Hot-pressing tank forming mold with metal sliding block temperature control function and sliding block thickness optimization method

Abstract

The invention discloses an autoclave forming mold with a metal sliding block temperature control function and a sliding block thickness optimization method. The mold molded surface is arranged at the top of the support, a guide rail groove is formed in the bottom of the mold molded surface, and a plurality of sliding blocks are installed in the guide rail groove in a sliding mode; during heating, the thick sliding block absorbs heat to inhibit the heating rate, and during cooling, the thick sliding block releases heat to compensate for heat loss, so that the molded surface temperature difference in autoclave molding of a large composite material component is remarkably reduced; the problems of non-uniform local curing, performance reduction and thermal expansion deformation caused by temperature difference are effectively solved, and the product quality and the size precision are improved; the modular guide rail sliding block design supports flexible adjustment of the position, the thickness and the distance, compared with topological optimization, the modular guide rail sliding block design has higher process adaptability and machinability, and rapid optimization and iteration aiming at different process conditions are achieved by combining parametric modeling and an automatic optimization technology.

Description

Technical Field

[0001] This invention relates to the field of mold design technology, specifically to a thermoforming mold for autoclaves with temperature control via a metal slider and a method for optimizing slider thickness. Background Technology

[0002] Carbon fiber reinforced composite materials are widely used in the aerospace field. Airbus in Europe, Boeing in the United States, and the C929 wide-body passenger aircraft currently under development in China all use carbon fiber reinforced composite fuselage panels. Currently, aerospace carbon fiber reinforced composite components are mainly produced through autoclave molding. However, due to the large mold size and complex ventilation hole structure, uneven temperature distribution on the mold surface can occur. This means that the mold temperature at the nitrogen inlet end of the autoclave is higher than the mold temperature at the outlet end, or the mold edge temperature is higher than the middle temperature. The maximum temperature difference during heating and cooling can reach over 40°C. This causes uneven curing of the composite panel, exacerbating the degree of curing deformation. This affects the assembly of the composite panel and, more seriously, can lead to aircraft safety issues. Currently, to reduce the temperature difference caused by mold ventilation problems, topology optimization methods are commonly used to optimize the shape and position of the ventilation holes. However, the following problems still exist:

[0003] (1) Optimizing the shape and location of ventilation holes will reduce the support strength;

[0004] (2) The optimized shape of the through hole is complex and difficult to process;

[0005] (3) Even after optimization, a large temperature difference still exists, and the effect is limited;

[0006] (4) The optimized mold structure is fixed and only applicable to specific process conditions, which is not flexible. Summary of the Invention

[0007] The purpose of this invention is to provide a thermoforming mold for an autoclave with temperature control via a metal slider and a method for optimizing the slider thickness, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a thermostatic precipitator forming mold with a metal slider for temperature control, comprising:

[0009] support;

[0010] The mold surface is placed on top of the support. A guide groove is opened at the bottom of the mold surface. Multiple sliders are slidably installed inside the guide groove. The thickness of the slider near the nitrogen inlet is greater than the thickness of the slider near the nitrogen outlet. This is used to regulate the temperature distribution of the mold surface and reduce the temperature difference of the mold surface during the heating and cooling process.

[0011] The coefficient of thermal expansion of the slider material is greater than that of the mold surface material, and the specific heat capacity of the slider material is greater than that of the mold surface material.

[0012] Preferably, the guide rail groove is a T-shaped guide rail groove or a dovetail guide rail groove.

[0013] A method for optimizing the thickness of a thermoforming mold with a metal slider for temperature control, wherein the method is a finite element analysis optimization method for slider thickness parameter design, and the steps of the method are as follows:

[0014] Step 1: Open the CATIA modeling software and enable its macro recording function to create the initial mold geometry model, including the mold surface, support, and guide rail groove below the mold surface. Also, create metal sliders of the same initial thickness that are evenly distributed on the guide rail groove.

[0015] Step 2: Establish a simplified model of the autoclave; the simplified model of the autoclave includes an air inlet, an air outlet, and the body. Assemble the simplified model of the autoclave and the mold model in the corresponding positions, then export the assembled geometric model and save it as a parametric modeling Python file.

[0016] Step 3: Open SpaceClaim CAD software, import the geometric assembly model from Step 2, and name the selection sets in SpaceClaim software.

[0017] Step 4: Open Fluent fluid analysis software, import the geometric assembly model from Step 3, and generate a volume mesh;

[0018] Step 5: Switch to solve mode, initialize the model temperature and fluid velocity, and submit the calculation;

[0019] Step 6: Based on the optimized slider thickness parameters obtained from the calculation, automatically update the script program code in the Python file in Step 2, and then run the updated script through CATIA software to obtain the updated digital model;

[0020] Step 7: Repeat steps 3-6 to obtain the surface temperature of the model after the first optimization, and compare the temperature difference before and after optimization;

[0021] Step 8: Following the optimization method in Step 6, further optimize the thickness of the metal slider, and repeat Steps 3-6 to calculate the optimized surface temperature of the model until the surface temperature difference no longer changes, thus obtaining the best result.

[0022] Preferably, the guide rail groove is a dovetail guide rail groove.

[0023] Preferably, the steps for generating the volume mesh are as follows: add local dimensions, generate surface mesh, define boundary conditions, specify region type, add boundary layer, and generate volume mesh.

[0024] Preferably, the specific method of step 5 is as follows: Open the energy equation sequentially – select the fluid viscosity model – define the mold material parameters and air material parameters – define the inlet gas inflow velocity (1~5 m / s), define the inlet temperature process curve (which can be controlled by UDF); define the outlet pressure (0~2 MPa), define the mold-air coupled heat exchange – define the results to be output – initialize the temperature – submit the calculation. In step 1, the metal sliders are named K1 to K in the order of 1 to N. N The thickness of the slider is H1 to H N The output results include a mold surface temperature cloud map, the average temperature of the mold surface projection area corresponding to each metal slider from 1 to N, and the average temperature of the entire mold surface;

[0025] Preferably, the method for optimizing the thickness of the slider in step 6 is as follows:

[0026] At the end of the controlled inlet heating process, the temperature difference of the mold surface is at its maximum. At the inlet temperature inflection point, the average temperature of the projected area of ​​the mold surface corresponding to each metal slider from 1 to N is extracted and denoted as T1 to T. N The T1 to T N The temperature at the inflection point from heating to constant temperature is used to optimize the thickness based on the temperature difference at this moment. The average temperature of the entire mold surface at this point is extracted and denoted as T. 均 ; Calculate T1 to T respectively N The difference ΔT between T and the mean;

[0027] For any metal slider, the average temperature T of the projected area of ​​the mold surface is... i If T i If the value is greater than T, then ΔT is positive, the slider thickness increases, and the increase is ΔT / T. 均 If T i equal to T 均 If ΔT = 0, the thickness of the slider remains unchanged. If T i Less than T 均 If ΔT is negative, the thickness of the slider decreases by a ratio of ΔT / T. 均 Based on the optimized slider thickness parameters obtained from the calculation, the script program code in step 2 is automatically updated, and then the updated script is run through CATIA software to obtain the updated digital model.

[0028] Preferably, the guide rail groove is a T-shaped guide rail groove.

[0029] Preferably, in step 4, the mold surface regions corresponding to metal sliders 1 to N are selected and established, and the set is named S1 to SN. The entire mold surface set is selected and established and named S_u ...

[0030] Preferably, the specific method of step 5 is as follows: Select transient analysis, open the energy control equation, define the viscous fluid equation, define the nitrogen and steel material properties, define the inlet gas rate, inlet temperature conditions, and outlet pressure, with the inlet temperature controlled by UDF; in the report definition, output the mold surface sets S1 to S2 corresponding to the regions of the metal sliders from 1 to N respectively. N The average temperature variation curve over time is output, along with the entire mold surface set S. 均 The average temperature changes over time; the model temperature and fluid velocity are initialized, and the calculation is submitted.

[0031] Compare the mold surface sets S1 to S2 corresponding to the regions of metal sliders 1 to N during the heating process. N The average temperature from T1 to T N With the entire mold surface set S 均 Average temperature T 均 The difference ΔT;

[0032] For S1 to S N S is a set of arbitrary metal slider surfaces i Average temperature T i If T i Greater than T 均 Then the thickness of the i-th slider increases by a factor of T. i / T 均 If T i equal to T 均 If the thickness of the i-th slider remains unchanged, then if T i Less than T 均 Then the thickness of the i-th slider decreases by a factor of T. i / T 均 ;

[0033] Read the temperature results calculated by FLUENT in the parametric modeling Python file, and optimize the thickness of the metal sliders from 1 to N according to the above correction factors; generate new metal slider molds and autoclave models with different thicknesses through parametric modeling; export the assembly file from CATIA; and save the parametric modeling Python file.

[0034] The optimized model was analyzed using FLUENT fluid simulation software to determine the temperature distribution during heating. Simultaneously, the mold surface sets S1 to S2 corresponding to the metal sliders 1 to N were compared during the heating process. N The average temperature from T1 to T N With the entire mold surface set S 均 Average temperature T 均 The difference ΔT is used to obtain a new metal slider thickness correction coefficient.

[0035] Compared with existing technologies, the beneficial effects of this invention are as follows: By designing metal sliders of different thicknesses at the bottom of the mold surface and cooperating with a guide rail structure, this invention utilizes the thermal capacity characteristics of the sliders to "shaving peaks and filling valleys" of heat flow during the heating and cooling process: when heating up, the thicker slider absorbs heat to suppress the heating rate, and when cooling down, it releases heat to compensate for heat loss, thereby significantly reducing the surface temperature difference in the autoclave molding of large composite material components. This effectively solves the problems of uneven local curing, performance degradation, and thermal expansion deformation caused by temperature differences, improving product quality and dimensional accuracy. At the same time, the modular guide rail slider design supports flexible adjustment of position, thickness, and spacing, which has stronger process adaptability and machinability compared to topology optimization. Combined with parametric modeling and automatic optimization technology, it realizes rapid optimization and iteration for different process conditions, greatly shortening the mold development cycle and reducing manufacturing costs. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the installation structure of the mold of the present invention;

[0037] Figure 2 This is a schematic diagram of the mold surface structure of the present invention;

[0038] Figure 3 This is a schematic diagram of the distribution structure of the slider in this invention;

[0039] Figure 4 This is a schematic diagram of the guide rail groove of the present invention;

[0040] Figure 5 This is a schematic diagram of the slider of the present invention;

[0041] Figure 6 Initialize the temperature contour map for this invention;

[0042] Figure 7 This is a temperature cloud map at 180°C according to the present invention;

[0043] Figure 8 The optimized temperature cloud map for this invention;

[0044] Figure 9 This is the optimized temperature cloud map at 180℃ according to the present invention;

[0045] Figure 10 The optimized slider thickness according to the present invention;

[0046] Figure 11 The diagram shows the centerline temperature before and after optimization of this invention.

[0047] Figure 12 This is a schematic diagram showing the temperature corresponding to the thickness of the slider before and after optimization in this invention (in the figure: KT represents the inlet control temperature, Max represents the highest temperature of the mold surface, and Min represents the lowest temperature of the mold surface).

[0048] In the diagram: 1. Support; 2. Mold surface; 3. Guide rail groove; 4. Slider; 5. Filler block. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Please see Figures 1-12 This invention provides a technical solution: a thermoforming mold for an autoclave with temperature control via metal sliders, comprising: a support 1; a mold surface 2 fixed to the top of the support 1, a guide rail groove 3 being provided at the bottom of the mold surface 2, a plurality of sliders 4 being slidably installed inside the guide rail groove 3, with a certain gap between the sliders, and a filling block 5 installed in the guide rail groove 3 corresponding to the gap, used to fill the position of the guide rail groove 3 where no slider 4 is installed, the thickness of the slider 4 near the nitrogen inlet is greater than the thickness of the slider 4 near the nitrogen outlet, used to regulate the temperature distribution of the mold surface and reduce the surface temperature difference during the heating and cooling process of the mold; the coefficient of thermal expansion of the slider 4 material is greater than the coefficient of thermal expansion of the mold surface 2 material, and the specific heat capacity of the slider 4 material is greater than the specific heat capacity of the mold surface 2 material.

[0051] It should be noted that during the heating process in this embodiment, the mold near the nitrogen inlet heats up quickly and reaches a high temperature. The design of a metal slider with a high specific heat capacity and a large thickness can absorb heat and slow down the heating rate. The thinner slider at the outlet has little impact, thus reducing the temperature difference during the heating process. During the cooling process, the nitrogen inlet cools down quickly. The design of a metal slider with a high specific heat capacity and a large thickness can transfer heat to the mold surface, compensating for heat loss and reducing the cooling rate. The thinner slider at the outlet has little impact, thus reducing the temperature difference. This invention employs a guide rail and slider design, which allows for flexible changes in the size, position, and spacing of the sliders to adapt to different process conditions. Both its temperature control effect and flexibility are superior to topology optimization methods.

[0052] A method for optimizing the thickness of a thermoforming mold with a metal slider for temperature control. This method is a finite element analysis optimization method for slider thickness parameter design, when the guide rail groove is a dovetail groove.

[0053] Step 1: Open CATIA CAD software and create the initial mold geometry model, including the profile and support. Create a dovetail groove below the mold profile and evenly distribute metal sliders of the same initial thickness on the guide rail. Name the metal sliders K1 to KN in the order of 1 to N. N The thickness of the slider is H1 to H N .

[0054] Step 2: Establish a simplified model of the autoclave, which includes the air inlet, air outlet, and autoclave body.

[0055] Step 3: Assemble the autoclave model and mold model in the appropriate positions. Then export the assembled geometric model.

[0056] Step 4: To automate the above modeling process and batch automate the modification of metal slider thickness parameters, enable the macro recording function and record the above process to a Python file, saving it as a script. Later, the geometric parameters of the model for metal sliders 1 to N can be modified in batches using the script code.

[0057] Step 5: Open SpaceClaim CAD software, import the geometric assembly model from step 3, and define the air inlet, air outlet, tank wall, and mold-air interface in SpaceClaim software.

[0058] Step 6: Open Fluent fluid analysis software, import the model geometry assembly model from step 5, and add local dimensions, generate surface mesh, define boundary conditions, specify region type, add boundary layer, and generate volume mesh in sequence.

[0059] Step 7: Switch to solve mode, open the energy equation in sequence - select the fluid viscosity model - define the mold material parameters and air material parameters - define the inlet gas inflow velocity (1~5 m / s), define the inlet temperature process curve (which can be controlled by UDF); define the outlet pressure (0~2MPa), define the mold and air coupled heat exchange - define the results to be output - initialize the temperature - submit the calculation.

[0060] The output results in steps 8 and 7 include the temperature cloud map of the mold surface, the average temperature of the mold surface projection area corresponding to each metal slider from 1 to N, and the average temperature of the entire mold surface.

[0061] Step 9: Optimize the thickness of the metal sliders. Specifically, control the temperature difference of the mold surface to be at its maximum at the end of the inlet heating. Extract the average temperature of the mold surface projection area corresponding to each metal slider from 1 to N at this time, and denot it as T1 to T2. N T1 to T N The temperature at the inflection point from heating to constant temperature is used to optimize the thickness based on the temperature difference at this moment. The average temperature of the entire mold surface at this point is extracted and denoted as T. 均 Calculate T1 to T2 respectively. N With T 均 The difference ΔT. For any metal slider, the average temperature T of the projected area of ​​the mold surface. i If T i Greater than T 均 If ΔT is positive, the thickness of the slider increases by ΔT / T. 均 If T i equal to T 均 If ΔT = 0, the thickness of the slider remains unchanged. If T i Less than T 均 If ΔT is negative, the thickness of the slider decreases by a ratio of ΔT / T. 均 Based on the optimized slider thickness parameters obtained from the calculation, the script program code in step 4 is automatically updated, and then the updated script is run through CATIA software to obtain the updated digital model.

[0062] Step 10: Repeat steps 5-8 to obtain the surface temperature of the model after the first optimization, and compare the temperature difference before and after optimization.

[0063] Step 11: Following the optimization method in step 9, further optimize the thickness of the metal slider, and repeat steps 5-8 to calculate the optimized surface temperature of the model until the surface temperature difference no longer changes, thus obtaining the best result.

[0064] A method for optimizing the slider thickness of a thermoforming mold with a metal slider for temperature control. This method is a finite element analysis optimization method for slider thickness parameter design, when the guide groove is a T-slot:

[0065] First, enable CATIA's macro recording function to create the initial mold geometry model, including the surface and support. Create a T-slot below the mold surface and evenly distribute metal sliders of the same initial thickness on the guide rail. To facilitate subsequent parametric modeling and automatic optimization of the metal slider thickness, create the metal slider geometry model in order from 1 to N, and name them T1 to T... N Then, a simplified model of the autoclave is created, and the autoclave model is assembled with the mold in the appropriate positions. The assembly file is then exported from CATIA, and the parametric modeling Python file is saved.

[0066] Import the assembly file into FLUENT fluid simulation software, select and create a set of geometric surfaces. This includes the gas inlet, gas outlet, outer wall of the autoclave, and the interface between the mold and the gas. Simultaneously, select and create the mold surface regions corresponding to metal sliders 1 to N, naming the sets S1 to S... N Select and create the entire mold surface set, named S 均 .

[0067] Further add local dimensions - generate surface mesh - describe geometry - update boundary - create region - trigger quality improvement - add boundary layer - generate volume mesh.

[0068] Switch to solver mode, select transient analysis, open the energy control equations, define the viscous fluid equations, define the nitrogen and steel material properties, define the inlet gas velocity, inlet temperature conditions, and outlet pressure. The inlet temperature is controlled via a UDF. In the report definition, output the mold surface sets S1 to S2 corresponding to the regions of metal sliders 1 to N. N The average temperature over time is displayed, along with the average temperature over time for the entire mold surface set S. The model temperature and fluid velocity are initialized, and the calculation is submitted.

[0069] Compare the mold surface sets S1 to S2 corresponding to the regions of metal sliders 1 to N during the heating process. N The average temperature from T1 to T N With the entire mold surface set S 均 Average temperature T 均 The difference ΔT.

[0070] For S1 to S N S is a set of arbitrary metal slider surfaces i Average temperature T i If T i Greater than T 均 Then the thickness of the i-th slider increases by a factor of T. i / T 均 If T i equal to T 均 If the thickness of the i-th slider remains unchanged, then if T i Less than T 均 Then the thickness of the i-th slider decreases by a factor of T. i / T 均 .

[0071] The parametric modeling Python file reads the temperature results calculated by FLUENT and optimizes the thickness of the metal sliders from 1 to N according to the aforementioned correction factors. New metal slider molds and autoclave models with varying thicknesses are generated through parametric modeling. Assembly files are exported from CATIA, and the parametric modeling Python file is saved.

[0072] The optimized model was analyzed using FLUENT fluid simulation software to determine the temperature distribution during heating. Simultaneously, the mold surface sets S1 to S2 corresponding to the metal sliders 1 to N were compared during the heating process. N The average temperature from T1 to T N With the entire mold surface set S 均 Average temperature T 均 The difference ΔT is used to obtain a new metal slider thickness correction coefficient.

[0073] The above optimization process is repeated until the temperature difference of the mold surface during the heating process is controlled within a reasonable range.

[0074] Example 1: A method for optimizing the thickness of a metal slider based on a T-slot

[0075] 1. Initial Modeling and Assembly

[0076] Step 1: Create a mold geometry model in CATIA. Create a T-slot below the mold surface. The slot is 10mm wide and 20mm deep, and is evenly distributed along the longitudinal direction of the mold surface.

[0077] Step 2: Create 10 metal sliders (K1~K10) with an initial thickness of 15mm. The bottom of the slider is a T-shaped boss, which is fitted with the T-slot of the mold with a clearance (0.1mm on one side) to ensure that the slider can slide along the slot but without vertical wobble.

[0078] Step 3: Create a simplified model of the autoclave. The autoclave is 3m in diameter and 6m long. The air inlet is located at the front end of the autoclave (nitrogen inlet), and the air outlet is located at the rear end (nitrogen outlet). Assemble the mold model with the autoclave model, ensuring that the longitudinal centerline of the mold coincides with the axis of the autoclave, and the air inlet faces the front end of the mold.

[0079] 2. Automated Modeling and Parametricization

[0080] Step 4: Enable CATIA macro recording to record the modeling and assembly process, generating a Python script. Define the slider thickness parameter as a variable in the script (H1=H2=...=H...). 10 =15), and subsequent batch adjustments can be achieved by modifying script parameters.

[0081] 3. Simulation Setup and Solution

[0082] Step 5: Import the assembly model into SpaceClaim and define the following naming selection set:

[0083] Inlet: Circular air inlet (0.5m in diameter) at the front of the autoclave;

[0084] Outlet: Circular air outlet at the rear of the autoclave (0.5m in diameter);

[0085] Can_Wall: The outer wall surface of the autoclave (insulation boundary);

[0086] Mold_Air: The upper surface of the mold that is in contact with air;

[0087] S1~S10: The mold surface projection area corresponding to the 10 sliders (each area is 0.3m²).

[0088] Step 6: Import the model into Fluent, perform mesh generation (surface mesh size 2mm, volume mesh expansion rate 1.2), and set boundary conditions:

[0089] Inlet: velocity 3m / s, temperature rise curve controlled by UDF (20℃→180℃ / 120min).

[0090] Outlet pressure: 1 MPa;

[0091] Mold material: steel (thermal conductivity 45W / m·K);

[0092] Slider material: aluminum (thermal conductivity 200W / m·K).

[0093] 4. Optimize iterations and results

[0094] Step 7: Submit the calculation and output the temperature cloud map of the mold surface at the end of the heating process (120 min) and the average temperature of each region (T1~T). 10 T 均 Initial simulation showed that the temperature at the front end of the mold (regions K1~K3) was 185℃, and the temperature at the rear end (K8~K...) was... 10 (Regional) Temperature 172℃, temperature difference ΔT=13℃.

[0095] Step 8: Adjust the slider thickness according to the optimization rules:

[0096] In the K1~K3 region: ΔT = +5℃, the slider thickness increases by ΔT / T. 均 ×15mm=0.42mm (new thickness 15.42mm);

[0097] K8~K10 region: ΔT=-3℃, slider thickness decreases by ΔT / T 均 ×15mm=0.25mm (new thickness 14.75mm).

[0098] Step 9: Update the Python script, regenerate the model, and perform simulation. After three iterations, the temperature difference on the mold surface decreased to 2℃, and the optimization was completed.

[0099] Example 2: Thickness Optimization Method for Metal Slider Based on Dovetail Groove

[0100] 1. Initial Modeling and Assembly

[0101] Step 1: Create a mold geometry model in CATIA. Create a dovetail groove below the mold surface. The groove is 15mm wide at the top, 25mm wide at the bottom, and 25mm deep. The groove angle is 45° and it is evenly distributed along the longitudinal direction of the mold surface.

[0102] Step 2: Create 10 metal sliders (K1~K) with an initial thickness of 15mm each. 10 The bottom of the slider has a dovetail-shaped boss that matches the dovetail groove of the mold (0.05mm clearance on one side) to ensure that the slider has no risk of vertically dislodging.

[0103] Step 3: Assemble the autoclave model (parameters same as in Example 1), offsetting the longitudinal centerline of the mold by 100mm from the autoclave axis to simulate asymmetric air intake conditions.

[0104] 2. Automated Modeling and Parametricization

[0105] Step 4: Record macros to generate Python scripts, defining slider thickness parameters and dovetail groove geometric constraints (such as groove angle and fit clearance).

[0106] 3. Simulation Setup and Solution

[0107] Step 5: Define a named selection set in SpaceClaim (same as in Example 1), but add Mold_Support (the interface between the mold support and the air) to simulate the heat dissipation effect of the support.

[0108] Step 6: Set asymmetric boundary conditions in Fluent:

[0109] Inlet: velocity 4 m / s, temperature profile (20℃→180℃ / 100 min);

[0110] Outlet pressure: 0.5 MPa;

[0111] Mold material (steel):

[0112] Thermal conductivity: 45 W / (m·K);

[0113] Specific heat capacity: 480 J / (kg·K);

[0114] Density: 7850 kg / m³;

[0115] Slider material (aluminum):

[0116] Thermal conductivity: 205 W / (m·K);

[0117] Specific heat capacity: 900 J / (kg·K);

[0118] Density: 2700 kg / m³;

[0119] 4. Optimize iterations and results

[0120] Step 7: Initial simulation display: Temperature on the left side of the mold (near the air inlet, K1~K4 area) is 185℃, and on the right side (K7~K... 10 (Regional) Temperature 165℃, temperature difference ΔT=20℃.

[0121] Step 8: Adjust the slider thickness:

[0122] In the K1~K4 region: ΔT=+10℃, the slider thickness increases by 10 / 175×15mm≈0.86mm (new thickness 15.86mm).

[0123] In the K7~K10 region: ΔT=-10℃, the slider thickness is reduced by 10 / 175×15mm≈0.86mm (new thickness 14.14mm).

[0124] Step 9:

[0125] Second iteration:

[0126] The temperature on the left side of the mold is 178℃, and the temperature on the right side is 172℃, with a temperature difference ΔT=6℃.

[0127] Fine-tuning slider thickness: K1~K4 increased by 0.3mm (16.16mm), K7~K 10 Reduced by 0.3mm (13.84mm).

[0128] 3rd iteration:

[0129] The temperature on the left side of the mold is 176℃, and the temperature on the right side is 174℃, with a temperature difference ΔT=2℃.

[0130] The right sliders (K9~K10) experienced slightly lower temperatures in some areas due to reduced thickness. Further fine-tuning of the slider spacing (K9~K10) was then performed. 10 (The spacing was increased by 5mm).

[0131] Final result: The temperature difference of the mold surface is stable within 2℃, which meets the optimization target.

[0132] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A thermostatic precipitator forming mold with a metal slider for temperature control, characterized in that: include: Support (1); The mold surface (2) is placed on top of the support (1). The bottom of the mold surface (2) is provided with a guide rail groove (3). Multiple sliders (4) are slidably installed inside the guide rail groove (3). The thickness of the slider (4) near the nitrogen inlet is greater than the thickness of the slider (4) near the nitrogen outlet. This is used to regulate the temperature distribution of the mold surface and reduce the temperature difference of the mold surface during the heating and cooling process. The coefficient of thermal expansion of the material of the slider (4) is greater than that of the material of the mold surface (2), and the specific heat capacity of the material of the slider (4) is greater than that of the material of the mold surface (2).

2. The autoclave forming mold with metal slider temperature control according to claim 1, characterized in that: The guide rail groove is a T-shaped guide rail groove or a dovetail guide rail groove.

3. A method for optimizing the slider thickness of a thermoforming mold with a metal slider for temperature control, characterized in that: The method described is a finite element analysis optimization method for slider thickness parameter design. The steps of the method are as follows: Step 1: Open the CATIA modeling software and enable its macro recording function to create the initial mold geometry model, including the mold surface, support, and guide rail groove below the mold surface. Also, create metal sliders of the same initial thickness that are evenly distributed on the guide rail groove. Step 2: Establish a simplified model of the autoclave; the simplified model of the autoclave includes an air inlet, an air outlet, and the body. Assemble the simplified model of the autoclave and the mold model in the corresponding positions, then export the assembled geometric model and save it as a parametric modeling Python file. Step 3: Open SpaceClaim CAD software, import the geometric assembly model from Step 2, and name the selection sets in SpaceClaim software. Step 4: Open Fluent fluid analysis software, import the geometric assembly model from Step 3, and generate a volume mesh; Step 5: Switch to solve mode, initialize the model temperature and fluid velocity, and submit the calculation; Step 6: Based on the optimized slider thickness parameters obtained from the calculation, automatically update the script program code in the Python file in Step 2, and then run the updated script through CATIA software to obtain the updated digital model; Step 7: Repeat steps 3-6 to obtain the surface temperature of the model after the first optimization, and compare the temperature difference before and after optimization; Step 8: Following the optimization method in Step 6, further optimize the thickness of the metal slider, and repeat Steps 3-6 to calculate the optimized surface temperature of the model until the surface temperature difference no longer changes, thus obtaining the best result.

4. The slider thickness optimization method according to claim 3, characterized in that: The guide rail groove is a dovetail guide rail groove.

5. The slider thickness optimization method according to claim 4, characterized in that: The steps for generating a volume mesh are as follows: add local dimensions, generate a surface mesh, define boundary conditions, specify the region type, add a boundary layer, and generate a volume mesh.

6. The slider thickness optimization method according to claim 5, characterized in that: The specific method for step 5 is as follows: Open the energy equation sequentially – select the fluid viscosity model – define the mold material parameters and air material parameters – define the inlet gas inflow velocity (1~5 m / s), define the inlet temperature process curve (which can be controlled via UDF); define the outlet pressure (0~2 MPa), define the mold-air coupled heat exchange – define the results to be output – initialize the temperature – submit the calculation. In step 1, the metal sliders are named K1 to K in the order of 1 to N. N The thickness of the slider is H1 to H N The output results include a mold surface temperature cloud map, the average temperature of the mold surface projection area corresponding to each metal slider from 1 to N, and the average temperature of the entire mold surface.

7. The slider thickness optimization method according to claim 6, characterized in that: The method for optimizing the thickness of the slider in step 6 is as follows: At the end of the controlled inlet heating process, the temperature difference of the mold surface is at its maximum. At the inlet temperature inflection point, the average temperature of the mold surface projection area corresponding to each metal slider from 1 to N is extracted and denoted as T1 to T. N。 The T1 to T N The temperature at the inflection point from heating to constant temperature is used to optimize the thickness based on the temperature difference at this moment. The average temperature of the entire mold surface at this point is extracted and denoted as T. 均 ; Calculate T1 to T respectively N The difference ΔT between T and the mean; For any metal slider, the average temperature T of the projected area of ​​the mold surface is... i If T i If the value is greater than T, then ΔT is positive, the slider thickness increases, and the increase is ΔT / T. 均 If T i equal to T 均 If ΔT = 0, the thickness of the slider remains unchanged. If T i Less than T 均 If ΔT is negative, the thickness of the slider decreases by a ratio of ΔT / T. 均 Based on the optimized slider thickness parameters obtained from the calculation, the script program code in step 2 is automatically updated, and then the updated script is run through CATIA software to obtain the updated digital model.

8. The slider thickness optimization method according to claim 4, characterized in that: The guide rail groove is a T-shaped guide rail groove.

9. The slider thickness optimization method according to claim 8, characterized in that: In step 4, the mold surface regions corresponding to metal sliders 1 to N are selected and established, and the set is named S1 to SN. The entire mold surface set is selected and established and named S_u ...

10. The slider thickness optimization method according to claim 9, characterized in that: The specific method for step 5 is as follows: Select transient analysis, open the energy control equation, define the viscous fluid equation, define the properties of nitrogen and steel materials, define the inlet gas rate, inlet temperature conditions, and outlet pressure. The inlet temperature is controlled by UDF. In the report definition, output the mold surface sets S1 to S2 corresponding to the regions of the metal sliders from 1 to N. N The average temperature variation curve over time is output, along with the entire mold surface set S. 均 The average temperature changes over time; the model temperature and fluid velocity are initialized, and the calculation is submitted. Compare the mold surface sets S1 to S2 corresponding to the regions of metal sliders 1 to N during the heating process. N The average temperature from T1 to T N With the entire mold surface set S 均 Average temperature T 均 The difference ΔT; For S1 to S N S is a set of arbitrary metal slider surfaces i Average temperature T i If T i Greater than T 均 Then the thickness of the i-th slider increases by a factor of T. i / T 均 If T i equal to T 均 If the thickness of the i-th slider remains unchanged, then if T i Less than T 均 Then the thickness of the i-th slider decreases by a factor of T. i / T 均 ; Read the temperature results calculated by FLUENT in the parametric modeling Python file, and optimize the thickness of the metal sliders from 1 to N according to the above correction factors; generate new metal slider molds and autoclave models with different thicknesses through parametric modeling; export the assembly file from CATIA; And save the parametric modeling Python file; The optimized model was analyzed using FLUENT fluid simulation software to determine the temperature distribution during heating. Simultaneously, the mold surface sets S1 to S2 corresponding to the metal sliders 1 to N were compared during the heating process. N The average temperature from T1 to T N With the entire mold surface set S 均 Average temperature T 均 The difference ΔT is used to obtain a new metal slider thickness correction coefficient.

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