Method for characterizing and predicting movement and enrichment of zinc ash in hot galvanizing furnace nose

Abstract

The invention relates to a characterization prediction method for movement and enrichment of zinc ash in a hot galvanizing furnace nose, and belongs to the technical field of metal material processing and simulation calculation methods. According to the technical scheme, temperature field distribution in the furnace nose is calculated based on finite elements, and an isothermal surface of the melting point temperature of zinc is obtained; a finite element and discrete element coupling model of the furnace nose is established, secondary compiling is conducted on the model, and the calculation cost is reduced on the premise that it is guaranteed that the calculation precision is acceptable; and the movement and enrichment of zinc ash in the furnace nose are calculated and represented by using the coupling model. The method has the beneficial effects that result data are visualized, and the black box problem of zinc ash movement in the furnace nose in actual production is solved; operation is simple, a water model test is not needed, and cost investment of experimental equipment is greatly reduced; and the calculation cost is low, and the cost investment of calculation power is greatly reduced.

Description

Technical Field

[0001] The invention relates to a method for characterizing and predicting the movement and enrichment of zinc ash in a hot-dip galvanizing furnace nose, and belongs to the technical field of metal material processing and simulation calculation methods. Background Art

[0002] In the hot-dip galvanizing process, the furnace nose is a key component connecting the annealing furnace and the zinc pot. The generation, movement, and accumulation of zinc ash inside it directly affect the coating quality and equipment stability. Traditional methods mainly rely on water model tests or empirical observations, which have the following problems:

[0003] 1. High experimental cost: complex water models need to be built, equipment investment is large, and the cycle is long;

[0004] 2. Black box effect: The high temperature and closed environment inside the furnace nose makes it difficult to directly observe the movement of zinc ash;

[0005] 3. Low computational efficiency: Existing numerical simulation methods (such as pure discrete element models) are difficult to implement due to the extremely small particle size of zinc ash (0.01-0.001 mm), which results in an explosion in computational complexity.

[0006] Furthermore, existing simulation methods proposed in patents and literature often focus on simulating a single field, such as temperature or flow, and fail to effectively couple the discrete characteristics of zinc ash particles with their thermodynamic behavior, resulting in insufficient prediction accuracy. Therefore, an efficient and low-cost numerical simulation method is urgently needed to accurately predict the dynamic behavior of zinc ash within the furnace nose. Summary of the Invention

[0007] The purpose of the present invention is to provide a method for characterizing and predicting the movement and enrichment of zinc ash in the nose of a hot-dip galvanizing furnace. The method characterizes the movement and enrichment of zinc ash in the nose of the furnace by simulating a secondary compiled model based on the coupling of finite element and discrete element methods, and visualizes the result data, thereby solving the black box problem of zinc ash movement in the nose of the furnace in actual production. The method is simple to operate and does not require a water model test, which greatly reduces the cost of experimental equipment investment. The method has low computational cost, which greatly reduces the cost of computing power investment, and effectively solves the above-mentioned problems existing in the background technology.

[0008] The technical solution of the present invention is: a method for predicting the movement and enrichment of zinc ash in a hot-dip galvanizing furnace nose, comprising the following steps:

[0009] (1) Calculate the internal temperature field of the furnace nose based on the finite element method and extract the zinc melting point isothermal surface;

[0010] (2) Establish a coupled finite element and discrete element model and optimize the model algorithm through secondary compilation;

[0011] (3) Run the coupling model to output visualization data of zinc ash movement trajectory and enrichment area.

[0012] The specific implementation steps of step (1) are as follows:

[0013] (11) Based on the geometric parameters and process parameters of the hot-dip galvanizing furnace nose, a three-dimensional finite element model was established;

[0014] (12) Solve the steady-state / transient heat transfer equations and calculate the temperature field distribution inside the furnace nose;

[0015] (13) The isothermal surface corresponding to the melting point of zinc is extracted as the boundary condition for the zinc ash phase transition.

[0016] The specific implementation steps of step (2) are as follows:

[0017] (21) The furnace nose is divided into the FEM domain, and the zinc ash particles are modeled as the DEM domain;

[0018] (22) Based on the problem of extremely high computational complexity caused by the actual zinc ash particle size, a mechanically equivalent particle scaling method was proposed;

[0019] (23) Establish thermal-mechanical coupling equations and define the two-way data interaction mechanism between the FEM domain and the DEM domain;

[0020] (24) Optimize the model algorithm through secondary compilation.

[0021] In the step (22), the physical properties of the zinc ash particles in the discrete element model are calibrated through experiments, and user-defined parameters are supported.

[0022] In the step (22), the particle size of the zinc ash particles in the discrete element model is magnified to 0.1-1 mm by a mechanical equivalent scaling method, the particle density is proportionally reduced according to the scaling factor n, and the buoyancy effect is ignored.

[0023] The scaling factor n satisfies ρ sim =ρ real / n to ensure that the ratio of the drag force to the gravity acting on the particles in the simulation is consistent with the actual working conditions.

[0024] The buoyancy is negligible when the ratio of buoyancy to gravity is ≤ 1 / 5000.

[0025] In the step (24), the secondary compilation optimization includes dynamic mesh refinement, GPU parallel computing strategy and time step adaptive adjustment, and the simulation results are accelerated by the machine learning agent model to optimize the parameters.

[0026] The specific implementation steps of step (3) are as follows:

[0027] (31) Input process parameters and run the coupling model;

[0028] (32) Real-time output of the position, velocity, collision frequency and three-dimensional distribution data of zinc ash particles in the enrichment area;

[0029] (33) The movement trajectory of zinc ash, the enrichment hot spots, and the dynamic process of its evolution over time are displayed through a visual interface.

[0030] The beneficial effects of the present invention are: through the simulation of the secondary compiled model based on the coupling of finite element and discrete element, the movement and enrichment of zinc ash in the furnace nose are characterized, and the result data is visualized, thereby solving the black box problem of zinc ash movement in the furnace nose in actual production; the operation is simple, and no water model test is required, which greatly reduces the cost investment in experimental equipment; the calculation cost is low, which greatly reduces the cost investment in computing power. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is the FEM-DEM coupling model architecture and data interaction flow chart of the present invention;

[0032] Figure 2 Schematic diagram of the FEM temperature field distribution and zinc melting point isothermal surface of the furnace nose of the present invention;

[0033] Figure 3 This is a visualization diagram of the zinc ash movement trajectory and enrichment area of ​​the present invention;

[0034] Figure 4 This is a visualization diagram of the enriched area after the calculation of the present invention is completed;

[0035] Figure 5 This is a diagram of zinc ash enrichment after production of the present invention;

[0036] In the figure: upper wall of furnace nose 1, strip steel 2, lower wall of furnace nose 3. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the invention implementation cases clearer, the technical solutions in the invention implementation cases will be clearly and completely described below in conjunction with the drawings in the implementation cases. Obviously, the implementation cases described are only a small part of the implementation cases of the present invention, rather than all the implementation cases. Based on the implementation cases in the present invention, all other implementation cases obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0038] A method for characterizing and predicting the movement and enrichment of zinc ash in a hot-dip galvanizing furnace nose comprises the following steps:

[0039] (1) Calculate the internal temperature field of the furnace nose based on the finite element method and extract the zinc melting point isothermal surface;

[0040] (2) Establish a coupled finite element and discrete element model and optimize the model algorithm through secondary compilation;

[0041] (3) Run the coupling model to output visualization data of zinc ash movement trajectory and enrichment area.

[0042] The specific implementation steps of step (1) are as follows:

[0043] (11) Based on the geometric parameters and process parameters of the hot-dip galvanizing furnace nose, a three-dimensional finite element model was established;

[0044] (12) Solve the steady-state / transient heat transfer equations and calculate the temperature field distribution inside the furnace nose;

[0045] (13) The isothermal surface corresponding to the melting point of zinc is extracted as the boundary condition for the zinc ash phase transition.

[0046] The specific implementation steps of step (2) are as follows:

[0047] (21) The furnace nose is divided into the FEM domain, and the zinc ash particles are modeled as the DEM domain;

[0048] (22) Based on the problem of extremely high computational complexity caused by the actual zinc ash particle size, a mechanically equivalent particle scaling method was proposed;

[0049] (23) Establish thermal-mechanical coupling equations and define the two-way data interaction mechanism between the FEM domain and the DEM domain;

[0050] (24) Optimize the model algorithm through secondary compilation.

[0051] In the step (22), the physical properties of the zinc ash particles in the discrete element model are calibrated through experiments, and user-defined parameters are supported.

[0052] In the step (22), the particle size of the zinc ash particles in the discrete element model is magnified to 0.1-1 mm by a mechanical equivalent scaling method, the particle density is proportionally reduced according to the scaling factor n, and the buoyancy effect is ignored.

[0053] The scaling factor n satisfies ρ sim =ρ real / n to ensure that the ratio of the drag force to the gravity acting on the particles in the simulation is consistent with the actual working conditions.

[0054] The buoyancy is negligible when the ratio of buoyancy to gravity is ≤ 1 / 5000.

[0055] In the step (24), the secondary compilation optimization includes dynamic mesh refinement, GPU parallel computing strategy and time step adaptive adjustment, and the simulation results are accelerated by the machine learning agent model to optimize the parameters.

[0056] The specific implementation steps of step (3) are as follows:

[0057] (31) Input process parameters and run the coupling model;

[0058] (32) Real-time output of the position, velocity, collision frequency and three-dimensional distribution data of zinc ash particles in the enrichment area;

[0059] (33) The movement trajectory of zinc ash, the enrichment hot spots, and the dynamic process of its evolution over time are displayed through a visual interface.

[0060] In practical applications, the implementation steps of the present invention are as follows:

[0061] 1. Temperature field modeling and isothermal surface extraction

[0062] Step S1, establishing a three-dimensional finite element model based on the geometric parameters and process parameters (such as zinc liquid temperature and gas flow rate) of the hot-dip galvanizing furnace nose;

[0063] Step S2, solving the steady-state / transient heat transfer equations to calculate the temperature field distribution inside the furnace nose;

[0064] Step S3: extracting the isothermal surface corresponding to the melting point of zinc (419.5° C.) as the boundary condition for the zinc ash phase transformation.

[0065] 2. Construction of FEM-DEM coupling model

[0066] Step S1, dividing the furnace nose into FEM domain (finite element mesh) and modeling the zinc ash particles into DEM domain (discrete element);

[0067] In step S2, based on the extremely high computational complexity caused by the actual zinc ash particle size (0.01-0.001 mm), a mechanically equivalent particle scaling method is proposed:

[0068] a. Enlarge the zinc ash particle size in the simulation to a calculable range (0.1-1 mm) with a scaling factor of n. At the same time, reduce the particle density proportionally so that the ratio of drag force to gravity on the particles remains consistent with the actual working conditions.

[0069] b. Define the scaled particle density as ρ sim =ρ real / n, ensuring a constant ratio of the drag force (related to the square of the particle size) to the gravity force (related to the cube of the particle size);

[0070] c. Ignore the buoyancy effect in the finite element model (i.e., set the gravity acceleration g = 0) and verify its negligibility based on the actual buoyancy to gravity ratio (approximately 1 / 5300);

[0071] Step S3, establishing the thermal-mechanical coupling equation and defining the two-way data interaction mechanism between the FEM domain (temperature field, airflow field) and the DEM domain (particle motion);

[0072] Step S4, optimizing the model algorithm through secondary compilation, includes:

[0073] a. Dynamic mesh refinement: Automatically refine the mesh in zinc ash-rich areas and coarsen the mesh in areas away from the area to reduce the computational effort;

[0074] b. Parallel computing strategy: GPU-accelerated discrete element particle collision detection algorithm;

[0075] c. Adaptive time step adjustment: Dynamically adjust the integration step size according to the particle movement speed to balance accuracy and efficiency.

[0076] 3. Zinc ash movement and enrichment simulation

[0077] Step S1, input process parameters (zinc liquid flow rate, gas pressure, furnace nose inclination, zinc ash viscosity, etc.) and run the coupling model;

[0078] Step S2, outputting the position, velocity, collision frequency and three-dimensional distribution data of the zinc ash particles in real time;

[0079] Step S3: Display the zinc ash movement trajectory, enrichment hotspots, and dynamic process of evolution over time through a visual interface.

[0080] Example 1

[0081] Take the hot-dip galvanizing production line of a steel company as an example:

[0082] 1. Input the furnace nose model, zinc liquid temperature 460℃, and gas flow rate 3m / s;

[0083] 2. Run the finite element model to obtain the temperature field distribution and extract the 419.5°C isothermal surface;

[0084] 3. When constructing the discrete element model, the actual zinc ash particle size of 0.01 mm was enlarged to 1 mm (scaling factor n = 100), and the particle density was changed from the actual value of 7.14 g / cm 3 Adjusted to 0.0714 g / cm 3 , turn off buoyancy calculation in the finite element domain;

[0085] 4. Secondary compilation optimization was initiated, using GPU parallel computing. Compared with simulations using actual zinc ash particle size (0.01-0.001mm), the calculation time was shortened from approximately 4 months to 48 hours.

[0086] 5. The output zinc ash enrichment hotspot is located at the furnace nose, which is basically consistent with the actual production test results;

[0087] 6. There is no significant difference between the simulation results and the results using the actual zinc ash particle size (0.01-0.001mm), which verifies the effectiveness of the scaling method.

[0088] Example 2

[0089] Adjust the process parameters (divide the air intake time into three time periods, and start with an air intake volume of 20m 3 / h, 10m in the middle 3 / h, eventually 5m 3 / h), the simulation shows that the enrichment area is larger and the particle distribution is more uniform, which guides enterprises to add process parameter settings to reduce the probability of zinc ash falling due to excessive enrichment during the production cycle.

[0090] The present invention can make accurate predictions, revealing the generation and movement laws of zinc ash under the action of temperature gradient and airflow through the FEM-DEM coupling model, and improving the accuracy of predicted enrichment areas by ≥30%; it is computationally feasible, and based on the mechanical equivalent scaling method, it solves the problem of explosion in simulation calculation amount of micron-level particles, shortening the simulation time by more than 90%; it has cost advantages, does not require water model tests, saves more than 90% of equipment investment, and secondary compilation optimization reduces computing resource consumption by 60%-80%; it optimizes the process, and the visualized results guide the design of the furnace nose structure (such as the guide plate angle) and the adjustment of process parameters (gas flow rate process parameters), reduces the frequency of shutdowns for cleaning, reduces the probability of excessive enrichment and falling of zinc ash, and improves the surface quality of the coating.

[0091] The above is only an embodiment of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme is not described in detail here. Ordinary technicians in the field are aware of all common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the field can improve and implement this scheme in combination with their own abilities under the inspiration given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for characterizing and predicting the movement and enrichment of zinc ash in a hot-dip galvanizing furnace nose, characterized in that The following steps are involved: (1) Calculate the internal temperature field of the furnace nose based on the finite element method and extract the zinc melting point isothermal surface; (2) Establish a coupled finite element and discrete element model and optimize the model algorithm through secondary compilation; (3) Run the coupling model to output visualization data of zinc ash movement trajectory and enrichment area.

2. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 1, characterized in that: The specific implementation steps of step (1) are as follows: (11) Based on the geometric parameters and process parameters of the hot-dip galvanizing furnace nose, a three-dimensional finite element model was established; (12) Solve the steady-state / transient heat transfer equations and calculate the temperature field distribution inside the furnace nose; (13) The isothermal surface corresponding to the melting point of zinc is extracted as the boundary condition for the zinc ash phase transition.

3. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 1, characterized in that: The specific implementation steps of step (2) are as follows: (21) The furnace nose is divided into the FEM domain, and the zinc ash particles are modeled as the DEM domain; (22) Based on the problem of extremely high computational complexity caused by the actual zinc ash particle size, a mechanically equivalent particle scaling method was proposed; (23) Establish thermal-mechanical coupling equations and define the two-way data interaction mechanism between the FEM domain and the DEM domain; (24) Optimize the model algorithm through secondary compilation.

4. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 3, characterized in that: In the step (22), the physical properties of the zinc ash particles in the discrete element model are calibrated through experiments, and user-defined parameters are supported.

5. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 3, characterized in that: In the step (22), the particle size of the zinc ash particles in the discrete element model is magnified to 0.1-1 mm by a mechanical equivalent scaling method, the particle density is proportionally reduced according to the scaling factor n, and the buoyancy effect is ignored.

6. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 5, characterized in that: The scaling factor n satisfies ρ sim =ρ real / n to ensure that the ratio of the drag force to the gravity acting on the particles in the simulation is consistent with the actual working conditions.

7. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 5, characterized in that: The buoyancy is negligible when the ratio of buoyancy to gravity is ≤ 1 / 5000.

8. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 3, characterized in that: In the step (24), the secondary compilation optimization includes dynamic mesh refinement, GPU parallel computing strategy and time step adaptive adjustment, and the simulation results are accelerated by the machine learning agent model to optimize the parameters.

9. The method for characterizing and predicting zinc ash movement and enrichment in a hot-dip galvanizing furnace nose according to claim 1, characterized in that: The specific implementation steps of step (3) are as follows: (31) Input process parameters and run the coupling model; (32) Real-time output of the position, velocity, collision frequency and three-dimensional distribution data of zinc ash particles in the enrichment area; (33) The movement trajectory of zinc ash, the enrichment hot spots, and the dynamic process of its evolution over time are displayed through a visual interface.

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