Numerical calculation method for simulating combustion of iron powder group particles

Abstract

The invention discloses a numerical calculation method for simulating combustion of iron powder group particles, belongs to the field of numerical simulation calculation of iron powder combustion, can perform numerical simulation on single-particle and iron powder group combustion under a microgravity condition, quantitatively analyzes the influence of differential diffusion on single-particle iron powder and iron powder group combustion flame temperature, and improves the calculation accuracy of the single-particle and iron powder group combustion flame temperature. And meanwhile, the influence of iron powder combustion characteristics and flame propagation speeds under different iron powder and oxygen concentration conditions is considered. The method has a certain guiding significance in research on low-propagation-speed lean-burn iron powder flames and subsequent application of iron powder fuel. The microgravity environment can eliminate the influence of convection and buoyancy, so that the combustion process is more stable and predictable, and the basic mechanisms of iron powder combustion, including combustion rate, oxidation process, phase change and the like, can be deeply researched.

Description

Technical Field

[0001] The present invention belongs to the field of numerical simulation and calculation of iron powder combustion, and particularly relates to a numerical calculation method for simulating the combustion of iron powder cluster particles. Background Art

[0002] As a reactive metal, iron is expected to promote the conversion to low-carbon energy. In recent years, relevant scholars have carried out many experiments and simulations on iron powder combustion. The experimental research on iron powder combustion is mostly based on single iron powder particle tests on the ground. However, to reduce the influence of particle sedimentation and natural convection on the measurement of the lean combustion iron flame speed, the diameter of the iron powder particles is limited to less than 10 μm, which is likely to cause thermal diffusion instability. Therefore, some scholars have conducted iron powder combustion experiments under microgravity conditions. However, the experiments under microgravity conditions have high costs and strict technical requirements. In terms of numerical calculation, previous work mainly focused on the numerical simulation of single-particle and particle-group combustion considering gravity conditions. The disadvantage of this type of research is that it cannot consider the influence of particle dynamics caused by gravity and buoyancy on flame propagation. At the same time, previous work did not consider the influence of differential diffusion on the combustion process of iron powder clusters. Summary of the Invention

[0003] Aiming at the problems raised in the background art, the present invention provides a numerical calculation method for simulating the combustion of iron powder cluster particles. This calculation method is applicable to both the combustion of single iron particles and the combustion of iron powder clusters, and can handle the combustion of iron powder clusters under microgravity conditions, different oxygen concentrations, and considering differential diffusion conditions.

[0004] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] A numerical calculation method for simulating the combustion of iron powder cluster particles, comprising the following steps:

[0006] Step 1, establish a multiphase turbulent combustion mathematical model, determine the size distribution, shape, and initial temperature of iron powder particles, and select a reaction mechanism according to the chemical reaction characteristics of iron powder combustion and the calculation resource situation, etc.; use the heat transfer and mass transfer calculation results of iron powder particles as the source terms of each gas equation to realize the establishment and solution of the solid-phase-gas-phase coupling system;

[0007] Step 2, combine the grid division situation, geometric model characteristics, initial conditions, and boundary conditions to perform numerical discretization on the multiphase turbulent combustion mathematical model established in Step 1 to obtain an algebraic equation system for velocity, density, components, temperature, and pressure, and perform nonlinear processing on the algebraic equation system;

[0008] Step 3: Progress time step by step using numerical methods. Within each time step, iteratively solve the non - linear equations in Step 2. Gradually correct the velocity and pressure fields through an outer loop, and use the updated pressure field to correct the velocity field to ensure convergence; correct the turbulence model; through the above three steps, realize the numerical simulation process of the combustion of iron - powder particle groups.

[0009] Further, the size distribution and shape of the iron powder in Step 1 can be determined according to relevant experimental parameters.

[0010] Further, the chemical reaction mechanism in Step 1 should take into account the oxidation reaction kinetics on the particle surface.

[0011] Further, in Step 2, based on the grid division of the computational domain using the finite - volume method, discretize the spatial derivatives of velocity, components, temperature, pressure, and density through the central - difference scheme or the upwind scheme, and then introduce explicit, implicit, or semi - implicit time - discretization schemes to obtain the algebraic equations defined at the grid center points.

[0012] Further, in the boundary conditions of Step 2, the coupling relationship between particles and gas needs to be considered, including the drag - force model and the heat - transfer model.

[0013] Further, in Step 3, use the implicit method to progress time, and adopt the PIMPLE algorithm during the solution process.

[0014] Further, the governing equations involved in Step 3 include two parts: the gas phase and the particle phase, and the parameters of each component are obtained by directly solving the governing equations of the components.

[0015] Beneficial effects:

[0016] 1. It can be used to handle the effects of differential diffusion and microgravity conditions on the combustion of single and iron - powder groups, eliminate the influence of convection and buoyancy, more accurately describe the mass, heat, and momentum exchange between iron - powder particles and the surrounding gas, and the simulation results can help develop more stable burners;

[0017] 2. By changing the iron - powder concentration and oxygen concentration, the combustion of iron powder under conditions such as lean combustion and rich combustion can be simulated and calculated, which helps to develop more environmentally friendly combustion technologies. Description of the Drawings

[0018] Figure 1 This is the simulation calculation method for the combustion of iron - powder group particles of the present invention.

[0019] Figure 2 This is the comparison diagram of the position distribution of iron - powder particles and the flame front in the simulation and experiment of the embodiment of the present invention.

[0020] Figure 3This is a comparison chart of the predicted and experimental values of the flame speed at different iron powder concentrations in the embodiments of the present invention.

[0021] Figure 4 This is a change curve graph of the particle temperature and the normalized Damköhler number in different environments in the embodiments of the present invention.

[0022] Figure 5 This is a contour map of the gas temperature superimposed by iron particles, an average curve graph of the oxygen mass fraction, and a distribution map of the iron oxide mass fraction under different conditions in the embodiments of the present invention.

[0023] Figure 6 This is a time evolution graph of the 850K isotherm and a propagation change graph of the negative curvature region under the condition of 40% oxidant in the embodiments of the present invention. Detailed implementation mode

[0024] The present invention will be introduced in detail below in conjunction with the accompanying drawings and specific embodiments. However, the following embodiments are only for explaining the present invention, and the protection scope of the present invention should include all the contents of the claims. Moreover, through the description of the following embodiments, those skilled in the art can fully implement all the contents of the claims of the present invention. The present invention couples the pressure and velocity correction methods within the framework of the finite volume method, considers the governing equations of the particle phase and the gas phase, realizes the numerical solution of the reactive flow, and can handle the numerical calculation process of the combustion of iron powder under microgravity conditions.

[0025] As Figure 1 shown, a numerical calculation method for simulating the combustion of iron powder cluster particles of the present invention specifically includes the following steps:

[0026] Step 1: Establish a multiphase turbulent combustion mathematical model, determine the size distribution, shape, and initial temperature of the iron powder particles, and select a suitable reaction mechanism according to the chemical reaction of iron powder combustion; at the same time, the heat transfer and mass transfer calculation results of the iron powder particles need to be used as the source terms of each gas equation to realize the establishment and solution of the solid-gas coupling system;

[0027] Step 2: Combine the initial conditions, grid division situation, and boundary conditions. Discretize the multiphase turbulent combustion mathematical model established in Step 1 to obtain algebraic equations of velocity, density, composition, temperature, and pressure, and perform nonlinear processing on the algebraic equations;

[0028] Step 3: Gradually advance the time through numerical methods. In each time step, iteratively solve the nonlinear equations in Step 2, gradually correct the velocity and pressure fields through the outer loop, and correct the velocity field with the updated pressure field to ensure convergence; correct the turbulence model; through the above three steps, realize the numerical simulation process of the combustion of iron powder particle clusters.

[0029] Specifically, asFigure 1 As shown, the multiphase turbulent combustion mathematical model established in Step 1 includes the following equations:

[0030] (1) The Navier-Stokes equations describe the momentum change of iron powder particles during movement, considering factors such as the inertia, viscosity, pressure gradient, and external forces of the reaction flow.

[0031] (2) Species equations: Based on the principles of mass conservation and species conservation, the species equations describe the mass transport process of iron powder reacting with oxygen to form oxides during combustion. The oxide in this embodiment is assumed to be iron oxide;

[0032] (3) Temperature equation: Solving the temperature equation requires combining the momentum equation and the species equations. Based on the law of conservation of energy, it describes the heat transfer and temperature change process during combustion and can predict the temperature distribution during the combustion of iron powder.

[0033] (4) Pressure equation: The pressure equation includes four parts: a time derivative term, a convection term, a diffusion term, and a source term, and is a transport equation for the pressure variable. In the present invention, when solving the pressure equation, the changes in density and the pressure gradient term, viscous stress term, and source term of the momentum equation are considered. The pressure equation will be discretized and iteratively solved during the solution process until the convergence condition is met.

[0034] (5) Mass equation: The mass equation is used to describe the conservation characteristics of the fluid mass. The mass equation is discretized by the finite volume method, and the discretized mass equation is solved by an iterative method.

[0035] In Step 2, the finite volume method is adopted to divide the computational domain into a finite number of small control volumes, apply the conservation laws to each control volume, perform volume integration of the species equations, pressure equation, temperature equation, and momentum equation established in Step 1 within each grid, and then perform time integration within the time step. By adopting different spatial discretization schemes and time discretization schemes, algebraic equations defined at the center point of the grid are obtained. Then, the same operations are performed on all grids to obtain the algebraic equation sets of each equation within the entire computational domain. The algebraic equation sets are non-linearized and iteratively solved to obtain the corresponding variable fields.

[0036] As Figure 1 shown, in Step 3, the multiphase turbulent combustion model is coupled to the pressure and velocity correction method, and the variable fields during the combustion process of the iron powder particle group can be solved. The specific solution steps are as follows:

[0037] Step (1) Determine the time step and initialize the values of the velocity field and pressure field. The determination of the time step is based on the CFL (Courant-Friedrichs-Lewy) condition or is dynamically adjusted during the calculation to ensure calculation stability;

[0038] Step (2) solves the velocity field and pressure field satisfying mass conservation through a pressure-velocity coupling algorithm;

[0039] Step (3) solves the discretized particle-phase and gas-phase momentum equations, considering the effects of convection, diffusion, pressure gradient, etc. on the velocity field;

[0040] Step (4) solves the discretized energy equation and component equations based on the corrected velocity field and pressure field to obtain the distributions of the temperature field and component field;

[0041] Step (5) updates the pressure field data using the discretized pressure equation, corrects the velocity field according to the new pressure field, and completes one pressure correction cycle; and judges the residual of the mass conservation equation. If the residual of the mass conservation equation is less than the set value, the loop is exited and the next step is entered;

[0042] Step (6) repeats the above steps (3) to (5) until the specified number of iterations or time step is reached;

[0043] Step (7) updates the density value by solving the ideal gas state equation;

[0044] Step (8) judges whether the set end time is reached. Otherwise, repeat steps (1) to (7).

[0045] In the above process, before solving each algebraic equation system, the algebraic equation system needs to be nonlinearized. A complex nonlinear equation system is solved by establishing a diagonal matrix, dealing with nonlinear terms, applying relaxation factors, and constructing a pressure correction equation; at the same time, the influence of differential diffusion needs to be considered when solving the component equation, and the interaction between particles and the surrounding gas needs to be considered in the heat and mass transfer process. In the predictor-corrector iteration of the pressure and velocity correction method, the latest calculated temperature, density, and component mass fraction are adopted. When solving each equation in the process of correcting the pressure and velocity, the interaction between the particle phase and the gas phase, as well as the influence of differential diffusion, needs to be considered.

[0046] Embodiment

[0047] Taking the numerical calculation of simulating the combustion of iron powder particle groups under microgravity conditions as an example, the present invention is described in detail and comprehensively. This method is not limited to the microgravity condition scenario and is applicable to all iron powder particle group combustion scenarios. The embodiments of the present invention are mainly divided into the following steps: Step 1, description of the mathematical model and selection of relevant parameters; Step 2, determination of the computational domain, initial conditions, and boundary conditions; Step 3, grid division and description of the calculation process; Step 4, prediction and analysis of the flame temperature field, velocity field, and component field based on this numerical calculation method.

[0048] Step 1, first describe the mathematical model and select relevant parameters:

[0049] The numerical model for this simulation work adopts a solver applicable to multiphase turbulent combustion. In this solver, the governing equations for the mass, momentum, species, and energy of the gas phase are solved. The governing equations for the species and energy of the gas phase are in the form of:

[0050] Species equation: ,

[0051] Energy equation: ,

[0052] where : Gas-phase density; : Mass fraction of species ; : Eulerian time; : Component of the gas-phase velocity in the -th direction; : Cartesian coordinate in the -th direction; : Mass diffusivity, assuming a Lewis number of 1, i.e., , where: : Thermal conductivity, : Specific heat capacity of the gas phase; : Thermal diffusivity, and : Two-way coupling source terms. The governing equations for the particle phase are in the form of:

[0053] Velocity equation: ,

[0054] Chemical reaction rate equation: ,

[0055] where : Particle velocity in the -th direction, : Drag coefficient calculated based on the solid sphere assumption, : Particle density, calculated as , where : Particle mass, : Magnitude of the relative velocity between the gas and the particle, : Gravitational acceleration in the -th direction. Where : Total particle surface area; : Mass fraction of oxygen; : Reactive particle surface area; : Surface reaction rate (calculated from a single-step reaction and a first-order Arrhenius reaction), , where : Pre-exponential factor, : Activation energy. Assuming the iron oxidation product is FeO, we can obtain = 7.5·10 6 m / s, = 1.2·10 8 J / kmol. : The diffusion coefficient of oxygen from the gas side to the particle surface can be calculated as , : Sherwood number, : Particle diameter, calculated from the mass and density of iron and iron oxide, : The diffusion coefficient of oxygen in the thin layer on the particle surface can be calculated from the following formula:

[0056] ,

[0057] In the formula, : The gas thermal conductivity on the iron powder surface; : The specific heat capacity of the gas phase on the iron powder surface; : The Lewis number of oxygen. According to the mixture-averaged diffusion model in the oxidation environment, its value is set to 0.63. The relative importance of the oxygen diffusion rate and the surface reaction rate can be determined by the normalized Damköhler number (Damk hlernumber) Defined as:

[0058] = ,

[0059] It can be seen from the above formula that when The number is close to 1, the overall reaction rate is controlled by the oxygen diffusion rate; when The number is close to 0, the total reaction rate is controlled by the surface chemical reaction rate.

[0060] Heat transfer between the iron powder particles and the surrounding gas occurs through convection, the heat release rate of the particles, and energy transfer due to mass transfer, etc. The instantaneous temperature of the iron powder particles can be calculated from the following formula:

[0061] ,

[0062] Among them, : The specific heat capacity of the particle phase; : Particle mass; : Nusselt number, calculated from the Ranz-Marshall model; Prandtl number Is set to 0.6. The relaxation time of the particle is calculated from , among which, : Particle density, : Gas-phase dynamic viscosity. Combustion enthalpy Set to 4844 kJ / kg according to previous experimental data, stoichiometric ratio : Ratio of the change in unburned particle mass to the change in burned particle mass, the last term : Energy change due to interphase mass transfer. The total enthalpy of oxygen can be calculated as, , where : Reference temperature, : Enthalpy of formation of oxygen at the reference temperature.

[0063] In this embodiment, the combustion characteristics of the iron powder cluster are defined as the particle combustion time and the characteristic time of heat transfer between spatial particles of the ratio. To quantitatively analyze the relative importance of these two times, a discrete space parameter is introduced.

[0064] ,

[0065] where, : Gas-phase thermal diffusivity; : Average value of the spatial distance between particles in the iron powder cluster. When the spatial discrete parameter is much greater than 1, that is, when the particle combustion time dominates, the flame speed and its dependence on thermochemical quantities can be approximated by the corresponding single-phase flame model; when the heat transfer between spatial particles becomes a limiting factor, it is more appropriate to use the discrete model at this time.

[0066] Step 2, determination and description of the computational domain, initial conditions, and boundary conditions:

[0067] This step studies the combustion characteristics of iron powder particle clusters under different volume fraction conditions (20% O2 / 80% Xe (xenon) and 40% O2 / 60% Xe). The average particle size of the iron powder in the simulation is about 28 μm. The gas-phase thermal diffusivity is calculated from the thermal conductivity, density, and specific heat capacity of the gas mixture. When the oxygen volume fraction is 20%, ; when the oxygen volume fraction is 40%, . When the particle size distribution is the same, the average value of the distance between particles is only related to the fuel mass concentration . In this embodiment, the discrete parameters of different volume fractions of oxygen at three mass concentrations are calculated.

[0068] Table 1. Discrete parameters for different iron powder concentrations and oxygen environments

[0069] The simulated calculation region is a rectangular region with a length of 80 mm and a width of 30 mm. Iron powder particles with different mass concentrations are randomly distributed within the calculation region. The calculation of the particles is based on the PSI-CELL (particle-source-in cell) model, that is, the particles are treated as point sources in the calculation. The simulation corresponds to the instant when the inside of the tube is completely filled with the iron powder group in the experiment. At this time, the iron particles and the gas enter a static state, and the propagation characteristics of the flame in the iron powder group can be effectively observed. At the start of the simulation, all iron powder particles within the region of x < 1 mm are preheated to 2000 K to ignite the unburned iron powder particles in the region of x > 1 mm, thereby forming an iron powder flame propagating in the x direction.

[0070] Step 3. Description of the numerical simulation calculation process for the combustion of iron powder group particles under microgravity conditions:

[0071] First, the calculation domain is physically discretized, with 10 grid points set between the average spacing of each particle to solve the heat transfer problem between particles. Then, the component equation, temperature equation, pressure equation, mass equation, and momentum equation are numerically discretized on all grids using the finite volume method; among them, the second-order central difference method is used for spatial discretization, and the Euler difference algorithm is used for time discretization. Finally, the algebraic equations regarding velocity, density, components, temperature, and pressure at the center point of each grid obtained are non-linearized.

[0072] Next, the non-linear equations are solved according to the solution method of the pressure-velocity correction coupled multiphase turbulent combustion model. The specific steps are as follows:

[0073] Step 1: Solve the velocity field and pressure field that satisfy mass conservation through the pressure-velocity coupling algorithm;

[0074] Step 2: Solve the momentum equations of the particle phase and the gas phase, considering the effects of convection, diffusion, pressure gradient, etc. on the velocity field to obtain the corrected velocity values;

[0075] Step 3: Based on the corrected velocity field and pressure field, considering the effects of differential diffusion and oxygen concentration, solve the discretized energy equation and component equation to obtain the distributions of the temperature field and the component field;

[0076] Step 4: Update the pressure field data with the discretized pressure equation, substitute the calculated value of the pressure into the velocity equation and solve to obtain the velocity correction value; and judge the magnitude relationship between the residual of the mass conservation equation and the set value. When the residual is less than the set value, proceed to the next step;

[0077] Step 5: Loop through Step 2 to Step 4 until the specified number of iterations or time step is reached;

[0078] Step 6: Update the density value by solving the ideal gas state equation;

[0079] Step 7: Determine whether the set end time has been reached. Otherwise, repeat Steps 1 to 6.

[0080] Step 4: Predict and analyze the combustion flame temperature field, velocity field, and component field of the iron powder particle group:

[0081] The simulation results using the patented method are basically consistent with the results of the sounding rocket experiment. The comparison diagram of the overall flame structure is shown in Attachment Figure 2 . Figure 2 of (a): , , temperature contour (T = 850K) and particle position distribution diagram under the condition of 40% O2 / 60% Xe; Figure 2 of (b): , , oxygen mass fraction contour and particle temperature distribution diagram under the condition of 40% O2 / 60% Xe; Figure 2 of (c): Experimental high-speed camera recording images under the same iron powder concentration and oxygen conditions. It can be seen from the figure that when the distance between particles is relatively small, the flame burns violently, while the iron powder particles near the wall surface are extinguished due to the low temperature; the comparison results of the flame velocity under different oxygen concentration conditions show that when the oxygen volume fraction is 20%, the coefficient of dispersion is roughly in the range of 0.08 - 0.2; when the oxygen volume fraction is 40%, the coefficient of dispersion is between 0.03 - 0.07. For details, see Attachment Figure 3 .

[0082] For the combustion of a single iron powder particle, the design of the simulation calculation area is similar to the experiment, that is, a cylinder with a length of 300 mm and an inner diameter of 12 mm. To calculate the differential diffusion of oxygen, and two cases are considered.

[0083] 1. The combustion of a single iron particle is mainly controlled by diffusion. This is because for different Lewis numbers (considering the influence of differential diffusion), changes very little; when differential diffusion is considered, for the two cases of 20% O2 and 40% O2, the predicted values of the particle temperature increase by 320K and 350K respectively. See Attachment Figure 4 , Figure 4 of (a): Curve of particle temperature varying with time under different oxygen concentrations, Figure 4 of (b): Curve of the normalized Damköhler number ( ) varying under different oxygen concentration conditions.

[0084] 2. The flame structure depends on the local concentration of iron powder under lean combustion conditions. When is 0.63, that is, the flame propagation speed considering differential diffusion is 4.7 mm / s faster than that without considering differential diffusion; see the appendix for details Figure 5 , Figure 5 of (a): Contour distribution of gas temperature superimposed with iron particles colored by mass fraction of iron oxide when Le = 0.63, Figure 5 of (b): Contour distribution of gas temperature superimposed with iron particles colored by mass fraction of iron oxide when Le = 1.0, Figure 5 of (c): , , Variation curves of gas temperature and oxygen mass fraction under two cases of Le = 0.63 and Le = 1.0 when the oxygen content is 40%, Figure 5 of (d): , , Variation curve of mass fraction of iron oxide under two cases of Le = 0.63 and Le = 1.0 when the oxygen content is 40%.

[0085] 3. Before t = 0.6 s, the influence of differential diffusion on the flame structure is very small; while after t = 0.8 s, there are significant differences in the flame structures under the two cases, because the flame in the negative curvature region considering differential diffusion will propagate in different directions. Without considering differential diffusion ( ), the negative curvature flame front propagates in the x - direction, and when (considering differential diffusion), the negative curvature flame front propagates in the transverse direction, forming a sharp region, as shown by the green arrow in the appendix Figure 6 . Then the flame fronts in the sharp negative curvature regions merge with each other to form a positive curvature flame front. This phenomenon still exists in the case of high iron powder concentration, see the appendix Figure 6 , Figure 6 of (a): , Time evolution of the 850K temperature contour (from t = 0.2 s to t = 1.0 s) under the condition of 40% O2, Figure 6 of (b): , Time evolution of the 850K temperature contour (from t = 0.2 s to t = 1.0 s) under the condition of 40% O2. The solid line represents the case of Le = 0.63, and the dashed line represents the case of Le = 1.0.

[0086] The above are only specific embodiments of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A numerical calculation method for simulating the combustion of iron powder particles, characterized in that: The steps include: Step 1: Establish a mathematical model of multiphase turbulent combustion, determine the size distribution, shape, and initial temperature of the iron powder particles, and select the reaction mechanism based on the chemical reaction characteristics of the iron powder combustion and the computing resources. Use the heat and mass transfer calculation results of the iron powder particles as the source terms of the gas equations to achieve the establishment and solution of the solid-gas coupling system. Step 2: numerically discretize the multiphase turbulent combustion mathematical model established in step 1 in combination with the grid division, geometric model characteristics, initial conditions and boundary conditions, obtain a set of algebraic equations about velocity, density, component, temperature and pressure, and perform nonlinear processing on the set of algebraic equations; Step three, gradually advance the time through the numerical discretization method, iteratively solve the nonlinear equations in step two in each time step, and gradually correct the velocity and pressure fields through the outer loop, and use the updated pressure field to correct the velocity field to ensure convergence; correct the turbulence model; through the above three steps, realize the numerical simulation process of iron powder particle group combustion.

2. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: The mathematical model of multiphase turbulent combustion established in step 1 includes the following equations: Navier-Stokes equation: describes the momentum change of iron powder particles during motion, taking into account the inertia, viscosity, pressure gradient and external forces of the reaction flow; Component equation: Based on the principles of mass conservation and component conservation, it describes the mass transport process of iron powder reacting with oxygen to generate oxides during combustion; Temperature equation: The solution of the temperature equation combines the momentum equation and the component equation, based on the law of conservation of energy, to describe the heat transfer and temperature change process during the combustion process, and is used to predict the temperature distribution during the combustion of iron powder; Pressure equation: It consists of four parts: time derivative term, convection term, diffusion term and source term. It is a transport equation about the pressure variable. The pressure equation is discretized and solved iteratively during the solution process until the convergence conditions are met. Mass equation: The mass equation is used to describe the conservation characteristics of fluid mass. The mass equation is discretized by the finite volume method and solved by the iterative method.

3. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: In step 2, the finite volume method is used to divide the computational domain into a finite number of small control volumes. The conservation laws are applied to each control volume. The component equation, pressure equation, temperature equation, mass equation, and momentum equation established in step 1 are volume integrated in each grid, and then time integrated within the time step. By using different spatial and temporal discrete formats, the algebraic equation defined at the center point of the grid is obtained. The same operation is then performed on all grids to obtain the algebraic equation group of each equation in the entire computational domain. The algebraic equation group is nonlinearized and solved iteratively to obtain the corresponding variable field.

4. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: Step 3: Couple the multiphase turbulent combustion model to the pressure and velocity correction method to solve the variable fields in the iron powder group particle combustion process. The solution steps are as follows: Step 1: Determine the time step and initialize the values ​​of the velocity field and pressure field. The time step is determined based on the CFL (Courant-Friedrichs-Lewy) condition or is dynamically adjusted during the calculation process to ensure calculation stability. Step 2, solving the velocity field and pressure field satisfying mass conservation by using the pressure-velocity coupling algorithm; Step 3: Solve the momentum equations of the discrete particle phase and gas phase, considering the effects of convection, diffusion, pressure gradient, etc. on the velocity field; Step 4: On the basis of the corrected velocity field and pressure field, solve the discretized energy equation and component equation to obtain the distribution of the temperature field and component field; Step 5: Use the discretized pressure equation to update the pressure field data, and correct the velocity field according to the new pressure field to complete a pressure correction cycle; and determine the residual of the mass conservation equation. If the residual of the mass conservation equation is less than the set value, exit the loop and enter the next step; Step 6: Repeat steps 3 to 5 until the specified number of iterations or time step is reached; Step 7: Update the density value by solving the ideal gas state equation; Step 8: Determine whether the set end time has been reached, otherwise repeat steps 1 to 7.

5. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: The size distribution and shape of the iron powder in step 1 can be determined based on relevant parameters of a comparative experiment.

6. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: The chemical reaction mechanism in step 1 should take into account the oxidation reaction kinetics on the surface of the iron powder particles.

7. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: In step 2, the finite volume method is used to discretize the spatial derivatives of velocity, composition, temperature, pressure and density based on the grid division of the computational domain through the central difference format or the upwind format, and then an explicit, implicit or semi-implicit time discretization format is introduced to obtain the algebraic equation defined at the center point of the grid.

8. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: The boundary conditions in step 2 consider the coupling relationship between particles and gas, including a drag model and a heat transfer model.

9. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: In step three, the implicit method is used to advance time, and the PIMPLE algorithm is used in the solution process.

10. A numerical calculation method for simulating the combustion of iron powder particles according to claim 1, characterized in that: The control equations involved in step three include gas phase and particle phase. The parameters of each component are obtained by directly solving the control equations of the components.

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