A method and system for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam

Abstract

The present invention belongs to the technical field of laser welding defect prediction, and discloses a method for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams. Through the macro-microscopic thermal-mass coupling simulation of laser welding, the present invention accurately calculates the temperature / solid fraction (TB / fB) of the lap points of adjacent dendrites in the mushy zone of the weld seam and the T-fS curve; proposes a new method for predicting the solidification crack sensitivity by integrating microstructure information, realizes the accurate prediction of the solidification crack sensitivity of aluminum alloy laser welding, and reveals the solidification crack inhibition mechanism of ultrafine equiaxed crystal structure shortening the intergranular liquid phase channel and reducing solute segregation, which has very important engineering application significance for realizing crack-free solidification welding of high-strength aluminum alloy thick-walled components.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser welding defect prediction, and particularly relates to a method and system for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams. Background Technique

[0002] Solidification crack is one of the common defects in aluminum alloy welding. Aluminum alloy welding solidification cracks usually occur in the mushy zone of the molten pool (i.e., the liquid-solid two-phase coexistence zone), which is closely related to the evolution behavior of dendritic microstructure during the solidification process. When the dendrites grow during the solidification of the molten pool, the low-melting-point eutectic phase segregates between the dendrites, and liquid films or droplets are generated on the dendrites, forming a dendritic network structure (with low ductility) in the mushy zone; at the same time, due to factors such as solidification shrinkage and base metal thermal shrinkage, large shrinkage deformation will occur in the mushy zone; when the shrinkage deformation amount exceeds the ductility of the dendritic network structure and the liquid phase reflux feeding ability is insufficient, solidification cracks will be generated. Relevant research shows that the low-ductility dendritic network structure in the mushy zone, such as the liquid film morphology, grain morphology and size, directly affects the solidification crack sensitivity. Therefore, clarifying the evolution law of aluminum alloy welding solidification microstructure, revealing the change of dendritic network structure in the late stage of solidification, and realizing the prediction of solidification crack sensitivity are of great significance for suppressing solidification cracks.

[0003] At present, the main prediction methods for aluminum alloy welding solidification cracks are as follows: 202310956914.4, this patent uses a macro-micro coupling method to obtain the microstructure evolution information during two-dimensional solidification, calculates the pressure drop using the RDG model, and compares the calculated pressure drop results with the liquid film bearing capacity model to judge the occurrence of hot cracks. 202410092277.5, this patent proposes a method for deriving the criterion for the sensitivity of directional solidification hot cracks under a unified permeability, and high-precision simultaneous calculations are obtained for the permeability values in different regions. 201710779447.7 proposes a new method for predicting the hot cracking tendency of alloys through experiments based on the Clyne-Davies model. However, several problems still need to be solved: First, the prediction mainly focuses on two dimensions, and the prediction of the three-dimensional solidification crack sensitivity of the weld seam still needs to be carried out; second, for the key lap temperature (TB) and T-fS curve in the prediction of solidification crack sensitivity, they are still mainly estimated or evaluated through experiments, and the prediction accuracy is relatively low.

[0004] Through the above analysis, the problems and defects existing in the prior art are:

[0005] (1) The prediction mainly focuses on two dimensions, and the prediction of the three-dimensional solidification crack sensitivity of the weld seam still needs to be carried out.

[0006] (2) For the key lap temperature (TB) and T-fS curve in the prediction of solidification crack sensitivity, they are still mainly estimated or evaluated through experiments, and the prediction accuracy is relatively low. Summary of the Invention

[0007] Aiming at the problems existing in the prior art, the present invention provides a method for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams.

[0008] The present invention is implemented as follows. A method for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams includes:

[0009] Step 1, obtaining macroscopic temperature field information;

[0010] Based on the flow and heat transfer control equations, ray tracing control equation, driving force control equation, and thermal boundary control equation, a macroscopic heat and mass transfer model for laser welding is established;

[0011] Step 2, simulating the microstructure in the mushy zone and obtaining key information;

[0012] Taking the temperature field data obtained from the macroscopic simulation as the input, an isothermal three-dimensional mushy zone microstructure simulation is carried out considering the grain boundary energy of adjacent grains;

[0013] Step 3, predicting the solidification crack sensitivity;

[0014] Based on the T-fS curve, calculate the crack sensitivity value SCS according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension.

[0015] Furthermore, the obtaining of the macroscopic temperature field information:

[0016] Based on the flow and heat transfer control equations, ray tracing control equation, driving force control equation, and thermal boundary control equation, a macroscopic heat and mass transfer model for laser welding is established; based on the actual welding specimen, three-dimensional geometric modeling is carried out, the model is meshed, the thermal physical property parameters, initial conditions, and boundary condition information are set, and the macroscopic heat flow calculation of aluminum alloy laser welding under the coupling of heat, mass, and force is carried out; observe the penetration and weld width indexes of the simulation results, and extract the temperature field data at different times of the entire weld seam when the penetration and weld width are basically stable and unchanged.

[0017] Furthermore, the simulating the microstructure in the mushy zone and obtaining key information:

[0018] Taking the temperature field data obtained from the macroscopic simulation as the input, an isothermal three-dimensional mushy zone microstructure simulation is carried out considering the grain boundary energy of adjacent grains; the numerical simulation results are visually processed. When two adjacent grains overlap, the judgment condition is that the liquid fraction at the adjacent grain boundary is less than 0.5. At this time, the temperature of the entire calculation domain is used as the overlap point temperature TB, and the solid fraction of the calculation domain is used as the overlap point solid fraction fB; extract the temperature-solid fraction curve T-fS curve within the entire calculation domain.

[0019] Furthermore, the calculation dimension includes two-dimensional / three-dimensional.

[0020] Furthermore, the prediction of solidification crack sensitivity is as follows:

[0021] Based on the T-fS curve, calculate the crack sensitivity value SCS according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension.

[0022] (1) For two-dimensional columnar crystals, plot the T-|dT / d(fs)| curve, and when f = fB, SCS = |dT / d(fs)|.

[0023] (2) For two-dimensional equiaxed crystals, plot the T-|dT / d(fs)^(1 / 2)| curve, and when f = fB, SCS = |dT / d(fs)^(1 / 2)|.

[0024] (3) For three-dimensional columnar crystals, plot the T-|dT / d(fs)^(1 / 2)| curve, and when f = fB, SCS = |dT / d(fs)^(1 / 2)|.

[0025] (4) For three-dimensional equiaxed crystals, plot the T-|dT / d(fs)^(1 / 3)| curve, and when f = fB, SCS = |dT / d(fs)^(1 / 3)|.

[0026] Another object of the present invention is to provide a three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding seams, including:

[0027] A macroscopic temperature field information acquisition module for acquiring macroscopic temperature field information; based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, establish a macroscopic heat transfer and mass transfer model for laser welding.

[0028] A key information acquisition module for simulating the microstructure in the mushy zone and acquiring key information; using the temperature field data obtained from macroscopic simulation as input, and performing isothermal three-dimensional mushy zone microstructure simulation considering the grain boundary energy of adjacent grains.

[0029] A prediction module for predicting solidification crack sensitivity; based on the T-fS curve, calculate the crack sensitivity value SCS according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension.

[0030] Another object of the present invention is to provide a computer device, which includes a memory and a processor. When the computer program stored in the memory is executed by the processor, the processor executes the steps of the three-dimensional solidification crack sensitivity prediction method for aluminum alloy laser welding seams.

[0031] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to execute the steps of the method for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam.

[0032] Another object of the present invention is to provide an information data processing terminal for implementing the system for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam.

[0033] Combined with the above technical solutions and solved technical problems, the advantages and positive effects of the technical solution to be protected by the present invention are analyzed from the following aspects:

[0034] First, the present invention provides a method for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam. This method has successfully realized the prediction of the three-dimensional solidification crack sensitivity of high-strength aluminum alloy, and on this basis, the suppression of solidification cracks in aluminum alloy laser welding has been realized.

[0035] (1) Through the macro-micro thermal mass coupling simulation of laser welding, the present invention accurately calculates the temperature / solid phase fraction (TB / fB) of the lap joints of adjacent dendrites in the weld mushy zone and the T-fS curve.

[0036] (2) A new method for predicting solidification crack sensitivity that integrates microstructure information is proposed, realizing the accurate prediction of the solidification crack sensitivity of aluminum alloy laser welding, and revealing the solidification crack suppression mechanism of ultrafine equiaxed grain structure shortening the intergranular liquid phase channel and reducing solute segregation, which has very important engineering application significance for realizing crack-free welding of high-strength aluminum alloy thick-walled components.

[0037] Second, the technical solution of the present invention fills the technical gap in the industry at home and abroad: The existing methods for predicting welding solidification cracks at home and abroad mainly focus on two dimensions, and research shows that there is a large deviation between the two-dimensional prediction results and the actual results. The present invention provides a prediction model for aluminum alloy solidification cracks, filling the gap in the three-dimensional model for predicting aluminum alloy solidification cracks at home and abroad. At the same time, the present invention introduces the macroscopic temperature field into the prediction of solidification cracks, using macroscopic information to make up for the deviation of microscopic prediction results and improve the prediction accuracy, making up for the problem of low accuracy in predicting aluminum alloy welding solidification cracks at home and abroad.

[0038] The technical solution of the present invention solves the technical problem that people have been eager to solve but have never succeeded in: the key parameters in the prediction of solidification cracks in aluminum alloy welding have always been mainly estimated or evaluated by experiments, and the prediction accuracy is relatively low. The present invention proposes a method for predicting the sensitivity of solidification cracks by integrating macroscopic temperature fields and microscopic structure information, which solves the problem of low prediction accuracy. At the same time, a three-dimensional solidification crack prediction model is innovatively constructed, breaking through the problem of low prediction accuracy of two-dimensional models that people have always had.

[0039] Does the technical solution of the present invention overcome technical prejudice? Due to the long calculation time and high cost of numerical simulation, it has been restricted in the actual application process. However, the research on solidification cracks cannot do without numerical simulation. Therefore, people generally adopt two-dimensional low-precision prediction means to reduce the calculation time and cost. The present invention adopts MPI parallel computing technology, which greatly improves the calculation efficiency of the numerical model, breaks through the dilemma that the prediction accuracy and cost of solidification cracks cannot be both obtained, and makes it possible to predict the solidification cracks of aluminum alloy efficiently and with high precision.

[0040] Thirdly, the technical solution of the present invention effectively solves the technical problems in the industrial application of existing aluminum alloy laser welding, such as low prediction accuracy of the sensitivity of three-dimensional solidification cracks in the weld, long debugging time, and difficulty in real-time adjustment. Traditional methods usually rely on a single temperature field or only based on static microstructural features to predict crack sensitivity, resulting in inaccurate prediction results and difficulty in dealing with the changing parameters in complex welding processes. In particular, the traditional solutions lack targeted data processing and feedback mechanisms, and cannot effectively cope with the influence brought by parameter fluctuations during the welding process, thus restricting the optimization and stability of the welding process.

[0041] Through the collaborative work of multiple modules, the present invention significantly improves the prediction accuracy of the sensitivity of solidification cracks in the weld. The temperature field acquisition module combines the control equations of fluid flow and heat transfer, ray tracing, driving force, and thermal boundary, and establishes a dynamic temperature field model to reflect the heat conduction and heat distribution during the welding process in real time. This module not only obtains more accurate temperature field data, but also, with the support of the dynamic feedback adjustment unit, can dynamically adjust according to the real-time monitored welding parameters to ensure that the temperature field data is consistent with the actual welding process, significantly improving the real-time performance and accuracy of the prediction.

[0042] In addition, in the aspect of microstructure simulation, the present invention introduces a grain growth direction prediction unit, making the simulation of grain lap and morphology evolution more accurate, and further refining the microstructure of the weld seam. This module can effectively capture the grain growth in the three-dimensional mushy zone, providing important data such as grain boundary energy and solid fraction, and laying a solid data foundation for subsequent crack sensitivity prediction. The crack sensitivity prediction module realizes the dynamic calculation and hierarchical management of SCS (Solidification Crack Sensitivity Numerical Value) through a data comparison and verification unit, making the crack sensitivity prediction more accurate and comprehensive. In addition, the visual report generated by the system provides intuitive crack sensitivity levels and risk prompts for operators, helping to quickly adjust welding parameters.

[0043] In summary, the present invention has made remarkable technological progress in improving the accuracy of crack sensitivity prediction, shortening the commissioning time, and enhancing welding stability, has broad industrial application value, and provides reliable technical support for the optimization of aluminum alloy welding processes. Brief Description of the Drawings

[0044] Figure 1 is a flowchart of a three-dimensional solidification crack sensitivity prediction method for an aluminum alloy laser welding weld seam provided by an embodiment of the present invention.

[0045] Figure 2 is a structural block diagram of a three-dimensional solidification crack sensitivity prediction system for an aluminum alloy laser welding weld seam provided by an embodiment of the present invention.

[0046] Figure 3 is a schematic diagram of macroscopic heat and mass transfer and a control equation diagram for laser welding provided by an embodiment of the present invention.

[0047] Figure 4 is a calculation domain diagram of macroscopic heat and mass transfer provided by an embodiment of the present invention.

[0048] Figure 5 is a temperature curve diagram at different positions of the weld seam provided by an embodiment of the present invention.

[0049] Figure 6 is a schematic diagram of a three-dimensional polycrystalline phase field model and a control equation diagram provided by an embodiment of the present invention.

[0050] Figure 7 is a diagram of the three-dimensional equiaxed crystal solidification process and solidification crack sensitivity under different initial nucleation rates provided by an embodiment of the present invention.

[0051] Figure 8 is a diagram of the columnar crystal morphology under different initial primary dendrite spacings provided by an embodiment of the present invention.

[0052] Figure 9 is a diagram of the variation of the solid-liquid interface morphology of dendritic and non-dendritic columnar crystals with temperature provided by an embodiment of the present invention.

[0053] Figure 10 It is the T-fS curve and solidification crack sensitivity coefficient diagram of dendritic and non-dendritic columnar crystals provided by the embodiments of the present invention.

[0054] Figure 11 It is the simulation result diagram of the solid-liquid interface in the columnar crystal region varying with temperature when considering the grain boundary energy provided by the embodiments of the present invention.

[0055] Figure 12 It is the liquid fraction diagram at the center line of the grain boundary between two adjacent grains at the eutectic temperature provided by the embodiments of the present invention. Detailed implementation manners

[0056] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0057] As Figure 1 shown, a method for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam provided by the embodiments of the present invention includes the following steps:

[0058] S101, obtaining macroscopic temperature field information;

[0059] Based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, a macroscopic heat and mass transfer model for laser welding is established;

[0060] S102, simulating the microstructure in the mushy zone and obtaining key information;

[0061] Taking the temperature field data obtained from the macroscopic simulation as the input, an isothermal three-dimensional mushy zone microstructure simulation is carried out considering the grain boundary energy of adjacent grains;

[0062] S103, predicting the solidification crack sensitivity;

[0063] Based on the T-fS curve, calculate the crack sensitivity value SCS according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension.

[0064] The macroscopic temperature field information acquisition provided by the embodiments of the present invention:

[0065] Based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, a macroscopic heat and mass transfer model for laser welding is established; based on the actual welding specimen, three-dimensional geometric modeling is carried out, the model is meshed, the thermal physical properties parameters, initial conditions, and boundary condition information are set, and the macroscopic heat flow calculation of aluminum alloy laser welding under the coupling of heat, mass, and force is carried out; observe the penetration depth and weld width indexes of the simulation results, and extract the temperature field data at different times of the entire weld when the penetration depth and weld width are basically stable and unchanged.

[0066] Microstructure simulation of the mushy zone and acquisition of key information provided by the embodiments of the present invention:

[0067] Taking the temperature field data obtained from the macroscopic simulation as the input, an isothermal three-dimensional mushy zone microstructure simulation is carried out considering the grain boundary energy of adjacent grains; the numerical simulation results are visually processed. When two adjacent grains overlap, the judgment condition is that the liquid fraction at the adjacent grain boundary is less than 0.5. At this time, the temperature of the entire calculation domain is used as the overlap point temperature TB, and the solid fraction of the calculation domain is used as the overlap point solid fraction fB; extract the temperature-solid fraction curve T-fS curve within the entire calculation domain.

[0068] The calculation dimensions provided by the embodiments of the present invention include two-dimensional / three-dimensional.

[0069] Prediction of solidification crack sensitivity provided by the embodiments of the present invention:

[0070] Based on the T-fS curve, calculate the crack sensitivity numerical value SCS according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension:

[0071] (1) For two-dimensional columnar crystals, plot the T-|dT / d(fs)| curve, and when f = fB, SCS = |dT / d(fs)|;

[0072] (2) For two-dimensional equiaxed crystals, plot the T-|dT / d(fs)1 / 2| curve, and when f = fB, SCS = |dT / d(fs)1 / 2|;

[0073] (3) For three-dimensional columnar crystals, plot the T-|dT / d(fs)1 / 2| curve, and when f = fB, SCS = |dT / d(fs)1 / 2|;

[0074] (4) For three-dimensional equiaxed crystals, plot the T-|dT / d(fs)1 / 3| curve, and when f = fB, SCS = |dT / d(fs)1 / 3|.

[0075] As Figure 2 shown, a three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding seams provided by the embodiments of the present invention includes:

[0076] A macro temperature field information acquisition module is used to acquire macro temperature field information; based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, a macro heat and mass transfer model for laser welding is established.

[0077] A key information acquisition module is used for the simulation of the microstructure in the mushy zone and the acquisition of key information; taking the temperature field data obtained from the macro simulation as the input, an isothermal three-dimensional mushy zone microstructure simulation is carried out considering the grain boundary energy of adjacent grains.

[0078] A prediction module is used for the prediction of solidification crack sensitivity; based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension.

[0079] Another object of the present invention is to provide a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the steps of the method for predicting the three-dimensional solidification crack sensitivity of the aluminum alloy laser welding seam.

[0080] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method for predicting the three-dimensional solidification crack sensitivity of the aluminum alloy laser welding seam.

[0081] Another object of the present invention is to provide an information data processing terminal, which is used to implement the three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding seams.

[0082] The specific implementation of the present invention:

[0083] Example 1: Prediction of solidification crack sensitivity of the three-dimensional solidification process of aluminum alloy laser welding under different nucleation rates

[0084] (1) First, perform macro numerical simulation to obtain the cooling rate of the layout area when the weld is stable.

[0085] (1) The schematic diagram and control equations of macro heat and mass transfer are as Figure 3 shown. The main welding process parameters are: laser welding power 10kW, welding speed 110mm / s; the calculation domain information is as Figure 4 shown; the thermophysical parameters of the aluminum alloy are: liquid metal density 2350kg m -3 , solid metal density 2670kg m -3 , viscosity 1.3×10 -3 kg m -1 s -1 , liquid specific heat 1170J kg -1 K-1 - Specific heat of solid phase: 1040 J / kg -1 K -1 - Thermal conductivity of liquid phase: 90 W / (m·K) -1 K -1 - Thermal conductivity of solid phase: 150 W / (m·K) -1 K -1 - Liquidus temperature: 913.15 K, Solidus temperature: 813.15 K, Heat transfer coefficient: 20 W / (m²·K) -2 K -1 - Surface tension: 0.907 N / m -1 - Latent heat of fusion: 3.62×10³ J / kg 5 J / kg -1 - Latent heat of vaporization: 1.08×10⁶ J / kg 7 J / kg -1 - Surface tension gradient: -0.271×10⁻³ N / (m·K) -3 N / m -1 K -1 。

[0086] (2) Numerical simulation calculation to obtain the local area cooling rate at steady state. As shown in Figure 5 , the cooling rate is 1672 K / s at this time.

[0087] 2. Microstructure simulation in the mushy zone and obtaining the T-f S curve

[0088] (1) Schematic diagram of the microscopic multi-component three-dimensional polycrystalline phase field model and the governing equations are as shown in Figure 6 . The thermophysical parameters required for the simulation: Initial Cu concentration 4.0 wt%, Melting temperature of pure Al 933.47 K, Liquidus slope in Al-Cu -5.08 ((Tm - Tl) / c0), Partition coefficient in Al-Cu 0.169 ((Tl - Tm) / (Ts - Tm)), Diffusion coefficient of Cu in the liquid phase 3.0×10⁻⁹ m² / s 2 s -1 - Diffusion coefficient of Cu in the solid phase 1.0×10⁻¹² m² / s 2 s -1 - Al-Cu Gibbs-Thompson coefficient 2.4×10⁻⁷ K·m, Anisotropy (ε4) 0.02. -7 K m

[0089] (2) Simulate the three-dimensional microstructures at different nucleation rates, and the simulation results are as shown in Figure 7 (a). It can be seen from the figure that in the case of low nucleation rate, with the decrease of temperature, at the initial stage of solidification, f SThe rate of increase slows down. This may be because the supercooling is small at this time and the grain growth is slow. In addition, due to the low equilibrium concentration of the liquid phase, the solute discharged from the solid phase can easily reach equilibrium near the solid-liquid interface, which leads to a slowdown in the growth rate. As the temperature continues to decrease, the supercooling increases, and the liquid phase equilibrium concentration limit increases. At this time, the smaller solid phase area needs to grow rapidly to reach equilibrium. In the late stage of solidification, the solid phase has occupied most of the area, and the distribution of liquid phase solute is basically balanced, causing the supercooling to become smaller again, which makes f S The change of f also slows down. For equiaxed crystals with high nucleation rate, f S The change is relatively gentle, and the solidification process slows down significantly only in the late solidification stage. Further, the change of the solidification crack sensitivity coefficient of the three-dimensional microstructure with temperature was calculated, and the results are as follows Figure 7 (b) The results show that as the temperature decreases, the solidification crack sensitivity first fluctuates gently and then increases sharply. Compared with equiaxed grains with a high nucleation rate, the solidification crack sensitivity is initially larger, then decreases, and finally remains high in the later stages of solidification.

[0090] Example 2: Comparison of solidification crack sensitivity between dendritic columnar crystals and non-dendritic columnar crystals

[0091] 1. First, microscopic numerical simulation is performed to obtain the microstructural morphology of the dendrite growth directional solidification stability under different primary dendrite spacing.

[0092] The microscopic simulation results are as follows Figure 8 As shown in the figure, when the primary dendrite spacing is small, secondary dendrites are difficult to form, and the liquid phase channel is smooth and continuous. However, when the primary dendrite spacing is large, secondary dendrites will form, and some small tertiary dendrites may be present. During the solidification process, temperature and solute disturbances can lead to the formation of secondary dendrites. The interface instability caused by solute disturbances and the large degree of supercooling are the causes of secondary dendrite formation.

[0093] 2. A portion of the microstructure of the mushy zone was intercepted for simulation and comparative analysis of solidification crack sensitivity was carried out.

[0094] Figure 9 The figure shows the change of the solid-liquid interface morphology of dendritic and non-dendritic columnar crystals with temperature. It can be observed from the figure that as the temperature decreases, both columnar crystals begin to coarsen. The fluctuation of the solid-liquid interface on the non-dendritic columnar crystal gradually becomes smooth. Subsequently, bridging occurs between the primary dendrites, and only some independent droplets remain. For dendritic columnar crystals, they will also coarsen as the temperature decreases. Some small secondary dendrites will be melted. As the temperature decreases, the tips of the secondary dendrites begin to gradually approach and eventually achieve bridging. At this time, the liquid phase channel is not smooth, as shown in Figure 1. Figure 9 shown.

[0095] The Kou model is selected as the basic criterion for predicting solidification crack sensitivity. This criterion is derived based on the growth of columnar grains in three-dimensional space. Kou et al. comprehensively considered three factors, namely, grain separation caused by external forces, growth of adjacent grains, and feeding of the remaining liquid phase along grain boundaries, based on a physical basis, and derived a new SCS criterion. The specific expression is as follows:

[0096]

[0097] In the formula, ε local is the local stress, fS is the solid fraction, β is the solidification shrinkage rate, T is the temperature, and v z is the flow rate of the intergranular liquid.

[0098] When the separation speed of adjacent grains is greater than the growth of grains and the feeding of the remaining liquid phase along grain boundaries, solidification cracks will occur. After further simplification, when f S is close to 1, the maximum value of |dT / d(f S ) 1 / 2 is the solidification crack sensitivity index of the weld.

[0099] Furthermore, Figure 10 the T-f S curves of dendritic and non-dendritic columnar grains were statistically analyzed, and the solidification crack sensitivity was calculated according to the Kou model. It can be seen from the figure that when cellular bridges occur, f S = 0.9645 (i.e., the f B value), while when dendritic columnar grain bridges occur, f S = 0.8711 (i.e., the f B value). In addition, the crack sensitivity of dendritic columnar grains is relatively low, only 1 / 6 of that of cellular grains. This shows that the smooth liquid phase channels of columnar grains in the later stage of solidification are not conducive to suppressing solidification cracks. This is because different liquid phase channel morphologies have a huge impact on the f B value in the later stage of solidification, resulting in significant differences in the solidification crack sensitivity of different grain morphologies. When the microstructure morphology is non-dendritic columnar grains, there is less remaining liquid phase in the smooth liquid phase channels, and the reflux channels are single. This makes it impossible for the remaining liquid phase to be effectively replenished in a timely manner when solidification cracks are initiated by tensile stress. This will inevitably increase the solidification crack sensitivity. When the microstructure morphology is dendritic columnar grains, due to the presence of secondary or even higher-order dendrites that can bridge in advance. The liquid phase between dendrites is sufficient, and the remaining liquid phase can timely replenish the dendrite fractures caused by tensile stress, thereby reducing the formation of solidification cracks.

[0100] Example 3: Prediction of solidification crack sensitivity considering grain boundary energy

[0101] 1. Relationship between grain boundary energy and grain orientation difference

[0102] This method uses the multi-phase field model used by Guo et al., which can consider the influence of the interface energy between adjacent grains with different misorientation angles on the growth of the microstructure. Among them, the interface energy relationship adopts the relationship between the grain boundary energy and the misorientation angle proposed by Read-Shockley et al.:

[0103] σ SS = 2.2σ SL [θ / θ m [1 - ln(θ / θ m )]

[0104] where θ is the misorientation angle between two adjacent grains, σ SS is the intergranular energy, θm is the angle when the grain boundary energy reaches the maximum value, and σ SL is the solid-liquid interface energy. In the present invention, θm = 20°. If the misorientation angle between adjacent grains is greater than this value, the intergranular energy between grains remains unchanged, and σ SS = 2.2σ SL .

[0105] 2. Prediction of solidification crack sensitivity considering different grain misorientation angles of adjacent grains and the interface energy difference caused by different grain misorientation angles

[0106] Two grains with different orientations are set in the computational domain. Different from Example 2, in this example, in order to better compare the simulation results, the influence of noise in the solute is not considered, but the secondary dendrites are directly generated by designing the initial secondary dendrites. The initial conditions are as Figure 1 shown. The initial solid phase is the yellow area, and the rest of the area is set as the liquid phase. Since the value of f S is set differently initially, therefore, the solidification crack sensitivity between dendrites is only indirectly qualitatively described through the lapping behavior. Figure 11 It is a simulation result diagram of the solid-liquid interface in the columnar crystal region changing with temperature under different misorientation angles. It can be seen from the figure that when the misorientation angle between adjacent grains is 0°, the secondary dendrites grow synchronously, and when the dendrite arms start to contact, the dendrites directly bridge ( Figure 11 a)). However, affected by the grain misorientation angle and the interface energy, the grain bridging becomes difficult ( Figure 11 (b) and (c)). Figure 11 The AA' line in (b) and Figure 11 the BB' line in (c) represent the dividing lines between grains. The liquid fraction values of each point on this line at the eutectic temperature are as Figure 12 shown. The arrow indicates that the adjacent two grains have been bridged at this time. Compared with the misorientation angle of 10°, the dendrites hardly bridge at the misorientation angle of 20°. It shows that when the interface energy exists, even at the eutectic temperature, there is still a large amount of residual liquid phase between the two adjacent grains. And the liquid phase channel is relatively smooth, which will inevitably increase the solidification crack sensitivity in the columnar crystal region.

[0107] Based on the above simulation results, there may be two reasons for the formation of solidification cracks in the columnar crystal region during single-laser welding of medium and thick aluminum alloy plates: First, the columnar crystal region in the weld sometimes occupies more than half of the weld. The columnar crystals in this region mainly show a non-dendritic form, without obvious secondary dendrites to facilitate the bridging of adjacent grains, thereby reducing the sensitivity to solidification cracks. Second, due to reasons such as competitive growth, there may be a large orientation difference between adjacent grains, which may prevent them from overlapping when the temperature drops to the eutectic temperature, thus easily leading to the formation of solidification cracks.

[0108] 3. By adopting the above solution, this aspect has the following advantages compared with the prior art: (1) Through the macro-micro thermal-mass coupling simulation of laser welding, the present invention accurately calculates the temperature / solid fraction (T B / f B ) of the lap points of adjacent dendrites in the mushy zone of the weld and the T-f S curve; (2) A new method for predicting the sensitivity to solidification cracks by integrating microstructural information is proposed, realizing the accurate prediction of the sensitivity to solidification cracks in aluminum alloy laser welding, and revealing the mechanism of solidification crack suppression in which ultrafine equiaxed crystal structures shorten the intergranular liquid channels and reduce solute segregation. This has very important engineering application significance for achieving solidification crack-free welding of high-strength aluminum alloy thick-walled components.

[0109] During the welding process, welding parameters (such as laser power, welding speed, and gas flow rate) will fluctuate with changes in the environment and material state, thus affecting the stability of the temperature field. The temperature field acquisition module monitors these parameters in real time through the dynamic feedback adjustment unit. The dynamic feedback adjustment unit obtains the current welding parameters through sensors, inputs them into the control system, and adjusts the relevant parameters in the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations based on real-time data. This can dynamically adjust the temperature field data according to the actual welding conditions, improving the timeliness and accuracy of the temperature field data and providing a reliable basis for the accurate simulation of the microstructure during weld solidification.

[0110] Optimization of the three-dimensional microstructure simulation accuracy of the grain growth direction prediction unit

[0111] The grain growth direction prediction unit in the microstructure simulation module predicts the grain growth direction based on the gradient distribution of the temperature field. Specifically, when the temperature field data is input into the grain growth direction prediction unit, the unit calculates the temperature gradient and uses this gradient information to predict the growth direction and speed of the grains in the three-dimensional mushy zone. Subsequently, by combining the grain boundary energy data under the condition of adjacent grain lap, the grain growth direction prediction unit can simulate how the grains interact with adjacent grains during solidification, generating a more accurate grain morphology evolution model. In this way, not only the simulation accuracy of the grain boundary temperature and solid fraction data is improved, but also the accuracy of the overall microstructure simulation is enhanced, thus providing more refined microscopic data support for crack sensitivity prediction.

[0112] Crack Sensitivity Prediction and Risk Level Classification of the Data Comparison and Verification Unit

[0113] The data comparison and verification unit in the crack sensitivity prediction module quantifies the crack sensitivity of the weld by calculating the solidification crack sensitivity value SCS. First, the system calculates SCS based on the values generated by the T-fS curve, grain type (equiaxed grains or columnar grains), and calculation dimension, and transfers the result to the data comparison and verification unit. This unit compares the calculated SCS value with a preset crack sensitivity threshold and classifies the crack risk of the weld according to the magnitude of the SCS value. Specifically, the higher the SCS value, the greater the sensitivity of the solidification crack; the data comparison and verification unit divides the risk into different levels such as low, medium, and high according to different SCS intervals. Finally, the system generates a visual report of the crack sensitivity, displays the crack sensitivity and crack risk level in the form of charts, and gives corresponding adjustment suggestions. This makes the optimization of welding process parameters intuitive and efficient, helping operators adjust welding parameters in a timely manner and reduce the crack risk.

[0114] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those of ordinary skill in the art can understand that the above devices and methods can be implemented using computer-executable instructions and / or included in processor control code, such as provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuits of programmable hardware devices such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above hardware circuits and software such as firmware.

[0115] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A system for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams, characterized in that, The system includes: A temperature field acquisition module, which is used to establish a macroscopic heat transfer and mass transfer model for laser welding based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, and extract the temperature field data of the entire weld at different times during the welding process; A microstructure simulation module, which is used to input the temperature field data into the isothermal three-dimensional mushy zone microstructure simulation to simulate and obtain the grain boundary energy, temperature, and solid fraction data under the condition of adjacent grain lap; A data processing and visualization module, which is used to process the numerical results of the microstructure simulation and generate a temperature-solid fraction curve and the liquid fraction at the adjacent grain boundaries; A crack sensitivity prediction module, which is used to draw corresponding curves based on the T-fS curve and the grain type and calculation dimension in the calculation area, and calculate the solidification crack sensitivity value SCS; The mushy zone microstructure simulation and key information acquisition: Taking the temperature field data obtained from the macroscopic simulation as the input, perform an isothermal three-dimensional mushy zone microstructure simulation considering the grain boundary energy of adjacent grains; visually process the numerical simulation results. When two adjacent grains lap, the judgment condition is that the liquid fraction at the adjacent grain boundary is less than 0.

5. At this time, the temperature of the entire calculation domain is used as the lap point temperature TB, and the solid fraction of the calculation domain is used as the lap point solid fraction fB; extract the temperature-solid fraction curve T-fS curve within the entire calculation domain; The calculation dimension includes two-dimensional / three-dimensional; The solidification crack sensitivity prediction: Based on the T-fS curve, calculate the crack sensitivity value SCS according to whether the calculation area is equiaxed grains or columnar grains and the calculation dimension: (1) For two-dimensional columnar grains, draw a T-|dT / d(fs)| curve, and when f = fB, SCS = |dT / d(fs)|; (2) For two-dimensional equiaxed grains, draw a T-|dT / d(fs)^(1 / 2)| curve, and when f = fB, SCS = |dT / d(fs)^(1 / 2)|; (3) For three-dimensional columnar grains, draw a T-|dT / d(fs)^(1 / 2)| curve, and when f = fB, SCS = |dT / d(fs)^(1 / 2)|; (4) For three-dimensional equiaxed grains, draw a T-|dT / d(fs)^(1 / 3)| curve, and when f = fB, SCS = |dT / d(fs)^(1 / 3)|.

2. The system according to claim 1, characterized in that The temperature field acquisition module further includes a dynamic feedback adjustment unit, which is used to dynamically adjust the parameters of the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations according to the welding parameters monitored in real time during the welding process, so as to improve the timeliness and accuracy of the temperature field data; The microstructure simulation module also includes a grain growth direction prediction unit, which is used to predict the grain growth direction based on the gradient distribution of the temperature field, and combine the grain boundary energy data under the condition of adjacent grain lap to simulate the morphological evolution of grains in the three-dimensional mushy zone, further improving the simulation accuracy of the grain boundary temperature and solid fraction data.

3. The system according to claim 1, wherein The crack sensitivity prediction module includes a data comparison and verification unit, which is used to compare the predicted solidification crack sensitivity value SCS with a preset crack sensitivity threshold, classify the crack risk according to different SCS intervals, and output a visual report of the crack sensitivity for the optimization and adjustment of welding process parameters.

4. The system for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams according to claim 1, characterized in that The temperature field acquisition module also includes a three-dimensional geometric modeling unit, which is used to generate a three-dimensional model based on the actual welding specimen, perform mesh division, set thermal physical properties, initial conditions and boundary conditions, and perform macroscopic heat flow calculation under thermo-fluid-structure coupling.

5. The system for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding seams according to claim 1, wherein The microstructure simulation module contains a grain lap judgment unit, which is used to judge whether grains lap according to whether the liquid fraction at the boundary of two adjacent grains in the simulation is less than 0.5, and extract the temperature and solid fraction of the lap points based on this information.

6. A method for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam, which applies the three-dimensional solidification crack sensitivity prediction system of the aluminum alloy laser welding seam according to any one of claims 1 to 5, is characterized in that, It includes the following steps: Step 1, obtaining macroscopic temperature field information; Based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, a macroscopic heat and mass transfer model for laser welding is established; Step 2, simulating the microstructure in the mushy zone and obtaining key information; Taking the temperature field data obtained from the macroscopic simulation as input, perform isothermal three-dimensional mushy zone microstructure simulation considering the grain boundary energy of adjacent grains; Step 3, predicting the solidification crack sensitivity; Based on the T-fS curve, calculate the crack sensitivity value SCS according to whether the calculation region is equiaxed crystal or columnar crystal and the calculation dimension.

7. The method for predicting the three-dimensional solidification crack sensitivity of the aluminum alloy laser welding seam according to claim 6, characterized in that, The obtaining of the macroscopic temperature field information: Based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, establish a macroscopic heat and mass transfer model for laser welding; perform three-dimensional geometric modeling based on the actual welding specimen, perform mesh division on the model, set thermal physical property parameters, initial conditions, and boundary condition information, and perform macroscopic heat flow calculation for aluminum alloy laser welding under thermo-fluid-structure coupling; observe the penetration and weld width indexes of the simulation results, and extract the temperature field data at different times of the entire weld when the penetration and weld width are basically stable and unchanged.

8. A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to execute the steps of the method for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding seam according to any one of claims 6-7.

9. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the three-dimensional solidification crack sensitivity prediction system for an aluminum alloy laser welding seam according to any one of claims 1-5.

Images