient radiation characteristic parameter calculation model and accurately predicting the radiation transmission characteristic parameters, thus avoiding the problem that the traditional spectral band model cannot take into account both accuracy and efficiency when calculating radiation transmission, and provides a new idea for the calculation of high-temperature gas radiation transmission characteristics.

[0201] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0202] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for measuring the radiation transmission characteristics of high temperature gas, characterized in that: The high-temperature gas radiation transmission characteristic determination method comprises: obtaining accurate gas radiation characteristic parameters; establishing a multi-width spectral band K distribution model; calculating optimized gas radiation characteristic parameters; establishing an optimized gas radiation characteristic parameter database; accurately predicting gas radiation transmission characteristic parameters under given conditions; calculating the emission intensity of radiation transmission; optimizing the solution of the radiation transmission equation by establishing a radiation characteristic parameter calculation model and accurately predicting the radiation transmission characteristic parameters; The method for measuring the radiation transmission characteristics of high temperature gas comprises the following steps: The first step is to obtain accurate gas radiation characteristic parameter spectrum: input ambient temperature T, pressure P, gas mole fraction Mf, gas molecular spectrum center wave number σ, line intensity S in the spectrum database σ , transition lower state energy E l , air broadening temperature dependence index N t 、Air widening half width L env and self-widening half width L self According to the principle that Doppler broadening and Lorentz broadening are independent of each other, the Voigt line shape is used to determine the spectral line intensity S under non-standard conditions. σ (P, T) and line function F(σ-σ0), using the line-by-line integration model, calculate the exact absorption coefficient spectrum k(σ) after superposition; The second step is to calculate the trend of the spectrum line of the precise gas radiation characteristic parameters: input the precise absorption coefficient spectrum line k(σ), the narrow band width Δσ, and calculate the fitting slope k'(σ) of the spectrum line at the wave number σ by the three-point derivation method; The third step is to establish the multi-width band K distribution MWBK model: input the precise absorption coefficient spectrum line k(σ), the spectrum line fitting slope k'(σ), the optimal slope critical value k'0, and the spectrum band division bandwidth range Δσ min -Δσ max , establish a multi-width band K distribution model, and calculate the absorption coefficient spectrum line K(σ) under the optimal slope critical value k'0; Step 4: Establish an optimized gas radiation characteristic parameter database: Input the ambient temperature range T1~T n , pressure range P1~P n , gas mole fraction distribution Mf1~Mf n Repeat the first step to the third step to establish different gradient temperatures T i , pressure P i , mole fraction Mf i The optimized absorption coefficient database K Ti,Pi,Mfi (σ); Step 5: Calculate the gas radiation transmission characteristics based on the optimized radiation characteristic parameter database: Based on the optimized absorption coefficient database, the absorption coefficient K under given conditions is predicted by a three-dimensional linear interpolation algorithm. T*,P*,Mf* (σ); solve the radiation transfer equation and calculate the gas radiation emission intensity I(σ) along the LOS direction in the flow field by the apparent ray method LOS; The first step of obtaining accurate gas radiation characteristic parameter spectrum includes the following steps: (1) Calculate the spectral line intensity S under non-standard conditions σ (P,T): Input pressure P0, temperature T0, line intensity S under standard conditions σ (P0, T0), flow field temperature T, pressure P, total partition function Q(T), transition low state energy E l , Planck constant h, speed of light c, Boltzmann constant k, obtain the intensity S of the spectral line at wave number σ σ (P,T); (2) Calculate the broadening line function F(σ-σ0) of the spectral line with the central wave number σ0 at the wave number σ: Input the half-height width W of the spectral line of Doppler broadening, Lorentz broadening and Voigt line type d , W l and W v According to the principle that Doppler broadening and Lorentz broadening are independent of each other, the Voigt line shape function F(σ-σ0) is calculated by approximation; (3) Calculate the precise gas absorption coefficient k of a single gas using the line-by-line integration model j (σ): Input spectral line intensity S under non-standard conditions σ (P, T) and linear function F(σ-σ0); superimpose the contribution of all absorption lines at wave number σ one by one to obtain the accurate gas absorption coefficient line k j (σ), j represents the type of gas; (4) Calculate the exact absorption coefficient spectrum k(σ) of the mixed gas: For the mixed gas, combine (1) and (2) to obtain the exact absorption coefficient spectrum k of the single gas j: j (σ), superimpose the contribution of all gas absorption lines at wave number σ one by one to obtain the precise absorption coefficient line k(σ) of the mixed gas; The second step of statistically accurately determining the gas radiation characteristic parameter spectrum trend comprises the following steps: (1) Calculate the average absorption coefficient of the absorption coefficient spectrum at wave number σ Input the unit bandwidth Δσ, divide the spectrum line into multiple small narrow bands along the wave number σ direction with Δσ as the unit, take a single small narrow band as the minimum calculation unit, and calculate the average absorption coefficient at the center wave number σ (2) Calculate the fitting slope k'(σ) of the absorption coefficient spectrum at wave number σ: Input the bandwidth Δσ, center wave number σ and average absorption coefficient of all small narrow bands Take the central wave number σ i The wave number σ of the adjacent i-1 , σ i+1 , the average absorption coefficient is k(σ i-1 ), k(σ i ), k(σ i+1 ), perform three-point derivation, and obtain the spectrum line at wave number σ i The fitting slope k'(σ i ), calculate the fitting slope k' of the spectrum line at all wave numbers σ in turn σ ; The third step of establishing a multi-width spectral band K distribution model comprises the following steps: (1) Calculate the optimal slope critical value k'0: Input the accurate gas absorption coefficient spectrum k(σ), slope critical value sample range k' min -k' max ; For each sample point k' i The gas absorption coefficient K is obtained by the multi-width band K distribution model i (σ), the modeling method of the multi-width band K distribution model is given in (2); Use k(σ) to calculate the total transmittance τ at the transmission distance L, and count the program time t, and calculate the total transmittance τ and radiation intensity I based on k(σ) L The (σ) method is given in (4); The total transmittance τ at the transmission distance L is calculated using Ki(σ) i and time t i , calculate the total transmittance τ and radiation intensity I based on K(σ) L The (σ) method is given in (5); Statistics at sample point k' i The error ratio E of the two calculation results is i and time consumption ratio T i , the formula is as follows: E i =t i -τ| / τ<E line ; T i =(t-t i ) / t>T line ; Where E line is the maximum allowable error ratio, T line In order to improve the minimum time consumption ratio, the sample points that do not meet the conditions are discarded; By using the data normalization method, the system performance P of each sample point is calculated. i : Count all sample point results so that the system performance P i The largest sample point k' i That is the optimal slope critical value k'0; (2) Establish a multi-width spectral band K distribution model: input the accurate gas absorption coefficient spectrum line k(σ), the spectrum line fitting slope k'(σ), the slope critical value k'0, and the spectral band division bandwidth range Δσ min -Δσ max ; Along the direction of increasing wave number σ, the spectrum line k(σ) is divided into the spectrum segment Mi where the spectrum line fitting slope k'(σ) is less than the slope critical value k'0, and the spectrum segment Ma where the spectrum line fitting slope k'(σ) is greater than the slope critical value k'0; For each Mi spectrum segment, the minimum bandwidth Δσ is divided according to the spectrum band min Divided into MMi small spectral bands; for each small spectral band, the K distribution method is used to obtain the spectral band center wave number σ Mi The absorption coefficient K Mi (σ Mi ), the K distribution method is given in (3); For each Ma spectral band, the spectral band width Δσ is divided into the number of Divide into MMa large spectral bands; for each large spectral band, use the K distribution method to obtain the spectral band center wave number σ Ma The absorption coefficient K Ma (σ Ma ); Count the central wavenumbers and absorption coefficients of all spectral bands to obtain the optimized absorption coefficient spectrum line K(σ); (3) Calculate the gas radiation characteristic parameter K using the spectral band K distribution method K (σ K ): Input the accurate gas absorption coefficient spectrum line k(σ) and wave number σ within the spectral band Δσ; introduce the Dirac-delta function δ(k), calculate its probability density function f(k) and cumulative distribution function g(k) for k(σ); use the Gauss-Lobatto 7-point integration method to obtain the 7 corresponding value points g in g(k) j A set of gas absorption coefficients K K (σ K ):K1-K7; (4) Calculate the total transmittance τ and radiation intensity I based on k(σ) L (σ): Input the accurate gas absorption coefficient spectrum line k(σ) and wave number σ, and use k(σ) to calculate the radiation intensity I at the transmission distance L L (σ) and total transmittance τ; (5) Calculate the total transmittance τ and radiation intensity I based on K(σ) L (σ): Input gas absorption coefficient K(σ): K1-K7, wave number σ; 7 weight parameters ω corresponding to Gauss-Lobatto 7-point integral j , the total transmittance τ expression is: Where i represents the i-th spectral band, N represents the number of all spectral bands; Kj K(σ) represents the j-th absorption coefficient Kj at wave number σ; Δσ represents the spectral band width at the center wave number σ; For each wide spectral band, the spectral band width Δσ is divided into multiple small narrow bands with a width of Δσ0, the blackbody radiation intensity of each small narrow band is calculated, and the average blackbody radiation intensity I is taken. b (σ), the expression is:

2. The method for measuring the radiation transmission characteristics of high temperature gas according to claim 1, characterized in that: The fourth step of establishing an optimized gas radiation characteristic parameter database includes the following steps: inputting flow field data, determining the database temperature, pressure, and mole fraction gradient according to the flow field temperature, pressure, and gas mole fraction distribution, repeating the first step to the third step, and establishing different temperature T i , pressure P i , mole fraction Mf i Database of gas absorption coefficients optimized under gradient.

3. The method for measuring the radiation transmission characteristics of high temperature gas according to claim 1, characterized in that: The fifth step of using the three-dimensional linear interpolation algorithm to predict the gas absorption coefficient spectrum under given conditions includes the following steps: (1) Obtaining gas radiation characteristic parameter database data K(σ): Input flow field temperature T*, pressure P*, and mole fraction Mf*. Based on the temperature T, pressure P, and mole fraction Mf data points in the optimized gas absorption coefficient database, select the data points T1 and T2, P1 and P2, Mf1 and Mf2 in the database that are close to T*, P*, and Mf*, respectively. Take the eight gas absorption coefficients K in the database where T = T1 and T2, P = P1 and P2, and Mf = Mf1 and Mf2. Ti,Pi,Mfi (σ), i = 1-8; (2) Predict the absorption coefficient spectrum K(σ) under given conditions: Input flow field temperature T*, pressure P*, mole fraction Mf*, database data points T1, T2, P1, P2, Mf1, Mf2, gas absorption coefficient K Ti,Pi,Mfi (σ), i = 1-8; predict the gas absorption coefficient spectrum K under given conditions through a three-dimensional linear interpolation algorithm T*,P*,Mf* (σ); The fifth step of calculating the radiation emission intensity along the LOS direction in the flow field includes the following steps: (1) Obtain the environmental variable Data in the flow field by using the LOS method: the flow field medium on the transmission path is divided into N layers, each layer is regarded as an isothermal and uniform medium, and the mean value of each flow field parameter in each layer is taken as Data1-DataN; (2) Solve the radiation transfer equation: Input the absorption coefficient k(σ) at the σ wave number, and the radiation intensity I at the σ wave number in a specific direction σ , the blackbody radiation intensity I at the wave number σ in a specific direction bσ Ignoring scattering, the radiation transfer equation of the gas can be transformed by integrating to obtain the radiation intensity I of a ray along the LOS direction passing through the nth layer of flow field. n (σ); (3) Calculate the radiation emission intensity I(σ): Starting from the wall, based on the flow field data and the radiation transfer recursion formula, calculate the radiation intensity I of the light passing through the nth layer layer by layer n (σ), and finally the radiation emission intensity I is obtained N (σ), and the average radiation emission intensity I(σ) is obtained according to the 7 weight parameters corresponding to the Gauss-Lobatto 7-point integral.

4. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for measuring the radiation transfer characteristics of high-temperature gas according to any one of claims 1 to 3.

5. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the method for measuring the radiation transfer characteristics of a high temperature gas according to any one of claims 1 to 3.

6. A high temperature gas radiation transfer characteristic measurement system for implementing the high temperature gas radiation transfer characteristic measurement method according to any one of claims 1 to 3, characterized in that: The high temperature gas radiation transmission characteristic measurement system comprises: Distribution model building module, used to obtain accurate gas radiation characteristic parameters; establish multi-width spectral band K distribution model; Parameter calculation module, used to calculate optimized gas radiation characteristic parameters; A database establishment module is used to establish an optimized gas radiation characteristic parameter database; Gas radiation characteristic parameter prediction module, used to accurately predict the gas absorption coefficient under given conditions; The emission intensity calculation module is used to calculate the emission intensity of radiation transmission.

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