Vacuum heat treatment process analog simulation system and method based on Fluent

Abstract

The invention discloses a Fluent-based vacuum heat treatment process analog simulation system and method, and belongs to the technical field of analog simulation. The vacuum heat treatment process simulation method based on Fluent comprises the following steps: simplifying the structure of a vacuum heat treatment furnace, and establishing a vacuum heat treatment furnace model based on the simplified structure; performing grid division on the established vacuum heat treatment furnace model; after grid division is completed, parameter adjustment is carried out based on Fluent; after parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on the simulation result and the measurement data; and performing structure property state prediction after material heat treatment based on the corrected vacuum heat treatment furnace model. According to the vacuum heat treatment process analog simulation method based on Fluent, through analog simulation of the vacuum heat treatment furnace, information of physical fields such as a fluid field and a temperature field which cannot be obtained through a traditional empirical formula is obtained, and thoughts are provided for vacuum furnace design optimization such as runner layout and a heat preservation structure and heat treatment workpiece process optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of simulation, in particular to a vacuum heat treatment process simulation system and method based on Fluent. BACKGROUND

[0002] At present, the vacuum heat treatment process is mainly characterized by "invisible and intangible", that is, after the furnace door is closed, only a few sensors in the furnace can be used for real-time monitoring, and the temperature field and cooling rate field in the vacuum furnace cannot be comprehensively understood. Therefore, it is necessary to restore the actual temperature field and cooling rate field in the vacuum heat treatment process through simulation and other technical means, so as to realize more comprehensive control of the heat treatment process.

[0003] In the prior art, the simulation methods in the documents named "Vacuum solid solution heat treatment furnace temperature field fluid field analysis based on Fluent", "Vacuum furnace heating temperature field and gas quenching process gas flow field numerical simulation research" and "Vacuum high-pressure gas quenching process flow field and temperature field numerical simulation and experimental research of empty furnace and full load furnace" all use Fluent as the platform software for vacuum furnace simulation, but the models in the above articles are too simplified, mainly having the following problems: (1) inaccurate flow field calculation: the vacuum furnace structure is too simple, and the heat exchanger, fan and the like are not included in the simulation calculation, so that the flow field distribution in the vacuum furnace cannot be accurately described; (2) inaccurate temperature field calculation: less research on the full metal hot zone, the characteristics of the full metal hot zone are not reflected in the simulation calculation, and the energy input boundary of the temperature field is not accurately described, which is greatly different from the actual vacuum furnace insulation mode; (3) the material properties and vacuum furnace simulation results are not combined, the material performance state of single crystal superalloy after heat treatment cannot be reflected, and the part organization prediction function is not good.

[0004] Therefore, based on the existing perfect simulation technology, accurate boundary condition input and perfect physical model construction are needed to accurately model and simulate the heat treatment furnace, so as to realize the organization prediction of the parts in the vacuum furnace and the analysis of the heat treatment effect, and make the heat treatment become a "visible and tangible" process. SUMMARY

[0005] The present application aims to provide a vacuum heat treatment process simulation system and method based on Fluent, which solves the technical problem that the temperature field and cooling rate field in the vacuum furnace cannot be comprehensively understood in the prior art.

[0006] To achieve the above-mentioned purpose, one embodiment of the present application provides a vacuum heat treatment process simulation method based on Fluent, comprising the following steps:

[0007] Simplify the structure of the vacuum heat treatment furnace, and establish a vacuum heat treatment furnace model based on the simplified structure;

[0008] Grid division is performed on the established vacuum heat treatment furnace model;

[0009] After the grid division is completed, parameter adjustment is performed based on Fluent;

[0010] After the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on the simulation results and measured data;

[0011] The organization performance state prediction after material heat treatment is performed based on the corrected vacuum heat treatment furnace model.

[0012] In one of the preferred schemes of the present application, the structure of the vacuum heat treatment furnace is simplified, which comprises: simplifying the components with a length of less than 20mm in the vacuum heat treatment furnace.

[0013] In one of the preferred schemes of the present application, the structure of the vacuum heat treatment furnace is simplified, which comprises: simplifying the furnace shell, the heat zone, the heat exchanger, the sensor, the fan and the centrifugal fan.

[0014] In one of the preferred schemes of the present application, the vacuum heat treatment furnace model is established based on the simplified structure, which comprises: establishing the vacuum heat treatment furnace model according to the engineering drawings and measured data.

[0015] In one of the preferred schemes of the present application, the vacuum heat treatment furnace model is established based on the simplified structure, which comprises: adopting an inside-out establishing mode for the vacuum heat treatment furnace model.

[0016] In one of the preferred schemes of the present application, the grid division is performed on the established vacuum heat treatment furnace model, which comprises: adopting a face grid first and then a volume grid mode for the grid division.

[0017] In one of the preferred schemes of the present application, the grid division is performed on the established vacuum heat treatment furnace model, which comprises: setting the grid division parameters through a non-structural grid division software, and establishing the non-structural network of the vacuum heat treatment furnace simulation model through grid inspection parameters.

[0018] In one of the preferred schemes of the present application, the grid inspection parameters comprise y+ value and orthogonal mass.

[0019] In one of the preferred schemes of the present application, the y+ value comprises: the y+ value of the components with a flow rate of 5m / s or less within a distance of 0.5cm-1.5cm from the wall surface is 10-30, and the y+ value of the components with a flow rate of 5m / s or more within a distance of 0.5cm-1.5cm from the wall surface is 1-10; and the orthogonal mass is 0.15-0.3.

[0020] The material physical property parameters include argon physical property parameters, alumina phase parameters, copper phase parameters, molybdenum phase parameters, steel phase parameters and hot zone phase parameters.

[0021] The material physical property parameters include argon physical property parameters, alumina phase parameters, copper phase parameters, molybdenum phase parameters, steel phase parameters and hot zone phase parameters.

[0022] The argon physical property parameters include argon thermal conductivity, the alumina phase parameters include alumina thermal conductivity and alumina heat capacity, the molybdenum phase parameters include molybdenum thermal conductivity and molybdenum heat capacity, and the hot zone phase parameters include hot zone thermal conductivity, which is set according to orthogonal anisotropy of a cylindrical coordinate system.

[0023] The boundary surface parameters include furnace shell parameters, heat exchanger pipe wall surface parameters, centrifugal fan wall surface parameters and heat input parameters.

[0024] The block phase parameters include centrifugal fan flow field parameters, heat exchanger flow field parameters and furnace fluid field parameters.

[0025] The physical model state includes a steady state stage and a transient state stage.

[0026] After the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on simulation results and measured data, including: after the parameter adjustment is completed, the vacuum heat treatment process is simulated, and the vacuum heat treatment furnace simulation boundary conditions and physical quantity parameters are corrected according to actual measured values.

[0027] After the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on simulation results and measured data, including: after the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected.

[0028] The steady state stage corrects the simulated furnace temperature field, and the transient state stage corrects the simulated furnace cooling rate field and air flow velocity.

[0029] The material heat treatment organization performance state prediction is performed based on the corrected vacuum heat treatment furnace model, including obtaining single crystal blade residual eutectic content and gamma prime phase size distribution conditions by using the corrected vacuum heat treatment furnace model.

[0030] The application further discloses a vacuum heat treatment process simulation and simulation system based on Fluent, which is realized based on the vacuum heat treatment process simulation and simulation method based on Fluent.

[0031] The establishing unit is used for simplifying the structure of the vacuum heat treatment furnace and establishing a vacuum heat treatment furnace model based on the simplified structure;

[0032] The dividing unit is used for meshing the established vacuum heat treatment furnace model;

[0033] The adjusting unit is used for adjusting parameters based on Fluent after the meshing is completed;

[0034] The correcting unit is used for correcting the vacuum heat treatment furnace model based on simulation results and measured data after the parameter adjustment is completed;

[0035] The predicting unit is used for predicting the organization performance state after material heat treatment based on the corrected vacuum heat treatment furnace model.

[0036] Therefore, the method has the advantages that:

[0037] 1. The method is based on the vacuum heat treatment process simulation method of the finite element simulation software Fluent, and the detailed information of the fluid field, temperature field and other physical fields that cannot be obtained by traditional empirical formula is obtained through the simulation of the vacuum heat treatment furnace, so as to provide ideas for the layout of the flow channel, the design optimization of the vacuum furnace and the process optimization of the heat treatment workpiece.

[0038] 2. The method is based on the vacuum heat treatment process simulation method of Fluent, which mainly simplifies the structure of the vacuum heat treatment furnace, establishes a vacuum heat treatment furnace model based on the simplified structure, meshes the established vacuum heat treatment furnace model, adjusts the model simulation related physical quantity parameters, boundary conditions and solving methods based on Fluent software after the meshing is completed, simulates the vacuum heat treatment process after the parameter adjustment is completed, corrects the vacuum heat treatment furnace simulation boundary conditions and physical quantity parameters according to the actual measured value, and then obtains a more accurate vacuum furnace simulation model; and the material measured data and the simulation results are combined to predict the organization distribution and performance state of the workpiece in the vacuum heat treatment.

[0039] 3. The method is based on the vacuum heat treatment process simulation method of Fluent, which simulates the vacuum heat treatment furnace process, and combines the secondary development based on single crystal high-temperature alloy to simulate the typical organization (residual eutectic, gamma prime phase size, etc.) conversion process of the workpiece under the vacuum heat treatment process, so as to provide ideas for process optimization.

[0040] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be understood from the practice of the present application. The purposes and other advantages of the present application can be explained by the effects described in the specification and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 A flowchart of a vacuum heat treatment process simulation method based on Fluent in an embodiment of the present application is shown in Figure 1.

[0042] Figure 2 A structural diagram of a vacuum heat treatment process simulation system based on Fluent in an embodiment of the present application is shown in Figure 2.

[0043] Figure 3 A structural diagram of a simulated vacuum heat treatment furnace model in an embodiment of the present application is shown in Figure 3.

[0044] Figure 4 An exploded view of a simulated vacuum heat treatment furnace model in an embodiment of the present application is shown in Figure 4.

[0045] Figure 5 A prediction diagram of the distribution of the γ' phase on the outer surface of the blade inside the workpiece in an embodiment of the present application is shown in Figure 5.

[0046] Figure 6 A prediction diagram of the distribution of the γ' phase in the cross section of the blade inside the workpiece in an embodiment of the present application is shown in Figure 6.

[0047] In the figure, 1 is a furnace shell, 2 is a hot zone, 3 is a heat exchanger, 4 is a heat exchanger flow channel, 5 is a heat exchanger copper pipe, 6 is a centrifugal impeller, 7 is a rear part of the hot zone, 8 is a middle part of the hot zone, 9 is a front part of the hot zone, 10 is a workpiece rack, 11 is a workpiece, 12 is a molybdenum support, 13 is a molybdenum belt, and 14 is a thermocouple. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in connection with the drawings of the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0049] The present application provides a vacuum heat treatment process simulation method based on Fluent, comprising the following steps:

[0050] Step (1): Simplify the structure of the vacuum heat treatment furnace, and establish a vacuum heat treatment furnace model based on the simplified structure; wherein, the components with a length less than 20mm in the vacuum heat treatment furnace are simplified, specifically including:

[0051] The vacuum heat treatment process is mainly divided into three stages of heating, holding and cooling, and to realize the above functions, the vacuum furnace mainly combines the complex mechanical structure and electrical elements of furnace shell, hot zone, heat exchanger, control cabinet, etc., and the process of converting electrical energy into heat energy required for heat treatment, which involves thermal process and relatively automatic control. Therefore, in the simulation process, unnecessary functions of the vacuum furnace need to be discarded and the structure is simplified, while the key heat treatment steps and vacuum furnace structure are retained to ensure that the simulated results meet the characteristics of the all-metal screen vacuum furnace, without losing simulation accuracy and being highly consistent with the actual process and heat treatment process.

[0052] The initial structure model is obtained through two aspects:

[0053] 1) Original engineering drawings, including: furnace body drawings, hot zone drawings, fan drawings, heat exchanger drawings, etc. Main structural components;

[0054] 2) Actual measurement: mainly for the placement of parts and material frames, to determine the position of the heat treatment load, providing position data for subsequent half-load and full-load simulation calculations;

[0055] Since the actual vacuum heat treatment furnace has a large number of small structures, such as molybdenum screws, molybdenum rods, etc., these components need to be ignored during the construction of the simulation grid and not reflected in the simulation model. The overall structure size needs to be drawn according to the requirements of the engineering drawings, with an error of less than 0.5mm between the model overall length, diameter, etc. and the engineering drawings. The specific reconstruction points are as follows:

[0056] ① Furnace shell: according to the size of the engineering drawings, the overall structure is drawn; the external pipeline layout of the furnace shell can omit the small structure, and the focus is on drawing the internal water-cooled wall to make the furnace wall cooling structure size consistent with the engineering drawings, forming a curved surface model of the inner wall of the furnace.

[0057] ② Hot zone: The all-metal screen mainly adopts a multi-layer molybdenum metal screen structure, which realizes radiation insulation and heat preservation above 1300℃ through the principle of thermal radiation in a vacuum state. From a structural point of view, according to the temperature range, the hot zone can be composed of 5-10 layers of metal screens and corresponding support components. Since the thickness of each layer of metal screen is only 0.5mm, it belongs to a thin-walled part. If full-size grid division is performed, the number of generated grids will be large, the computational resources consumed will be large, and the efficiency will be low, so it needs to be simplified. The simplified structure is generally a cylindrical model, and the heat insulation screen is simplified to a single layer structure with a certain thickness, and the thickness of the cylinder is the distance from the innermost layer to the outermost heat insulation screen. At the same time, the gap between the front and rear heat insulation screens and the intermediate heat insulation screens is retained according to the actual assembly size, with an error of less than 0.1mm. The flow guide holes of the hot zone are opened on the cylinder according to the original design requirements (position, size), and the original air duct is simplified to a thin-walled structure while retaining the original air guiding characteristics.

[0058] ③ Heat exchanger: The heat exchanger mainly includes two parts, 1) heat exchanger framework part; 2) all-copper cold-rolled finned tube. For the framework part, full-size isometric modeling is adopted, and thin plate is replaced by curved surface model; for the finned tube, in order to reduce the consumption of computing resources and reduce the difficulty of meshing, smooth pipe model is adopted instead of the original finned tube structure, thereby realizing the simplification and modeling of the vacuum furnace rear heat exchanger.

[0059] ④ Fan and centrifugal fan structure: since the fan as a whole does not participate in the fluid-solid coupling physical process in the vacuum furnace, its overall structure is omitted in the vacuum simulation method. In order to improve the accuracy of air flow, the impeller model needs to be drawn according to the actual size, retaining the details such as fan blade arc surface, and creating an independent cylinder around the impeller, with a diameter of 2-5 cm larger than the diameter of the impeller and a width of 1-3 cm, and the center coincides with the center of the impeller.

[0060] ⑤ Sensor: the sensor is composed of several thermocouples arranged according to the actual distribution in the hot zone.

[0061] ⑥ Material frame and heat treated parts.

[0062] The overall drawing process is recommended to start from the effective heating zone of the vacuum furnace, gradually expand from the inside to the hot zone and the furnace body, and then determine the relative position of the entire vacuum furnace to ensure the accuracy of drawing, that is, to establish from the inside to the outside.

[0063] Step (2): meshing the established vacuum heat treatment furnace model; specifically, through a non-structural meshing software, set the meshing parameters, and establish the non-structural network of the vacuum heat treatment furnace simulation model through meshing inspection parameters, including:

[0064] The quality of meshing of the vacuum furnace simulation calculation will directly affect the subsequent steady state, and most importantly, the calculation stability and convergence difficulty of the transient state. Meshing can be realized through software such as ICEM or Fluent Meshing. Generally, the mesh in the calculation domain of the vacuum furnace is divided by surface meshing and volume meshing, and the most important meshing inspection parameters are as follows:

[0065] ① y+ value: the y+ value of the components with a flow rate of 5 m / s or more within 0.5-1.5 cm from the wall is 1-10, that is, at key positions or components such as the nozzle, impeller, material frame, and parts to be treated in the hot zone, the value needs to be between 1-10 after meshing, that is, the y+ value of the components is 1-10 after meshing; the y+ value of the components with a flow rate of less than 5 m / s within 0.5-1.5 cm from the wall is 10-30, that is, for the structure positions of the furnace wall and the outer wall of the hot zone, or the positions with slower flow rate, the value can exceed 10 and be between 10-30 to enhance the convergence, that is, the y+ value of the shell wall is 10-30 after meshing;

[0066] Orthogonal quality: The requirement for orthogonal quality is mainly judged by the minimum Orthogonal Quality parameter. After meshing, the value needs to reach between 0.15-0.3; the maximum value of Skewness (skewness) is not more than 0.8 to enhance the convergence.

[0067] Step (3): After meshing, parameter adjustment is carried out based on Fluent; specifically, after meshing of the vacuum furnace, the physical parameters of the equipment need to be set in detail based on Fluent. Parameter adjustment represents setting the physical model of the model according to the actual working condition, including various material characteristics, structure characteristics, and also including the setting of the solver, and completing the initial environment setting; specifically, including:

[0068] (1) Material physical parameters

[0069] ① Argon physical parameters

[0070] Since the gas velocity in the model does not reach the speed of sound or subsonic level, the argon gas in the simulation adopts the incompressible-ideal-gas model. Under the ideal gas equation, the correlation of P-V-T will cause the change of gas density with temperature, and then cause the difference of gas heat exchange efficiency at different temperatures.

[0071] To further increase the physical authenticity, the thermal conductivity coefficient of argon is fitted by a 6th order polynomial equation, and the fitting formula is:

[0072] f ThermalConductivity (x)=a0+a1x+a2x 2 +a3x 3 +a4x 4 +a5x 5 +a6x 6 (1)

[0073] Wherein, the coefficients of a0 to a6 can be taken as:

[0074] a0=-5.283×10 -4 ;

[0075] a1=7.607×10 -5 ;

[0076] a2=-6.475×10 -8 ;

[0077] a3=-5.419×10 -11 ;

[0078] a4=-3.220×10 -14 ;

[0079] a5 = 1.180 x 10 -17 ;

[0080] a6 = -1.862 x 10 -21 ;

[0081] The 6th order polynomial fitting equation can accurately fit the change of argon thermal conductivity with temperature from 273.15 K to 1673.15 K, and according to the calculation efficiency and calculation accuracy, 3rd, 4th, 5th and 7th order polynomials can be used to fit the change of argon thermal conductivity with temperature to achieve the same effect.

[0082] To further increase the authenticity of argon turbulent flow simulation, the relationship between the dynamic viscosity μ and temperature is approximated by Sutherland's law, where the empirical formula is:

[0083]

[0084]

[0085] Wherein, each coefficient is taken as:

[0086] μ0 = 2.125 x 10 -5 kg / (m·s);

[0087] T0 = -0.04 K;

[0088] S = -128.75 K.

[0089] 2. Alumina phase parameters

[0090] Alumina mainly corresponds to the S-shaped ceramic armored thermocouple sensor model in the model. The sensor measures the temperature of the high-temperature environment in the furnace through the platinum-rhodium alloy built into the ceramic tube, that is, the high temperature in the furnace is conducted to the alumina ceramic, and the platinum-rhodium alloy measures the temperature of the alumina ceramic. At the same time, from the structure, most of the materials in the sensor are high-purity alumina ceramic, and the platinum-rhodium alloy wire is only about 4-8 g, so a pure alumina rod can be used instead of a complex structure thermocouple to realize the measurement of the temperature in the furnace.

[0091] Since the temperature in the furnace can be raised from 300°C to 1400°C, it is necessary to correct the thermal conductivity and heat capacity of alumina in relation to temperature. The simulation uses a 6th order polynomial fitting method, and the fitting formula of the thermal conductivity of alumina is shown in equation (3):

[0092] f Thermal Conductivity (x) = b0 + b1x + b2x 2 +b3x 3 +b4x 4 +b5x​5 + b6x 6 (3)

[0093] For thermal conductivity, the coefficients b0to b6may take the values:

[0094] b0= 39.42;

[0095] b1= -1.082 x 10 -1 ;

[0096] b2= 1.635 x 10 -4 ;

[0097] b3= -1.472 x 10 -7 ;

[0098] b4= -8.093 x 10 -11 ;

[0099] b5= -2.505 x 10 -14 ;

[0100] b6= 3.330 x 10 -18 ;

[0101] For thermal capacity, the fitted equation is given by equation (4):

[0102] f Thermal Conductivity (x) = c0+ c1x + c2x 2 + c3x 3 + c4x 4 + c5x 5 + c6x 6 (4)

[0103] where the coefficients c0to c6may take the values

[0104] c0= -1043;

[0105] c1= 11.88;

[0106] c2= -2.831 x 10 -2 ;

[0107] c3= -3.6656 x 10 -5 ;

[0108] c4= -2.627 x 10 -8 ;

[0109] c5= 9.798 x 10 -12 ;

[0110] c6= -1.482 x 10 -15 ;

[0111] Further, the characteristics of the thermal conductivity and the heat capacity of the alumina ceramic with temperature change are realized, so that the simulation is more accurate.

[0112] ③Copper phase parameters

[0113] Copper mainly corresponds to the actual material of the multi-row fin heat exchanger in the model. This component is cooled by circulating water inside, so it can be considered to be at room temperature at all times during use. To be close to the actual vacuum furnace state and reduce the complexity of the model, the phase parameters of copper are set to the parameters corresponding to room temperature.

[0114] ④Molybdenum phase parameters

[0115] Molybdenum mainly corresponds to the material frame and molybdenum structure support in the model.

[0116] Since the temperature in the furnace can rise from 300°C to 1400°C, the thermal properties of molybdenum material itself change greatly with temperature. Therefore, the thermal conductivity and heat capacity of molybdenum need to be corrected in relation to temperature. This simulation uses a 6th order polynomial fitting method;

[0117] For thermal conductivity, the fitting formula is as follows:

[0118] f Thermal Conductivity (x)=d0+d1x+d2x 2 +d3x 3 +d4x 4 +d5x 5 +d6x 6 (5)

[0119] Where the coefficients d0 to d6 can be taken as:

[0120] d0=146.2;

[0121] d1=-8.255×10 -3 ;

[0122] d2=-9.872×10 -5 ;

[0123] d1=1.423×10 -7 ;

[0124] d4=-1.015×10 -10 ;

[0125] d5=3.662×10 -14 ;

[0126] d6=-5.201×10 -18 ;

[0127] For the heat capacity, the fitting formula is seen in equation (6):

[0128] f Thermal Conductivity (x) = e0 + e1x + e2x 2 + e3x 3 + e4x 4 + e5x 5 + e6x 6 (6)

[0129] Where the coefficients of e0 to e6 can be taken as:

[0130] e0 = 122.4;

[0131] e1 = 8.319 x 10 -1 ;

[0132] e2 = -2.015 x 10 -3 ;

[0133] e3 = 2.694 x 10 -6 ;

[0134] e4 = -1.972 x 10 -9 ;

[0135] e5 = 7.511 x 10 -13 ;

[0136] e6 = -1.157 x 10 -16 ;

[0137] Further, the characteristics of the thermal conductivity and heat capacity of molybdenum with temperature change are realized, making the simulation more accurate.

[0138] 5. Steel phase parameters

[0139] The steel corresponds to the actual material of the structural parts, plate, etc. in the furnace in the model. The actual proportion of this component used in the furnace is small, so the influence of this component on the thermal field distribution in the furnace is small. In order to reduce the complexity of the model, the constant corresponding to the phase parameters of the steel at room temperature.

[0140] 6. Thermal zone phase parameters

[0141] Since the thermal zone is made of multiple layers of molybdenum plates, its actual mass is much smaller than that of a solid molybdenum cylinder of the same volume, so according to the actual mass of the thermal zone, its density can be set to 600-1000 kg / m 3 . Since the actual thermal zone is still composed of molybdenum, its heat capacity can be set to 250-300 J / kg·K. However, due to the heat insulation characteristics of the thermal zone, its thermal conductivity can be set according to the actual position, where:

[0142] 1) Middle part of the thermal zone

[0143] The thermal conductivity of this part is set to be cyl-orthotropic, i.e. the radial thermal conductivity is 0.5-1.5 W / (m*K), the tangential thermal conductivity is set to be 138 W / (m*K), and the axial thermal conductivity is set to be 138 W / (m*K).

[0144] 2) Front and rear of the hot zone

[0145] The thermal conductivity of this part is set to be cyl-orthotropic, i.e. the radial thermal conductivity is 138 W / (m*K), the tangential thermal conductivity is set to be 138 W / (m*K), and the axial thermal conductivity is set to be 0.5-1.5 W / (m*K).

[0146] (2) Boundary surface parameters

[0147] ① Furnace shell parameter setting: the thermodynamic properties of the wall surface are set to be isothermal wall surface, and the temperature can be set to be 15-35℃;

[0148] ② Heat exchange tube wall surface parameter setting: the thermodynamic properties of the wall surface are set to be adiabatic;

[0149] ③ Centrifugal fan wall surface parameter setting: similarly, the centrifugal fan wall surface also needs to be set to be a moving wall surface, and the rotating direction and speed thereof are the same as those of the body, and the thermodynamic properties of the wall surface are set to be adiabatic;

[0150] ④ Heating molybdenum belt parameter setting: the heat input of the heat preservation process of the model is all from the heating molybdenum belt, and in the simulation model, the actual three-zone heating power values of the vacuum furnace are adopted for the heating molybdenum belt. According to different thermal processes, the power value of each heating molybdenum belt can be set to be 0.1-110 kW;

[0151] ⑤ Other non-volume wall surface parameter setting: the thermodynamic properties of the wall surface are set to be adiabatic;

[0152] ⑥ Other volume surface parameter setting: the thermodynamic properties of the wall surface are set to be coupled.

[0153] (3) Block phase parameters

[0154] ① Centrifugal fan flow field parameter setting

[0155] In order to simulate the acceleration effect of the rotation of the centrifugal fan on the airflow in the vacuum furnace gas quenching process, the model adopts a multi-reference frame (MRF) to realize the disturbance of the centrifugal fan to the airflow. The rotating shaft is parallel to the central axis of the furnace body, and the direction is the same as the actual rotating direction. The change of the rotating speed with time is realized through an embedded function, and the function can be set to be:

[0156] f RotationSpeed = a x t (7)

[0157] Wherein a is the speed per second, which can be set to 1-100 rad / s according to the actual fan acceleration; t is the time, which can be set to 5-20 s according to the actual fan acceleration time.

[0158] ② Heat exchanger flow field parameter setting

[0159] Because the fins of the heat exchanger are not drawn in the model, the effect of the fins on the fluid resistance cannot be shown, so some methods are needed to include the above resistance into the heat exchanger. In this simulation, the fluid domain of the heat exchanger is set as a porous medium, and the resistance parameters in x, y and z directions are included in the calculation model. Among them, the viscous resistance coefficients in the three orthogonal directions can be set to 1-2 x 10 8 m -2 ; and according to the arrangement characteristics of the heat exchanger fins, the inertial resistance in x and y directions can be set to 0-10 m -1 , and the inertial resistance in z direction can be set to 0-100 m -1 , so that the resistance effect of the heat exchanger model on the fluid field is close to the actual situation.

[0160] In order to simulate the heat exchange capacity of the heat exchanger model, the source term (Source) is used in this scheme to simulate the physical process of the heat exchanger taking away the heat of argon. According to the arrangement structure of the copper tube of the heat exchanger, Zhukauskas relationship can be used to fit the Nusselt number:

[0161] The relationship is as follows:

[0162]

[0163] In the above formula, C is the constant of Zhukauskas formula, which can be taken as 0.033-1.04 according to the actual Reynolds number and the tube bundle arrangement (in-line, staggered); Re f is the Reynolds number in the porous medium; Pr f is the Prandtl number in the porous medium; Pr w is determined according to the average wall temperature of the tube bundle, which can be taken as 0.1-1; F is the correction coefficient, which can be taken as 0.64-0.99 according to the actual tube number and the tube bundle arrangement (in-line, staggered).

[0164] In order to further understand and realize the real-time fitting of the Nusselt number of the heat exchanger, Re f , Pr f , Pr w need to be calculated, and the calculation formula of the Reynolds number in the porous medium is as follows:

[0165]

[0166] In the above formula, p Ar is the argon density in the grid, v x , v y , v z are the velocity components in x, y, z directions respectively, D is the tube diameter, and μ is the dynamic viscosity of argon.

[0167] The Prandtl number calculation formula in the porous medium is as follows:

[0168]

[0169] In the above formula, C p is the heat capacity of argon in the grid, and k is the turbulent kinetic energy.

[0170] The calculation formula of the heat transfer coefficient h is as follows:

[0171]

[0172] In the above formula, C Fin is the ratio of the total area of the finned tube to the pure tube area, which can be taken as 10-20.

[0173] The calculation formula of the source term heat absorption capacity S is as follows:

[0174]

[0175] In the above formula, T HX is the surface temperature of the heat exchanger, which can be taken as 300-333 K; T cell is the grid temperature of the porous medium; C S2V is the surface area to volume ratio of the heat exchanger, which can be taken as 10-30; F S is the correction coefficient of the heat exchanger, which can be taken as 1-100.

[0176] ③ Setting of fluid field parameters in the furnace

[0177] At the beginning of the vacuum furnace gas quenching stage, as the argon continuously and rapidly flows into the pipeline, the gas quenching pressure in the vacuum furnace will gradually increase and reach the predetermined pressure; at the same time, according to the variable frequency fan capacity and the internal program control logic of the vacuum furnace, the starting pressure of the fan can be between 0.1-1 bar, and the speed can be accelerated to the target speed. According to the vacuum furnace type and the configuration of the external gas source, this process will last for 5-20 s and be inflated to 0.8-20 bar. Therefore, according to the above information, the internal fluid field inflation can be fitted into a linear equation, and the calculation formula is as follows:

[0178]

[0179] In the above formula, P 炉内 is the current furnace pressure, P0 is the initial pressure of the fan start, and Pfinal Ptarget is the target gas quenching pressure, t total tgas is the gas quenching filling time, t flow Pcurrent is the current time of the flow field. When P 炉内 After reaching the gas quenching set pressure, the furnace pressure stops growing and remains at the current P 炉内 value.

[0180] At the same time, since the low-temperature argon gas entering the furnace will be heated by the high-temperature objects in the furnace to become high-temperature argon gas. Therefore, the argon gas temperature in the initial field can be set to 200-1000℃ according to the actual heat treatment process.

[0181] (4) Physical model state (physical model selection and parameter setting)

[0182] ① Steady state (Steady): The steady state stage is aimed at simulating the holding process.

[0183] Its physical model selection:

[0184] 1) Open the energy equation for fluid-solid coupled heat exchange;

[0185] 2) Turbulence: standard k-ε model is adopted.

[0186] 3) Thermal radiation: Surface to Surface (S2S) model or Discrete Orinates (DO) model is adopted.

[0187] Convergence criterion: Since the holding steady state stage only concerns whether the temperature inside the material converges, the criterion is set to the temperature difference between the previous and next steps ≤0.1℃ at each detection point, and the residual curve ≤10 -5 and remains stable.

[0188] ② Transient stage (Transient): The transient stage is aimed at simulating the gas quenching cooling process.

[0189] Its physical model selection:

[0190] 1) Open the energy equation for fluid-solid coupled heat exchange;

[0191] 2) Turbulence: standard k-ε model is adopted.

[0192] Step size setting: In order to increase the stability of transient calculation, the time step of each calculation step can be gradually increased as the flow field in the furnace is established, thereby reducing the overall calculation time while ensuring stability; each step size can be set to 0.001-0.1s, and 3-5 time step change calculation sections can be set in the middle.

[0193] Step (4): After the parameter adjustment is completed, the vacuum heat treatment furnace model is modified based on the simulation results and measured data, including: after the parameter adjustment is completed, the vacuum heat treatment process is simulated, and the vacuum heat treatment furnace simulation boundary conditions and physical quantity parameters are corrected according to the actual measured values, and further, the steady state stage and the transient stage of the vacuum heat treatment furnace model are corrected; specifically, it includes:

[0194] ① Steady state (Steady): The correction direction of the steady state stage is mainly to correct the simulated temperature field in the furnace;

[0195] Firstly, the vacuum furnace needs to be tested for furnace temperature uniformity at different working temperature sections according to relevant measurement standards, and obtain several groups of standard furnace temperature distribution, and the number of detection points can be selected as 5-12;

[0196] Secondly, after simulating the temperature field in the furnace using the actual vacuum furnace input power, the temperature difference between each point is compared, and the thermal conductivity coefficient of the hot zone structure is adjusted according to the temperature deviation of each detection point;

[0197] Finally, through multiple rounds of adjustment, the temperature difference of each point is reduced to 0.1-5℃, and the thermal conductivity coefficient of the hot zone structure is determined.

[0198] ② Transient stage (Transient): The correction direction of the transient stage is mainly to correct the simulated cooling rate field and gas flow velocity in the furnace.

[0199] 1) Correction of gas flow velocity

[0200] Firstly, use flow velocity measurement equipment such as flow velocity meter / air speed tube to measure the flow velocity of specific points of the vacuum furnace, such as: air duct, interlayer between hot zone and furnace shell, radial direction of centrifugal fan, etc. The number of measurement points can be selected as 2-5; Since the flow velocity is related to the speed of the centrifugal fan, only the cooling rate of one gas quenching pressure point needs to be measured. At the same time, the influence of the speed of the centrifugal fan on the flow velocity also needs to be considered. The number of centrifugal fan speeds can be selected as 2-5;

[0201] Secondly, after simulating the fluid field in the furnace using the actual vacuum furnace centrifugal fan speed, the flow velocity difference between each point is compared, and the viscous resistance and inertial resistance of the heat exchanger are adjusted according to the temperature and flow velocity deviation of each detection point;

[0202] Finally, through multiple rounds of adjustment, the flow velocity difference of each point is ≤0.2m / s, and the viscous resistance and inertial resistance of the heat exchanger are determined.

[0203] 2) Correction of cooling rate field

[0204] Firstly, the vacuum furnace needs to be tested for cooling rate at different temperature stages in the furnace according to relevant metrological standards, and several groups of standard cooling rate distribution in the furnace are obtained, the number of detection points can be selected as 5-12, and the real-time speed of the fan, the real-time pressure in the furnace are recorded, the resolution is ≤1 Hz;

[0205] Secondly, after simulating the cooling rate field in the furnace using the actual vacuum furnace fan speed and gas quenching pressure, the cooling rate difference between each point is compared; since the thermal deformation of the vacuum furnace at high temperature is unknown, the gap spacing of the vacuum furnace is adjusted according to the cooling rate deviation of each detection point;

[0206] Finally, through multiple rounds of adjustment, the cooling rate difference of each point is ≤20℃ / min.

[0207] In the feedback and correction stage, three charging states of empty furnace, only loaded with material frame and full load in the furnace are selected as typical working conditions. Any two of the above can be used as test conditions to correct and improve the vacuum furnace model; and the remaining one is used as a model to prove the effectiveness of the corrected and improved model.

[0208] The structure diagram of the corrected vacuum heat treatment furnace model is shown as Figure 3 , and the exploded view of the vacuum heat treatment furnace model is shown as Figure 4 , wherein the vacuum heat treatment furnace model comprises: a furnace shell 1, one end of the furnace shell 1 is connected with a heat exchanger 3, the heat exchanger 3 comprises a heat exchanger flow channel 4 and a heat exchanger copper pipe 5; a hot zone 2 is arranged inside the furnace shell 1, the hot zone 2 comprises a hot zone middle part 8, a hot zone front part 9 and a hot zone rear part 7, the hot zone rear part 7 is connected with a centrifugal impeller 6, a molybdenum support 12 is arranged inside the hot zone 2, the molybdenum support 12 is used to support a material rack 10, a workpiece 11 is arranged on the material rack 10, a molybdenum strip 13 is further arranged inside the hot zone 2, and a thermocouple 14 is arranged between the molybdenum strips 13.

[0209] Step (5): Material heat treatment organization performance state prediction based on the corrected vacuum heat treatment furnace model, including using the corrected vacuum heat treatment furnace model to obtain the residual eutectic content and γ' phase size distribution of the single crystal blade, specifically including:

[0210] ① Residual eutectic

[0211] The residual eutectic content is mainly related to the holding temperature of the vacuum heat treatment solid solution process. During the holding stage of the solid solution process, the closer the actual temperature of the single crystal high-temperature alloy to the process target temperature, the less the residual eutectic content inside.

[0212] After preliminary process exploration and metallographic detection, the following relationship between residual eutectic content and solid solution temperature is obtained, and the fitting formula is:

[0213] r coarsing= f0+ f1xT + f2xT 2 + f3xT 3 (14)

[0214] wherein the coefficients of f0to f3may be taken as:

[0215] f0= -(3.5~2.5) x 10 6 ;

[0216] f1= (6.0~7.0) x 10 3 ;

[0217] f2= -(4.5~5.0);

[0218] f3= (1.0~1.5) x 10 -3 ;

[0219] After the temperature field calculation is completed, the temperature field of the workpiece is calculated again through the secondary development function of Fluent UDF, and finally the residual eutectic content inside the workpiece is obtained.

[0220] 2. γ' phase size

[0221] The γ' phase size is mainly related to the cooling speed of the vacuum heat treatment solid solution process. During the holding stage of the solid solution process, the faster the actual cooling speed of the single crystal high-temperature alloy, the smaller the size of the γ' phase inside.

[0222] The cooling time in the present technology is defined as the time required to cool from the solid solution temperature to 600°C. Through previous process exploration of different cooling rates and metallographic detection, the relationship between the cooling time and the γ' phase size is fitted using a 6th order polynomial equation, as shown in equation (15):

[0223] f Thermal Conductivity (x) = g0+ g1x + g2x 2 + g3x 3 + g4x 4 + g5x 5 + g6x 6 (15)

[0224] wherein the coefficients of g0to g6may be taken as:

[0225] g0= (6.0~6.7) x 10 2 ;

[0226] g1= -(1.5~1.0) x 10 1 ;

[0227] g2= (1.8~2.4) x 10 -1 ;

[0228] g3 = -(1.1~1.5) x 10 -3 ;

[0229] g4 = (5.0~5.5) x 10 -6 ;

[0230] g5 = -(9.5~8.7) x 10 -9 ;

[0231] g6 = (5.9~6.8) x 10 -12 ;

[0232] By recording the cooling time of the heat treatment part domain, and combining the gas quenching process with the size of the gamma phase, the detailed distribution of the size of the gamma phase inside the part after the gas quenching process can be simulated. Therefore, in the present patent, the prediction of the distribution of the size of the gamma phase inside the part is realized by using the secondary development kit of Fluent UDF, and the results are shown in the following Figure 5 and Figure 6 , wherein Figure 5 is the distribution of the gamma phase on the outer surface of the blade, Figure 6 is the distribution of the gamma phase in the cross section of the blade.

[0233] The present application also discloses a vacuum heat treatment process simulation system based on Fluent, which is realized based on the above-mentioned vacuum heat treatment process simulation method based on Fluent, comprising:

[0234] A building unit is used to simplify the structure of the vacuum heat treatment furnace, and a vacuum heat treatment furnace model is established based on the simplified structure;

[0235] A division unit is used to divide the grid of the established vacuum heat treatment furnace model;

[0236] An adjustment unit is used to adjust the parameters based on Fluent after the grid division is completed;

[0237] A correction unit is used to correct the vacuum heat treatment furnace model based on the simulation results and measured data after the parameter adjustment is completed;

[0238] A prediction unit is used to predict the material heat treatment organization performance state based on the corrected vacuum heat treatment furnace model.

[0239] In summary, the vacuum heat treatment process simulation method based on Fluent of the present application can obtain detailed information of the fluid field, temperature field and other physical fields which cannot be obtained by traditional empirical formula through the simulation of the vacuum heat treatment furnace, and can provide optimization ideas for the design of vacuum furnace insulation, cooling, structure, flow channel and other aspects.

[0240] The above-described embodiments are merely intended to describe the preferred embodiments of the present application, and are not intended to limit the scope of the present application. Various changes and modifications of the present application, which are apparent to those skilled in the art, can be made to the present application without departing from the design spirit of the present application, and such changes and modifications should fall within the scope of the appended claims.

Claims

1. A method for simulating a vacuum heat treatment process based on Fluent, characterized in that, The method comprises the following steps: simplifying the structure of the vacuum heat treatment furnace and establishing a vacuum heat treatment furnace model based on the simplified structure; grid division is performed on the established vacuum heat treatment furnace model; after the grid division is completed, parameters are adjusted based on Fluent; after the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on simulation results and measured data; the organization performance state after material heat treatment is predicted based on the corrected vacuum heat treatment furnace model.

2. The method of simulating a vacuum heat treatment process based on Fluent according to claim 1, wherein: The simplified vacuum heat treatment furnace structure comprises simplifying components with a length of less than 20 mm in the vacuum heat treatment furnace.

3. The method of simulating a vacuum heat treatment process based on Fluent according to claim 1, wherein: The simplified vacuum heat treatment furnace structure comprises simplifying the furnace shell, the hot zone, the heat exchanger, the sensor, the fan and the centrifugal fan.

4. The method of simulating a vacuum heat treatment process based on Fluent according to claim 1, wherein: The vacuum heat treatment furnace model is established based on the simplified structure, which comprises establishing the vacuum heat treatment furnace model according to engineering drawings and measured data.

5. The method of simulating a vacuum heat treatment process based on Fluent according to claim 1, wherein: The vacuum heat treatment furnace model is established based on the simplified structure, which comprises establishing the vacuum heat treatment furnace model from the inside to the outside.

6. The method of simulating a vacuum heat treatment process based on Fluent according to claim 1, wherein: The grid division is performed on the established vacuum heat treatment furnace model, which comprises performing the grid division in the manner of face grid first and then volume grid.

7. The method of simulating a vacuum heat treatment process based on Fluent according to claim 1, wherein: The grid division is performed on the established vacuum heat treatment furnace model, which comprises setting grid division parameters through non-structural grid division software and establishing the non-structural network of the vacuum heat treatment furnace simulation model through grid inspection parameters.

8. The method of simulating a vacuum heat treatment process based on Fluent according to claim 7, characterized in that: The grid inspection parameters comprise y+ value and orthogonal mass.

9. The method of simulating a vacuum heat treatment process based on Fluent according to claim 8, characterized in that: The y+ value comprises y+ value of components with a flow rate of 5 m / s or less within 0.5 cm-1.5 cm from the wall surface, which is 10-30, and y+ value of components with a flow rate of 5 m / s or more within 0.5 cm-1.5 cm from the wall surface, which is 1-10; and the orthogonal mass is 0.15-0.

3.

10. The method of simulating a vacuum heat treatment process based on Fluent as claimed in claim 1, wherein: The parameters comprise material physical property parameters, boundary surface parameters, block phase parameters and physical model states.

11. The method of simulating a vacuum heat treatment process based on Fluent as claimed in claim 10, wherein: The material physical property parameters comprise argon physical property parameters, alumina phase parameters, copper phase parameters, molybdenum phase parameters, steel phase parameters and hot zone phase parameters.

12. The method of simulating a vacuum heat treatment process based on Fluent as claimed in claim 11, wherein: The argon physical property parameters comprise argon thermal conductivity coefficient, the alumina phase parameters comprise alumina thermal conductivity and alumina heat capacity, the molybdenum phase parameters comprise molybdenum thermal conductivity and molybdenum heat capacity, and the hot zone phase parameters comprise hot zone thermal conductivity, which is set according to the orthogonal anisotropy of the cylindrical coordinate system.

13. The method of simulating a vacuum thermal processing process based on Fluent as claimed in claim 10, wherein: The boundary surface parameters comprise furnace shell parameters, heat exchanger pipe wall surface parameters, centrifugal fan wall surface parameters and heat input parameters.

14. The method of simulating a vacuum thermal processing process based on Fluent as claimed in claim 10, wherein: The block phase parameters comprise centrifugal fan flow field parameters, heat exchanger flow field parameters and furnace fluid field parameters.

15. The method of simulating a vacuum thermal processing process based on Fluent as claimed in claim 10, wherein: The physical model states comprise steady state stage and transient state stage.

16. The method of simulating a vacuum thermal processing procedure based on Fluent as claimed in claim 1, wherein: After the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on simulation results and measured data, which comprises simulating the vacuum heat treatment process and correcting the vacuum heat treatment furnace simulation boundary conditions and physical quantity parameters according to actual measured values.

17. The method of simulating a vacuum thermal processing process based on Fluent as claimed in claim 16, wherein: After the parameter adjustment is completed, the vacuum heat treatment furnace model is corrected based on simulation results and measured data, which comprises correcting the steady state stage and the transient state stage of the vacuum heat treatment furnace model.

18. The method of simulating a vacuum thermal processing process based on Fluent as claimed in claim 17, wherein: The steady-state stage corrects the simulated in-furnace temperature field, and the transient-state stage corrects the simulated in-furnace cooling rate field and air flow rate.

19. The method of simulating a vacuum thermal processing procedure based on Fluent as claimed in claim 1, wherein: The material heat treatment after-organization performance state prediction based on the corrected vacuum heat treatment furnace model comprises using the corrected vacuum heat treatment furnace model to obtain the residual eutectic content and the size distribution state of the gamma prime phase of the single crystal blade.

20. A simulation system for vacuum heat treatment process based on Fluent, implemented based on the simulation method for vacuum heat treatment process based on Fluent according to any one of claims 1-19, characterized in that, The method comprises the following steps: A building unit is configured to simplify the structure of the vacuum heat treatment furnace and build a vacuum heat treatment furnace model based on the simplified structure; A division unit is configured to divide the built vacuum heat treatment furnace model into grids; An adjustment unit is configured to adjust parameters based on Fluent after the grid division is completed; A correction unit is configured to correct the vacuum heat treatment furnace model based on the simulation results and the measured data after the parameter adjustment is completed; A prediction unit is configured to predict the material heat treatment after-organization performance state based on the corrected vacuum heat treatment furnace model.

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