Spontaneous combustion foil combustion diffusion dynamic simulation method facing surface source infrared interference

Abstract

The invention discloses a surface source infrared interference-oriented spontaneous combustion foil combustion diffusion dynamic simulation method. The method comprises the following steps of: obtaining a large airflow field and foil initial parameters; establishing a geometric model comprising a foil, a scattering mechanism and a flow field area; establishing an atmospheric flow model in a computational fluid mechanics solver, and establishing a combustion model based on a metal oxidation reaction in a discrete element solver; a computational fluid mechanics-discrete element two-way coupling method is adopted, and dynamic tracking of the foil spatial position and the temperature field is achieved by alternately transmitting flow field parameters and foil motion states. The method can accurately simulate the foil diffusion and temperature evolution process under the coupling action of gas-solid two-phase flow and chemical reaction, has the characteristics of clear physical mechanism, high universality and high precision, and provides an effective simulation means for dynamic behavior research of spontaneous combustion foil type surface source interference.

Description

Technical Field

[0001] This invention relates to a dynamic simulation method for the combustion and diffusion of spontaneously combusting foil in the face of surface-source infrared interference, and relates to the field of computer simulation technology. This method is applicable to the prediction of the diffusion and combustion performance of spontaneously combusting foil and the study of the interaction mechanism between foil and the environment. Background Technology

[0002] With the development of infrared imaging guidance technology, traditional point-source jamming methods are becoming increasingly ineffective against advanced seekers with target recognition capabilities. Area-source infrared jamming, by simulating the spectral and motion characteristics of real targets, can effectively improve the realism of jamming and countermeasures, thus becoming an important development direction in the field of modern passive optoelectronic countermeasures. These systems typically use a large number of self-igniting foil sheets to form a jamming cloud with specific spatial distribution and radiation characteristics, thereby deceiving and interfering with threatening targets.

[0003] Spontaneous combustion foil, as the core medium for area-source interference, is characterized by its lightweight and low aspect ratio, enabling it to ignite rapidly after being dispersed and form a continuously burning diffusion cloud. Its unique aerodynamic properties endow it with excellent loitering ability and diffusion stability, meeting the performance requirements of interference systems for rapid prototyping and sustained radiation. High-fidelity simulation of the diffusion and combustion process of spontaneous combustion foil can reproduce the entire process from release ignition to settling and cooling in a digital environment, thus playing a crucial role in predicting the performance of spontaneous combustion foil and developing novel formulations.

[0004] In the modeling of motion diffusion, existing methods are mainly divided into two categories: probabilistic distribution methods and numerical methods. Probabilistic distribution methods, as an approximation, typically describe the geometric characteristics of diffusion clouds based on statistical assumptions. For example, the "Particle Modeling Method for Fast Surface-Source Infrared Decoys Applicable to Real-Time Simulation" proposed by Yang Yao and Chen Ting (CN106529078A) achieves rapid simulation of cloud morphology under ideal conditions by establishing the spatial distribution density function of the decoy's combustion units. However, its adaptability is limited in most practical applications. Numerical methods, on the other hand, are based on dynamic equations, solving for the motion trajectory and spatial distribution of the foil under given initial conditions and assumptions. For instance, Zou Tao, Wang Chaozhe, and others used computational fluid dynamics to obtain the aerodynamic coefficients of the foil at different angles of attack and established motion models for the ignition and complete combustion stages (diffusion law of foil-type infrared surface-source decoys, Acta Aeronautica et Astronautica Sinica). Although this method considers the aerodynamic interference between foils, it has not yet introduced a dynamic coupling mechanism between the foil and the combustion process. In terms of temperature field evolution modeling, existing research mainly involves constructing a foil combustion model and jointly solving the hydrodynamic control equations and foil thermal balance equations under high-speed flow field conditions to obtain its surface temperature distribution, such as the research conducted by Huang Hesong et al. (Numerical and experimental study of pyrophoric activated metal Mg surface combustion characteristics, Royal Society Open Science).

[0005] Traditional simulation methods typically decouple the motion characteristics of self-igniting foil from temperature field changes. While this simplifies modeling complexity to some extent, its inherent limitations are becoming increasingly apparent, particularly in accurately reflecting the dynamic coupling mechanism between kinematics and thermodynamics. Specifically, the combustion and motion of self-igniting foil constitute a dynamic interactive system: the foil's motion influences the combustion reaction by altering the surrounding flow field (such as pressure and oxygen concentration); simultaneously, the changes in flow field and physical properties caused by combustion react on the foil, driving changes in its trajectory. Simulation strategies that isolate motion and temperature fields can only provide temperature field simulations under static or preset conditions, making it difficult to accurately reproduce the real dynamic process of a large number of foils after ignition in actual use, including the evolution of their diffusion cloud morphology and the real-time changes in temperature fluctuations with motion states (such as collisions, flips, and deceleration) and environmental conditions. Therefore, these traditional methods are no longer sufficient to meet the urgent need for high-confidence predictions of dynamic combustion characteristics in the current development of self-igniting foil. Summary of the Invention

[0006] The purpose of this invention is to propose a dynamic simulation method for the combustion and diffusion of spontaneously combusting foil in the face of surface-source infrared interference. This method can simulate the trajectory, diffusion morphology, and temperature field evolution of the spontaneously combusting foil after triggering. This method overcomes the limitation of decoupling motion and combustion in traditional simulations, achieving integrated simulation of the entire process of foil throwing, flow field interaction, and combustion, and profoundly reveals the transient interaction mechanism between multiple physics fields. This research lays a solid simulation foundation for the design and performance prediction of spontaneously combusting foil.

[0007] The technical solution of this invention is as follows: Based on the Euler-Lagrange framework, the atmosphere is considered as a continuous phase, and fluid flow is simulated by solving the fluid dynamics control equations in the Euler coordinate system; the foil is considered as a discrete phase, and the dynamic behavior of each foil is tracked in the Lagrange coordinate system using the discrete element method combined with Newton's laws of motion. Based on this, a self-igniting foil combustion model is established, and a two-way coupling mechanism between the gas and solid phases is introduced to accurately characterize the momentum and energy exchange process between the foil and the flow field. Ultimately, the dynamic simulation of foil diffusion and temperature field under the coupling effect of gas-solid two-phase flow and chemical reaction is achieved. The specific steps are as follows:

[0008] (1) Obtain initial information of the atmospheric external flow field and the spontaneous combustion foil, wherein the initial information of the atmospheric external flow field includes wind speed and air temperature, and the initial information of the spontaneous combustion foil includes the initial position, temperature and physical property parameters of the foil;

[0009] (2) Establish a geometric model of the self-igniting foil, the scattering mechanism, and the external flow field region;

[0010] (3) Establish an atmospheric flow model for foil diffusion in the computational fluid dynamics solver;

[0011] (4) Generate the stacked foil bundles in the foil-throwing mechanism based on the geometric model of the foil and the throwing mechanism;

[0012] (5) Based on the oxidation reaction mechanism in the spontaneous combustion process of metal foil, a combustion model is established in the discrete element solver to solve the combustion rate, mass change and temperature of the foil;

[0013] (6) The simulation method of computational fluid dynamics-discrete element bidirectional coupling is adopted. Based on the set time step and number of calculation steps, the computational fluid dynamics solver transmits the calculated fluid component velocity, pressure field and temperature field to the discrete element solver. The discrete element solver feeds back the position, velocity and temperature of each foil to the computational fluid dynamics solver, thereby obtaining the spatial position and temperature of the foil at each time.

[0014] The specific implementation steps of "establishing an atmospheric flow model" in step (3) are as follows: turn on the component transport model and set the initial gas phase mixture components to O2 and N2; set the boundary conditions, with the inlet in the incoming flow direction being a velocity inlet and the outlet being a pressure outlet, and the wall being a non-slip wall; use the k-omega SST turbulence model; use transient simulation and set the time step for flow field calculation.

[0015] The specific process of "generating the stacked foil bundles in the dispensing mechanism" in step (4) is as follows:

[0016] The first step is to import the 3D models of the scattering mechanism and foil into the discrete element solver;

[0017] The second step is to align the direction of the injected foil with the direction of the piston in the dispensing mechanism.

[0018] The third step is to set the size and position of the foil injection port: the injection port size is consistent with the piston size, and the injection port position is a distance S shifted along the piston's direction of movement on the plane where the piston is located. The relationship between the shift distance S and the foil thickness l is as follows:

[0019]

[0020] Step 4: Set the simulation time and the mass flow rate of the injected foil: The relationship between the simulation time t, the mass flow rate m of the injected foil, and the relevant parameters of the foil and the dispensing mechanism is as follows:

[0021]

[0022] The density of a single foil is ρ, the length and width of its bottom surface are both W, and the axial length of the scattering mechanism is L.

[0023] The specific process of "establishing a combustion model" in step (5) is as follows: the heat balance equation of the foil is established as follows:

[0024]

[0025] Among them, T s T represents the foil temperature. ∞ For ambient temperature, and These are the densities of the foil and the metal oxide, respectively. and The specific heat capacities of the foil and the metal oxide, respectively, r s and r b These are the foil radius and the inner diameter of the oxide layer, respectively, ε p denoted as porosity of the porous oxide layer, h as convective heat transfer coefficient, and ε as emissivity of the foil surface. Q represents the rate of O2 consumption at the reaction interface. relThe reaction heat is given by h, the convective heat transfer coefficient, and the O2 consumption rate is determined by the chemical reaction rate constant and the O2 concentration on the foil surface. Control, for

[0026]

[0027] The chemical reaction rate constant is

[0028]

[0029] Where A1 is the pre-exponential factor, E is the activation energy, and R is the gas constant, under steady-state conditions, the rate of O2 consumption is related to the oxygen concentration in the flow field. The relationship is

[0030]

[0031] in, D is the mass transfer coefficient of O2 in the external flow field. e denoted as the diffusion coefficient of the porous oxide layer.

[0032] In step (6), to simulate the dynamic process of the foil detaching from the throwing mechanism, the piston is set to move at a constant linear speed v along the axis of the throwing mechanism, and the end cap wall collision model is disabled.

[0033] In step (6), the "simulation method using computational fluid dynamics-discrete element method" is described in the following specific process:

[0034] The first step is to perform initial flow field calculations on the computational fluid dynamics solver to obtain fluid velocity, pressure, temperature, and component mass fraction, and then transfer them to the discrete element solver.

[0035] The second step is to calculate the foil volume fraction and initial interaction terms on the discrete element solver, and then transfer the calculated interaction forces, heat transfer rate, and local volume fraction of the foil to the computational fluid dynamics solver.

[0036] The third step is to perform time step correction in the computational fluid dynamics solver to obtain an integer multiple of the time step of the discrete element solver.

[0037] The fourth step is to update the foil physics field in the computational fluid dynamics solver;

[0038] The fifth step involves the semi-implicit transfer of interaction forces, explicit transfer of heat transfer rates, foil velocities, and foil volume fractions from the discrete element solver to the computational fluid dynamics solver.

[0039] The sixth step is to transfer the velocity, pressure, temperature, and mass fraction of each component from the computational fluid dynamics solver to the discrete element solver.

[0040] Step 7: Repeat steps 4, 5, and 6 until the total simulation time is reached.

[0041] The advantages of this invention compared to the prior art are:

[0042] (1) It breaks through the limitation of treating the movement of spontaneously combusting foil, combustion reaction and heat transfer process in isolation in traditional simulation. It adopts the computational fluid dynamics-discrete element bidirectional coupling modeling strategy, comprehensively considers the multi-physics field coupling mechanism of foil collision, air resistance and combustion reaction, and realizes high-precision integrated simulation of spontaneously combusting foil diffusion process and temperature field dynamic evolution.

[0043] (2) Based on the numerical simulation framework combining computational fluid dynamics and discrete element method, compared with the statistical method based on probability distribution, this method has a clear physical mechanism, wide applicability, stronger theoretical foundation and reliable prediction accuracy;

[0044] (3) The spontaneous combustion reaction process of the foil is dynamically coupled with its motion behavior, which more realistically restores the combustion diffusion mechanism of the spontaneous combustion foil in the actual environment, significantly improves the accuracy and completeness of motion modeling, and effectively overcomes the shortcomings of existing models in dynamic interactive simulation. Attached Figure Description

[0045] Figure 1 Here is a flowchart of the implementation method of the present invention:

[0046] Figure 2 This is a flowchart of a two-way coupled computational fluid dynamics-discrete element method. Detailed Implementation

[0047] The present invention uses the working conditions of horizontally deploying a bundle of foils with Fe as the self-igniting material as an example. In practical applications, the method provided by the present invention is also applicable to the numerical simulation of other self-igniting metal foils under different release conditions and configurations.

[0048] like Figure 1 As shown, this invention discloses a method for dynamic simulation of combustion diffusion of self-igniting foil in the face of surface source infrared interference, the specific steps of which are as follows:

[0049] (1) Obtain initial information on the atmospheric external flow field and the self-igniting foil;

[0050] The initial information of the atmospheric external flow field includes wind speed and air temperature, while the initial information of the spontaneously combusting foil includes the initial position, temperature, and physical property parameters of the foil.

[0051] (2) Establish a geometric model of the self-igniting foil, the scattering mechanism, and the external flow field region;

[0052] In the 3D modeling software SpaceClaim, a 3D model of a piston-type dispensing mechanism and a rectangular foil was created. The dispensing mechanism is 60cm long, 5cm wide, and 5cm high. The rectangular foil is 4.8cm long and wide, and 0.1mm thick. A cuboid fluid region was created outside the dispensing mechanism. To ensure that the outer flow field includes the entire foil diffusion trajectory, the left boundary of the outer flow field was set to be 0.1m from the left surface of the dispensing mechanism, the right boundary of the outer flow field was set to be 40m from the right surface of the dispensing mechanism, the upper boundary of the outer flow field was set to be 0.1m from the upper surface of the dispensing mechanism, the lower boundary of the outer flow field was set to be 5m from the lower surface of the dispensing mechanism, and the front and rear boundaries of the outer flow field were set to be 5m from the front and rear surfaces of the dispensing mechanism, respectively.

[0053] (3) Establish an atmospheric flow model for foil diffusion in the computational fluid dynamics solver;

[0054] Mesh generation of the external flow field region: Import the 3D model of the external flow field into ICEM mesh generation software, discretize the region using uniformly sized meshes in the x, y, and z directions, with the mesh size set to 0.2m. After mesh generation, check the mesh quality to ensure it is greater than 0.5, and name each boundary surface of the external flow field region after mesh generation.

[0055] The component transport model is set up as follows: the gas phase mixture consists of O2 and N2, and their initial mass fractions are set to 21% and 79%, respectively.

[0056] Set boundary conditions: the right boundary inlet of the outer flow field is set as a velocity inlet, the left boundary of the outer flow field is set as a pressure outlet, and the wall surface is a no-slip wall surface;

[0057] Turbulence model settings: k-omega SST;

[0058] Set the time step for the transient simulation solution to 0.01s.

[0059] (4) Generate the stacked foil bundles in the foil-throwing mechanism based on the geometric model of the foil and the throwing mechanism;

[0060] The first step is to import the 3D models of the scattering mechanism and foil into the discrete element solver;

[0061] The second step is to align the direction of the injected foil with the direction of the piston in the dispensing mechanism.

[0062] The third step is to set the size and position of the foil injection port: the injection port size is consistent with the piston size, and the injection port position is a distance S shifted along the piston's direction of movement on the plane where the piston is located. The relationship between the shift distance S and the foil thickness l is as follows:

[0063]

[0064] Step 4: Set the simulation time and the mass flow rate of the injected foil: The relationship between the simulation time t, the mass flow rate m of the injected foil, and the relevant parameters of the foil and the dispensing mechanism is as follows:

[0065]

[0066] The density of a single foil is ρ, the length and width of its bottom surface are both W, and the axial length of the scattering mechanism is L.

[0067] (5) Based on the oxidation reaction mechanism in the Fe auto-ignition process, a combustion model is established in the discrete element solver to solve the burning rate, mass change and temperature of the foil;

[0068] The heat balance equation for the foil is established as follows:

[0069]

[0070] Among them, T s T represents the foil temperature. ∞ For ambient temperature, and The densities of Fe and Fe3O4 are respectively. and The specific heat capacities of Fe and Fe3O4 are respectively, r s and r b These are the foil radius and the inner diameter of the oxide layer, respectively, ε p denoted as porosity of the porous oxide layer, h as convective heat transfer coefficient, and ε as emissivity of the foil surface. Q represents the rate of O2 consumption at the reaction interface. rel The reaction heat is given by h, the convective heat transfer coefficient, and the O2 consumption rate is determined by the chemical reaction rate constant and the O2 concentration on the foil surface. Control, for

[0071]

[0072] The chemical reaction rate constant is

[0073]

[0074] Where A1 is the pre-exponential factor, E is the activation energy, and R is the gas constant. Under steady-state conditions, the rate of O2 consumption is related to the oxygen concentration in the flow field. The relationship is

[0075]

[0076] in, D is the mass transfer coefficient of O2 in the external flow field. e denoted as the diffusion coefficient of the porous oxide layer.

[0077] (6) The simulation method of computational fluid dynamics-discrete element bidirectional coupling is adopted. Based on the set time step and number of calculation steps, the computational fluid dynamics solver transmits the calculated fluid component velocity, pressure field and temperature field to the discrete element solver. The discrete element solver feeds back the position, velocity and temperature of each foil to the computational fluid dynamics solver, so as to obtain the spatial position and temperature of the foil at each time.

[0078] To simulate the dynamic process of the foil detaching from the dispensing mechanism, gravity was enabled in the discrete element solver, and the piston was set to move in a uniform linear motion along the axis of the dispensing mechanism at a speed of v = 20 m / s. The end cap wall model was disabled. To characterize the dynamic coupling mechanism between the motion field and the combustion field of the self-igniting foil, a two-way coupled computational fluid dynamics-discrete element method was used. The calculation process is as follows: Figure 2 As shown.

[0079] The first step is to perform initial flow field calculations on the computational fluid dynamics solver to obtain fluid velocity, pressure, temperature, and component mass fraction, and then transfer them to the discrete element solver.

[0080] The second step is to calculate the foil volume fraction and initial interaction terms on the discrete element solver, and then transfer the calculated interaction forces, heat transfer rate, and local volume fraction of the foil to the computational fluid dynamics solver.

[0081] The third step is to perform time step correction in the computational fluid dynamics solver to obtain an integer multiple of the time step of the discrete element solver.

[0082] The fourth step is to update the foil physics field in the computational fluid dynamics solver;

[0083] The fifth step involves the semi-implicit transfer of interaction forces, explicit transfer of heat transfer rates, foil velocities, and foil volume fractions from the discrete element solver to the computational fluid dynamics solver.

[0084] The sixth step is to transfer the velocity, pressure, temperature, and mass fraction of each component from the computational fluid dynamics solver to the discrete element solver.

[0085] Step 7: Repeat steps 4, 5, and 6 until the total simulation time is reached.

[0086] The specific embodiments of the present invention have been described above. It should be noted that the present invention is not limited to the specific embodiments described above. Those skilled in the art can make various modifications or variations within the scope of the claims, which do not affect the substantive content of the present invention.

Claims

1. A method for dynamic simulation of combustion diffusion of self-igniting foil in the face of surface-source infrared interference, characterized in that: It includes the following steps: (1) Obtain initial information of the atmospheric external flow field and the spontaneous combustion foil, wherein the initial information of the atmospheric external flow field includes wind speed and air temperature, and the initial information of the spontaneous combustion foil includes the initial position, temperature and physical property parameters of the foil; (2) Establish a geometric model of the self-igniting foil, the scattering mechanism, and the external flow field region; (3) Establish an atmospheric flow model for foil diffusion in the computational fluid dynamics solver; (4) Generate the stacked foil bundles in the foil-throwing mechanism based on the geometric model of the foil and the throwing mechanism; (5) Based on the oxidation reaction mechanism in the spontaneous combustion process of metal foil, a combustion model is established in the discrete element solver to solve the combustion rate, mass change and temperature of the foil; (6) The simulation method of bidirectional coupling of computational fluid dynamics and discrete element method is adopted. Based on the set time step and number of calculation steps, the computational fluid dynamics solver transmits the calculated fluid component velocity, pressure field and temperature field to the discrete element solver. The discrete element solver feeds back the position, velocity and temperature information of each foil to the computational fluid dynamics solver, so as to obtain the spatial position and temperature of the foil at each time.

2. The method for dynamic simulation of combustion diffusion of self-igniting foil resistant to surface-source infrared interference as described in claim 1, characterized in that: The specific implementation steps for "establishing an atmospheric flow model" mentioned in step (3) are as follows: Activate the component transport model and set the initial gas phase mixture components to be O2 and N2; set the boundary conditions, with the inlet in the incoming flow direction being a velocity inlet and the outlet being a pressure outlet, and the wall being a no-slip wall; use the k-omega SST turbulence model; use transient simulation and set the time step for flow field calculation.

3. The method for dynamic simulation of combustion diffusion of self-igniting foil resistant to surface-source infrared interference as described in claim 1, characterized in that: The specific implementation process of "generating the stacked foil bundles in the dispensing mechanism" mentioned in step (4) is as follows: The first step is to import the 3D models of the scattering mechanism and foil into the discrete element solver; The second step is to align the direction of the injected foil with the direction of the piston in the dispensing mechanism. The third step is to set the size and position of the foil injection port: the injection port size is consistent with the piston size, and the injection port position is a distance S shifted along the piston's direction of movement on the plane where the piston is located. The relationship between the shift distance S and the foil thickness l is as follows: Step 4: Set the simulation time and the mass flow rate of the injected foil: The relationship between the simulation time t, the mass flow rate m of the injected foil, and the relevant parameters of the foil and the dispensing mechanism is as follows: The density of a single foil is ρ, the length and width of its bottom surface are both W, and the axial length of the scattering mechanism is L.

4. The method for dynamic simulation of combustion diffusion of self-igniting foil resistant to surface-source infrared interference according to claim 1, characterized in that: The "combustion model" mentioned in step (5) is, ； Among them, T s T represents the foil temperature. ∞ For ambient temperature, and These are the densities of the foil and the metal oxide, respectively. and The specific heat capacities of the foil and the metal oxide, respectively, r s and r b These are the foil radius and the inner diameter of the oxide layer, respectively, ε p denoted as porosity of the porous oxide layer, h as convective heat transfer coefficient, and ε as emissivity of the foil surface. Q represents the rate of O2 consumption at the reaction interface. rel The reaction heat is given by h, the convective heat transfer coefficient, and the O2 consumption rate is determined by the chemical reaction rate constant and the O2 concentration on the foil surface. Control, for: ； The chemical reaction rate constant is: ； Where A1 is the pre-exponential factor, E is the activation energy, and R is the gas constant, under steady-state conditions, the rate of O2 consumption is related to the oxygen concentration in the flow field. The relationship is: ； in, D is the mass transfer coefficient of O2 in the external flow field. e denoted as the diffusion coefficient of the porous oxide layer.

5. The method for dynamic simulation of combustion diffusion of self-igniting foil resistant to surface-source infrared interference according to claim 1, characterized in that: In step (6), in order to simulate the dynamic process of the foil detaching from the throwing mechanism, the piston is set to move in a uniform linear motion along the axis of the throwing mechanism at a speed v, and the end cap wall collision model is disabled.

6. The method for dynamic simulation of combustion diffusion of self-igniting foil resistant to surface-source infrared interference according to claim 1, characterized in that: The specific implementation process of "using the computational fluid dynamics-discrete element bidirectional coupling simulation method" mentioned in step (6) is as follows: The first step is to perform initial flow field calculations on the computational fluid dynamics solver to obtain fluid velocity, pressure, temperature, and component mass fraction, and then transfer them to the discrete element solver. The second step is to calculate the foil volume fraction and initial interaction terms on the discrete element solver, and then transfer the calculated interaction forces, heat transfer rate, and local volume fraction of the foil to the computational fluid dynamics solver. The third step is to perform time step correction in the computational fluid dynamics solver to obtain an integer multiple of the time step of the discrete element solver. The fourth step is to update the foil physics field in the computational fluid dynamics solver; The fifth step involves the semi-implicit transfer of interaction forces, explicit transfer of heat transfer rates, foil velocities, and foil volume fractions from the discrete element solver to the computational fluid dynamics solver. The sixth step is to transfer the velocity, pressure, temperature, and mass fraction of each component from the computational fluid dynamics solver to the discrete element solver. Step 7: Repeat steps 4, 5, and 6 until the total simulation time is reached.

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