Method for constructing transient high-temperature pressure hydrogen-oxygen premixed combustion numerical model of closed container

Abstract

The invention belongs to the technical field of hydrogen-oxygen combustion mixed emission, and discloses a closed container transient high-temperature pressure hydrogen-oxygen premixed combustion numerical model construction method, which comprises the following steps: establishing a geometric model in simulation software according to the actual structure size of a closed container, and then establishing a transient high-temperature pressure hydrogen-oxygen premixed combustion numerical model on the basis of the constructed physical model. Setting a control equation, a turbulence model, a combustion model, a solver algorithm and initial conditions, finally operating the models to carry out transient calculation, evaluating the mixing uniformity of the hydrogen-oxygen mixed gas by utilizing spatial mixing unevenness SMD, and evaluating the filling accuracy by utilizing a filling quality error. According to the method, by constructing the high-precision numerical model, the mixing and combustion mechanism can be deeply explored, and a theoretical basis and method support are provided for optimization design, DDT inhibition and realization of accurate injection and safe and efficient combustion of oxyhydrogen gas.

Description

Technical Field

[0001] This application belongs to the field of hydrogen-oxygen combustion and co-firing technology, specifically relating to a method for constructing a numerical model of transient high-temperature and high-pressure hydrogen-oxygen premixed combustion in a closed container. Background Technology

[0002] Since its inception, artillery firing technology has relied on the chemical energy of energetic materials for energy release. Conventional solid propellant artillery uses the combustion of solid propellant within the chamber to generate high-temperature, high-pressure gas. This gas expands and performs work, propelling the projectile along the barrel to achieve a high initial velocity. In this process, the effective pressure propelling the projectile is the pressure at the base of the projectile, and the pressure gradient between the chamber base and the projectile base is a strong function of the propellant mass ratio. Therefore, maintaining a high-pressure environment at the base of the projectile is an effective way to increase its initial velocity, and standard artillery typically achieves this by increasing the propellant mass.

[0003] However, this technical approach faces two significant bottlenecks: First, increasing the propellant charge inevitably leads to a sharp increase in maximum chamber pressure, posing a serious challenge to launch safety. Second, and more fundamentally, the high molecular weight of traditional carbon-nitrogen-based propellant gases results in lower sound speed and greater acoustic inertia. When the initial velocity of the projectile exceeds 1700 m / s, the rate at which the gas expands to replenish the pressure at the projectile base can hardly keep up with the projectile's acceleration, causing a sharp increase in the pressure difference between the chamber base and the projectile base, and a significant decrease in energy utilization. At this point, further increasing the propellant mass has negligible effect on increasing the initial velocity, and conventional solid propellants have encountered a physical bottleneck in pursuing ultra-high speeds. To overcome this bottleneck, the industry has proposed a technical approach to reduce the acoustic inertia of propellant gases, namely, using low molecular weight propellants. Hydrogen, due to its smallest molecular weight and extremely high sound speed, is an ideal choice. The combustion product of hydrogen and oxygen is water vapor, with an extremely low molecular weight. Its high-speed characteristics ensure that the high pressure at the chamber base can be transferred to the projectile base very quickly, effectively reducing the pressure gradient, thus theoretically supporting projectiles to achieve speeds far exceeding those of traditional artillery.

[0004] The hydrogen-oxygen premixed combustion launch technology based on this principle involves pre-injecting hydrogen and oxygen into a sealed combustion chamber at a specific equivalence ratio under high pressure. After ignition, they undergo violent combustion, generating a high-temperature, high-pressure working fluid that propels the projectile or piston. This technology possesses potential advantages such as low acoustic inertia of the working fluid, high theoretical muzzle velocity, and superior loading density. However, this process also presents significant technical challenges: First, rapid and uniform mixing of hydrogen and oxygen under high pressure is a prerequisite for controllable combustion, and its mixing characteristics and efficiency require in-depth research. Second, the high-pressure premixed gas combustion in a confined space has an extremely high energy release rate, and its combustion process can easily and uncontrollably transform from a gentle deflagration into a destructive detonation (DDT), posing a significant threat to the structural safety of the combustion chamber.

[0005] Currently, purely experimental research methods face numerous challenges in studying this transient, high-temperature, high-pressure turbulent combustion process accompanied by complex chemical reactions, including difficulties in measuring point placement, instantaneous parameter capture, high experimental costs, and significant risks. Therefore, developing a numerical model capable of accurately characterizing the mixing behavior of high-pressure hydrogen-oxygen premixed gas, flame propagation characteristics, and the risk of DDT transition is crucial for a deeper understanding of the physicochemical mechanisms of this process, optimizing combustion chamber design and fueling strategies, and ultimately suppressing uncontrolled detonation. It is also a core issue that urgently needs to be addressed to advance hydrogen energy launch technology from theory to engineering application. Summary of the Invention

[0006] To address the technical challenges of controlling the uniformity and rate of hydrogen-oxygen gas mixing under high pressure, and the susceptibility of detonation-to-detonation (DDT) during combustion, this application provides a method for constructing a numerical model of transient high-temperature and high-pressure hydrogen-oxygen premixed combustion in a closed container. By constructing this high-precision numerical model, the mixing and combustion mechanisms can be explored in depth, providing a theoretical basis and methodological support for optimized design, suppression of DDT, and the accurate filling and safe and efficient combustion of hydrogen-oxygen gas.

[0007] In one aspect of this application, a method for constructing a numerical model of transient high-temperature and high-pressure hydrogen-oxygen premixed combustion in a closed container is provided, comprising the following steps: S1. Constructing a physical model: Based on the actual structure of the sealed container, establish a simplified geometric model, which includes the container body and the internal fuse structure; S2. Constructing mathematical models: The flow process is described by the compressible Navier-Stokes equations, the combustion process is described by the multi-component elementary reaction model, and the turbulent process is described by the large eddy simulation (LES) or Reynolds-averaged simulation (RANS) methods. S3. Set up the solver and algorithm: Select a pressure-based solver, use the PISO algorithm for pressure-velocity coupling, and set up the transient calculation mode. S4. Initialization and boundary condition setting: Set the initial working medium to oxygen and introduce hydrogen to mix it. S5. Evaluation of Mixing Uniformity: Spatial Mixing Inhomogeneity (SMD) is used as the evaluation index. The SMD values ​​are calculated on the radial and axial profiles to determine the uniformity of hydrogen-oxygen mixing.

[0008] In one embodiment, the physical model is a frustum cylinder with a bottom diameter larger than its top diameter, and has an ignition fuse inside.

[0009] In one implementation, the combustion process in the mathematical model adopts a 9-component, 19-step elementary reaction model.

[0010] In one implementation, the turbulence simulation method employs the RANS method and selects the k-ω turbulence model.

[0011] In one implementation, the solver is a pressure-based solver that uses the PISO algorithm for transient calculations and sets the gravity direction.

[0012] In one embodiment, the initial pressure of the initial medium is 5.4 MPa.

[0013] In one implementation, the formula for calculating the spatial mixing inhomogeneity (SMD) is:

[0014] Among them, standard deviation ( σ f The formula for calculating ) is: σ f=

[0015] in, N This represents the total number of grid nodes within the statistical scope; Represents the first two-dimensional measurement plane i Fuel mass fraction at each grid node; This represents the arithmetic mean of the fuel mass fraction of all nodes on the plane.

[0016] In one embodiment, the gas quality error during the hydrogen refueling process is controlled within ±1%.

[0017] In one implementation, a physical model is constructed using ANSYS Fluent or ANSYS CFX in step S1.

[0018] In another aspect of this application, a hydrogen-oxygen premixed combustion simulation system based on the above method is provided, comprising: The geometric modeling module is used to construct a three-dimensional geometric model of the sealed container, including the main structure of the container and the internal ignition fuse structure. The mathematical model configuration module is used to configure the control equations and model parameters for the flow process, combustion process, and turbulence process. The solver configuration module is used to select the solver type, set the pressure-velocity coupling algorithm, time advancement mode, and convergence conditions; The post-processing and analysis module is used to visualize the simulation results and calculate the spatial mixing inhomogeneity (SMD) to evaluate the homogeneity of hydrogen-oxygen mixing.

[0019] The beneficial effects of this application are as follows: 1) Revealing complex mechanisms and enhancing inherent safety: The high-fidelity numerical model constructed in this application can clearly reproduce the detailed process of transient high-pressure hydrogen-oxygen combustion in a sealed container, especially successfully capturing the deflagration-to-detonation (DDT) phenomenon. Through simulation, the physicochemical mechanisms leading to DDT, such as the coupling of pressure waves with the flame surface and turbulent acceleration of the flame, can be studied in depth. This provides a theoretical basis and visualization means for designing explosion suppression schemes and formulating safety criteria from the root, greatly improving the inherent safety of hydrogen energy launch technology.

[0020] 2) Achieving Precise Prediction and Optimized Design: By employing detailed elementary reaction models and advanced turbulence models, this model achieves significantly higher prediction accuracy for key parameters such as combustion rate, peak pressure, and temperature distribution compared to traditional empirical or quasi-global reaction models. This allows engineers to virtually optimize the combustion chamber structure, igniter position, fuel mix, and fueling strategy before physical testing, effectively shortening the development cycle, reducing trial-and-error costs, and ultimately achieving higher performance designs (such as higher projectile muzzle velocities).

[0021] 3) Significantly reduces R&D costs and risks: This method replaces or reduces high-risk, high-cost repetitive physical experiments (especially under high pressure environments >30MPa) through computer numerical simulation. It enables the study of extreme conditions (such as near-detonation conditions) in an absolutely safe virtual environment, thereby avoiding potential experimental explosion risks and saving a significant amount of human, material, and financial resources. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating the method for constructing a numerical model of transient high-temperature and high-pressure hydrogen-oxygen premixed combustion in a closed container according to this application. Figure 2 This is a structural diagram of the mixing chamber of this application; where a is the external structure and b is a cross-sectional view. Figure 3 This is a grid diagram of the mixing chamber in this application; Figure 4 This is a mass distribution cloud map showing the variation in the number of vertically placed holes according to an embodiment of this application; where a represents a single hole at the bottom (diameter 20mm), b represents two holes at the bottom (diameter 14.14mm), and c represents four holes at the bottom (diameter 10mm). Figure 5 This is a graph showing the variation of the number of filling holes with the vertically placed SMD in an embodiment of this application. Detailed Implementation

[0023] The technical solution of this application will be clearly and completely described below with reference to specific embodiments. However, those skilled in the art will understand that the embodiments described below are only some embodiments of this application, not all embodiments, and are only used to illustrate this application, and should not be regarded as limiting the scope of this application. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] In one specific embodiment of this application, a method for constructing a numerical model of transient high-temperature and high-pressure hydrogen-oxygen premixed combustion in a closed container is provided to elucidate the flame propagation law, the combustion-detonation transition mechanism, and its suppression method. (Refer to...) Figure 1 As shown, the process includes: constructing a physical model: based on the actual structure of the sealed container, a simplified geometric model is established, which includes the container body and the internal fuse structure; constructing a mathematical model: the flow process is described using the compressible Navier-Stokes equations, the combustion process is described using a multi-component elementary reaction model, and the turbulence process is described using large eddy simulation or Reynolds-averaged simulation; setting the solver and algorithm: a pressure-based solver is selected, the PISO algorithm is used for pressure-velocity coupling, and a transient calculation mode is set; initialization and boundary condition setting: the initial working fluid is set to oxygen, and hydrogen is introduced for mixing; mixing uniformity evaluation: the spatial mixing non-uniformity (SMD) is used as the evaluation index, and the SMD values ​​are calculated on the radial and axial profiles to determine the hydrogen-oxygen mixing uniformity. The specific process is as follows: 1) Physical model construction: Based on the actual structure of the sealed container, a simplified geometric model is established, which includes the container body and the internal fuse structure.

[0025] The simplified model has a volume of three liters, is an approximately cylindrical shape with a slightly larger diameter at the bottom, and contains a cylindrical fuse at the center. The specific structure is as follows: Figure 2 As shown, specific parameters are listed in Table 1. The physical model was constructed using ANSYS Fluent or ANSYS CFX. A schematic diagram of the fluid domain profile is shown below. Figure 2 As shown in b, the internal blank volume is the fuse, serving as an ignition point. The geometry is imported into Fluent, with the specific mesh as shown... Figure 3 As shown.

[0026] Table 1 Cavity Parameters

[0027] 2) Constructing mathematical models: The compressible Navier-Stokes equations are used to describe the flow process, the multi-component elementary reaction model is used to describe the combustion process, and the large eddy simulation or Reynolds-averaged simulation method is used to describe the turbulent process.

[0028] In some embodiments of this application, the combustion process employs a 9-component, 19-step elementary reaction model, as shown in Table 2 below.

[0029] Table 2. Chemical kinetic mechanism model of 19 elementary reactions involving 9 components of hydrogen and oxygen.

[0030] Unit: (cm) 3 (mol, sec, cal, K) In the implementation of the numerical model in this application, the jet mixing process generates highly nonlinear turbulent flow, thus requiring the selection of an appropriate turbulence numerical simulation method. Currently, the mainstream methods include direct numerical simulation (DNS) and indirect numerical simulation methods.

[0031] The direct numerical simulation method described above analyzes vortex structures at all scales by directly solving the transient Navier-Stokes equations. However, this method requires capturing the smallest-scale vortices, placing extremely stringent demands on mesh size and time step, and consuming enormous computational resources, far exceeding the capabilities of current conventional engineering computing hardware, thus making it difficult to apply in practice.

[0032] The indirect numerical simulation methods mentioned include Large Eddy Simulation (LES) and Reynolds-Averaged Flow (RANS). While LES, by directly analyzing large-scale eddies and modeling small-scale eddies, can accurately depict flow field details, it still places high demands on computational grids and resources. In contrast, RANS, by solving time-averaged Navier-Stokes equations, represents transient fluctuations through a model, focusing on characterizing the time-averaged flow field changes caused by turbulence. This method has higher computational efficiency and is the most widely used in engineering practice.

[0033] Preferably, given that the model involved in this application needs to balance computational accuracy and feasibility, the Reynolds-averaged method is chosen as the turbulence simulation method. This method introduces a closed turbulence model and solves the RANS equations; specifically, it employs an eddy viscosity model based on the Boussinesq assumption, introducing turbulent viscosity... μ t With respect to Reynolds stress tensor τ ij To model it, its expression is:

[0034]

[0035] in, S ij Represents the average strain rate tensor, For fluid density, For the average speed at i Components of direction For the average speed at j Components of direction For turbulent viscosity, For the mean strain rate tensor, For turbulent kinetic energy, For the Kronecker function, Let be the velocity divergence.

[0036] Reynolds stress and strain rate tensor S ij The relationship is represented as:

[0037] in, In order to be in i Components of directional pulsation velocity In order to be in j Components of directional pulsation velocity for i , j Covariance of pulsation velocity in direction This refers to turbulent viscosity.

[0038] In some embodiments, the RANS method incorporates multiple turbulence models, and the appropriate model must be selected based on the specific flow characteristics. For example, the SA (Spalart-Allmaras) model exhibits good convergence characteristics when simulating external flow problems such as transonic flow in airfoils, but it lacks integrated wall functions, limiting its ability to resolve near-wall flows. The k-ε model is suitable for flows without significant separation or strong pressure gradients, but its prediction of adverse pressure gradients and flow separation is insufficient. The k-ω model, by introducing a specific turbulent dissipation rate ω that is easier to solve than ε, significantly improves the simulation accuracy for curved flows, separated flows, and conditions with adverse pressure gradients, and is therefore widely used in internal flow problems such as jets. Given that the hydrogen-oxygen mixed jet process within a closed container simulated in this application involves a significant curvature in the flow channel structure, making flow separation prone to occur and potentially creating adverse pressure gradient regions, the k-ω turbulence model is preferably used for numerical calculations to accurately capture these flow characteristics.

[0039] 3) Set up the solver and algorithm: Select a pressure-based solver, use the PISO algorithm for pressure-velocity coupling, and set up the transient calculation mode.

[0040] In some embodiments, the ANSYS Fluent software platform provides two different types of solvers: a pressure-based solver and a density-based solver, the latter also known as a coupled solver. The pressure-based solver uses the projection method to solve the continuity equation and momentum equation separately. It first solves the momentum equation to obtain the velocity field, and then corrects the velocity field by solving the pressure correction equation to ensure mass conservation. This method has relatively low memory requirements and low computational cost, making it very suitable for simulating subsonic and incompressible flows. Given that the initial flow velocity in the hydrogen-oxygen mixing and combustion process within the closed container simulated in this invention is low, and that the pressure-based solver fully meets the accuracy and stability requirements of this simulation, the pressure-based solver is selected in this embodiment.

[0041] Furthermore, the pressure-based solver algorithm is configured. Fluent provides several pressure-velocity coupling algorithms, including SIMPLE, SIMPLEC, PISO, and a pressure-based coupled algorithm (Coupled). For the transient calculations involved in this application, especially in cases where large time steps or mesh distortion may exist, the Pressure Implicit Operator Splitting (PISO) algorithm shows significant advantages. The PISO algorithm belongs to the prediction-correction class of methods. By introducing Neighbor Correction and Skewness Correction, it performs multiple pressure corrections within a single iteration, thereby solving the pressure-velocity field coupling problem more efficiently. This algorithm maintains computational stability even when the relaxation factor is set to 1.0, making it very suitable for transient calculations and effectively accelerating the convergence of unsteady problems. Therefore, this embodiment explicitly selects the PISO algorithm as the pressure-velocity coupling scheme.

[0042] In addition, the physical environment needs to be defined. Since gravity has a potential impact on the stratification and mixing of gases within the container, gravity is enabled in the calculations and its direction is correctly set. The fluid medium is defined as a mixture of hydrogen (H2) and oxygen (O2). When setting up the multiphase flow model, the primary phase is defined as oxygen, and the secondary phase is defined as hydrogen, to accurately simulate the initial state of hydrogen being injected into a container filled with oxygen.

[0043] The convergence of the calculation was assessed using residual monitoring. The residual convergence criterion for all relevant physical quantities (such as continuity, momentum, composition, and energy) was set to 1 × 10⁻⁶. -3 When the residual values ​​of all monitored quantities are below this threshold, the calculation results of the current time step are considered to have converged, and the calculation of the next time step can proceed.

[0044] 4) Initialization and boundary condition setting: Set the initial working medium to oxygen and introduce hydrogen gas for mixing.

[0045] The model was initialized using a hybrid initialization method, which provides a more physically plausible initial field distribution. The initial conditions were set as follows: the entire computational domain was filled with oxygen at a pressure of 5.4 MPa. After the transient calculation began, hydrogen was introduced into this initial environment through boundary condition settings to simulate a real hydrogen refueling process.

[0046] In some embodiments, achieving precise hydrogen and oxygen gas dispensing is a key prerequisite for ensuring the reliability and reproducibility of simulation results. Therefore, the precision of the dispensing process has been specifically defined and controlled.

[0047] The accuracy of the refueling process hinges on the precision of controlling the mass of hydrogen introduced into the container. This application quantifies this accuracy by setting a mass error range for the refueling gas and relating it to the refueling time. Specifically, in numerical simulations, the actual refueling process is simulated by precisely controlling boundary conditions (such as inlet flow rate and pressure variation curves over time). The setting of this refueling curve (or program) fully considers the dynamic characteristics of pneumatic control valves, such as their opening and closing response times, in engineering practice, thereby ensuring that the simulated refueling process accurately reflects the transient behavior of the physical system.

[0048] Based on the sensitivity of hydrogen-oxygen combustion to the equivalence ratio and its engineering feasibility, in this application: at the end of refueling, the error between the actual mass of hydrogen in the container and the theoretical target mass must be controlled within the allowable range of ±1%. This error range is the passing standard for judging whether the refueling process is "precise".

[0049] To achieve this high precision requirement of ±1%, the refueling strategy (such as valve opening rate, refueling duration, etc.) needs to be repeatedly optimized through numerical simulation during implementation until the calculated refueling mass of hydrogen stably falls between 99% and 101% of the target mass at the set refueling time.

[0050] 5) Evaluation of mixing uniformity: Spatial mixing non-uniformity (SMD) is used as the evaluation index. The SMD values ​​are calculated on the radial and axial profiles to determine the mixing uniformity of hydrogen and oxygen.

[0051] To objectively and accurately evaluate the mixing effect, this application introduces Spatial Mixing Non-uniformity (SMD) as a core evaluation indicator.

[0052] The SMD is mathematically defined as the coefficient of variation, which is the standard deviation of a sample. σ f ) and mean ( The ratio of ) is calculated using the following formula:

[0053] Among them, standard deviation ( σ f The formula for calculating ) is: σ f=

[0054] in, N This represents the total number of grid nodes within the statistical scope; Represents the first two-dimensional measurement plane i Fuel mass fraction at each grid node; This represents the arithmetic mean of the fuel mass fraction of all nodes on the plane.

[0055] The physical meaning of this indicator is that the smaller the value, the more uniform the fuel distribution in the oxidizer. Specifically: When SMD≈1, it means that the fuel and oxidant are almost completely separated and in a stratified state, with extremely poor mixing effect; When SMD≈0, it indicates that the fuel concentration distribution tends to be consistent throughout the statistical region, and the mixing is highly uniform.

[0056] To comprehensively evaluate the mixing situation within the container, this application calculates the SMD value along two orthogonal directions, namely the radial and axial profiles, to obtain the spatial distribution characteristics of the mixing uniformity.

[0057] Based on engineering practice and referring to relevant standards for swirl burners, this application sets the acceptable standard for mixing uniformity as: SMD < 0.01. When the calculated SMD value is lower than this threshold, the uniformity of the hydrogen-oxygen mixture is considered to meet the requirements for transient high-pressure combustion.

[0058] In another specific embodiment of this application, a hydrogen-oxygen premixed combustion simulation system based on the above method is provided, including a geometric modeling module, a mathematical model configuration module, a solver configuration module, and a post-processing and analysis module.

[0059] The geometric modeling module is used to construct a three-dimensional geometric model of the sealed container, including the main structure of the container and the internal ignition fuse structure; the geometric modeling module further includes a three-dimensional modeling unit and a mesh generation unit. The three-dimensional modeling unit is used to generate a solid model of the sealed container and the fuse; the mesh generation unit is used to discretize the solid model into a computational mesh.

[0060] The mathematical model configuration module is used to configure the governing equations and model parameters for the flow process, combustion process, and turbulence process. The mathematical model configuration module includes a reaction mechanism setting unit and a turbulence model setting unit. The reaction mechanism setting unit is used to set the multi-step elementary reaction mechanism of hydrogen-oxygen combustion; the turbulence model setting unit is used to select and configure the RANS or LES turbulence model and its parameters.

[0061] The solver configuration module is used to select the solver type, set the pressure-velocity coupling algorithm, time progression mode, and convergence conditions. The solver configuration module includes an algorithm selection unit and a physical condition setting unit. The algorithm selection unit is used to select a pressure-based solver and the PISO algorithm. The physical condition setting unit is used to set the initial pressure, working fluid type, gravity direction, and boundary conditions.

[0062] The post-processing and analysis module is used to visualize the simulation results and calculate the spatial mixing inhomogeneity (SMD) to evaluate the homogeneity of hydrogen-oxygen mixing. The post-processing and analysis module includes an SMD calculation unit and a visualization output unit. The SMD calculation unit is used to calculate the dispersion coefficient of fuel mass fraction on specified radial and axial profiles. The visualization output unit is used to generate spatiotemporal distribution maps of pressure, temperature, and concentration fields.

[0063] The system also includes a refueling control module, which is used to simulate the hydrogen refueling process and adjust the refueling strategy based on quality error feedback, controlling the error within ±1%.

[0064] Example: Analysis of the effect of the number of injection holes on mixing uniformity Hydrogen-oxygen gas is filled into a cylindrical container with a volume of 3 liters. First, the corresponding geometric structure is obtained according to the structural dimensions, as shown in the specific structure below. Figure 2 As shown in (a), the specific parameters are shown in Table 1.

[0065] A schematic diagram of the fluid domain profile is shown below. Figure 2 As shown in (b), the internal blank volume is the ignition tube, which serves to ignite the flame. The geometry is imported into Fluent, and the specific mesh is as follows... Figure 3 As shown.

[0066] Assuming the model is placed vertically, with a constant mass flow rate (0.5 kg / min) and a dispensing time of 20 seconds, simulations were conducted under multiple operating conditions. The specific mass fraction distribution contour plot at 20 seconds is shown below. Figure 4 As shown in Table 3, the specific results are as follows.

[0067] Table 3. Changes in the number of vertically placed holes (hydrogen-oxygen mixture)

[0068] Combination Figure 5 Observations revealed that as the number of pores increased from 1 to 4, the horizontal mass distribution (SMD) of hydrogen in the axial direction gradually decreased from 0.0369 to 0.0118, indicating that the hydrogen distribution became more uniform with increasing pore number. Therefore, under vertical placement conditions, a higher number of pores results in a more uniform mixing of hydrogen and oxygen.

[0069] Although the embodiments of this application have been described above in conjunction with the accompanying drawings, this application is not limited to the specific embodiments and application fields described above. The specific embodiments described above are merely illustrative and instructive, not restrictive. Those skilled in the art can make many other forms based on the guidance of this specification and without departing from the scope of protection of the claims of this application, and these are all within the scope of protection of this application.

Claims

1. A method for constructing a numerical model of transient high-temperature pressurized hydrogen-oxygen premixed combustion in a closed vessel, characterized in that, The method comprises the following steps: S1, constructing a physical model: based on the actual structure of the closed container, a simplified geometric model is established, which comprises a container body and an internal ignition fuse structure; S2, constructing a mathematical model: the flow process is described by using a compressible Navier-Stokes equation, the combustion process is described by using a multi-component elementary reaction model, and the turbulent flow process is described by using a large eddy simulation or a Reynolds average simulation method; S3, setting a solver and an algorithm: a pressure-based solver is selected, a PISO algorithm is used for pressure-velocity coupling, and a transient calculation mode is set; S4, initialization and boundary condition setting: the initial working medium is set to be oxygen, and hydrogen is introduced for mixing; S5, mixing uniformity evaluation: a spatial mixing non-uniformity SMD is used as an evaluation index, and the SMD value is calculated on the radial and axial cross sections respectively, so as to judge the hydrogen-oxygen mixing uniformity.

2. The method according to claim 1, wherein The physical model is a circular truncated column with a bottom diameter greater than a top diameter, and an internal ignition fuse is arranged.

3. The method according to claim 1, wherein In the mathematical model, the combustion process adopts a 9-component 19-step elementary reaction model.

4. The method according to claim 1, wherein The turbulent flow simulation method adopts a Reynolds average simulation method, and a k-ω turbulent flow model is selected.

5. The method of claim 1, wherein the method is characterized by: The solver is a pressure-based solver, a PISO algorithm is used for transient calculation, and the gravity direction is set.

6. The method of claim 1, wherein the method is characterized by: The initial pressure of the initial medium is 5.4 MPa.

7. The method of claim 1, wherein the method further comprises: The calculation formula of the spatial mixing non-uniformity SMD is as follows: wherein the standard deviation The gas mass error of the hydrogen filling process is controlled within ±1%. f The formula for calculating the standard deviation is: In step S1, ANSYS Fluent or ANSYS CFX is used to construct the physical model. f= in, N This represents the total number of grid nodes within the statistical scope; Represents the first two-dimensional measurement plane i Fuel mass fraction at each grid node; This represents the arithmetic mean of the fuel mass fraction of all nodes on the plane.

8. The method of claim 1, wherein the method is characterized by: The method comprises the following steps:

9. The method of claim 1, wherein the method is characterized by: A geometric modeling module is used to construct a three-dimensional geometric model of the closed container, which comprises a container body structure and an internal ignition fuse structure; 10. The hydrogen-oxygen premixed combustion numerical simulation system of any one of claims 1 to 9, wherein, A mathematical model configuration module is used to configure control equations and model parameters of the flow process, the combustion process and the turbulent flow process; A solver configuration module is used to select a solver type, set a pressure-velocity coupling algorithm, a time advancing mode and a convergence condition; A post-processing and analysis module is used to visually process the simulation results, and calculate a spatial mixing non-uniformity to evaluate hydrogen-oxygen mixing uniformity. ​ ​

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