Real-time simulation and model prediction method for arc additive manufacturing based on event sequences.

Abstract

This provides a real-time simulation and model prediction method for arc additive manufacturing based on event sequences. [Solution] In a real-time process of arc additive manufacturing of metal structures, the method includes the steps of: activating units in real time by event sequence and guiding the heat source in real time; setting parameters for the heat source model, thermal simulation, and mechanical simulation, and performing a real-time thermal-mechanical simulation of arc additive manufacturing; and constructing a theoretical model for a simplified calculation of the residual stress field and correcting the calculation model prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of additive manufacturing, and more specifically, to a real-time simulation and model prediction method for arc additive manufacturing based on an event sequence.

Background Art

[0002] With the continuous progress of modern intelligent manufacturing technology, wire arc additive manufacturing (WAAM), an innovative process that combines traditional welding technology and modern additive manufacturing technology, is becoming a research hotspot in the field of metal additive manufacturing due to its high material utilization rate and excellent workpiece forming ability.

[0003] The WAAM technology forms complex metal structural parts by melting metal wires with an electric arc heat source and stacking them layer by layer. During the WAAM process, due to the movement of the heat source and the rapid heating and cooling of the material, complex thermal and mechanical behaviors occur, which affect the forming quality and mechanical properties of the structural parts. Currently, heat treatment and high-pressure rolling are commonly used to improve the mechanical properties of the formed structural parts. However, these methods are costly and the processes are complex, so there are still many challenges remaining for their application in the manufacture of large and complex metal structural parts. Therefore, it is particularly important to effectively control the defects of the structural parts formed during the WAAM process. The high heat input during the WAAM process often causes various temperature-related defects in the formed metal structure, such as pores, microcracks, residual stresses, and shape distortions. The residual stresses and deformations of the formed structure are mainly caused by the constraints of thermal expansion and contraction of the additive manufacturing part, which directly affect the mechanical properties of the final formed structure. Therefore, studying and predicting the thermal and mechanical behaviors of the WAAM process is very important for improving the forming quality and reducing the influence of defects.

[0004] Existing studies on the thermal and mechanical behavior of the WAAM process are primarily experimental, focusing on the measurement of residual stress and deformation, and the propagation behavior of fatigue cracks. However, experimental studies are typically time-consuming and labor-intensive, making it difficult to extract stress from specific locations, and making it impossible to monitor changes in stress distribution during the WAAM process in real time. [Overview of the Initiative]

[0005] The objective of this invention is to solve the shortcomings of existing technologies by proposing a real-time simulation and model prediction method for arc additive manufacturing based on event sequences.

[0006] In the first embodiment, a real-time simulation and model prediction method for arc additive manufacturing based on an event sequence is provided, and this method is: S1, In a real-time process of arc additive manufacturing of metal structures, the steps include activating the unit in real time using an event sequence and guiding the heat source in real time. Based on the event sequence method of S2 and S1, the heat source model parameters, thermal simulation parameters, and mechanical simulation parameters are set, and a real-time thermal-mechanical coupled simulation of arc additive manufacturing is performed. The process includes constructing a theoretical model for a simplified calculation of the residual stress field based on the stress diffusion distribution and normal stress interface correction deviation obtained from the thermal-mechanical coupled real-time simulations of S3 and S2, and correcting the calculation model predictions, wherein the event sequence is used to set up virtual blocks to move in three-dimensional space along a predetermined path and time so as to add the influence of the three-dimensional field to the path that the virtual blocks traverse.

[0007] Preferably, S1 is S101, a step of reconfiguring the real-time process of arc additive manufacturing using an event sequence, and activating each unit one by one along the path traversed by the virtual block of the event sequence, S102 includes the step of guiding the position of a virtual block in the event sequence as the position of a moving heat source, and using the Goldak double ellipsoid heat source model.

[0008] Preferably, S1 is S201 is a step in which thermal simulation parameters and mechanical simulation parameters are set, and a coupled thermal-mechanical simulation model is constructed. S202 includes the steps of constructing a linear deposition simulation model to simulate the deposition process of multilayer multipass arc additive manufacturing, and obtaining the stress diffusion distribution of the deposited layer based on the deposition stress simulation results, wherein the setting of thermal simulation parameters includes setting thermal boundary conditions, latent heat of phase change, thermal conductivity and specific heat, and the setting of mechanical simulation parameters includes setting thermal expansion coefficient, material mechanical parameters and boundary mechanical constraints.

[0009] Preferably, in S202, the linear deposition simulation model includes a single-line deposition simulation model, a double-line deposition simulation model, and a triple-line deposition simulation model, wherein in the single-line deposition simulation model, the laminated layer is located in the center of the substrate; in the double-line deposition simulation model, the laminated layer is located at both edges in the longitudinal direction of the substrate; and in the triple-line deposition simulation model, the laminated layer is located at both edges in the longitudinal direction and in the center.

[0010] Preferably, S3 includes S301, the step of constructing a theoretical model of the simplified calculation, and S302, the step of correcting the calculation model prediction. In S301, the theoretical model of the simplified calculation consists of a substrate and a laminated portion in the arc additive manufacturing process, and includes the stress field distribution before the release of the fixing constraint and the stress field distribution after the release of the fixing constraint. At the boundary between the laminated portion and the substrate, a diffusion effect of the deposition stress occurs before and after the release of the fixing constraint, and the boundary exhibits a semicircular shape. The aforementioned S302 is, For the entire T-shaped cross-section component consisting of a substrate and a laminated part, the substrate, deposition wall, and the centroid height of the entire component

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[0011] In a second embodiment, a real-time simulation and model prediction system for arc additive manufacturing based on an event sequence is provided, which is used to perform any of the methods of the first embodiment. In the real-time process of arc additive manufacturing of metal structures, an activation guidance module is used to activate units in real time via an event sequence and to provide real-time guidance for the heat source. The simulation module receives input for the activation guidance module, including heat source model parameters, thermal simulation parameters, and mechanical simulation parameters, and performs real-time thermal and mechanical simulations of arc additive manufacturing. The simulation module takes the acquired stress diffusion distribution and normal stress interface correction deviation as input, constructs a theoretical model for simplified calculations, and includes a prediction module for correcting the calculation model predictions, the event sequence is used to set up virtual blocks to move in three-dimensional space along a predetermined path and time so as to add the influence of the three-dimensional field to the path that the virtual blocks traverse.

[0012] In a third embodiment, a computer storage medium is provided on which a computer program is stored, and when the computer program is executed on a computer, it performs any of the methods of the first embodiment.

[0013] In the fourth embodiment, an electronic device is provided, and said electronic device is Memory configured to store computer programs, The system comprises a processor configured to execute the computer program in order to perform any of the methods of the first embodiment.

[0014] The beneficial effects of this invention are as follows: 1. In this invention, by employing an event sequence method, real-time simulation of the arc additive manufacturing process is performed, significantly reducing the difficulty of modeling. Unit activation no longer depends on numerous analysis steps, and unit activation can be performed in a single analysis step along with the event sequence, effectively reducing the complexity of operation. By defining an event sequence, only position coordinates and time information are required for complex path planning, making it easier to simulate the arc additive manufacturing process for curved welds and irregularly shaped structural parts.

[0015] 2. In this invention, the real-time prediction accuracy of the model is effectively improved by considering the stress diffusion distribution that occurs at the boundary between the laminated portion and the substrate due to repeated heat input, and by correcting and predicting the theoretical calculation of residual stress during arc additive manufacturing.

[0016] 3. In this invention, the unit is activated by an event sequence to guide the heat source, enabling simulation of high-temperature, high-speed multi-layer multi-pass deposition in arc additive manufacturing usage scenarios. Real-time thermal and mechanical simulation of arc additive manufacturing is used to obtain the stress diffusion effect due to repeated heat input at the boundary between the laminated portion of dissimilar materials and the substrate. By performing theoretical calculations and corrected predictions of residual stress in a T-shaped cross-section integrated part manufactured by arc additive manufacturing, taking the stress diffusion effect into account, the deposition stress and deformation during arc additive manufacturing are efficiently and accurately predicted in real time. [Brief explanation of the drawing]

[0017] [Figure 1] This is a schematic diagram showing the overall flow of the real-time simulation and model prediction method for arc additive manufacturing based on event sequences according to the present invention. [Figure 2] This is a schematic diagram illustrating a simulation that controls unit activation and heat source movement in an event sequence. [Figure 3a] This is a schematic diagram showing the molten pool configuration of a double ellipsoid heat source model. [Figure 3b] This is a schematic diagram showing the geometric parameters of the molten pool in the double ellipsoid heat source model. [Figure 4] This is a schematic diagram showing the thermal boundary conditions for a T-shaped cross-section integrated component model. [Figure 5a] This is a schematic diagram showing the cross-sectional stress field of a single-line deposition simulation model. [Figure 5b] This is a schematic diagram showing the cross-sectional stress field of a double-line deposition simulation model. [Figure 5c] This is a schematic diagram showing the cross-sectional stress field of the triple-line deposition simulation model. [Figure 6a] This is a schematic diagram showing the constraints of the fixing device in a single-line deposition simulation model. [Figure 6b] This is a schematic diagram showing the central narrow channel constraint in a single-line deposition simulation model. [Figure 7] This is a schematic diagram showing the temperature field (in °C) during printing in a single-line deposition simulation model. [Figure 8] This is a schematic diagram showing the residual stress distribution before and after the release of the fixing device constraints in the arc additive manufacturing process. [Figure 9] This is a schematic diagram showing the stress diffusion in the deposited layer before and after the release of the fixing constraints on a T-shaped cross-section integrated component model. [Figure 10] This is a comparison curve of theoretical and simulated stresses for three integrated component models after deviation correction. [Figure 11] This is a schematic diagram of the geometric parameters of a T-shaped integrated component consisting of a substrate and a laminated portion. [Modes for carrying out the invention]

[0018] The present invention will be further described below with reference to examples. The following description of examples is intended to aid in understanding the present invention. Those skilled in the art should note that many modifications can be made without departing from the principles of the present invention, and these improvements and modifications are also within the scope of protection of the present invention. [Examples]

[0019] With the continuous improvement of computer performance, three-dimensional transient thermal-mechanical coupled numerical models are gradually being applied to simulation studies of arc welding processes, which share several similarities with arc additive manufacturing processes. Numerical models can serve as an effective auxiliary tool for obtaining thermal-mechanical parameter information from actual arc additive manufacturing experiments, and by expanding the range of parameter values, it is possible to obtain large amounts of data results that are difficult to acquire experimentally. Therefore, the development of accurate and rapid real-time simulation and model prediction methods for stress in multi-layer multi-pass additive manufacturing, combined with thermal-mechanical theoretical models of arc additive manufacturing, is extremely important.

[0020] In this regard, Embodiment 1 of this application provides a real-time simulation and model prediction method for arc additive manufacturing based on event sequences. This enables real-time simulation of multi-layer multi-pass stacking under high-temperature and high-speed conditions, as well as efficient and accurate prediction of stacking stress and deformation, in arc additive manufacturing applications.

[0021] As shown in Figure 1, the method specifically includes the following steps.

[0022] S1, in the real-time process of arc additive manufacturing of metal structures, an event sequence is used to activate units in real time and to guide the heat source in real time. The event sequence is used to define a three-dimensional field that changes with time and space, which is equivalent to setting a virtual block to move in three-dimensional space along a predetermined path and time so that the three-dimensional field influences the path the virtual block takes. Therefore, the event sequence method can be easily applied to real-time simulation of the electric arc additive manufacturing process.

[0023] S1 includes the following steps:

[0024] S101 reconfigures the real-time process of arc additive manufacturing using an event sequence, activating each unit one by one along the path traversed by the virtual block of the event sequence. Here, the size of the virtual block is definable and is used to control the range of units to be activated.

[0025] As shown in Figure 2, in the real-time simulation, multilayer printing deposition of the WAAM laminated portion 2 is performed on the substrate 1 along the deposition path 3. The layer below, where deposition is already completed, is designated as the previous layer 4, and the deposition layer above, where printing is in progress, is designated as the current layer 5. In the current layer 5, the adjacent unit in front of the location of the moving heat source 6 is designated as the unit to be activated 7. Since the temperature fields of different simulation models are different, the temperature field values ​​can be normalized in the temperature field cloud map, with the highest temperature set to 1 and the lowest temperature to 0. In this embodiment, the event sequence function module of the ABAQUS software is used to perform a real-time activation simulation of the unit.

[0026] In S102, the position of the virtual block in the event sequence is guided as the position of the moving heat source, and by using the Goldak double ellipsoid heat source model, the creation of user subroutines is eliminated, and the workload for constructing the heat source model guidance is greatly reduced.

[0027] S101 and S102 enable the realization of the additive manufacturing effect and heat source movement throughout the entire arc additive manufacturing process using the event sequence method.

[0028] As shown in Figures 3a and 3b, the Goldak double ellipsoid heat source model is a volumetric heat source model that takes laser transmission into account and is relatively accurate and practical for simulating melting phenomena in arc additive manufacturing. In the Goldak double ellipsoid heat source model, the heat source is described non-axisymmetrically, and its power density exhibits a Gaussian distribution within the composite double ellipsoid. The temperature gradient in front of the heat source is much steeper than the temperature gradient at the trailing edge of the molten pool, and the power densities in the forward and backward regions of the arc center are defined separately.

[0029] Power density distribution q in the positive quadrant of the Z axis f It can be expressed by the following formula.

[0030]

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[0031] Power density distribution q in the negative quadrant of the Z axis f It can be expressed by the following formula.

[0032]

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[0033] Here,

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[0034] As shown in Figure 3b, the Goldak double ellipsoid heat source model allows for the simulation of different arc additive manufacturing processes by adjusting the model parameters, and parameters corresponding to the size and shape of the molten pool can be obtained.

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[0035] Based on the S2 and S1 event sequence methods, the heat source model parameters, thermal simulation parameters, and mechanical simulation parameters are set, and a real-time thermal-mechanical simulation of arc additive manufacturing is performed.

[0036] S1 includes the following steps:

[0037] S201 sets thermal simulation parameters and mechanical simulation parameters to construct a coupled thermal-mechanical simulation model. The setting of thermal simulation parameters includes setting thermal boundary conditions, latent heat of phase change, thermal conductivity, and specific heat, while the setting of mechanical simulation parameters includes setting thermal expansion coefficient, material mechanical parameters, and boundary mechanical constraints.

[0038] In real-time simulations, the thermal simulation parameters that need to be set include thermal boundary conditions, latent heat of phase change, thermal conductivity, and specific heat. Subsequently, the change in the 3D temperature field is calculated in real time using the event sequence method. Furthermore, when calculating the change in the 3D stress-strain field in real time, the real-time results of the 3D temperature field are used as known input conditions, and the change curves of mechanical simulation parameters such as the coefficient of thermal expansion, mechanical parameters of the material, and boundary mechanical constraints are determined along with the temperature field, thereby calculating the results of the 3D stress-strain field of the guide model before and after the release of the fixture constraints in real time.

[0039] In arc additive manufacturing, boundary mechanical constraints are applied to the structure before the start of the additive manufacturing process to suppress deformation of the molded structure. These constraints are usually achieved by placing fixtures on the substrate, and the fixture constraints are released after cooling at the end of the additive manufacturing process. At the same time, the thermal conductivity, specific heat, coefficient of thermal expansion, and mechanical parameters of the material (Young's modulus, Poisson's ratio, yield strength) of the molded structure all change with the temperature field.

[0040] As shown in Figure 4, in setting the thermal boundary conditions for a T-shaped integrated part, the thermal emissivity of the surface of the integrated part is

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[0041] S202 constructs a linear deposition simulation model to simulate the deposition process of multilayer multipass arc additive manufacturing, and obtains the stress diffusion distribution of the deposited layer based on the deposition stress simulation results.

[0042] In S202, as shown in Figures 5a, 5b, and 5c, the linear deposition simulation model includes single-line, double-line, and triple-line deposition simulation models. All three simulation models are set up as multi-layer multi-pass deposition sections with identical geometric dimensions. In the single-line deposition simulation model, the deposited layers are located in the center of the substrate; in the double-line deposition simulation model, the deposited layers are located at both longitudinal edges of the substrate; and in the triple-line deposition simulation model, the deposited layers are located at both longitudinal edges and in the center.

[0043] As shown in Figures 6a and 6b, all three simulation models employ the same fixture constraint method and mesh generation method. Taking the single-line deposition simulation model as an example, the fixture constraint has a significant impact on the final deformation of the single-line deposition. To effectively simulate actual printing conditions, a rigid support plate is added under the substrate, with the top surface of the support plate as the master surface and the bottom surface of the substrate as the slave surface, creating rigid contact between the two. This ensures that the entire component moves only along the positive Y-axis throughout the entire printing process. In actual operation, the substrate needs to be clamped to secure it to the printing platform. This condition is simulated by fixing the position of the red dot on the top surface of the substrate, and the fixture constraint is released at the end of the simulation process. Since the deformation of this type of simulation model is mainly warping deformation at both ends, the stress and deformation results of the simulation model are obtained by selecting a unit of a narrow segment of the substrate and constraining its displacement without constraining the rotation angle, simultaneously with the final release of the fixture constraint.

[0044] As shown in Figure 7, in the arc additive manufacturing process, the first layer of multi-pass interlayer printing is performed first. After the first layer is printed, interlayer cooling occurs, followed by the printing of the second layer, and so on. In the single-line deposition simulation model, the transient method of ABAQUS software is used to analyze the temperature field and stress / strain field of the arc additive manufacturing process. In the actual printing process, by controlling the temperature, the effect of having only the newly printed parts reach the melting point can be obtained, effectively reducing the adverse effects on molding quality due to material collapse during additive manufacturing.

[0045] Based on the stress diffusion distribution and normal stress interface correction deviation obtained from the thermal-mechanical coupled real-time simulations of S3 and S2, a theoretical model for a simplified calculation of the residual stress field is constructed, and the calculation model predictions are corrected. [Examples]

[0046] Based on Example 1, Example 2 of this application provides a real-time simulation and model prediction method for arc additive manufacturing based on an event sequence, the method being:

[0047] S1, In a real-time process of arc additive manufacturing of metal structures, the steps include activating the unit in real time using an event sequence and guiding the heat source in real time.

[0048] Based on the event sequence method of S2 and S1, the heat source model parameters, thermal simulation parameters, and mechanical simulation parameters are set, and a real-time thermal-mechanical simulation of arc additive manufacturing is performed.

[0049] The process includes constructing a theoretical model for a simplified calculation of the residual stress field based on the stress diffusion distribution and normal stress interface correction deviation obtained from the thermal-mechanical coupled real-time simulations of S3 and S2, and correcting the calculation model predictions, wherein the event sequence is used to set up virtual blocks to move in three-dimensional space along a predetermined path and time so as to add the influence of the three-dimensional field to the path that the virtual blocks traverse.

[0050] S3 includes the following steps:

[0051] S301. A theoretical model for simplified calculations is constructed. The theoretical model for simplified calculations consists of a substrate and a layered portion in the arc additive manufacturing process, and includes the stress field distribution before the release of the fixing constraints and the stress field distribution after the release of the fixing constraints.

[0052] Furthermore, at the boundary between the laminated portion and the substrate, a diffusion effect of deposited stress occurs before and after the release of the fixing device, and the area exhibits a semi-circular shape. In this application, by analyzing scenarios with and without considering the diffusion effect of deposited stress, S301 includes the following steps.

[0053] In S3011, if the diffusion effect of depositional stress is not considered, the development and redistribution of the residual stress field do not change along the longitudinal length L, and edge effects are not considered. As shown in Figure 8, before the substrate fixing constraints are released, depositional tensile stress is generated in the depositional wall by the arc additive manufacturing process, and compressive stress is generated in the substrate to balance it. It is assumed that the stresses in the substrate and depositional wall are uniformly distributed in their respective areas, with abrupt changes at the boundary. The equivalent concentrated stresses in the substrate and depositional wall are respectively

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[0054] After releasing the constraints on the substrate's fasteners, the entire end of the component becomes free. The two equivalent concentrated forces are released, and an internal bending moment M is generated. The internal stresses of the structure are redistributed, becoming the final residual stresses of the component. The tensile stress above the neutral axis decreases linearly. If the height of the depositional wall is sufficient, compressive stress will be generated at the top of the depositional wall after stress redistribution.

[0055] S3012. Considering the diffusion effect of deposition stress, as shown in Figure 9, before the fixture constraint is released, the deposition normal stress is not limited to the deposition wall but tends to diffuse radially in the substrate portion below the interface. This is because the substrate below the interface is close to the deposition layer and is affected by thermal expansion and contraction. During the printing process, this portion undergoes repeated heating-cooling-heating cycles, generating large deposition stress. Therefore, the deposition stress also diffuses into the substrate. The stress on the deposition wall and substrate in the diffusion region and transition diffusion region exhibits an almost semicircular shape with a radius approximately equal to the deposition width. This diffusion effect still persists even after the constraint is released.

[0056] Furthermore, as shown in Figures 9 and 10, the correction deviation

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[0057] Different deposition models have different coordinates for the deviation location, and this is related to many factors, including the model's geometry, heat source parameters, and depositional material. (Residual stress correction deviation)

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[0058] In S302, the calculation model prediction is corrected. S302 includes the following steps.

[0059] As shown in Figure 11, for the entire T-shaped cross-section component consisting of a substrate and a laminated portion, the centroidal height of the substrate, the laminated wall, and the entire component is as follows:

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[0060]

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[0063] Here,

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[0064] S3022, moment of inertia of a T-shaped cross section

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[0065] Specifically, the metal wire material used in the additive manufacturing process is the same as the substrate material, and the centroid height of the entire component is

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[0066]

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[0067] S3023, Before releasing the constraints on the fixtures on the substrate, the deposition stress on the substrate during the arc additive manufacturing process

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[0068] S3023, Before releasing the constraints on the fixtures on the substrate, the deposition stress on the substrate during the arc additive manufacturing process

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[0069]

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[0070] Since the residual stresses in the substrate and the deposited wall are assumed to be uniformly distributed across their respective rectangular cross-sections, the corresponding equivalent concentrated forces act at the centroid of each rectangular cross-section, i.e., at the height of the substrate and the wall.

[0071] S3024, Before releasing the restraint of the fixture on the substrate, equivalent concentration

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[0072]

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[0073] S3025, after releasing the constraints on the fixing device on the substrate, the deformation curvature of the model

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[0074] Specifically, after the clamp constraints on the substrate are released, the deformation curvature of the model can be calculated using equation (9), and the parameters for calculating the curvature are the material and deposition factors, which are determined by the deposition stress and the elastic modulus E of the material.

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[0075]

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[0076] Here,

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[0077] S3026, After releasing the constraints on the fixing device on the substrate, normal stress interface deviation throughout the entire arc additive manufacturing process.

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[0078] After the constraints on the substrate are released, the stress field is redistributed as a result of the superposition of the initial deposition stress field and the stress caused by the bending moment M, and finally, the normal stress interface deviation occurs throughout the entire arc additive manufacturing process.

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[0079]

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[0080] Here,

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[0081] S3027, downward slope of residual stress field

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[0082]

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[0083] This embodiment also demonstrates the analysis and application of single-line, double-line, and triple-line deposition models for real-time simulation and model prediction methods of arc additive manufacturing based on event sequences.

[0084] As shown in Figure 11, the single-line deposition model has a relatively regular shape. The geometric dimensions of the model are the height of the deposition wall.

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[0085] Based on equations (3) to (11), the longitudinal stress descent gradients of the single-line, double-line, and triple-line deposition models obtained from the calculations are, respectively

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[0086] Considering the diffusion effect of the sedimentary layer, according to the results in Figure 9, the diffusion area is approximately

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[0087] In this embodiment, parts that are identical or similar to those in Embodiment 1 can be referenced to each other and will not be described redundantly in this application. [Examples]

[0088] Based on Examples 1 and 2, Example 3 of this application provides a real-time simulation and model prediction system for arc additive manufacturing based on event sequences, and the target system is

[0089] In the real-time process of arc additive manufacturing of metal structures, an activation guidance module is used to activate units in real time via an event sequence and to provide real-time guidance for the heat source.

[0090] The simulation module receives input for the activation guidance module, including heat source model parameters, thermal simulation parameters, and mechanical simulation parameters, and performs real-time thermal and mechanical simulations of arc additive manufacturing.

[0091] The simulation module takes the acquired stress diffusion distribution and normal stress interface correction deviation as input, constructs a theoretical model for simplified calculations, and includes a prediction module for correcting the calculation model predictions, the event sequence is used to set up virtual blocks to move in three-dimensional space along a predetermined path and time so as to add the influence of the three-dimensional field to the path that the virtual blocks traverse.

[0092] Specifically, the system provided in this embodiment corresponds to the system provided in Examples 1 and 2. Therefore, parts of this embodiment that are identical or similar to those in Examples 1 and 2 can be referenced to one another and will not be repeated in this application.

[0093] In summary, Embodiment 3 of this application, provided in the present invention, is a real-time simulation and model prediction method for arc additive manufacturing based on an event sequence. The event sequence activates a unit and guides the heat source, enabling simulation of high-temperature, high-speed, multi-layer, multi-pass deposition in arc additive manufacturing usage scenarios. Real-time thermal and mechanical simulation of arc additive manufacturing obtains the stress diffusion effect due to repeated heat input at the boundary between the laminated portion of dissimilar materials and the substrate. By performing theoretical calculations and corrected predictions of residual stress in a T-shaped cross-section integrated part produced by arc additive manufacturing, considering the stress diffusion effect, the method achieves efficient, real-time, and highly accurate prediction of deposition stress and deformation during arc additive manufacturing. Furthermore, actual verification has demonstrated the effectiveness of the method of the present invention.

[0094] Explanation of the symbols 1 circuit board 2 WAAM layered section 3. Stacking path 4 Previous layer 5. Current Layer 6 Mobile heat source 7 Units to be activated

Claims

1. A real-time simulation and model prediction method for arc additive manufacturing based on event sequences, S1, In a real-time process of arc additive manufacturing of metal structures, the steps include activating the unit in real time using an event sequence and guiding the heat source in real time, Based on the event sequence method of S2 and S1, the heat source model parameters, thermal simulation parameters, and mechanical simulation parameters are set, and a real-time thermal and mechanical simulation of arc additive manufacturing is performed. A real-time simulation and model prediction method for arc additive manufacturing based on an event sequence, characterized in that it includes the step of constructing a theoretical model for a simplified calculation of the residual stress field based on the stress diffusion distribution and normal stress interface correction deviation obtained from the thermal-mechanical coupled real-time simulations of S3 and S2, and correcting the calculation model prediction, the event sequence is used to set up virtual blocks to move in three-dimensional space along a predetermined path and time so as to add the influence of a three-dimensional field to the path that the virtual blocks pass through.

2. S1 is, S101, Reconstruct the real-time process of arc additive manufacturing using the event sequence, and activate each unit one by one along the path scanned by the virtual block of the event sequence, A real-time simulation and model prediction method for arc additive manufacturing based on an event sequence according to claim 1, comprising the steps of S102, guiding the position of a virtual block in the event sequence as the position of a moving heat source, and using a Goldak double ellipsoid heat source model.

3. S2 is, S201, the step of setting thermal simulation parameters and mechanical simulation parameters to construct a coupled thermal-mechanical simulation model, A real-time simulation and model prediction method for arc additive manufacturing based on an event sequence, according to claim 2, comprising the steps of S202, constructing a linear deposition simulation model to simulate the deposition process of multilayer multipass arc additive manufacturing, and obtaining the stress diffusion distribution of the deposited layer based on the deposition stress simulation results, wherein the setting of the thermal simulation parameters includes setting the thermal boundary conditions, latent heat of phase change, thermal conductivity and specific heat, and the setting of the mechanical simulation parameters includes setting the coefficient of thermal expansion, material mechanical parameters and boundary mechanical constraints.

4. In S202, the linear deposition simulation model includes a single-line deposition simulation model, a double-line deposition simulation model, and a triple-line deposition simulation model, wherein in the single-line deposition simulation model, the layered deposition layer is located in the center of the substrate; in the double-line deposition simulation model, the layered deposition layer is located at both edges in the longitudinal direction of the substrate; and in the triple-line deposition simulation model, the layered deposition layer is located at both edges in the longitudinal direction and in the center, characterized in that this is a real-time simulation and model prediction method for arc additive manufacturing based on an event sequence according to claim 3.

5. S3 includes steps S301, constructing a theoretical model for simplified calculations, and S302, correcting the calculation model predictions. In S301, the theoretical model of the simplified calculation consists of a substrate and a laminated portion in the arc additive manufacturing process, and includes the stress field distribution before the release of the fixing constraint and the stress field distribution after the release of the fixing constraint, and at the boundary between the laminated portion and the substrate, a diffusion effect of the deposition stress occurs before and after the release of the fixing constraint, and exhibits a semicircular shape. The aforementioned S302 is, S3021, Regarding an integrated component with a T-shaped cross-section consisting of a substrate and a laminated portion, the substrate, the laminated wall, and the centroid height of the integrated component [Math 1] 、 [Math 2] , and [Math 3] The steps to calculate, S3022, Moment of inertia of a T-shaped cross-section [Math 4] The steps to calculate, S3023, Before releasing the constraints on the fixtures on the substrate, the deposition stress on the substrate during the arc additive manufacturing process [Math 5] Equivalent concentration caused by [Math 6] and pressure inside the substrate [Number 7] The steps to calculate, S3024, Before releasing the restraint of the fixing device on the substrate, equivalent concentration force [Number 8] Positional displacement and internal pressure of the substrate [Number 9] Bending moment around the neutral axis caused by positional displacement [Number 10] The steps to calculate, S3025, After releasing the constraints on the fixing device on the substrate, the deformation curvature of the model [Math 11] The steps to calculate, S3026, After releasing the constraints on the fixing device on the substrate, normal stress interface deviation throughout the entire arc additive manufacturing process. [Math 12] Corrected residual stress field considering [Number 13] The steps are to calculate it using the following formula, [Number 14] Here, [Number 15] This is the height of the neutral axis. [Number 16] Located in the following place, [Number 17] This is a normal stress interface correction deviation caused by stress diffusion in the deposited layer. This correction deviation is applied only to the region where the longitudinal stress is "positive," i.e., the tensile stress region, and remains unchanged in the compressive stress region of the substrate. S3027, Downward slope of residual stress field [Number 18] A real-time simulation and model prediction method for arc additive manufacturing based on an event sequence according to claim 4, comprising the step of calculating a ...

6. A real-time simulation and model prediction system for arc additive manufacturing based on an event sequence, used to perform the method described in any one of claims 1 to 5, In the real-time process of arc additive manufacturing of metal structures, an activation guidance module is used to activate units in real time via an event sequence and to provide real-time guidance for the heat source. The simulation module receives input for the heat source model parameters, thermal simulation parameters, and mechanical simulation parameters corresponding to the activation guidance module, and performs real-time thermal and mechanical simulations of arc additive manufacturing. A real-time simulation and model prediction system for arc additive manufacturing based on an event sequence, characterized in that the acquired stress diffusion distribution and normal stress interface correction deviation from the simulation module are input, a prediction module is included to construct a theoretical model for simplified calculations and to correct the calculation model prediction, and the event sequence is used to set up virtual blocks to move in three-dimensional space along a predetermined path and time so as to add the influence of a three-dimensional field to the path that the virtual blocks travel.

7. A computer storage medium in which a computer program is stored, wherein the computer program, when executed by a computer, performs the method described in any one of claims 1 to 5.

8. It is an electronic device, Memory configured to store computer programs, An electronic device comprising a processor configured to execute the computer program in order to implement the method according to any one of claims 1 to 5.

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