Split blade diffusion welding tool design method based on multi-material analog simulation

Abstract

The invention provides a split blade diffusion welding tool design method based on multi-material analog simulation, and relates to the technical field of diffusion bonding. The method comprises the following steps: firstly, acquiring thermophysical and mechanical properties of a blade material (TC4) and a tool material (graphite IG56), constructing a constitutive model, and meanwhile, testing the properties and establishing a database; and then an initial tool is designed according to the blade structure, a temperature field and a stress field in the welding process are simulated through multi-material coupling simulation, and the tool structure is optimized to guarantee pressure uniformity. And finally, finishing shaping through experimental verification. According to the method, the tool design is driven through the simulation process, the split blade welding quality is improved, the research and development period is shortened, the cost is reduced, and the method is suitable for diffusion welding tool design of multi-material combined components.

Description

Technical Field

[0001] This invention relates to the field of diffusion bonding technology, and more particularly to a design method for diffusion welding fixtures for split blades based on multi-material simulation. Background Technology

[0002] In aerospace equipment manufacturing, split blades are core components, and the quality of their diffusion welding directly determines the operational reliability of the equipment. Split blades are typically manufactured using TC4 material, while diffusion welding fixtures require graphite (IG56) as a critical material.

[0003] Current design of diffusion welding fixtures for split blades has significant limitations: on the one hand, due to the significant differences in thermophysical and mechanical properties between blade materials and fixture materials, traditional empirical design is difficult to match the complex temperature and stress field distributions, resulting in excessive welding deformation or insufficient joint strength; on the other hand, the fixture design is disconnected from the simulation process, lacking accurate simulation of multi-material interactions, which leads to long fixture iteration cycles and high manufacturing costs. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a design method for diffusion welding fixtures for split blades based on multi-material simulation. This method aims to solve the problems of poor fixture adaptability and low iteration efficiency caused by the lack of accurate characterization of multi-material properties and simulation-driven design methods in the design of existing diffusion welding fixtures for split blades.

[0005] A design method for diffusion welding fixtures for split blades based on multi-material simulation includes the following steps:

[0006] Step 1: Collect multiple material parameters;

[0007] Specifically, the thermal expansion coefficient, thermal radiation coefficient, absorptivity, thermal conductivity, mass density, specific heat capacity, Young's modulus, and Poisson's ratio of the blade material titanium alloy TC4 and the tooling material graphite IG56 were collected.

[0008] Step 2: For titanium alloy TC4, the strain rate is 1s in different temperature ranges. -1 0.1s -1 0.01s -1 0.001s -1 Under these conditions, isothermal compression tests are conducted to obtain the actual stress-strain curves, and then the strain-stress-strain rate-temperature relationship is derived to construct a hyperbolic sinusoidal constitutive model.

[0009] For graphite IG56, the thermal conductivity, coefficient of thermal expansion, Young's modulus, and Poisson's ratio of graphite IG56 were measured and established as a material property database. Through the material property database, the material property parameters were dynamically correlated with the hyperbolic sine constitutive model, thereby constructing a multi-material finite element analysis model, namely a coupled simulation model of tooling-blade blank.

[0010] The coupled simulation model includes the interaction between two materials, titanium alloy TC4 and graphite IG56, including temperature field, stress field and post-weld deformation. The simulated temperature range is from room temperature to welding temperature, and the pressure range is 2MPa-30MPa.

[0011] The interaction between titanium alloy TC4 and graphite IG56 is mainly achieved through simulation. The entire welding process is input into the software, including heating, holding and pressurizing, and cooling. The hyperbolic sine constitutive model is one of the material properties in the coupled simulation model. It exists in the form of an equation and can reflect the deformation of a material under certain temperature, stress, and time.

[0012] Step 3: Design the initial tooling based on the split blade structure, design the dimensions and assembly method of the graphite tooling, and determine the contact conditions and pressurization path;

[0013] The initial tooling design is based on the structural dimensions and welding surface morphology of the split blades. It includes a positioning component, a pressurizing component, and a heat insulation component. The tooling is made of graphite material, and the contact method between the tooling and the blades, the pressurization path, and the target temperature field distribution are determined.

[0014] Step 4: Based on the coupled simulation model of tooling and blade blank, import multiple material parameters to simulate the temperature field and stress field of the welding process, and optimize the tooling structure until the pressure uniformity error at the welding interface is ≤5%;

[0015] The optimized tooling structure specifically includes adjusting the size and assembly method of the graphite tooling.

[0016] Step 5: Create a tooling prototype and conduct a physical welding test. Compare the stress distribution and deformation of the tooling before and after optimization with the physical welding test to finalize the design.

[0017] Based on the optimized tooling structure, a prototype was made, and a physical welding test was conducted. The deformation of the blades, the interface welding rate, and the joint strength after welding were collected. The stress distribution and deformation of the time were compared with those of the physical welding test before and after tooling optimization. The parameters of the coupled simulation model were corrected, and the tooling design was finally finalized.

[0018] The beneficial effects of adopting the above technical solution are as follows:

[0019] This invention provides a design method for diffusion welding fixtures for split blades based on multi-material simulation. Compared with existing technologies, the advantages of this solution are:

[0020] (1) Improve the compatibility of tooling and blade and welding quality: By accurately collecting the thermophysical and mechanical parameters of multiple materials, a hyperbolic sinusoidal constitutive model and a tooling-blade blank coupled simulation model are constructed to accurately simulate the temperature field, stress field and post-weld deformation under the interaction of multiple materials, so as to avoid the problem of uneven welding stress distribution leading to poor welding quality.

[0021] (2) Shorten tooling iteration cycle and reduce manufacturing cost: Use simulation to drive tooling structure optimization, and realize the design goal of pressure uniformity error ≤5% through simulation verification, reduce the blindness of relying on experience design, and at the same time combine physical test to correct the model, significantly reduce the number of tooling iterations and manufacturing cost.

[0022] (3) Achieve deep linkage between design and simulation: break the limitation of traditional tooling design and simulation being disconnected, establish dynamic correlation between multi-material performance database and simulation model, improve the accuracy and efficiency of tooling design, and provide a reliable method for diffusion welding tooling design of complex multi-material components. Attached Figure Description

[0023] Figure 1 The tooling design flowchart based on simulation is an embodiment of the present invention;

[0024] Figure 2 The embodiment of this invention simulates the overall stress distribution of the workpiece;

[0025] Figure 3 This invention provides a workpiece simulation interface stress distribution.

[0026] Figure 4 Microstructure of the blade weld joint in an embodiment of the present invention. Detailed Implementation

[0027] The specific implementation methods of this application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0028] As a core component of aero-engines, the diffusion welding quality of split blades directly affects the engine's operational performance and safety reliability. This invention proposes a design method for diffusion welding fixtures for split blades based on multi-material simulation. By accurately characterizing the properties of blade and fixture materials and combining simulation analysis, the method achieves efficient and optimized fixture design.

[0029] A design method for diffusion welding fixtures for split blades based on multi-material simulation includes the following steps:

[0030] Step 1: Collect multiple material parameters;

[0031] Specifically, the thermal expansion coefficient, thermal radiation coefficient, absorptivity, thermal conductivity, mass density, specific heat capacity, Young's modulus, and Poisson's ratio of the blade material titanium alloy TC4 and the tooling material graphite IG56 were collected.

[0032] In this embodiment, a laser thermal expansion meter was used to test the thermal expansion coefficient of graphite. The test temperature range was 30-950℃, and the heating rate was controlled at 5℃ / s. The entire test was conducted in a vacuum environment to avoid graphite oxidation affecting the test accuracy. A simultaneous thermal analyzer was used to determine the specific heat capacity and thermal diffusivity of TC4 and graphite, and the thermal conductivity was calculated based on the measurement results. Tensile tests were performed using a universal testing machine to obtain the Young's modulus and Poisson's ratio of the three materials, providing basic data for subsequent model construction.

[0033] Step 2: For titanium alloy TC4, the strain rate is 1s in different temperature ranges. -1 0.1s -1 0.01s -1 0.001s -1 Under these conditions, isothermal compression tests are conducted to obtain the actual stress-strain curves, and then the strain-stress-strain rate-temperature relationship is derived to construct a hyperbolic sinusoidal constitutive model.

[0034] For graphite IG56, the thermal conductivity, Young's modulus, and Poisson's ratio of graphite IG56 are established as a material property database. The thermal expansion coefficient is tested through the material property database. The material property parameters are dynamically correlated with the hyperbolic sine constitutive model, thereby constructing a multi-material finite element analysis model, namely a coupled simulation model of tooling-blade blank.

[0035] The coupled simulation model includes the interaction between two materials, titanium alloy TC4 and graphite IG56, including temperature field, stress field and post-weld deformation. The simulated temperature range is from room temperature to welding temperature, and the pressure range is 2MPa-30MPa.

[0036] In this embodiment, isothermal compression tests were conducted on the TC4 titanium alloy blade material using a thermal simulation testing machine. The test specimen was a φ8mm×12mm TC4 cylindrical specimen, and the tests were performed in temperature ranges of 800℃-930℃ and 1075℃-1225℃ for 1 second. -1 0.1s -1 0.01s -1 0.001s -1Under strain rate conditions, isothermal compression tests were conducted to obtain the true stress-strain curves, and then the strain-stress-strain rate-temperature relationship was derived. Based on the Arrhenius constitutive model, the collected data were fitted to derive the hyperbolic sine constitutive equation, which is used to describe the mechanical behavior of the material at different temperatures.

[0037] For tooling materials, the thermal expansion coefficient of graphite IG56 from room temperature to 940℃ needs to be tested. The thermal conductivity, Young's modulus, and Poisson's ratio of graphite IG56 need to be collected to establish a material property database. Based on this data, a multi-material finite element analysis model is then constructed to ensure the dynamic correlation between material performance parameters and temperature and pressure conditions. The interaction between titanium alloy TC4 and graphite IG56 is mainly achieved through simulation. The entire process of welding is input into the software, including heating, heat preservation and pressurization, and cooling. The hyperbolic sine constitutive model is one of the material properties in the coupled simulation model. It exists in the form of an equation that reflects the deformation of a material at a certain temperature and under a certain stress for a certain period of time.

[0038] Step 3: Design the initial tooling based on the split blade structure, design the dimensions and assembly method of the graphite tooling, and determine the contact conditions and pressurization path;

[0039] The initial tooling design is specifically based on the structural dimensions and welding surface morphology of the split blades. It includes a positioning component, a pressurizing component, and a heat insulation component. The tooling is made of graphite material, and the high temperature resistance of graphite is used to ensure structural stability. The contact method between the tooling and the blades, the pressurization path, and the temperature field distribution target are determined.

[0040] In this embodiment, initial tooling design was performed. Based on the specific structural parameters of the split blade and the 3D model of the split blade, the tolerance of the tooling positioning groove was designed to be ±0.02mm. An assembly model of the tooling and blade was established using ABAQUS software. The contact property of TC4 was set to thermal conduction, and the contact coefficient between the blade and the graphite tooling was set to 0.5. Simulation loading followed the actual welding process: first, the temperature was raised to 850℃ and held for 30 minutes, then pressurized to 10MPa, followed by a temperature increase to 940℃ and a holding time of 60 minutes, and finally depressurized and cooled. During the simulation, the pressure distribution at the welding interface and the maximum deformation of the tooling were analyzed to provide a basis for tooling optimization.

[0041] Step 4: Based on the coupled simulation model of tooling and blade blank, import multiple material parameters to simulate the temperature field and stress field of the welding process, and optimize the tooling structure until the pressure uniformity error at the welding interface is ≤5%;

[0042] The optimized tooling structure specifically includes adjusting the size and assembly method of the graphite tooling.

[0043] In this embodiment, the tooling is optimized and verified step by step based on the simulation results. If the simulation shows that the pressure at the blade edge is more than 5% lower than that at the center, the thickness of the graphite positioning block needs to be increased by 2mm, and the chamfer radius needs to be adjusted to R3mm. Then, the simulation is repeated until the pressure uniformity meets the standard.

[0044] Step 5: Create a tooling prototype and conduct a physical welding test. Compare the stress distribution and deformation of the tooling before and after optimization with the physical welding test to finalize the design.

[0045] Based on the optimized tooling structure, a prototype was made, and a physical welding test was conducted. The deformation of the blades, the interface welding rate, and the joint strength after welding were collected. The stress distribution and deformation of the time were compared with those of the physical welding test before and after tooling optimization. The parameters of the coupled simulation model were corrected, and the tooling design was finally finalized.

[0046] In this embodiment, a prototype was fabricated according to the optimized tooling design, and welding tests were conducted using a vacuum diffusion welding furnace. After welding, the blade deformation was measured using a coordinate measuring machine to ensure that the deformation was ≤0.1mm / m. Simultaneously, tensile tests were performed on samples to verify the joint strength; the joint strength was ≥80% of the base material strength, ensuring the rationality and reliability of the tooling design.

[0047] Figure 1 The diagram illustrates the technical process of this invention. This method constructs a multi-physics performance model of the TC4 blade material and the graphite tooling material to accurately capture the material behavior under different temperature and pressure conditions. By using tooling-blade coupled simulation, the temperature and stress field distribution during the welding process is simulated, and structural parameters such as the stiffness of the positioning components and the thickness of the insulation layer of the graphite tooling are optimized to ensure the uniformity of the welding interface pressure. Combined with physical test verification and model correction, a complete tooling design process is formed.

[0048] This simulation-driven design approach fully leverages the high-temperature resistance and chemical stability of graphite tooling to achieve precise clamping and improved welding quality of split blades. At the same time, it shortens the tooling development cycle and reduces manufacturing costs, providing strong support for high-quality and high-efficiency diffusion welding of split blades.

[0049] Figure 2 , Figure 3 The figure shows the stress distribution of the tooling and interface during the actual simulation process. It can be seen that the stress distribution of the tooling before adjustment is mainly concentrated on one side of the blade clamping end, resulting in insufficient pressure at the intermediate assembly position. This can easily lead to uneven welding quality, defects such as holes and incomplete welding, and a decrease in joint performance. Figure 4The image shows the actual welded joint microstructure of the TC4 blade under the adjusted tooling application. It can be seen that the joint has a typical two-phase microstructure of titanium alloy and there is no obvious weld line, indicating that a good metallurgical bond has been achieved, the microstructure is uniform, and the base material has not suffered significant thermal damage.

[0050] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a computer program product.

[0051] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0052] The scope of protection of this application is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from the scope and spirit of this disclosure. If such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, then the intent of this disclosure also includes such modifications and variations.

Claims

1. A split vane diffusion welding tooling design method based on multi-material simulation simulation, characterized in that, The method comprises the following steps: Step 1: collecting multi-material parameters; Specifically, the thermal expansion coefficient, thermal radiation coefficient, absorption rate, thermal conductivity, mass density, specific heat capacity, Young's modulus, and Poisson's ratio of the blade material titanium alloy TC4 and the tooling material graphite IG56 are collected; Step 2: isothermal compression test is carried out on titanium alloy TC4 at different temperature ranges and strain rates of 1s -1 , 0.1s -1 , 0.01s -1 , 0.001s -1 , respectively, to obtain the true stress-strain curve, and then derive the strain-stress-strain rate-temperature relationship, thereby constructing the hyperbolic sine constitutive model; For graphite IG56, the thermal conductivity, thermal expansion coefficient, Young's modulus, and Poisson's ratio of graphite IG56 are measured respectively, a material property database is established, and the material property parameters are dynamically associated with the hyperbolic sine constitutive model through the material property database, so as to construct a multi-material finite element analysis model, i.e., a coupling simulation model of the tooling-blade blank; Step 3: designing an initial tooling according to the split blade structure, designing the size and assembly method of the graphite tooling, and determining the contact condition and pressurization path; Step 4: based on the tooling-blade blank coupling simulation model, importing the multi-material parameters to simulate the temperature field and stress field during the welding process, optimizing the tooling structure, and until the uniformity error of the welding interface pressure is ≤5%; Step 5: manufacturing a tooling prototype and performing a physical welding test, comparing the time stress distribution and deformation before and after the optimization of the tooling, and completing the final design.

2. The split vane diffusion welding tooling design method based on multi-material simulation emulation of claim 1, wherein, The coupling simulation model includes the interaction of titanium alloy TC4 and graphite IG56, including temperature field, stress field, and post-weld deformation, simulating a temperature range of room temperature to welding temperature and a pressure range of 2MPa-30MPa.

3. The split vane diffusion welding tooling design method based on multi-material simulation emulation of claim 2, wherein, The interaction of the titanium alloy TC4 and the graphite IG56 is simulated by inputting the entire process during the welding process into the software, including heating, holding and pressurizing, and cooling.

4. The split vane diffusion welding tooling design method based on multi-material simulation emulation of claim 1, wherein, The initial tooling designed in step 3 is specifically designed according to the structure size and welding surface shape of the split blade, and includes a positioning assembly, a pressurizing assembly, and a heat preservation assembly, which are made of graphite material, and the contact mode, pressurization path, and temperature field distribution target of the tooling and the blade are determined.

5. The split vane diffusion welding tooling design method based on multi-material simulation emulation of claim 1, wherein, The optimization of the tooling structure in step 4 specifically includes adjusting the size and assembly method of the graphite tooling.

6. The split vane diffusion welding tooling design method based on multi-material simulation emulation of claim 1, wherein, Step 5 specifically manufactures a prototype according to the optimized tooling structure and performs a physical welding test.

7. The split vane diffusion welding tooling design method based on multi-material simulation emulation of claim 6, wherein, The physical welding test specifically collects the deformation amount of the welded blade, the interface welding rate, and the joint strength, compares the time stress distribution and deformation before and after the optimization of the tooling, corrects the parameters of the coupling simulation model, and finally completes the final design of the tooling.

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