Temperature field simulation method for spray quenching process based on FLUENT

Abstract

The invention discloses a FLUENT-based temperature field simulation method for a jet quenching process, belongs to the technical field of heat treatment numerical simulation, and aims to solve the technical problems that the temperature measurement difficulty of an anti-heat transfer method is high and the heat exchange coefficient at an interface is difficult to accurately and reversely deduce in the temperature field research of the quenching process of an existing large-scale variable-cross-section steel pipe. The temperature field simulation method comprises the following steps: S1, establishing a solid structure and an internal fluid geometric model; s2, constructing a solid structure and an internal fluid grid model; s3, setting a solving method; s4, setting calculation boundary conditions; s5, finite element simulation analysis is conducted on the quenching cooling process of the large-scale variable-cross-section steel pipe through Fluent software, and a simulation result is obtained; s6, analyzing a simulation result to obtain a temperature change curve and a temperature distribution cloud chart of the large-scale variable-cross-section steel pipe at different moments; and S7, determining quenching process parameters according to a simulation result. According to the method, more accurate and reliable temperature field data of the large variable-cross-section steel pipe in the inner-spraying and outer-spraying quenching process can be obtained.

Description

Technical Field

[0001] This invention belongs to the field of numerical simulation technology of heat treatment, and in particular relates to a temperature field simulation method for the spray quenching process based on FLUENT. Background Technology

[0002] Heat treatment plays a decisive role in the microstructure and properties of large variable cross-section steel pipe blanks, and is one of the important processes in the manufacturing of large variable cross-section steel pipes. A well-designed quenching heat treatment process can enable large variable cross-section steel pipe blanks to achieve higher strength and reduce deformation. This mainly depends on the quenching cooling rate and cooling uniformity. Therefore, calculating and predicting the temperature field during the quenching process of large variable cross-section steel pipes is of great significance in the field of steel product manufacturing.

[0003] Currently, large variable cross-section steel pipes in China still employ vertical heat treatment using pit furnaces, which suffers from slow and uneven cooling rates. This leads to coarse grains, uneven microstructure, severe deformation, and low production efficiency. Therefore, using a water-spray quenching process with strong cooling capacity can significantly improve the performance of variable cross-section steel pipe blanks, facilitating the full exploitation of the material's potential. However, due to the strong cooling capacity of water-spray quenching, a large temperature difference can occur between the surface and core of large forgings, increasing the risk of quenching cracks. Therefore, large variable cross-section steel pipe blanks require appropriate heat treatment processes and water spraying parameters to reduce the risk of cracking.

[0004] In water spray quenching, the density of the quenching medium jet and the quenching temperature are directly related to heat transfer and are crucial factors determining post-quenching deformation, microstructure distribution, and residual stress. This makes predicting and controlling the quenching state of large variable cross-section steel pipes a key step in achieving production goals. The finite element method (FEM) is widely used in quenching simulation, and many general-purpose FEM packages can be used to solve numerous problems in engineering. Currently, research on the temperature field during the quenching process of large components often employs experimental methods. This involves using measured temperature drop data of steel plates, calculating the average convective heat transfer coefficient using the reverse heat transfer method, and then using this average convective heat transfer coefficient as the boundary condition to calculate the quenching temperature field. However, this method cannot accurately and objectively reflect the internal temperature changes of the workpiece; the simulation results only provide qualitative analysis and lack flexibility. When quenching process parameters change, industrial experiments need to be repeated, resulting in high experimental costs. Summary of the Invention

[0005] Based on the above analysis, the present invention aims to provide a temperature field simulation method for the spray quenching process based on FLUENT, in order to solve the technical problem that the reverse heat transfer method is difficult to measure temperature in the temperature field research of the quenching process of large variable cross-section steel pipes, making it difficult to accurately deduce the heat transfer coefficient at the interface, and thus unable to objectively and realistically reflect the temperature change of the steel pipe.

[0006] The objective of this invention is mainly achieved through the following technical solutions:

[0007] This invention provides a temperature field simulation method for a spray quenching process based on FLUENT, the method comprising the following steps:

[0008] S1. Establish the geometric model of the solid structure and internal fluid;

[0009] The solid structure refers to a large variable cross-section steel pipe, and the internal fluid refers to a quenching medium.

[0010] S2. Mesh the solid structure and internal fluid geometry model to construct a mesh model of the solid structure and internal fluid.

[0011] The process of constructing the solid structure and internal fluid mesh model includes: importing the solid structure and internal fluid geometric model into CFD software; performing polyhedral mesh generation on the large variable cross-section steel pipe and the internal fluid as a whole; adding 4-7 boundary layers at the interface between the inner wall of the large variable cross-section steel pipe and the internal fluid for local refinement; and adding 4-6 boundary layers at the outer wall of the large variable cross-section steel pipe for local refinement, thus obtaining the solid structure and internal fluid mesh model; then importing the solid structure and internal fluid mesh model into Fluent software for quality inspection and mesh number estimation, finally obtaining the solid structure and internal fluid mesh model that meets the simulation requirements;

[0012] S3. Set the solution method;

[0013] The process of setting up the solution method is as follows: set up a simulation calculation model of the internal fluid of a large variable cross-section steel pipe and set the simulation parameters; the solution method is SIMPLE, and the momentum, turbulent kinetic energy, turbulent dissipation rate and energy parameters are all selected using the Second Order Upwind upwind scheme; the simulation calculation model of the internal fluid of the steel pipe is calculated using the Realizable k-ε turbulence model.

[0014] S4. Set the calculation boundary conditions;

[0015] Set calculation boundary conditions, including using the convective heat transfer coefficient h of the outer surface of steel pipes with different cross sections as calculation boundary conditions;

[0016] S5. The quenching and cooling process of large variable cross-section steel pipes was analyzed by finite element simulation using Fluent software, and the simulation results were obtained.

[0017] S6. Analyze the simulation results to obtain the temperature change curves and temperature distribution cloud maps of the large variable cross-section steel pipe at different times.

[0018] S7. Determine the quenching process parameters based on the simulation results;

[0019] Based on the simulation results, we analyze and judge whether the quenching and cooling of large variable cross-section steel pipes can achieve the expected rapid and uniform cooling, and determine the corresponding quenching process parameters, namely the water flow intensity of the internal water spray and the spray density of the external water spray.

[0020] Furthermore, in S1, the solid structure and internal fluid geometry model are established using DesignModeler software.

[0021] Furthermore, in S1, when establishing the solid structure and internal fluid geometry model, based on the geometry of the fixed structure, the solid structure is directly divided into different cross-sectional dimensions in the DesignModeler software and defined as bady1, body2...bodyN, where N represents the number of different cross-sectional dimensions, and N≤20.

[0022] Furthermore, in S1, the walls of the computational domain are defined. The inner and outer surfaces of the large variable cross-section steel pipe are defined as walls, the internal fluid is named fluid, one end of the internal fluid is defined as the inlet, and the other end of the internal fluid is defined as the outlet. Finally, the solid structure and the internal fluid are combined into a single component.

[0023] Furthermore, in step S4, steel pipe sections with different wall thicknesses are named bady1, body2...bodyN, where N represents the number of different cross-sectional dimensions, and N≤20; different jet water flow densities W are set according to the different steel pipe section thicknesses. f .

[0024] Furthermore, in S4, the fluid inlet flow velocity, fluid outlet, and residual convergence criteria are set as required.

[0025] Furthermore, in step S4, through iterative calculation, attention is paid to the convergence of the residuals. If the residuals converge but the temperature distribution does not meet the requirements, the calculation parameter, jet flow density w, is adjusted. f Recalculate until the requirements for residual convergence and temperature distribution are met.

[0026] Furthermore, in step S6, after the calculation is completed, the original data of the temperature monitoring points are exported to obtain the temperature change curves and distribution cloud maps of the large variable cross-section steel pipe at different times.

[0027] Furthermore, in S7, if the quenching and cooling of the large variable cross-section steel pipe does not achieve the expected rapid and uniform cooling, the process returns to S4, and the jet water flow density W is modified. fThe boundary conditions h are reset and the calculation is repeated until the steel pipe quenching and cooling achieves the expected rapid and uniform cooling effect.

[0028] Furthermore, in S4, the convective heat transfer coefficient h is specifically as follows:

[0029]

[0030] Among them, w f The density of the jet water flow is expressed in L / (m³). 2 ·s), where Ts is the surface temperature of the steel pipe, in °C.

[0031] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0032] (1) This invention can define dynamic convective heat transfer boundary conditions. In the prior art, the reverse heat transfer method is difficult to accurately deduce the heat transfer coefficient at the interface, and usually uses a static average value. This invention introduces a complex function related to the jet water flow density Wf and the steel pipe surface temperature Ts to define the convective heat transfer coefficient h. That is, in the simulation process of this invention, the heat transfer coefficient h is no longer a fixed value, but is dynamically adjusted according to the actual jet intensity of the quenching medium and the real-time surface temperature of the steel pipe. This dynamic boundary condition can more realistically reflect the complex heat transfer mechanism at the interface during the quenching process, and solves the core technical problem of the difficulty in accurately determining the heat transfer coefficient.

[0033] (2) Using the above geometric and mesh models, solution methods, and dynamic boundary conditions, transient finite element simulations were performed in FLUENT software to calculate the temperature distribution and changes of the steel pipe at different times. This method avoids expensive and time-consuming industrial experiments and provides more comprehensive internal temperature field data than experimental methods.

[0034] (3) The simulation results of this invention (e.g., temperature change curves and distribution cloud maps) provide detailed temperature field data, which can intuitively evaluate the uniformity and efficiency of quenching cooling. If the cooling effect is not ideal, the jet water flow density Wf process parameter can be adjusted in a targeted manner based on the feedback of the simulation results, and the simulation can be repeated. This iterative optimization process greatly reduces experimental costs and improves process development efficiency while ensuring simulation accuracy, and can obtain more accurate and reliable temperature field data, ultimately achieving rapid and uniform cooling of large variable cross-section steel pipes.

[0035] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0036] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0037] Figure 1 This is a flowchart of the temperature field simulation method for the spray quenching process based on Fluent according to the present invention.

[0038] Figure 2 This is a schematic diagram of the geometric structure and internal fluid structure of the large variable cross-section steel pipe of Embodiment 1 of the present invention;

[0039] Figure 3 This is a schematic diagram of the overall three-dimensional computational mesh for a large variable cross-section steel pipe according to Embodiment 1 of the present invention;

[0040] Figure 4 This is a schematic diagram of the local mesh for three-dimensional calculation of a large variable cross-section steel pipe according to Embodiment 1 of the present invention;

[0041] Figure 5 This is a schematic diagram defining the solution method of Embodiment 1 of the present invention;

[0042] Figure 6 This is a schematic diagram illustrating the selection of the turbulence model in Embodiment 1 of the present invention;

[0043] Figures 7a-7c This is a schematic diagram illustrating the definition of solid structure materials in Embodiment 1 of the present invention;

[0044] Figure 8 This is a schematic diagram of the activated energy equation state in Embodiment 1 of the present invention;

[0045] Figure 9 This is a schematic diagram illustrating the definition of the relaxation factor in Embodiment 1 of the present invention;

[0046] Figure 10 This is a schematic diagram illustrating the initialization parameter definition in Embodiment 1 of the present invention;

[0047] Figure 11 This is a schematic diagram of the local initialization parameter definition in Embodiment 1 of the present invention.

[0048] Figure 12 This is a schematic diagram illustrating the definition of temperature monitoring points for a large variable cross-section steel pipe according to Embodiment 1 of the present invention;

[0049] Figure 13 This is a schematic diagram illustrating the definition of the temperature boundary conditions on the outer wall of a large variable cross-section steel pipe according to Embodiment 1 of the present invention.

[0050] Figure 14 This is a schematic diagram defining the internal fluid pressure inlet boundary conditions in Embodiment 1 of the present invention;

[0051] Figure 15 This is a schematic diagram illustrating the definition of the internal fluid pressure outlet boundary conditions in Embodiment 1 of the present invention;

[0052] Figure 16 This is a schematic diagram illustrating the residual definition in Embodiment 1 of the present invention;

[0053] Figure 17 This is a schematic diagram illustrating the definition of the calculation time step in Embodiment 1 of the present invention;

[0054] Figure 18 This is a temperature evolution curve of the steel pipe at different axial positions under operating condition 1 in Embodiment 1 of the present invention;

[0055] Figure 19 This is a temperature evolution curve of the steel pipe at different axial positions under working condition 2 in Embodiment 1 of the present invention;

[0056] Figure 20 This is a temperature evolution curve of the steel pipe at different axial positions under working condition 3 in Embodiment 1 of the present invention;

[0057] Figure 21 This is a temperature evolution curve of the steel pipe at different axial positions under working condition 4 in Embodiment 1 of the present invention;

[0058] Figure 22 This is a cloud map showing the cooling temperature distribution of the steel pipe at different times under operating condition 1 in Embodiment 1 of the present invention;

[0059] Figure 23 This is a cloud map showing the cooling temperature distribution of the steel pipe at different times under operating condition 2 in Embodiment 1 of the present invention;

[0060] Figure 24 This is a cloud map showing the cooling temperature distribution of the steel pipe at different times under operating condition 3 in Embodiment 1 of the present invention;

[0061] Figure 25 This is a cloud map showing the cooling temperature distribution of the steel pipe at different times under working condition 4 in Embodiment 1 of the present invention. Detailed Implementation

[0062] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which constitute a part of the present invention and, together with Embodiment 1 of the present invention, are used to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0063] In existing technologies, research on the temperature field during the quenching process of large variable cross-section steel pipes often employs a combination of experimental and reverse heat transfer methods. Specifically, this involves calculating the average convective heat transfer coefficient using measured steel plate temperature drop data and then using this average heat transfer coefficient as a boundary condition to calculate the quenching temperature field. However, this method suffers from the following problems:

[0064] (1) Temperature measurement is difficult: The experimental method requires actual temperature measurement of large variable cross-section steel pipes. Due to the large size, complex structure and transient characteristics of the steel pipes and the quenching process, it is very difficult to perform accurate temperature measurement in the actual industrial environment.

[0065] (2) Difficulty in accurately deriving the heat transfer coefficient at the interface: The reverse heat transfer method can only calculate the average convective heat transfer coefficient and cannot accurately derive the local and transient heat transfer coefficient at the interface between the steel pipe and the quenching medium. During the quenching process, the heat transfer coefficient may vary significantly at different locations and times, and the average value cannot truly reflect the local heat transfer situation.

[0066] (3) It cannot truly and objectively reflect the internal temperature changes of the workpiece: Due to the limitations of the average heat transfer coefficient and the difficulty of measurement, the simulation results of the quenching temperature field calculated based on this method cannot truly and objectively reflect the actual internal temperature changes of the workpiece, especially inside complex variable cross-section steel pipes.

[0067] (4) The simulation results are qualitative and lack flexibility, and the experimental cost is high: The simulation results provided by the existing methods can often only be used for qualitative analysis and lack precise quantitative guidance. More importantly, when it is necessary to change the quenching process parameters (such as the density of the jet water flow, the quenching temperature, etc.), it is necessary to carry out expensive industrial experiments again to obtain new data, which leads to high experimental costs, long cycles and low efficiency.

[0068] This invention provides a temperature field simulation method for a Fluent-based spray quenching process, comprising the following steps:

[0069] S1. Establish the geometric model of the solid structure and internal fluid;

[0070] The solid domain and internal fluid domain within the geometric model are defined.

[0071] In step S1 above, a geometric model of the solid structure and internal fluid is established, and the solid domain and internal fluid domain within the geometric model are defined; wherein, the solid structure refers to a large variable cross-section steel pipe, and the internal fluid refers to the quenching medium.

[0072] In step S1 above, when establishing the geometric model, the geometric model of the solid structure (large variable cross-section steel pipe) and the internal fluid (quenching medium) is established by using DesignModeler software.

[0073] In step S1 above, based on the geometry of the solid structure, the solid structure (large variable cross-section steel pipe) is directly divided into different cross-sectional dimensions in the DesignModeler software and defined as bady1, body2...bodyN, where N represents the number of different cross-sectional dimensions, and N≤20.

[0074] In step S1 above, the walls of the computational domain are defined. The inner and outer surfaces of the large variable cross-section steel pipe are defined as walls. The internal fluid (quenching medium) is named fluid. One end of the internal fluid is defined as the inlet and the other end of the internal fluid is defined as the outlet. Finally, the solid structure and the internal fluid are combined into a component.

[0075] S2. Construct a solid structure and internal fluid mesh model;

[0076] In step S2 above, the process of constructing the solid structure and internal fluid mesh model includes: importing the geometric model of the solid structure (large variable cross-section steel pipe) and the internal fluid (quenching medium) into CFD software; performing polyhedral meshing on the large variable cross-section steel pipe and the internal fluid as a whole; adding 4-7 boundary layers at the interface between the inner wall of the large variable cross-section steel pipe and the internal fluid for local refinement; and adding 4-6 boundary layers at the outer wall of the large variable cross-section steel pipe for local refinement, thus obtaining the solid structure and internal fluid mesh model; then importing the solid structure and internal fluid mesh model (i.e., the large variable cross-section steel pipe and quenching medium mesh model) into Fluent software for quality inspection and mesh quantity estimation, finally obtaining the solid structure and internal fluid mesh model that meets the simulation requirements.

[0077] S3. Set the solution method;

[0078] In step S3 above, the process of setting the solution method is as follows: setting up a simulation calculation model of the internal fluid of a large variable cross-section steel pipe and setting simulation parameters; among them, the solution method is SIMPLE, and the momentum, turbulent kinetic energy, turbulent dissipation rate and energy are all selected from the second order upwind scheme; the simulation calculation model of the internal fluid of the steel pipe is calculated using the Realizable k-ε turbulence model.

[0079] The aforementioned Realizable k-ε turbulence model specifically includes:

[0080]

[0081] Where ρ is the fluid density, in kg / m³, and k is the turbulent kinetic energy, in m³ / s. 2 / s 2 t represents time, in seconds (s), u iFor velocity components, the unit is m / s, x i Let x be the spatial coordinate. j Let μ be the spatial coordinate. j P is the fluid dynamic viscosity, in Pa·s. k ε is the turbulent kinetic energy transport term, and ε is the turbulent kinetic energy dissipation term, in meters. 2 / s 3 .

[0082]

[0083] Where ρ is the fluid density, in kg / m³ 3 k is the turbulent kinetic energy, in m³. 2 / s 2 t represents time, in seconds (s), u i For velocity components, the unit is m / s, x i Let μ be the spatial coordinate. t The turbulent dynamic viscosity is expressed in Pa·s, σ ε C is the dissipation suppression function for turbulent flow. 1ε C 2ε These are model constants.

[0084] The simulation parameters set above include setting the properties of the fluid, such as density, specific heat capacity, and thermal conductivity; setting the flow velocity and flow intensity of the internal fluid; and setting the properties of the solid structure, including density, specific heat capacity, and thermal conductivity.

[0085] It is important to note that simulation parameters directly affect the accuracy of simulation results. Properly setting these parameters allows the simulation to more closely resemble the actual jet quenching process. When setting the fluid properties, the density, specific heat capacity, and thermal conductivity must be determined based on the actual characteristics of the selected quenching medium. Different quenching media will have significantly different properties; for example, water and oil, as quenching media, have different densities, specific heat capacities, and thermal conductivity. Accurate settings are crucial to ensuring the reliability of the simulation.

[0086] The settings for the flow velocity and intensity of the internal fluid need to be considered in conjunction with the actual spraying conditions in production. The flow velocity affects the contact time and heat transfer efficiency between the quenching medium and the large variable cross-section steel pipe, while the flow intensity relates to the uniformity of the quenching medium distribution.

[0087] Setting the property parameters of solid structures (large variable cross-section steel pipes) is equally important. Density, specific heat capacity, and thermal conductivity determine the heat transfer characteristics of the steel pipe during quenching. These property parameters differ for large variable cross-section steel pipes made of different materials. Accurate input of these parameter values ​​is crucial during simulation to realistically simulate the temperature field changes during spray quenching, providing a reliable basis for subsequent optimization of the quenching process.

[0088] S4. Set the calculation boundary conditions;

[0089] In step S4 above, calculation boundary conditions are set, including using the convective heat transfer coefficient h of the outer surface of steel pipes with different cross-sections as the calculation boundary conditions. The specific convective heat transfer coefficient h is as follows:

[0090]

[0091] Among them, w f The jet flow density is expressed in L / (m²·s), T s The surface temperature of the steel pipe is expressed in °C.

[0092] The steel pipe sections with different wall thicknesses are named bady1, body2, ..., bodyN, where N represents the number of different cross-sectional dimensions, and N≤20; different jet water flow densities W are set according to the different thicknesses of the steel pipe sections. f In addition, the inlet flow velocity, outlet flow velocity, and residual convergence criteria are set according to requirements. Through iterative calculations, the residual convergence is monitored; if the residual converges but the temperature distribution does not meet requirements, the calculation parameter, jet flow density w, is adjusted. f Recalculate until the requirements for residual convergence and temperature distribution are met.

[0093] The aforementioned convective heat transfer coefficient h can dynamically reflect the actual heat transfer situation.

[0094] S5. The quenching and cooling process of large variable cross-section steel pipes was analyzed by finite element simulation using Fluent software, and the simulation results were obtained.

[0095] In step S5 above, based on the accuracy requirements of the quenching and cooling data of large variable cross-section steel pipes, the Fluent software solver is used to set the Number of Time Steps (total number of time steps) and Time Step Size (time step size), and then click calculate to run the calculation, that is, to perform transient finite element simulation calculation of the spray quenching and cooling process of large variable cross-section steel pipes.

[0096] S6. Analyze the simulation results to obtain the temperature change curves and temperature distribution cloud maps of the large variable cross-section steel pipe at different times.

[0097] In step S6 above, after the calculation is completed, the original data of the temperature monitoring points are exported to obtain the temperature change curves and temperature distribution cloud maps of the large variable cross-section steel pipe at different times, that is, the data of temperature change over time and temperature distribution cloud maps at different times obtained from the simulation calculation of the large variable cross-section steel pipe.

[0098] S7. Determine the quenching process parameters based on the simulation results.

[0099] In step S7 above, based on the simulation results, it is analyzed and judged whether the quenching and cooling of large variable cross-section steel pipe can achieve the expected rapid and uniform cooling, and the corresponding quenching process parameters are determined, namely the water flow intensity of the internal spray and the spray density of the external water spray.

[0100] It should be explained that the jet flow density of the external water spray is used as a boundary condition for the calculation; the flow intensity of the internal water spray is a simulation parameter (fluid parameter) set when setting the solution method.

[0101] Furthermore, when analyzing the simulation results to determine whether the quenching and cooling of large variable cross-section steel pipes can achieve the expected rapid and uniform cooling, the criteria are: rapid cooling requires a cooling rate ≥ 1℃ / s, and uniform cooling requires a temperature difference ≤ 10℃ between adjacent steel pipe sections with different cross-sections; rapid and uniform cooling is a cooling requirement specific to the steel pipe itself. Additionally, Figure 1 The residuals are an important criterion for determining whether the simulation has converged.

[0102] If the quenching and cooling of the large variable cross-section steel pipe does not achieve the expected rapid and uniform cooling in step 7 above, then return to S4 and modify the jet water flow density W. f The boundary conditions h are reset and the calculation is repeated until the steel pipe quenching and cooling achieves the expected rapid and uniform cooling effect.

[0103] This invention overcomes the problems of traditional inverse heat transfer methods in the study of temperature field during spray quenching of large variable cross-section steel pipes, such as high measurement difficulty, difficulty in accurately determining the heat transfer coefficient, inability to accurately reflect internal temperature changes, and high experimental costs, by constructing a refined simulation platform based on FLUENT software. The implementation process is as follows:

[0104] First, geometric and mesh models of the solid structure (large variable cross-section steel pipe) and the internal fluid (quenching medium) are established. These two models form the basis for simulation accuracy. Traditional average heat transfer coefficients cannot capture local details, while this invention accurately models the complex variable cross-section structure of the large variable cross-section steel pipe and refines the mesh locally at the fluid-solid interface (especially the boundary layer), providing a high-precision spatial discretization basis for subsequent fluid flow and heat transfer calculations. This allows the simulation to capture more realistic temperature and changes inside and on the surface of the steel pipe, laying the foundation for accurate temperature field prediction.

[0105] Secondly, this invention ensures accurate simulation of the physical process by setting the solution method. The quenching process is a complex energy and momentum exchange process between the fluid (quenching medium) and the solid (large variable cross-section steel pipe). By using FLUENT software and selecting the Realizable k-ε turbulence model, the turbulent flow behavior of the quenching medium on the inner and outer surfaces of the large variable cross-section steel pipe and its convective heat transfer with the steel pipe can be accurately simulated. This overcomes the limitation of traditional methods that only consider average heat transfer, making the temperature field calculation closer to the actual physical process.

[0106] Furthermore, this invention can define dynamic convective heat transfer boundary conditions. In existing technologies, the reverse heat transfer method struggles to accurately deduce the heat transfer coefficient at the interface and typically uses static average values. This invention introduces a complex function related to the jet water flow density Wf and the steel pipe surface temperature Ts to define the convective heat transfer coefficient h. In other words, during the simulation process, the heat transfer coefficient h is no longer a fixed value but is dynamically adjusted based on the actual jet intensity of the quenching medium and the real-time surface temperature of the steel pipe. This dynamic boundary condition more realistically reflects the complex heat transfer mechanism at the interface during quenching, solving the core technical problem of accurately determining the heat transfer coefficient. In addition, using the aforementioned geometric and mesh models, solution methods, and dynamic boundary conditions, transient finite element simulations are performed in FLUENT software to calculate the temperature distribution and changes of the steel pipe at different times. This avoids expensive and time-consuming industrial experiments and provides more comprehensive internal temperature field data than experimental methods.

[0107] Finally, the simulation results of this invention (e.g., temperature change curves and distribution cloud maps) provide detailed temperature field data, allowing for a direct assessment of the uniformity and efficiency of quenching cooling. If the cooling effect is unsatisfactory, the jet water flow density Wf process parameter can be adjusted based on the simulation feedback, and the simulation can be repeated. This iterative optimization process, while ensuring simulation accuracy, significantly reduces experimental costs, improves process development efficiency, and obtains more accurate and reliable temperature field data, ultimately achieving rapid and uniform cooling of large variable cross-section steel pipes.

[0108] The following describes specific embodiments and appendices. Figures 2 to 25 The technical solution of the present invention will be further described in detail below.

[0109] Example 1

[0110] The temperature field simulation process of the Fluent-based jet quenching process in this embodiment includes the following steps:

[0111] S1. Establish a geometric model, including the solid structure (large variable cross-section steel pipe) and the internal fluid (quenching medium), and define the solid domain and the internal fluid domain;

[0112] In step S1 above, a geometric model is established. This is done using DesignModeler software to create geometric models of the solid structure (large variable cross-section steel pipe) and the internal fluid (quenching medium), such as... Figure 2 As shown; in the DesignModeler software, the solid structure (large variable cross-section steel pipe) is directly divided according to different cross-sectional dimensions and defined as bady1, body2, bady3, bady4, bady5, bady6, bady7, bady8, and body9. The solid domain walls are defined, the outer surface of the large variable cross-section steel pipe is defined as wall.outside, the inner surface of the large variable cross-section steel pipe is defined as wall.inside, the internal fluid (quenching medium) is named fluid, the internal fluid inlet is named inlet.fluid, and the internal fluid outlet is named outlet. Finally, the solid structure and the internal fluid are combined into a single component.

[0113] S2. Construct a solid structure and internal fluid mesh model;

[0114] The geometric models of the solid structure (large variable cross-section steel pipe) and the internal fluid (quenching medium) were imported into CFD software. A polyhedral mesh was then created for the entire large variable cross-section steel pipe and internal fluid. The polyhedral mesh structure is shown below. Figure 3 As shown; 4-7 boundary layers are added to the interface between the inner wall and the internal fluid of the large variable cross-section steel pipe for local densification, and 4-6 boundary layers are added to the outer wall of the large variable cross-section steel pipe for local densification, as shown. Figure 4 As shown, the quality of the divided mesh is checked and the number of meshes is estimated, and finally a high-quality structural mesh model that meets the simulation requirements is obtained.

[0115] S3. Set the solution method;

[0116] The process of setting up the solution method is as follows: Set up the simulation model of the fluid inside the steel pipe and set the simulation parameters; the solution method selected is SIMPLE, and the momentum, turbulent kinetic energy, turbulent dissipation rate, and energy are all calculated using the Second Order Upwind upwind scheme (e.g., ...). Figure 5 (As shown); the simulation calculation model for the fluid inside the steel pipe uses a Realizable k-ε turbulence model for calculation (e.g.) Figure 6 As shown), the Realizable k-ε turbulence model specifically includes:

[0117]

[0118] Where ρ is the fluid density, in kg / m³ 3 k represents turbulent kinetic energy, in m³. 2 / s 2t represents time, in seconds; u i x represents the velocity component, in m / s. i Let x be the spatial coordinate. j For spatial coordinates; μ j P is the fluid dynamic viscosity, in Pa·s. k ε is the turbulent kinetic energy transport term, and ε is the turbulent kinetic energy dissipation term, in meters. 2 / s 3 .

[0119]

[0120] Where ρ is the fluid density, in kg / m³ 3 k represents turbulent kinetic energy, in m³. 2 / s 2 t represents time, in seconds; u i x represents the velocity component, in m / s. i Let μ be the spatial coordinate. t σ is the turbulent dynamic viscosity, in Pa·s; ε Let ε be the turbulent flow dissipation suppression function, and ε be the turbulent kinetic energy dissipation term, in units of m. 2 / s 3 C 1ε C 2ε These are model constants.

[0121] Set simulation parameters, including fluid properties such as density, specific heat capacity, and thermal conductivity; internal fluid flow velocity and intensity; and solid structure properties such as density, specific heat capacity, and thermal conductivity (e.g., ...). Figures 7a-7c (As shown).

[0122] The flow field simulation example setup includes: enabling the energy equation (e.g.) Figure 8 As shown), modify the relaxation factor (e.g. Figure 9 As shown), set initialization (such as...) Figure 10 (as shown) and local initialization (such as) Figure 11 The process is shown in the figure. Flow field simulation examples are used to verify the rationality of the examples and the correctness of the calculation results.

[0123] Temperature monitoring points are equidistantly set at different wall thicknesses along the same axial direction and at the same radial distance in large variable cross-section steel pipes. In Embodiment 1 of this invention, a total of 14 temperature monitoring points are set, such as... Figure 12 As shown.

[0124] S4. Set the calculation boundary conditions;

[0125] In this embodiment, the convective heat transfer coefficient of the outer wall of the steel pipe is used as the boundary condition for setting the calculation boundary conditions. The specific convective heat transfer coefficient h is:

[0126]

[0127] Among them, w f The density of the jet water flow is expressed in L / m³. 2 ·s;T s The surface temperature of the steel pipe is expressed in °C.

[0128] The steel pipe sections with different wall thicknesses are named bady1, body2, bady3, bady4, bady5, bady6, bady7, bady8, and body9, respectively. Different jet water flow densities (w) are set according to the thickness of each steel pipe section. f ,like Figure 13 As shown. Furthermore, the inlet water flow velocity (e.g.) Figure 14 As shown), fluid outlet (e.g.) Figure 15 As shown), residual requirements (such as...) Figure 16 Configure the settings as shown. Through iterative calculations, monitor the residual convergence. If the residual converges but the temperature distribution does not meet the requirements, adjust the calculation parameters, specifically the jet flow density w. f The settings are shown in Table 1.

[0129] Table 1. Jet water flow density w for steel pipe sections with different wall thicknesses f (Unit: L / m) 2 ·s)

[0130]

[0131] S5. The quenching and cooling process of large variable cross-section steel pipes was analyzed by finite element simulation using Fluent software, and the simulation results were obtained.

[0132] Based on the accuracy requirements of quenching and cooling data for large variable cross-section steel pipes, the Number of Time Steps and Time Step Size parameters (e.g., ...) are set in the Fluent software solver. Figure 17 (As shown), click calculate to run the calculation.

[0133] S6. Analyze the simulation results to obtain the temperature change curves and temperature distribution cloud maps of the large variable cross-section steel pipe at different times.

[0134] After the calculation is completed, the original data of the temperature monitoring points are exported to obtain the temperature change curves and temperature distribution cloud maps of the large variable cross-section steel pipe at different times. That is, the data of temperature change over time and temperature distribution cloud maps at different times obtained from the simulation calculation of the large variable cross-section steel pipe.

[0135] S7. Determine the quenching process parameters based on the simulation results.

[0136] Based on the simulation results, we analyzed and judged whether the quenching and cooling of large variable cross-section steel pipes could achieve the expected rapid and uniform cooling, and determined the corresponding quenching process parameters, namely the water flow intensity of the internal water spray and the water flow density of the external water spray.

[0137] Figure 18-21 The curve showing the temperature change over time at the temperature monitoring point of the variable cross-section steel pipe, obtained by setting the relevant parameters in Table 1. Figure 18 The temperature evolution curves of the steel pipe at different axial positions under working condition 1 show that the maximum temperature difference in the axial height direction at the same radial depth occurs before t=400s, with a maximum temperature difference of 235℃. Figure 19 The temperature evolution curves of the steel pipe at different axial positions under operating condition 2 are shown, with a maximum temperature difference of 200℃. Figure 20 The temperature evolution curves of the steel pipe at different axial positions under working condition 3 are shown, with a maximum temperature difference of 175℃. Figure 21 The temperature evolution curves for the steel pipe at different axial positions under operating condition 4 are shown, with a maximum temperature difference of 74℃; combined with the cooling temperature distribution cloud maps under the four operating conditions, as follows... Figure 22-25 It can be found that the steel pipe has the best rapid and uniform cooling effect under operating condition 4 parameters.

[0138] In summary, this invention addresses the jet quenching and cooling process of the inner and outer surfaces of large variable cross-section steel pipes. It can predict the temperature distribution of large variable cross-section steel pipes at any time and any location without experimental testing. Based on the simulation results, the nozzle arrangement and process parameters can be adjusted to implement corresponding optimization and improvement measures for the quenching process. This provides data support for the formulation of subsequent quenching processes and helps improve the quenching process parameters of large variable cross-section steel pipes.

[0139] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A temperature field simulation method for a spray quenching process based on FLUENT, characterized in that, Includes the following steps: S1. Establish the geometric model of the solid structure and internal fluid; The solid structure refers to a large variable cross-section steel pipe, and the internal fluid refers to a quenching medium. S2. Mesh the solid structure and internal fluid geometry model to construct a mesh model of the solid structure and internal fluid. The process of constructing the solid structure and internal fluid mesh model includes: importing the solid structure and internal fluid geometric model into CFD software; performing polyhedral mesh generation on the large variable cross-section steel pipe and the internal fluid as a whole; adding 4-7 boundary layers at the interface between the inner wall of the large variable cross-section steel pipe and the internal fluid for local refinement; and adding 4-6 boundary layers at the outer wall of the large variable cross-section steel pipe for local refinement, thus obtaining the solid structure and internal fluid mesh model; then importing the solid structure and internal fluid mesh model into Fluent software for quality inspection and mesh number estimation, finally obtaining the solid structure and internal fluid mesh model that meets the simulation requirements; S3. Set the solution method; The process of setting up the solution method is as follows: set up a simulation calculation model of the internal fluid of a large variable cross-section steel pipe and set the simulation parameters; the solution method is SIMPLE, and the momentum, turbulent kinetic energy, turbulent dissipation rate and energy parameters are all selected using the Second Order Upwind upwind scheme; the simulation calculation model of the internal fluid of the steel pipe is calculated using the Realizable k-ε turbulence model. S4. Set the calculation boundary conditions; Set calculation boundary conditions, including using the convective heat transfer coefficient h of the outer surface of steel pipes with different cross sections as calculation boundary conditions; S5. The quenching and cooling process of large variable cross-section steel pipes was analyzed by finite element simulation using Fluent software, and the simulation results were obtained. S6. Analyze the simulation results to obtain the temperature change curves and temperature distribution cloud maps of the large variable cross-section steel pipe at different times. S7. Determine the quenching process parameters based on the simulation results; Based on the simulation results, we analyze and judge whether the quenching and cooling of large variable cross-section steel pipes can achieve the expected rapid and uniform cooling, and determine the corresponding quenching process parameters, namely the water flow intensity of the internal water spray and the spray density of the external water spray.

2. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 1, characterized in that, In S1, the solid structure and internal fluid geometry model are established using DesignModeler software.

3. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 2, characterized in that, In S1, when establishing the solid structure and internal fluid geometry model, the solid structure is directly divided into different cross-sectional dimensions and defined as bady1, body2...bodyN in the DesignModeler software according to the geometry of the fixed structure, where N represents the number of different cross-sectional dimensions and N≤20.

4. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 3, characterized in that, In S1, the walls of the computational domain are defined. The inner and outer surfaces of the large variable cross-section steel pipe are defined as walls. The internal fluid is named fluid. One end of the internal fluid is defined as the inlet and the other end of the internal fluid is defined as the outlet. Finally, the solid structure and the internal fluid are combined into a component.

5. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 4, characterized in that, In step S4, steel pipe sections with different wall thicknesses are named bady1, body2, ..., bodyN, where N represents the number of different cross-sectional dimensions, and N≤20; different jet water flow densities W are set according to the different thicknesses of the steel pipe sections. f .

6. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 5, characterized in that, In S4, the fluid inlet flow velocity, fluid outlet, and residual convergence criteria are set as required.

7. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 6, characterized in that, In step S4, iterative calculations are performed, focusing on the convergence of the residuals. If the residuals converge but the temperature distribution does not meet the requirements, the calculation parameter, jet flow density w, is adjusted. f Recalculate until the requirements for residual convergence and temperature distribution are met.

8. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 1, characterized in that, In step S6, after the calculation is completed, the original data of the temperature monitoring points are exported to obtain the temperature change curves and distribution cloud maps of the large variable cross-section steel pipe at different times.

9. The temperature field simulation method for the spray quenching process based on FLUENT according to claim 1, characterized in that, In step S7, if the quenching and cooling of the large variable cross-section steel pipe does not achieve the expected rapid and uniform cooling, the process returns to step S4, and the jet water flow density W is modified. f The boundary conditions h are reset and the calculation is repeated until the steel pipe quenching and cooling achieves the expected rapid and uniform cooling effect.

10. The temperature field simulation method for the spray quenching process based on FLUENT according to any one of claims 1-9, characterized in that, In S4, the convective heat transfer coefficient h is specifically as follows: Among them, w f The density of the jet water flow is expressed in L / (m³). 2 ·s), where Ts is the surface temperature of the steel pipe, in °C.

Images