Boiler water wall temperature multi-field coupling calculation method based on python script driving

Abstract

The invention discloses a boiler water-cooled wall temperature multi-field coupling calculation method based on python script driving, and belongs to the technical field of boiler water-cooled wall temperature simulation. The method comprises the steps that firstly, Fluent is used for simulating the flowing and combustion process of the smoke side in a hearth, and heat flux density distribution of the inner wall face of a water cooling wall is obtained; meanwhile, a working medium side flow and heat transfer calculation model is built, and the temperature field of the working medium in the water wall tube is solved. Data interaction between the two calculation models is achieved by writing a Python script, specifically, the heat flow density obtained on the smoke side serves as the heat boundary condition of the working medium side to be input, and meanwhile the working medium temperature obtained through calculation on the working medium side is fed back to the combustion side to be used for updating the boundary condition or physical property parameters. Bidirectional coupling solution of the flue gas side and the working medium side is achieved through iterative calculation, and the thermal coupling effect between two-phase physical fields is fully considered. The method can reflect the influence of operation working conditions such as different loads and combustion modes on the temperature distribution of the water-cooled wall, and is suitable for temperature field analysis of the boiler water-cooled wall under various working conditions.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of boiler wall temperature simulation calculation, and particularly relates to a boiler water cooling wall temperature multi-field coupling calculation method based on a python script driving. BACKGROUND

[0002] With the deepening of global energy-saving and emission-reducing policies, the installed capacity and power generation of new energy power generation show a rapid growth trend, and occupy an increasingly important position in the power supply system. However, due to the significant volatility and intermittency characteristics of new energy power generation, in the actual power grid operation process, it is often necessary to rely on thermal power units for peak shaving operation to ensure that new energy power can be large-scale and stable connected to the power grid system. Under this background, realizing the safe and stable operation of the boiler under low load conditions becomes one of the key prerequisites for deep peak shaving. Under low load conditions, due to the uneven distribution of the flame in the furnace, insufficient combustion power, and low system pressure, and other factors, it may lead to large steam temperature differences in the heating surface, which not only accelerates the aging process of the metal tube wall, but also may cause serious safety accidents such as over-temperature pipe explosion. Accurate control of the heating surface tube wall temperature is crucial to prevent pipe degradation and leakage accidents. Specifically, overheating of the tube wall can easily cause metal creep, oxidation, and high-temperature corrosion, which seriously affects the performance and service life of the boiler.

[0003] However, considering that the structure of large power plant boilers is large and in an extremely high temperature environment, it is difficult to implement a dense measurement point arrangement scheme, so it is not possible to monitor the temperature changes at each location of the heating surface in real time and accurately. Current numerical simulation research on boilers mostly focuses on the analysis of the combustion process inside the furnace, while the discussion of the working fluid flow and heat transfer characteristics is relatively simplified, usually assuming that the working fluid temperature or tube wall temperature is a fixed value. This modeling method ignores the complex interaction mechanism between the combustion on the flue gas side and the heat transfer on the working fluid side, making it difficult to accurately predict and effectively control the actual conditions of the boiler heating surface wall temperature, which is not conducive to timely discovering and solving the over-temperature problems that may occur in local areas. SUMMARY

[0004] In view of the problems existing in the prior art, the application provides a boiler water cooling wall temperature multi-field coupling calculation method based on a python script driving. This method establishes a collaborative calculation model of the flue gas side and the working fluid side, comprehensively considers the influence of the heat transfer process on both sides on the water cooling wall temperature distribution, and can obtain the temperature distribution results along the axial direction of the water cooling wall pipe, which helps to identify the areas that may exist local over-temperature, and provides data support for the operation analysis and structure improvement of the water cooling wall.

[0005] To achieve the above-mentioned purpose, the application provides a boiler water cooling wall temperature multi-field coupling calculation method based on a python script driving, which includes the following steps:

[0006] Step 1: Constructing the full furnace geometry model of the boiler and setting the initial boundary conditions

[0007] A three-dimensional geometric model is established according to the actual structural size of the boiler, and a physical model suitable for the coal combustion process is selected, including turbulence model, EDM combustion model, random track particle tracking model, double reaction competition model of coal pyrolysis, and dynamic / diffusion control model of coke combustion; the radiation heat transfer adopts P1 model, and the discrete format of all transport equations is set to first-order upwind format; the inlet mass flow, outlet pressure, wall type and initial working medium temperature are set, and the water wall surface is simplified as a two-dimensional wall with no thickness, and the initialization is carried out by using the convective heat transfer boundary condition. The gas phase turbulence and radiation calculation formulae are as follows:

[0008]

[0009] wherein, ρ is the fluid density, k is the turbulent kinetic energy, t is the time, U i is the component of the fluid velocity in the i direction, x i , x j is the spatial coordinate direction, μ is the dynamic viscosity of the fluid, μ t is the turbulent viscosity, σ k is the turbulent kinetic energy diffusion rate, P k is the turbulent kinetic energy generation term due to the average velocity gradient, P b is the turbulent kinetic energy generation term due to the buoyancy effect, ρε is the turbulent energy dissipation rate, S k is the user-defined source term.

[0010]

[0011]

[0012] wherein, F is the radiation flux vector, σ is the coefficient related to the optical properties of the medium, is the gradient of the radiation intensity I, I is the radiation intensity, is the Laplacian operator acting on the radiation intensity I, indicating the second-order spatial derivative of the radiation intensity, Q is the radiation source term.

[0013] Step 2: Perform the furnace combustion simulation and extract the heat flux density data

[0014] The steady-state numerical simulation of the full furnace combustion is completed in Fluent, and the flue gas temperature field, velocity field and heat flux density distribution of the heating surface wall in the furnace are obtained; after the simulation converges, the post-processing data file is read by Python script, the heat flux density values of each unit surface of the water wall are automatically extracted, and they are exported as structured data format, which is used for subsequent working medium side calculation.

[0015] Step 3: Divide the water-cooled wall calculation domain and establish the working fluid side heat transfer model

[0016] The boiler water-cooled wall is divided into multiple calculation regions along the working fluid flow direction, and the helical water-cooled wall is divided into grid in the inclined direction and the horizontal direction according to the actual helix angle; the three-dimensional water-cooled wall is unfolded into a two-dimensional plane in the Python environment, and each region is numbered according to the working fluid flow direction; based on the energy conservation equation, the total heat flow absorbed by each region and the working fluid mass flow are combined to calculate the working fluid enthalpy at the outlet of each region, and the interpolation is performed to obtain the property parameters such as specific heat capacity, viscosity, and thermal conductivity at the corresponding pressure and temperature through the IAPWS-IF97 international water and steam property standard.

[0017]

[0018] wherein Q is the heat flow absorbed by the calculation region; m is the working fluid flow through the calculation region; h in and h out are the inlet enthalpy and outlet enthalpy of the calculation region, respectively.

[0019] Step 4: Calculate the convective heat transfer coefficient and update the boundary conditions

[0020] The dimensionless numbers Prandtl number and Reynolds number are calculated according to the obtained parameters, and the corresponding correlation equation is selected according to the Reynolds number range to calculate the Nusselt number: for laminar flow (Re<2300), use Nu=4.36; for transition flow (2300≤Re<10000), use Seider-Tate equation; for turbulent flow (Re≥10000), select Gnielinski equation or Dittus-Boelter equation according to the Prandtl number range; the calculation equations of different flow stages are as follows:

[0021]

[0022]

[0023]

[0024] wherein H s is the convective heat transfer coefficient in the tube, Re is a dimensionless number, Reynolds number, Pr is a dimensionless number, Prandtl number, the value of n depends on the influence of temperature on the properties of the fluid, f is the friction factor, k is the thermal conductivity of the fluid, d is the characteristic length, which is the inner diameter of the pipe for circular pipes, Nu is a dimensionless number, Nusselt number, and the convective heat transfer coefficient can be obtained by calculating Nu, wherein the calculation of Nu is as follows,

[0025]

[0026] Step 5: Iterative solution and coupling convergence judgment

[0027] The outlet working fluid temperature of each region calculated in the current iteration is compared with the result of the previous iteration. If the maximum temperature difference is less than 1K, the calculation is considered to have converged and proceed to the next step. Otherwise, the arithmetic mean of the current outlet temperature and the inlet temperature is used as the new wall fluid temperature boundary condition, which is fed back to the Fluent model to update the water-cooled wall boundary condition. Then, step 2 is returned to re-execute the combustion simulation and data extraction until the convergence criterion is met.

[0028] Step 6: Calculate the temperature distribution on the water-cooled wall tubes.

[0029] After the coupled calculations converge, based on the final heat flux density q and working fluid temperature T f Pipe wall thickness δ m and the thermal conductivity k of the material m The temperature T of the inner wall of the water-cooled wall is calculated point by point using the following formula. w :

[0030]

[0031] Among them, T w T represents the wall temperature. f δ is the working fluid temperature; q is the heat flow rate; m For pipe wall thickness; k m The thermal conductivity of the pipe is used. Finally, a three-dimensional wall temperature distribution map of the entire water-cooled wall is generated for overheat risk identification and structural safety assessment.

[0032] Furthermore, in step 2, the heat flux density distribution data of the furnace heating surface is automatically extracted by calling the Fluent simulation results through a Python script, and used as the thermal boundary condition input for the working fluid side heat transfer model, realizing data transfer driven by an external script. The outlet working fluid temperature calculated on the working fluid side is fed back to the combustion side to update the convective heat transfer boundary conditions of the water-cooled wall in the next iteration, realizing bidirectional coupling.

[0033] Furthermore, in step 3, the three-dimensional water-cooled wall geometry is unfolded into a two-dimensional plane in the Python environment, and each region is numbered and managed according to the working fluid flow direction to facilitate regional heat transfer calculation.

[0034] Furthermore, in step 3, the physical property table of water is called through Python, and the physical property parameters such as density, specific heat capacity, viscosity and thermal conductivity of the working fluid are obtained by interpolation based on the pressure and temperature of the calculation area.

[0035] Furthermore, in step 4, based on the obtained working fluid properties, the Reynolds number and Prandtl number of each region are calculated, and the Nusselt number (Nu) is determined by selecting the appropriate empirical correlation according to the flow state (laminar, transitional, or turbulent), thereby solving for the convective heat transfer coefficient inside the pipe. For laminar flow (Re < 2300), Nu = 4.36 is used; for transitional flow (2300 ≤ Re < 10000), the Seider-Tate equation is used; for turbulent flow (Re ≥ 10000), the Gnielinski equation or the Dittus-Boelter equation is selected based on the Pr value range. The calculation equations for different flow stages are as follows:

[0036] The equation for calculating the convective heat transfer coefficient in the laminar flow stage is as follows:

[0037]

[0038] The equation for calculating the Nusselt number in the transition flow stage is as follows:

[0039]

[0040] The equation for calculating the Nusselt number in the turbulent flow stage is as follows:

[0041]

[0042] Among them, H s is the convective heat transfer coefficient inside the pipe, Re is a dimensionless number (Reynolds number), Pr is a dimensionless number (Prantz number), the value of n depends on the effect of temperature on fluid properties, f is the friction factor, k is the thermal conductivity of the fluid, d is the characteristic length (for circular pipes, this is the inner diameter of the pipe), and Nu is a dimensionless number (Nusel number). The convective heat transfer coefficient can be obtained by calculating Nu, where Nu is calculated as follows:

[0043]

[0044] In summary, the beneficial effects of the above-described technical solutions conceived by this invention compared with the prior art include:

[0045] (1) This invention realizes bidirectional data interaction between Fluent combustion simulation and working fluid side heat transfer calculation through Python script, takes the three-dimensional non-uniform heat flux density on the flue gas side as the accurate thermal boundary on the working fluid side, and updates the boundary conditions on the combustion side with the temperature feedback obtained from the dynamic calculation on the working fluid side. This overcomes the simplification defects of assuming constant wall temperature or working fluid temperature in traditional methods, fully considers the mutual influence between the combustion process and the working fluid heat transfer, and significantly improves the accuracy of water-cooled wall temperature prediction.

[0046] (2) In the coupling process, the present invention feeds back the working fluid temperature along the pipe and between pipes obtained from the working fluid side calculation to the flue gas side model as the wall thermal boundary condition, overcoming the error caused by the common use of constant or uniform working fluid temperature in traditional flue gas side simulation. This two-way data interaction mechanism fully considers the influence of steam temperature deviation on furnace radiative heat transfer and wall energy balance in actual operation, making the flue gas side heat flow prediction closer to the real physical process, and further enhancing the accuracy of the overall wall temperature calculation.

[0047] (3) In view of the geometric characteristics of the spiral water-cooled wall of the boiler, the present invention unfolds its three-dimensional surface into a two-dimensional plane in Python, and performs fine regional division along the flow direction and spiral angle. Combined with the energy conservation of the partition and the correlation calculation of the segmented heat transfer, it effectively captures the local heat transfer difference. It is especially suitable for predicting the wall temperature distribution under complex working conditions such as variable load and asymmetric combustion, and provides a reliable basis for preventing local overheating and optimizing the design of water-cooled wall. Attached Figure Description

[0048] Figure 1 This is a flowchart of a multi-field coupling calculation method for boiler water-cooled wall temperature driven by Python scripts;

[0049] Figure 2 This is a schematic diagram of the boiler structure in an embodiment of the present invention;

[0050] Figure 3 This is a grid diagram of the boiler structure in an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram of the two-dimensional flow unfolding on the spiral water-cooled wall surface of the furnace in an embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of the temperature distribution of the spiral water-cooled wall tube in an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use.

[0054] Example 1

[0055] A method for multi-field coupled calculation of boiler water-cooled wall temperature based on Python scripts includes the following steps:

[0056] Step 1: Construct the full furnace geometry model of the boiler and set the initial boundary conditions.

[0057] A three-dimensional geometric model was established based on the actual structural dimensions of the boiler, and a physical model suitable for the pulverized coal combustion process was selected, including... Turbulence model, EDM combustion model, stochastic orbit particle tracking model, dual-reaction competition model for coal pyrolysis, and dynamic / diffusion control model for coke combustion were used. Radiative heat transfer adopted the P1 model, and the discretization scheme for all transport equations was set to first-order upwind scheme. Inlet mass flow rate, outlet pressure, wall type, and initial working fluid temperature were defined, and the water-cooled wall surface was simplified to a two-dimensional wall with no thickness, initialized using convective heat transfer boundary conditions. The formulas for calculating gas-phase turbulence and radiation are as follows:

[0058]

[0059] Where ρ is the fluid density, k is the turbulent kinetic energy, an important parameter describing the intensity of turbulence, t is time, and U... i It is the component of the fluid velocity in the i-direction, x i ,x j It represents the spatial coordinate direction, μ is the dynamic viscosity of the fluid, μ t It is the turbulent viscosity, σ k It is the turbulent kinetic energy diffusivity, a dimensionless number, P. k The turbulent kinetic energy generation term P is due to the average velocity gradient. b The turbulent kinetic energy generation term is due to the buoyancy effect, where ρε is the turbulent energy dissipation rate, and S... k It is a user-defined source item.

[0060]

[0061]

[0062] Where F is the radiation flux vector, and σ is a coefficient related to the optical properties of the medium. It is the gradient of radiation intensity I, where I is radiation intensity. I is the Laplace operator applied to the radiation intensity I, represents the second spatial derivative of the radiation intensity, and Q is the radiation source term.

[0063] In actual operation, the boiler is modeled according to the boiler dimensions in the boiler design specification. The boiler structure includes water-cooled walls, burners, cold ash hoppers, economizers, superheaters, and reheaters, and its heating surfaces are preferably simplified. Figure 2 As shown.

[0064] When setting boundary conditions, it is preferable to set all inlets as velocity inlets and to set uniform output and air distribution for each burner. Meanwhile, a pressure outlet is preferred for the furnace outlet. Considering the characteristic of a power plant boiler exhibiting negative pressure inside the furnace under the action of the induced draft fan, its pressure parameter is preferably set to -20 Pa.

[0065] The furnace wall is set as a no-slip boundary condition, and the water-cooled wall and superheater are set as convective heat transfer boundary conditions. The water-cooled wall is set with a wall thickness of 0.0075m, and the thermal conductivity of the simulated wall material is modified according to the actual pipe material. The initial calculation is based on the working fluid temperature and convective heat transfer coefficient given in the thermodynamic calculation book.

[0066] Step 2: Perform furnace combustion simulation and extract heat flux density data

[0067] A steady-state numerical simulation of combustion in the entire furnace was performed in Fluent to obtain the temperature field, velocity field, and heat flux density distribution of the flue gas inside the furnace and the wall surface of the heated surface. After the simulation converged, the post-processed data file was read by a Python script, the heat flux density values ​​of each unit surface of the water-cooled wall were automatically extracted, and the data was exported as a structured data format for subsequent working fluid side calculations.

[0068] Step 3: Define the computational domain of the water-cooled wall and establish a heat transfer model on the working fluid side.

[0069] The boiler water-cooled wall is divided into multiple computational regions along the working fluid flow direction. The spiral water-cooled wall is meshed in the inclined and horizontal directions according to the actual spiral helix angle. In the Python environment, the three-dimensional water-cooled wall is unfolded into a two-dimensional plane, and each region is numbered according to the working fluid flow direction. Figure 4 This is a schematic diagram of the two-dimensional flow unfolding on the spiral water-cooled wall surface of the furnace in an embodiment of the present invention.

[0070] Based on the energy conservation equation, and combining the total heat flow absorbed by the region with the mass flow rate of the working fluid, the enthalpy of the working fluid at the outlet of each region is calculated. Then, by interpolation using the IAPWS-IF97 international standard for water and steam properties, the specific heat capacity, viscosity, thermal conductivity and other physical property parameters at the corresponding pressure and temperature are obtained.

[0071]

[0072] Where Q is the heat flow absorbed by the computational domain; m is the flow rate of the working fluid flowing through the computational domain; h in and h out These are the inlet enthalpy and outlet enthalpy of the calculation region, respectively.

[0073] Step 4: Calculate the convective heat transfer coefficient and update the boundary conditions.

[0074] Based on the obtained working fluid properties, the Reynolds number and Prandtl number for each region are calculated. The Nusselt number (Nu) is determined by selecting the appropriate empirical correlation according to the flow state (laminar, transitional, or turbulent), and then the convective heat transfer coefficient inside the pipe is solved. For laminar flow (Re < 2300), Nu = 4.36 is used; for transitional flow (2300 ≤ Re < 10000), the Seider-Tate equation is used; for turbulent flow (Re ≥ 10000), the Gnielinski equation or the Dittus-Boelter equation is selected based on the Pr value range. The calculation equations for different flow stages are as follows:

[0075]

[0076]

[0077]

[0078] Among them, H s is the convective heat transfer coefficient inside the pipe, Re is a dimensionless number (Reynolds number), Pr is a dimensionless number (Prantz number), the value of n depends on the effect of temperature on fluid properties, f is the friction factor, k is the thermal conductivity of the fluid, d is the characteristic length (for circular pipes, this is the inner diameter of the pipe), and Nu is a dimensionless number (Nusel number). The convective heat transfer coefficient can be obtained by calculating Nu, where Nu is calculated as follows:

[0079]

[0080] Step 5: Iterative solution and coupling convergence judgment

[0081] The outlet working fluid temperature of each region calculated in the current iteration is compared with the result of the previous iteration. If the maximum temperature difference is less than 1K, the calculation is considered to have converged and proceed to the next step. Otherwise, the arithmetic mean of the current outlet temperature and the inlet temperature is used as the new wall fluid temperature boundary condition, which is fed back to the Fluent model to update the water-cooled wall boundary condition. Then, step 2 is returned to re-execute the combustion simulation and data extraction until the convergence criterion is met.

[0082] Step 6: Calculate the temperature distribution on the water-cooled wall tubes.

[0083] After the coupled calculations converge, based on the final heat flux density q and working fluid temperature T f Pipe wall thickness δ m and the thermal conductivity k of the material m The temperature T of the inner wall of the water-cooled wall is calculated point by point using the following formula. w :

[0084]

[0085] Among them, Tw T represents the wall temperature. f δ is the working fluid temperature; q is the heat flow rate; m For pipe wall thickness; k m The thermal conductivity of the pipe is given. A three-dimensional wall temperature distribution map of the entire water-cooled wall is generated for overheat risk identification and structural safety assessment. Results are as follows: Figure 5 A schematic diagram of the temperature distribution of the spiral water-cooled wall tube in an embodiment of the present invention.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for multi-field coupled calculation of boiler water-cooled wall temperature based on Python scripts, characterized in that, Includes the following steps: Step 1: Construct the full furnace geometry model of the boiler and set the initial boundary conditions. Step 2: Perform furnace combustion simulation and extract heat flux density data A steady-state numerical simulation of combustion in the entire furnace was performed in Fluent to obtain the temperature field, velocity field, and heat flux density distribution of the flue gas inside the furnace and the wall surface of the heated surface. After the simulation converged, the post-processed data file was read by a Python script, the heat flux density values ​​of each unit surface of the water-cooled wall were automatically extracted, and the data was exported as a structured data format for subsequent working fluid side calculations. Step 3: Define the computational domain of the water-cooled wall and establish a heat transfer model on the working fluid side. The boiler water-cooled wall is divided into multiple computational regions along the working fluid flow direction. The spiral water-cooled wall is meshed in the inclined and horizontal directions according to the actual spiral helix angle. In the Python environment, the three-dimensional water-cooled wall is unfolded into a two-dimensional plane, and each region is numbered according to the working fluid flow direction. Based on the energy conservation equation, combined with the total heat flow absorbed by the region and the working fluid mass flow rate, the enthalpy of the working fluid at the outlet of each region is calculated. By interpolating from the property tables, the specific heat capacity, viscosity, and thermal conductivity parameters at the corresponding pressure and temperature can be obtained. Step 4: Calculate the convective heat transfer coefficient and update the boundary conditions. Based on the obtained working fluid physical property parameters, the Reynolds number and Prandtl number of each region are calculated, and the Nusselt number is determined by selecting the corresponding empirical correlation according to the flow state, and then the convective heat transfer coefficient in the pipe is solved. Step 5: Iterative solution and coupling convergence judgment Compare the outlet working medium temperature of each region calculated in the current iteration with the result of the previous iteration. If the maximum temperature difference is less than 1K, the calculation is considered to have converged and proceed to the next step. Otherwise, the arithmetic mean of the current outlet temperature and inlet temperature is used as the new wall fluid temperature boundary condition, which is fed back into the Fluent model to update the water-cooled wall boundary condition, and then the combustion simulation and data extraction are re-executed in step 2 until the convergence criterion is met. Step 6: Calculate the temperature distribution on the water-cooled wall tubes. After the coupled calculations converge, based on the final heat flux density q and working fluid temperature T f Pipe wall thickness δ m and the thermal conductivity k of the material m The temperature T of the inner wall of the water-cooled wall is calculated point by point using the following formula. w : ； Among them, T w T represents the wall temperature. f q represents the working fluid temperature; q represents the heat flow rate. For pipe wall thickness; k m The thermal conductivity of the pipe is used to generate a three-dimensional wall temperature distribution map of the entire water-cooled wall.

2. The calculation method according to claim 1, characterized in that, Step S1 specifically involves: establishing a three-dimensional geometric model based on the actual structural dimensions of the boiler, and selecting a physical model suitable for the pulverized coal combustion process, including... Turbulence model, EDM combustion model, stochastic orbit particle tracking model, dual-reaction competition model for coal pyrolysis, and dynamic / diffusion control model for coke combustion were used. Radiative heat transfer adopted the P1 model, and the discretization scheme for all transport equations was set to first-order upwind scheme. Inlet mass flow rate, outlet pressure, wall type, and initial working fluid temperature were defined, and the water-cooled wall surface was simplified to a two-dimensional wall with no thickness, initialized using convective heat transfer boundary conditions. The formulas for calculating gas-phase turbulence and radiation are as follows: ； Where ρ is the fluid density, k is the turbulent kinetic energy, t is time, and U i It is the component of the fluid velocity in the i-direction, x i ,x j It represents the spatial coordinate direction, μ is the dynamic viscosity of the fluid, μ t It is the turbulent viscosity, σ k It is the turbulent kinetic energy diffusivity, P k The turbulent kinetic energy generation term P is due to the average velocity gradient. b The turbulent kinetic energy generation term, ρ, is due to the buoyancy effect. ε It is the turbulent energy dissipation rate, S k It is a user-defined source item; ； ； Where F is the radiation flux vector, and σ is a coefficient related to the optical properties of the medium. It is the gradient of radiation intensity I, where I is radiation intensity. I is the Laplace operator applied to the radiation intensity I, represents the second spatial derivative of the radiation intensity, and Q is the radiation source term.

3. The calculation method according to claim 2, characterized in that, In step 2, the heat flux density distribution data of the furnace heating surface is automatically extracted by calling the Fluent simulation results through a Python script, and used as the thermal boundary condition input of the working fluid side heat transfer model to realize data transmission driven by external script; the outlet working fluid temperature calculated on the working fluid side is fed back to the combustion side to update the convective heat transfer boundary condition of the water-cooled wall in the next iteration, realizing bidirectional coupling.

4. The calculation method according to claim 3, characterized in that, In step 3, the enthalpy of the working fluid is calculated as follows: ； Where Q is the heat flow absorbed by the computational domain; m is the flow rate of the working fluid flowing through the computational domain; h in and h out These are the inlet enthalpy and outlet enthalpy of the calculation region, respectively.

5. The calculation method according to claim 4, characterized in that, In step 4, the flow state is laminar flow, transitional flow, or turbulent flow.

6. The calculation method according to claim 5, characterized in that, In step 4, for laminar flow Re < 2300, Nu = 4.36 is used; for transitional flow 2300 ≤ Re < 10000, the Seider-Tate equation is used; for turbulent flow Re ≥ 10000, the Gnielinski equation or the Dittus-Boelter equation is selected according to the range of Pr values.

7. The calculation method according to claim 6, characterized in that, In step 4, the calculation equations for different flow stages are as follows: The equation for calculating the convective heat transfer coefficient in the laminar flow stage is as follows: ； The equation for calculating the Nusselt number in the transition flow stage is as follows: ； The equation for calculating the Nusselt number in the turbulent flow stage is as follows: ； Among them, H s is the convective heat transfer coefficient inside the pipe, Re is the Reynolds number, Pr is a dimensionless number, Prandtl number, the value of n depends on the effect of temperature on fluid properties, f is the friction factor, k is the thermal conductivity of the fluid, d is the characteristic length, and Nu is the Nusselt number.

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