An efficient forming process suitable for crack-free densification of additive manufacturing of difficult-to-weld nickel-based superalloys

Abstract

The present application relates to a kind of efficient forming process suitable for the dense crack-free additive manufacturing of difficult-to-weld nickel-based superalloy, belongs to the technical field of metal additive manufacturing.The process simulates and determines the effective interval of laser power and scanning speed of difficult-to-weld nickel-based superalloy shaping laser additive manufacturing process through shaping laser molten pool flow-heat coupling model, then optimizes the parameters of laser power and scanning speed using response surface method, obtains the optimal process parameter combination and performs shaping laser forming, and obtains high-density and crack-free difficult-to-weld nickel-based superalloy parts.The present application solves the problems of easy cracking, many pores and low efficiency of process optimization of difficult-to-weld nickel-based superalloy through the cooperation of shaping laser and efficient parameter optimization, can stably prepare parts with density of more than 99%, no cracks, shorten the optimization cycle, reduce the cost, meet the stringent requirements of high-end equipment, and the technology is advanced and has significant application value.

Description

Technical Field

[0001] This invention relates to the field of metal additive manufacturing technology, and more specifically to a high-efficiency forming process suitable for dense, crack-free additive manufacturing of difficult-to-weld nickel-based high-temperature alloys. Background Technology

[0002] Difficult-to-weld nickel-based superalloys possess excellent high-temperature strength, creep resistance, oxidation resistance, and hot corrosion resistance, making them key structural materials for precision hot-end components such as aero-engine casings and turbine blades. Traditional forming methods such as casting, forging, and milling are complex processes with material utilization rates of only about 20%, making them unsuitable for the rapid iteration of aero-engine equipment manufacturing demands towards low cost, complexity, lightweight, and high performance. Laser powder bed melting (LPBF) additive manufacturing, with its advantages of short-process and high-efficiency forming of complex structural parts, has become a strategic frontier key technology for the integrated forming of complex precision nickel-based superalloy components for aero-engines, and has achieved initial applications in the manufacturing of components such as aero-engine fuel nozzles and 5th / 6th stage blades. However, existing LPBF equipment generally uses Gaussian lasers, whose non-uniform energy distribution (high at the center and low at the edges) easily leads to large thermal gradients and poor stability in the molten pool, inducing metallurgical defects such as cracks and voids, and easily forming large-angle grain boundary structures with weak high-temperature performance, posing a significant technical challenge to the high-quality additive manufacturing of difficult-to-weld nickel-based superalloys.

[0003] In LPBF additive manufacturing systems, molten pool characteristics are the core unit that induces metallurgical defects and determines microstructure and service performance. By precisely controlling the molten pool morphology, size, temperature gradient, and solidification characteristics, defects such as porosity and cracks can be effectively suppressed, and microstructures that meet high-temperature service requirements can be obtained. Meanwhile, process parameter optimization is equally crucial for improving the forming quality of additive manufacturing. However, traditional parameter optimization heavily relies on trial and error, requiring numerous repetitive orthogonal experiments to find the optimal combination, resulting in long optimization cycles, large sample consumption, and high R&D costs. Existing optimization methods such as numerical simulation and machine learning mostly employ single technical paths, failing to form an efficient collaborative mechanism of "forming technology—numerical initial selection—experimental optimization," thus failing to fully leverage the synergistic effect of heat source improvement and parameter optimization, and making it difficult to achieve efficient and stable forming of dense, crack-free components from difficult-to-weld nickel-based superalloys. Therefore, promoting the synergistic application of forming laser forming technology and efficient process parameter optimization methods to overcome the industry pain points of numerous defects, slow optimization, and high costs in additive manufacturing of difficult-to-weld nickel-based superalloys has significant engineering application value and practical significance. Summary of the Invention

[0004] Therefore, it is necessary to provide an efficient forming process suitable for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloy parts, addressing the technical challenges of easy cracking and long parameter optimization cycles in traditional Gaussian laser forming processes.

[0005] A highly efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys, characterized in that the process includes the following steps: S1. Using a laser-molten pool flow-thermal coupling model, the effective range of values ​​for the laser additive manufacturing process parameters for shaping difficult-to-weld nickel-based superalloys is simulated and determined. The process parameters include laser power and scanning speed. S2. Based on the effective range of process parameters determined in step S1, the response surface methodology is used to optimize the parameters and obtain the optimal combination of process parameters. S3. Perform shaping laser forming based on the optimal combination of process parameters obtained in step S2 to obtain highly dense and crack-free difficult-to-weld nickel-based high-temperature alloy parts.

[0006] In one embodiment, the specific steps of step S1 are as follows: S11. Based on the finite volume method, the energy distribution equation of the shaping laser is used as the boundary condition of the heat source. Combined with the mass conservation equation, momentum conservation equation and energy conservation equation, a molten pool flow-heat coupling model covering the entire process of shaping laser energy input, powder melting, molten pool flow and solidification heat transfer is established. S12. Input the thermophysical parameters of the difficult-to-weld nickel-based superalloy, and set the initial simulation range of laser power and scanning speed; S13. Run the model to obtain the temperature field and flow field distribution of the molten pool under different parameters, eliminate parameter combinations that produce non-fusion defects or keyhole effects, and screen out the effective value range of process parameters with stable molten pool morphology.

[0007] In one embodiment, the shaping laser in step S11 is a ring-shaped spot, which is obtained by shaping the incident Gaussian laser using a diffraction optical correction element.

[0008] In one embodiment, the energy distribution of the annular light spot satisfies the following equation:

[0009] Where r1 is the outer diameter of the ring laser, r2 is the inner diameter of the ring laser, x is the distance between the point and the center of the laser spot, m and n are correction coefficients, and P is the laser power.

[0010] In one embodiment, the beam quality M of the incident Gaussian laser 2 ≤1.1, beam diameter d0≤70μm, the beam quality M of the annular spot obtained after shaping by the diffraction optical correction element. 2 ≤2.8, the inner diameter d1 of the annular light spot is ≤76μm, and the outer diameter d2 of the annular light spot is ≤96μm.

[0011] In one embodiment, the specific steps of step S2 are as follows: S21. Using the effective value range of laser power and scanning speed obtained in step S1 as design variables, construct an experimental scheme using a central composite design, and generate randomized experimental parameter combinations using Design-Expert software; S22. According to the generated combination of experimental parameters, conduct a shaping laser forming experiment, detect the actual density of each sample, and calculate the corresponding relative density; S23. Using relative compactness as the corresponding response value, the experimental data were fitted with a quadratic polynomial using Design-Expert software to establish a response surface model between the response value and the design variable. S24. The optimal combination of process parameters can be obtained by intuitively solving the problem using 3D response surface plots.

[0012] In one embodiment, step S21 employs a central composite design to construct a 2-factor, 5-level experimental scheme, including the following experimental points: Four factor points, corresponding to combinations of laser power and scanning speed within ±1 levels; Four axial points correspond to combinations where one factor is at a level of ±1.414 and another factor is at a level of 0. Five center points were used for repeated experiments, with both laser power and scanning speed set to 0.

[0013] In one embodiment, step S22, which involves performing a shaping laser forming experiment according to the generated combination of experimental parameters, further includes setting fixed process auxiliary parameters, including layer thickness, scanning spacing, scanning mode, and interlayer rotation angle.

[0014] In one embodiment, the thermophysical parameters of the difficult-to-weld nickel-based superalloy in step S12 include latent heat of fusion, solid-liquid phase temperature, thermal conductivity, and specific heat capacity.

[0015] In one embodiment, in step S3, shaping laser additive manufacturing is performed according to the optimal process parameter combination obtained in step S2, and the resulting difficult-to-weld nickel-based high-temperature alloy part has a relative density greater than 99%, and no crack defects are observed in the microstructure.

[0016] The beneficial effects of this invention are as follows: The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys claimed in this invention, through the deep synergy of shaping laser forming technology and efficient process parameter optimization methods, constructs an integrated technical system of "heat source innovation - numerical simulation preliminary selection - response surface methodology optimization". This fundamentally solves the industry problem of easy cracking, incomplete fusion porosity and keyhole defects in difficult-to-weld nickel-based superalloys during the traditional Gaussian laser powder bed melting forming process. At the same time, it completely changes the inefficient mode of traditional process parameter optimization that relies on a lot of trial and error, has a long cycle, high cost, and huge sample consumption.

[0017] This process relies on laser forming technology, employing diffractive optical correction elements to reconstruct the incident Gaussian laser into a ring-shaped spot with weakened central energy and uniform distribution in the annular region. This alters the heat distribution and flow characteristics of the molten pool from the heat source input level, significantly reducing the molten pool temperature gradient and solidification thermal stress, providing a hardware foundation for suppressing hot cracks and reducing metallurgical defects. The efficient process parameter optimization method uses molten pool flow-thermal coupling numerical simulation as a preliminary screening tool. Based on the finite volume method and the three conservation equations of mass, momentum, and energy, a multiphysics model is established. The accurate energy distribution equation of the ring-shaped spot is used as the heat source boundary condition, realistically reproducing the entire process of laser energy input, powder melting, molten pool flow, and solidification heat transfer. Ineffective parameter combinations that easily lead to incomplete fusion defects or keyhole effects are quickly eliminated, clarifying the stable and effective range of laser power and scanning speed, avoiding numerous blind experiments. Furthermore, a response surface methodology based on central composite design is used for small-sample experimental optimization. Only 13 sets of experiments are needed to complete the quadratic polynomial fitting and optimal parameter solution, achieving efficient integration of numerical simulation and experimental optimization.

[0018] The synergistic effect of the two methods described above can shorten the process parameter optimization cycle by more than 30% and reduce the number of sample prints by 50%, significantly improving parameter optimization efficiency and reducing R&D costs. Shaping laser forming technology provides a low-defect, high-stability forming foundation for parameter optimization, while the efficient parameter optimization method maximizes the technological advantages of shaping lasers, precisely matching the process conditions that best utilize the uniform heating characteristics of the annular laser spot. The two methods support each other and work synergistically, ultimately enabling the stable fabrication of difficult-to-weld nickel-based superalloy parts with a relative density greater than 99% and free from macroscopic and microscopic cracks. The formed parts have a uniform internal structure and very few defects, fully meeting the stringent requirements of high-temperature service performance, high density, and crack-free quality for hot-end components in high-end equipment such as aero-engines. This synergistic solution overcomes the technical limitations of single heat source improvement or single parameter optimization, enabling truly high-quality, high-efficiency, and low-cost integrated forming of difficult-to-weld nickel-based superalloy additive manufacturing, demonstrating significant technological advancement and broad engineering application value. Attached Figure Description

[0019] Figure 1A flowchart of a high-efficiency forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys; Figure 2 Figures showing the simulation results of molten pool flow-thermal coupling under different energy densities; Figure 3 This is a 3D response surface plot showing the effect of laser power and scanning speed on the relative density of the formed part. Figure 4 The image shows the metallographic structure of the formed sample under optimal process parameters. Detailed Implementation

[0020] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0022] The following describes, with reference to the accompanying drawings, an efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based high-temperature alloys, according to some embodiments of the present invention.

[0023] like Figures 1 to 4 As shown, this application discloses a highly efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys, characterized in that the process includes the following steps: S1. Using a laser-molten pool flow-thermal coupling model, the effective range of values ​​for the laser additive manufacturing process parameters for shaping difficult-to-weld nickel-based superalloys is simulated and determined. The process parameters include laser power and scanning speed. S2. Based on the effective range of process parameters determined in step S1, the response surface methodology is used to optimize the parameters and obtain the optimal combination of process parameters. S3. Perform shaping laser forming based on the optimal combination of process parameters obtained in step S2 to obtain highly dense and crack-free difficult-to-weld nickel-based high-temperature alloy parts.

[0024] The above process uses laser-induced melt pool flow-thermal coupling simulation to quickly screen effective process ranges, and then combines response surface methodology to accurately optimize parameters. This achieves effective suppression of cracks, lack of fusion, and keyhole defects in the additive manufacturing of difficult-to-weld nickel-based high-temperature alloys, significantly improving process optimization efficiency, reducing trial-and-error costs, and ultimately enabling the stable production of high-density, crack-free parts that meet the stringent requirements of high-end equipment.

[0025] In addition to the features of the above embodiments, this embodiment further defines the specific steps of step S1 as follows: S11. Based on the finite volume method, the energy distribution equation of the shaping laser is used as the boundary condition of the heat source. Combined with the mass conservation equation, momentum conservation equation and energy conservation equation, a molten pool flow-heat coupling model covering the entire process of shaping laser energy input, powder melting, molten pool flow and solidification heat transfer is established. S12. Input the thermophysical parameters of the difficult-to-weld nickel-based superalloy, and set the initial simulation range of laser power and scanning speed; S13. Run the model to obtain the temperature field and flow field distribution of the molten pool under different parameters, eliminate parameter combinations that produce non-fusion defects or keyhole effects, and screen out the effective value range of process parameters with stable molten pool morphology.

[0026] In step S11 of this embodiment, the molten pool flow-thermal coupling model is a multi-physics numerical model based on the finite volume method, which covers the entire process of shaping laser energy input, powder melting, molten pool flow and solidification heat transfer. Its three governing equations of mass conservation, momentum conservation and energy conservation are the core theoretical basis of the model.

[0027] The mass conservation equation is as follows:

[0028] in, The density of the fluid within the molten pool. For time, The velocity of the fluid within the molten pool.

[0029] The mass conservation equation is used to describe the mass conservation law of fluid in the molten pool, constrain the continuity of mass during the flow of the molten pool, and ensure that the mass of the molten metal in the molten pool does not appear out of thin air or disappear during the melting, flow and solidification process, thus providing a basic constraint for the numerical solution of the flow field of the molten pool.

[0030] The momentum conservation equation (Navier-Stokes equation) is as follows:

[0031] in, The density of the fluid within the molten pool. For time, The velocity of the fluid within the molten pool. The dynamic viscosity of the fluid within the molten pool. For fluid pressure, This is the momentum source term.

[0032] The momentum conservation equation is used to describe the momentum change law of the fluid in the molten pool. It comprehensively considers the effects of the source term Sm, such as the viscous force of the melt, the pressure gradient, the surface tension gradient of the molten pool, and buoyancy. It accurately solves the flow velocity field of the melt in the molten pool, reveals the flow morphology, convection intensity and mass transfer law of the molten pool under the action of shaping laser, and provides a flow field basis for analyzing the formation mechanism of defects in the molten pool.

[0033] The energy conservation equation is as follows:

[0034] in, The density of the fluid within the molten pool. This represents the enthalpy of the fluid within the molten pool. For time, The velocity of the fluid within the molten pool. The thermal conductivity of the fluid within the molten pool. The temperature of the fluid inside the molten pool. This is an energy source term.

[0035] The energy conservation equation is used to describe the energy transfer and conservation laws within the molten pool. It couples the shaping laser energy input source term Se, melt convection heat transfer, heat conduction, and latent heat of melting to accurately solve the temperature field evolution law of the molten pool, clarify the melting range, temperature gradient, and cooling rate of the molten pool, and provide a temperature field basis for analyzing powder melting, molten pool solidification, and defect formation.

[0036] The aforementioned mass, momentum, and energy conservation equations work together to form a complete theoretical system for molten pool flow-thermal coupling simulation, enabling accurate characterization of the multiphysics field of the molten pool under the action of shaping lasers, and providing reliable simulation data support for process parameter optimization.

[0037] In step S12 of this embodiment, the thermophysical parameters of the difficult-to-weld nickel-based superalloy need to be input, including latent heat of fusion, solid-liquid line temperature, thermal conductivity, and specific heat capacity, to support the numerical solution of the molten pool flow-thermal coupling model. Specifically, the difficult-to-weld nickel-based superalloy selected in this embodiment is IN738LC, which is prepared using vacuum induction gas atomization technology to obtain alloy powder with a particle size distribution of 15–53 μm. Its chemical composition (mass fraction) is shown in Table 1. Table 1. Composition of IN738LC Alloy (Wt.%)

[0038] Numerical simulations were conducted based on the flow-thermal coupling model of the shaped laser molten pool constructed in step S11. The thermophysical parameters of the IN738LC alloy were input, including a latent heat of fusion of 279757 J / kg and solidus / liquidus temperatures ranging from 1506 K to 1587 K. The thermal conductivity and specific heat capacity at different temperatures are shown in Table 2. Table 2 Thermal conductivity and specific heat capacity of IN738LC alloy at different temperatures

[0039] Meanwhile, the initial simulation range for the laser process parameters was set: laser power P from 100W to 500W, and scanning speed V from 200mm / s to 2000mm / s. After running the model, the temperature field and flow field distribution of the molten pool under different combinations of process parameters can be obtained, as shown in the specific distribution pattern. Figure 2 As shown.

[0040] Analysis of the simulation results shows that when the energy density (Ev) ≤ 52.1 J / mm² 3 When the energy input to the molten pool is insufficient, unfused pores and unmelted powder particles appear in the molten channel; when the energy density (Ev) ≥ 416.7 J / mm 3 When the energy input is too high, the molten pool transforms into a typical keyhole pattern, with the center of the molten pool significantly concave downwards, forming a deep cavity-like keyhole structure, which easily leads to defects such as keyhole-type porosity. Based on the above defect formation rules, invalid parameter combinations that easily produce incomplete fusion and keyhole defects are eliminated, and the preliminary effective process window for laser additive manufacturing of IN738LC high-temperature alloy shaping is determined as follows: laser power P is 150–400W, and scanning speed V is 400–1200mm / s.

[0041] In addition to the features of the above embodiments, this embodiment further specifies that the shaping laser in step S11 is an annular spot, which is obtained by shaping the incident Gaussian laser through a diffraction optical correction element.

[0042] In addition to the features of the above embodiments, this embodiment further defines the beam quality M of the incident Gaussian laser. 2 ≤1.1, beam diameter d0≤70μm, the beam quality M of the annular spot obtained after shaping by a diffraction optical corrector is... 2 ≤2.8, the inner diameter of the annular spot d1≤76μm, and the outer diameter of the annular spot d2≤96μm.

[0043] In this embodiment, a self-developed shaping laser Dimetal280 equipment, modified from the commercial Dimetal280 laser selective melting equipment, is used for forming. The effective dimensions of the forming cavity are 250mm × 250mm × 300mm. The core modification of this equipment is the integration of a built-in diffraction optical correction element (DOE), which can reconstruct the incident Gaussian laser into a ring-shaped spot with weakened central energy and uniform distribution in the annular region. This enables precise control of the laser energy distribution and provides stable and reliable shaping light source conditions for molten pool flow-thermal coupling numerical simulation and subsequent process optimization.

[0044] The equipment is equipped with an incident Gaussian laser beam quality of M²≤1.1 and a beam diameter of d0≤70μm, giving the original laser excellent energy stability and beam directivity, providing a high-quality base light source for subsequent laser shaping. After DOE shaping, the annular spot has a beam quality of M²≤2.8, an inner diameter of d1≤76μm, and an outer diameter of d2≤96μm. This range of parameters significantly reduces the molten pool temperature gradient and solidification thermal stress, effectively suppressing hot cracks, incomplete fusion, and keyhole defects at the heat source level. Simultaneously, it can accurately match the heat source boundary input conditions of the molten pool flow-thermal coupling numerical simulation, improving simulation accuracy and the reliability of process parameter selection. This makes the additive manufacturing process of difficult-to-weld nickel-based superalloys more stable, resulting in higher density of the formed parts, ultimately achieving crack-free, high-density, and highly efficient forming.

[0045] In addition to the features of the above embodiments, this embodiment further defines the energy distribution of the annular light spot as satisfying the following equation:

[0046] Where r1 is the outer diameter of the ring laser, r2 is the inner diameter of the ring laser, x is the distance between the point and the center of the laser spot, m and n are correction coefficients, and P is the laser power.

[0047] The above-mentioned annular spot energy distribution equation is the core input boundary condition for constructing the molten pool flow-thermal coupling model. It accurately quantifies the spatial energy input characteristics of the shaping laser acting on the powder bed, provides a heat source loading basis that conforms to the actual working conditions for the molten pool flow-thermal coupling model, and ensures that the heat source input of the numerical simulation is highly consistent with the actual shaping laser forming process.

[0048] In addition to the features of the above embodiments, this embodiment further defines the specific steps of step S2 as follows: S21. Using the effective value range of laser power and scanning speed obtained in step S1 as design variables, construct an experimental scheme using a central composite design, and generate randomized experimental parameter combinations using Design-Expert software; S22. According to the generated combination of experimental parameters, conduct a shaping laser forming experiment, detect the actual density of each sample, and calculate the corresponding relative density; S23. Using relative compactness as the corresponding response value, the experimental data were fitted with a quadratic polynomial using Design-Expert software to establish a response surface model between the response value and the design variable. S24. The optimal combination of process parameters can be obtained by intuitively solving the problem using 3D response surface plots.

[0049] The response surface methodology optimization process, employing steps S21 to S24, uses the effective parameter range selected through numerical simulation in step S1 as the design variable. Combined with central composite design and Design-Expert software for experimental planning and data analysis, this significantly reduces the number of experiments and sample consumption, avoids the blindness of traditional trial-and-error methods, and substantially shortens the process parameter optimization cycle. By using relative density as the response index for quadratic polynomial fitting and establishing a response surface model, the influence of laser power and scanning speed on forming quality can be accurately revealed. The optimal combination of process parameters can be intuitively and quickly located using 3D response surface plots, improving the accuracy and efficiency of parameter optimization. This ensures that the final process parameters better match the forming characteristics of difficult-to-weld nickel-based superalloys, providing stable and reliable parameter guarantees for the preparation of high-density, crack-free additive manufacturing parts.

[0050] In addition to the features of the above embodiments, this embodiment further specifies that the experimental scheme constructed in step S21 using a central composite design with 2 factors and 5 levels includes the following experimental points: Four factor points, corresponding to combinations of laser power and scanning speed within ±1 levels; Four axial points correspond to combinations where one factor is at a level of ±1.414 and another factor is at a level of 0. Five center points were used for repeated experiments, with both laser power and scanning speed set to 0.

[0051] In addition to the features of the above embodiments, this embodiment further defines step S22, which involves performing a shaping laser forming experiment according to the generated experimental parameter combination, as including setting fixed process auxiliary parameters, such as layer thickness, scanning spacing, scanning mode, and interlayer rotation angle.

[0052] Specifically, based on the effective process parameter range determined in step S1 (laser power P of 150–400W, scanning speed V of 400–1200mm / s), laser power P and scanning speed V are used as design variables, denoted as X1 and X2 respectively. A two-factor experimental design is carried out using the central composite design (CCD) method. Each factor has 5 levels, with coded values ​​of 0, ±1, and ±1.414 respectively, resulting in a total of 13 experimental points. The specific settings are as follows: Factor points (4 groups): X1 and X2 are both coded ±1 level combinations, corresponding to the actual process parameters (150W, 400mm / s), (150W, 1200mm / s), (400W, 400mm / s), (400W, 1200mm / s). Axial points (4 groups): a single factor is coded at ±1.414 level, and another factor is coded at 0 level, corresponding to actual process parameters (98W, 800mm / s), (450W, 800mm / s), (275W, 230mm / s), (275W, 1360mm / s); Center point (5 groups): X1=275W, X2=800mm / s. Repeat the experiment 5 times to estimate the random error of the experiment and improve the reliability of the data and the accuracy of the model fitting.

[0053] After the test points were constructed, the Dimetal280 shaping laser equipment, independently developed in the above embodiments, was used to print 8mm×8mm×6mm cube samples according to the process parameters corresponding to the 13 sets of test points. Three parallel samples were printed for each set of process parameters to reduce random errors and ensure the stability and repeatability of the test data. During the experiment, other auxiliary process parameters needed to be kept constant, specifically: a printing layer thickness of 30μm, a scanning interval of 80μm, a bidirectional scanning strategy, and an interlayer rotation angle of 67°. Throughout the printing process, high-purity argon gas was continuously injected into the forming cavity, and the oxygen content was strictly controlled to 0.00ppm to prevent oxidation of the sample during high-temperature forming. After the sample was printed, it was separated from the substrate by wire cutting, ultrasonically cleaned with anhydrous ethanol for 5 minutes, and then dried at 60℃ for 30 minutes to thoroughly remove residual powder and moisture from the sample surface. After drying, the sample was ground and polished to eliminate surface defects, and the actual density of the sample was tested according to GB / T3850-2015 standard. The relative density is calculated using the following formula:

[0054] Among them, the theoretical density of IN738LC alloy =8.05g / cm³.

[0055] Based on the relative density data of 13 sets of samples obtained through detection and calculation, and using relative density as the response value, the experimental data were fitted with a quadratic polynomial using Design-Expert software to establish a response surface model between the response value and the design variable. The fitted response equation is as follows:

[0056] The 3D response surface diagram drawn based on the above response surface model is as follows: Figure 3 As shown, the optimal combination of process parameters can be intuitively obtained from the response surface: P=280W, V=680mm / s. Under these parameters, the predicted relative compactness can reach 99.95%.

[0057] In addition to the features of the above embodiments, this embodiment further specifies that in step S3, the forming laser additive manufacturing is performed according to the optimal process parameter combination obtained in step S2, and the resulting difficult-to-weld nickel-based high-temperature alloy part has a relative density greater than 99%, and no crack defects are observed in the microstructure.

[0058] This embodiment utilizes the optimal combination of process parameters obtained in step S2, along with auxiliary process parameters of 30 μm layer thickness, 80 μm scanning spacing, bidirectional scanning, and 67° interlayer rotation angle, to perform shaping laser additive manufacturing. The formed cube sample is then ground and polished before density testing, yielding an actual relative density of 99.94%. Simultaneously, crack detection is performed on the formed sample according to GB / T15749-2008 "Quantitative Metallographic Determination Methods," and metallographic images are observed and acquired under a light microscope at 50x magnification. The results are as follows: Figure 4 As shown in the figure. Observations show that no macroscopic or microscopic cracks were found inside the sample, the number of internal pores was extremely small, and the microstructure was uniform and dense. High-density, crack-free, and high-efficiency additive manufacturing of difficult-to-weld nickel-based superalloys was successfully achieved.

[0059] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0060] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A highly efficient forming process suitable for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys, characterized in that, The process includes the following steps: S1. Using a laser-molten pool flow-thermal coupling model, the effective range of values ​​for the laser additive manufacturing process parameters for shaping difficult-to-weld nickel-based superalloys is simulated and determined. The process parameters include laser power and scanning speed. S2. Based on the effective range of process parameters determined in step S1, the response surface methodology is used to optimize the parameters and obtain the optimal combination of process parameters. S3. Perform shaping laser forming based on the optimal combination of process parameters obtained in step S2 to obtain highly dense and crack-free difficult-to-weld nickel-based high-temperature alloy parts.

2. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 1, characterized in that, The specific steps of step S1 are as follows: S11. Based on the finite volume method, the energy distribution equation of the shaping laser is used as the boundary condition of the heat source. Combined with the mass conservation equation, momentum conservation equation and energy conservation equation, a molten pool flow-heat coupling model covering the entire process of shaping laser energy input, powder melting, molten pool flow and solidification heat transfer is established. S12. Input the thermophysical parameters of the difficult-to-weld nickel-based superalloy, and set the initial simulation range of laser power and scanning speed; S13. Run the model to obtain the temperature field and flow field distribution of the molten pool under different parameters, eliminate parameter combinations that produce non-fusion defects or keyhole effects, and screen out the effective value range of process parameters with stable molten pool morphology.

3. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 2, characterized in that, The shaping laser in step S11 is a ring-shaped spot, which is obtained by shaping the incident Gaussian laser using a diffraction optical correction element.

4. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 3, characterized in that, The energy distribution of the annular light spot shown satisfies the following equation: Where r1 is the outer diameter of the ring laser, r2 is the inner diameter of the ring laser, x is the distance between the point and the center of the laser spot, m and n are correction coefficients, and P is the laser power.

5. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 4, characterized in that, The beam quality M of the incident Gaussian laser 2 ≤1.1, beam diameter d0≤70μm, the beam quality M of the annular spot obtained after shaping by the diffraction optical correction element. 2 ≤2.8, the inner diameter d1 of the annular light spot is ≤76μm, and the outer diameter d2 of the annular light spot is ≤96μm.

6. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 1, characterized in that, The specific steps of step S2 are as follows: S21. Using the effective value range of laser power and scanning speed obtained in step S1 as design variables, construct an experimental scheme using a central composite design, and generate randomized experimental parameter combinations using Design-Expert software; S22. According to the generated combination of experimental parameters, conduct a shaping laser forming experiment, detect the actual density of each sample, and calculate the corresponding relative density; S23. Using relative compactness as the corresponding response value, the experimental data were fitted with a quadratic polynomial using Design-Expert software to establish a response surface model between the response value and the design variable. S24. The optimal combination of process parameters can be obtained by intuitively solving the problem using 3D response surface plots.

7. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 6, characterized in that, In step S21, a central composite design is used to construct a 2-factor, 5-level experimental scheme, which includes the following experimental points: Four factor points, corresponding to combinations of laser power and scanning speed within ±1 levels; Four axial points correspond to combinations where one factor is at a level of ±1.414 and another factor is at a level of 0. Five center points were used for repeated experiments, with both laser power and scanning speed set to 0.

8. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 6, characterized in that, Step S22, which involves conducting a shaping laser forming experiment according to the generated experimental parameter combination, also includes setting fixed process auxiliary parameters, including layer thickness, scanning spacing, scanning mode, and interlayer rotation angle.

9. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 2, characterized in that, The thermophysical parameters of the difficult-to-weld nickel-based superalloy in step S12 include latent heat of fusion, solid-liquid phase temperature, thermal conductivity, and specific heat capacity.

10. The efficient forming process for dense, crack-free additive manufacturing of difficult-to-weld nickel-based superalloys according to claim 1, characterized in that, In step S3, the forming laser additive manufacturing is carried out according to the optimal process parameter combination obtained in step S2. The resulting difficult-to-weld nickel-based high-temperature alloy part has a relative density of more than 99%, and no crack defects are observed in the microstructure.

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