Splashing behavior simulation method and device in selective laser melting process and medium

Abstract

The invention provides a splash behavior simulation method and device in the selective laser melting process and a medium, and belongs to the technical field of metal material additive manufacturing. The method comprises the following steps: forming a simulated flow field through a flow field in a forming cavity for a fluid dynamics simulation experiment; according to the splashing experiment image, determining particle parameters of experiment sputtering, and according to the particle parameters, determining initial conditions of particle simulation spraying; setting an injection area in the simulation flow field, and controlling the particle injection simulation source to emit particles meeting initial conditions; tracking and simulating each splashing particle in the flow field by adopting a dispersed phase model, and obtaining a splashing track of the splashing particles according to initial conditions; capturing boundary conditions are set, and the removal rate of splashing particles is determined according to the splashing track and the capturing boundary conditions; and setting a region of interest, and counting the distribution trend of the splashing particles in the region of interest according to the splashing trajectory. The spattering behavior in the LPBF machining process is simulated and analyzed, and the influence of spattering on the quality of formed parts is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of metal material additive, and in particular to a method, a device and a medium for simulating splashing behavior in a laser selective melting process. Background Art

[0002] Laser powder bed fusion (LPBF) technology is a major technical approach in the additive manufacturing of metal materials. It uses laser as the energy source and scans the metal powder bed layer by layer according to the path planned in the 3D CAD slice model. The scanned metal powder is melted and solidified to achieve metallurgical bonding, and finally the metal parts designed by the model are obtained.

[0003] However, the larger forming cavity in large laser powder bed fusion (LPBF) equipment leads to a higher incidence of residual spatter, which has an adverse effect on the quality of formed parts. Although the circulating inert gas flow can effectively remove the spatter, the residual spatter still affects the quality of formed parts. In the existing technology, the trajectory and residence of the residual spatter under the action of the gas flow are rarely simulated for comprehensive research. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a method, equipment and medium for simulating the spatter behavior of the laser selective melting process, so as to simulate, predict and analyze the spatter behavior during the LPBF process, so as to reduce the influence of spatter on the quality of the formed parts during the LPBF process.

[0005] To achieve the above-mentioned purpose, one aspect of an embodiment of the present application provides a method for simulating spatter behavior in a laser selective melting process, the method comprising: A simulated flow field is formed by using the flow field in the forming cavity of a laser powder bed melting device used in a fluid dynamics simulation experiment; Acquire a splash test image, determine the particle parameters of the experimental sputtering according to the splash test image, and determine the initial conditions of the particle simulation injection according to the particle parameters; An injection region is set in the simulated flow field, a particle injection simulation source is provided on the injection region, and the particle injection simulation source is controlled to emit particles that meet the initial conditions; Using a discrete phase model to track each splashing particle in the simulated flow field, and obtaining a splashing trajectory of the splashing particle according to the initial conditions; According to the forming cavity and the injection area, a capture boundary condition is set, and according to the splashing trajectory and the capture boundary condition, a removal rate of the splashing particles is determined; An area of ​​interest is set according to the set area size and the spraying area, and a distribution trend of the splashing particles in the area of ​​interest is counted according to the splashing trajectory.

[0006] Furthermore, the flow field in the forming cavity of the laser powder bed melting device used in the fluid dynamics simulation experiment is formed by: According to the inert gas in the forming cavity, the fluid of the simulated flow field is set, and the control equations of mass conservation and momentum conservation of the flow field are determined by fluid dynamics to form the simulated flow field; Adoption of standards The turbulence model simulates the turbulent airflow field formed in the forming cavity in the simulated flow field.

[0007] Further, the acquiring of the splash test image and determining the particle parameters of the experimental sputtering according to the splash test image specifically includes: Performing filtering and segmentation processing on the splash test image, drawing the closed contours of the molten pool and the splash plume in the forming cavity, and extracting the minimum rectangular contour of the splash according to the closed contour; Determine the splashing speed, splashing pixel area and total splashing quantity of the splashing according to the minimum rectangular outline and the splashing test image; According to the splash test image, determining a scanning direction corresponding to the splash test image and an air flow velocity for performing the splash test in the forming cavity; Counting the diameters of the splashing particles falling on the area of ​​interest set in the forming cavity, and determining the particle diameter data and the number of splashing particles with respect to the scanning direction and the airflow speed according to the splashing pixel area and the total number of splashes; The particle parameters are determined according to the number of splashing particles, the sputtering speed and the particle diameter data.

[0008] Furthermore, the particle parameters include the number of particles, the particle injection speed and the particle size; and the initial conditions for the particle simulation injection are determined according to the particle parameters, specifically including: Acquiring a current fluid velocity of the simulated flow field, and determining the number of particles, the particle injection velocity, and the particle size corresponding to the current fluid velocity according to the current fluid velocity, so as to reproduce a splashing experiment; The set particle density and the set particle mass are obtained, and according to the particle size, the particle quantity and the particle injection velocity, the injection particle group, injection velocity and injection angle of the particle injection simulation source are determined to determine the initial condition.

[0009] Further, the adopting of the discrete phase model to track each splashing particle in the simulated flow field and obtaining the splashing trajectory of the splashing particle according to the initial condition specifically includes: Acquiring a current fluid density of the simulated flow field, and calculating the acceleration of the splashing particles according to the current fluid velocity, the fluid density and the initial condition to determine the splashing trajectory; The acceleration calculation formula of the splashing particles is as follows:

[0010] in, is the particle mass of the injected particle group, is the current fluid velocity, is the fluid density, is the particle density of the injected particle group, For additional force, It's resistance. is the particle relaxation time, , is the molecular viscosity of the fluid, is the particle diameter of the injected particle group, , is the relative Reynolds number.

[0011] Further, setting a capture boundary condition according to the forming cavity and the injection area, and determining a removal rate of splashing particles according to the splashing trajectory and the capture boundary condition specifically includes: Acquiring a capture size on the powder bed in the forming cavity, taking one side of the injection area as a starting boundary, and setting a capture boundary according to the capture size to form the capture boundary condition; According to the splashing trajectory, the splashing particles falling within the starting boundary to the capturing boundary are regarded as captured splashing particles, and the remaining splashing particles are regarded as escaped particles; The number of the captured splashing particles and the total number of the sprayed splashes are counted, and the clearance rate is calculated according to the number of the captured splashing particles and the total number of the sprayed splashes.

[0012] Further, setting an area of ​​interest according to the set area size and the spraying area, and counting the distribution trend of the splashing particles in the area of ​​interest according to the splashing trajectory specifically includes: Taking one side of the injection area as the starting boundary, and setting the region of interest according to the set region size, wherein the region of interest is located within the range from the starting boundary to the capture boundary; The region of interest is divided into four regions along a direction away from the spraying region, and the average splash diameters and the splash quantities of the splash particles in the four regions are counted to obtain the distribution trend.

[0013] Further, controlling the particle injection simulation source to emit particles satisfying the initial condition specifically includes: The particle injection simulation source is controlled to emit the injection particle group according to the injection speed and injection angle to meet the initial condition.

[0014] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the spatter behavior simulation method of the laser selective melting process described above is implemented.

[0015] To achieve the above objectives, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for simulating spattering behavior in the laser selective melting process described above is implemented.

[0016] The embodiments of the present application include at least the following beneficial effects: The present application provides a method, device, and medium for simulating spattering behavior in a laser selective melting process. The scheme simulates a simulated flow field through fluid dynamics, and uses a discrete phase model to track each individual spattering particle in the simulated flow field. Based on the coupled simulation of fluid dynamics and discrete phase models, a model of the interaction between the airflow field and the jet spattering in the LPBF forming process is established, and the initial conditions of the particle simulation jet are determined through the spattering experimental image to reproduce the spattering behavior during the experiment. According to the initial conditions and the discrete phase model, the spattering trajectory of the spattering particles in the simulation experiment is predicted, the capture boundary conditions and the area of ​​interest are set, the spatter removal rate is calculated, and the distribution trend of the residual spatter is recorded to analyze and verify the accuracy of the model. The spattering behavior in the LPBF processing process is predicted by simulating and predicting, which facilitates the analysis of the spattering behavior and minimizes the impact of spatter on the quality of large-size laser powder bed fusion formed parts. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic flow chart of a method for simulating spatter behavior in a laser selective melting process provided by an embodiment of the present application; Figure 2 It is a schematic diagram of a three-dimensional model of a forming cavity of a method for simulating splashing behavior in a laser selective melting process provided in an embodiment of the present application; Figure 3 It is a schematic diagram of spatter feature extraction of a spatter behavior simulation method of a laser selective melting process provided by an embodiment of the present application; Figure 4 It is a schematic diagram of calculating the splashing velocity of a method for simulating the splashing behavior of a laser selective melting process provided by an embodiment of the present application; Figure 5It is a schematic diagram of splashing trajectories under different conditions simulated by a method for simulating splashing behavior in a laser selective melting process provided by an embodiment of the present application; Figure 6 This is a comparison chart of splash capture rates at different gas flow rates in a simulation result of a method for simulating splash behavior in a laser selective melting process provided in an embodiment of the present application; Figure 7 This is a comparison chart of the percentage of splashes in the sensing area obtained by experiment and simulation under a gas flow rate of 1.5 m / s for a method for simulating splashes in a laser selective melting process provided by an embodiment of the present application; Figure 8 This is a comparison diagram of the average diameter distribution of splashes in the sensing area obtained by experiment and simulation under a gas flow rate of 1.5 m / s in a method for simulating splashing behavior in a laser selective melting process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0019] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0020] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0022] In order to make the inventive concept of the present application easy to understand, before describing the embodiments of the present application in detail, the English abbreviations (terms) / related concepts involved in the embodiments of the present application are first described. The English abbreviations (terms) / related concepts involved in the embodiments of the present application are subject to the following explanations.

[0023] Computational Fluid Dynamics (CFD) The basic axioms of fluid dynamics are conservation laws, especially conservation of mass, conservation of momentum (also known as Newton's second and third laws), and conservation of energy.

[0024] The Reynolds number can be used to estimate the effect of the viscosity of the fluid on the description of the problem.

[0025] Discrete Phase Model (DPM) is used to describe the motion trajectory of a small number of discrete particles (such as particles, droplets, etc.) in the flow field and their interaction with the continuous phase (gas or liquid).

[0026] Laser Powder Bed Fusion (LPBF) is an additive manufacturing technology that uses laser as the energy source to scan the metal powder bed layer by layer according to the path planned in the 3D CAD slice model. The scanned metal powder is melted and solidified to achieve a metallurgical bonding effect, and finally the metal parts designed by the model are obtained.

[0027] As described in the background art, the larger forming cavity in large laser powder bed fusion (LPBF) equipment leads to a higher incidence of residual spatter, which has an adverse effect on the quality of formed parts. Although the circulating inert gas flow can effectively remove the spatter, the residual spatter still affects the quality of formed parts. However, in the prior art, the trajectory and residence of the residual spatter under the action of the gas flow are rarely simulated for comprehensive research.

[0028] Based on this, an embodiment of the present invention proposes a method, device, and medium for simulating spatter behavior in a laser selective melting process to simulate, predict, and analyze spatter behavior during LPBF processing to reduce the impact of spatter on the quality of formed parts during LPBF processing.

[0029] Figure 1 is an optional flow chart of a method for simulating spatter behavior in a laser selective melting process provided in an embodiment of the present application. Figure 1The method may include but is not limited to including S100 to S600.

[0030] S100, forming a simulated flow field through a flow field in a forming cavity of a laser powder bed melting device used in a fluid dynamics simulation experiment; S200, acquiring a splash test image, determining the particle parameters of the experimental sputtering according to the splash test image, and determining the initial conditions of the particle simulation injection according to the particle parameters; S300, setting a spraying area in the simulated flow field, providing a particle spraying simulation source on the spraying area, and controlling the particle spraying simulation source to emit particles that meet initial conditions; S400, uses a discrete phase model to track each splashing particle in the simulated flow field and obtains the splashing trajectory of the splashing particle based on the initial conditions; S500, setting a capture boundary condition according to the forming cavity and the injection area, and determining a removal rate of splash particles according to the splash trajectory and the capture boundary condition; S600, setting an area of ​​interest according to the set area size and the spraying area, and counting the distribution trend of the splashing particles in the area of ​​interest according to the splashing trajectory.

[0031] S100 to S600 shown in the embodiments of the present application simulate the flow field through fluid dynamics, and use a discrete phase model to track each individual splashing particle in the simulated flow field. Based on the coupled simulation of fluid dynamics and discrete phase models, a model of the interaction between the airflow field and the jet splashing in the LPBF forming process is established, and the initial conditions of the particle simulation injection are determined through the splashing experimental images to reproduce the splashing behavior during the experiment. According to the initial conditions and the discrete phase model, the splashing trajectory of the splashing particles in the simulation experiment is predicted, the capture boundary conditions and the area of ​​interest are set, the splash removal rate is calculated, and the distribution trend of the residual splash is recorded to analyze and verify the accuracy of the model. The splashing behavior in the LPBF processing process is predicted by simulation, which facilitates the analysis of the splashing behavior and minimizes the impact of splashing on the quality of large-size laser powder bed fusion formed parts.

[0032] In S100, a three-dimensional model is established for the forming cavity of the laser powder bed melting device used in the experiment, and fluid dynamics is used to simulate the flow field of the forming cavity. The existence of the powder bed or laser source in the forming cavity is not considered, and the inert gas in the forming cavity is set to an ideal incompressible Newtonian fluid with constant properties, which is used as the fluid of the simulated flow field. The temperature field in the simulated flow field is set to be constant and uniform, so that the control equations of mass conservation and momentum conservation of the simulated flow field are determined by fluid dynamics.

[0033] When the inert gas flow rate in the forming cavity is too large, the Reynolds number may exceed the critical value, resulting in turbulence. The splashing behavior will be affected by the air flow field and present different flight trajectories. Therefore, the standard The turbulence model is used to simulate the phenomenon of the air flow field when the gas flow velocity in the forming cavity is too high to form turbulence.

[0034] For example, refer to Figure 2 A 1:1 three-dimensional model of the molding cavity of the LPBF equipment used in the experiment with a length (x-axis) of 500 mm, a width (y-axis) of 500 mm, and a height (z-axis) of 400 mm was established as the simulation domain. Fluid dynamics was used to simulate the flow field of the molding cavity. The presence of the powder bed or laser source in the molding cavity was not considered. The inert gas in the molding cavity was set as an ideal incompressible Newtonian fluid with constant properties, which was used as the fluid for simulating the flow field. Heat transfer was not considered, and the temperature field in the simulated flow field was set to be constant and uniform, so that the control equations of mass conservation and momentum conservation of the simulated flow field were determined by fluid dynamics.

[0035] In this example, the fluid dynamics and standard The turbulence model is combined to simulate the airflow field in the forming cavity more accurately, thereby improving the simulation degree and the accuracy of determining the flight trajectory of the splashing particles in the subsequent steps.

[0036] In S200, for the splash test images collected during the experiment, since during the experiment, the laser scanning area of ​​the molding cavity is limited to the scanning direction of the reverse airflow ( ) and the scanning direction along the airflow ( ) The unidirectional vectors at these two injection positions, i.e., the reference Figure 2 In the three-dimensional model, the scanning direction of the reverse and forward airflows is along the positive and negative directions of the x-axis. In addition, the region of interest set in the forming cavity in the experiment is also set along the x-axis direction. The speed along the y-axis has the least effect on the number of splashes and the capture rate, so it is easier to collect images of particle injection speed and angle in the xz plane.

[0037] In the experiment conducted in the forming cavity, splash images at different air flow velocities and different laser scanning directions were collected to obtain splash experimental images.

[0038] Reference Figure 3 and Figure 4 , filter, segment and identify the splash test images, extract splash features, and determine the minimum rectangular contour of the splash. Through the minimum rectangular contour, the splash angle, splash speed and splash pixel area of ​​each splash are determined. Through the splash test images, the number of splashes in each frame is calculated to determine the total number of splashes.

[0039] The diameters of the splashing particles falling in the area of ​​interest set in the forming cavity are counted, and the splashing particles are divided into different groups corresponding to different air flow velocities according to the diameters of the splashing particles, so that the particle diameter data of the splashing particles can be selected for different fluid velocities when simulating to determine the initial conditions.

[0040] According to the splash pixel area and the total splash number, the number of splash particles corresponding to different airflow velocities and different scanning directions is determined, so that when the initial conditions are determined by simulation, the splash particle group can be introduced into the particle injection simulation source to realize discrete phase model tracking.

[0041] The particle parameters are determined by the data of the number of spattering particles, sputtering velocity and particle diameter.

[0042] Particle parameters include: particle number, particle injection speed and particle size.

[0043] The current fluid velocity of the simulated flow field is obtained, and according to the current fluid velocity, the number of particles, the particle injection velocity and the particle size corresponding to the current fluid velocity are selected from the splashing particle number, the splashing velocity and the particle diameter data, so as to reproduce the splashing experiment.

[0044] The particle mass and particle density required for simulation are obtained, and used as the set particle mass and the set particle density. The ejection particle group, ejection velocity and ejection angle of the particle ejection simulation source are determined according to the particle number, particle size, particle ejection velocity, the set particle mass and the set particle density. The initial conditions are formed by the ejection particle group, ejection velocity and ejection angle of the particle ejection simulation source.

[0045] In this embodiment, the splashing particle data about the flow rate and scanning direction are determined by using the splashing experimental images of different flow rates and different scanning directions obtained during the experiment. The particle parameters and the particle mass and particle density required to be simulated are determined by the splashing particle data, and the parameters of the injection particle group, injection velocity and injection angle input by the particle injection simulation source during the simulation are determined, thereby determining the initial conditions.

[0046] In S300, a spraying area is set in the simulated flow field, splashing particles are sprayed from the spraying area, and the splashing particles are sprayed by a particle spraying simulation source in the spraying area. The initial conditions are used as initial inputs of the particle spraying simulation source to reproduce the splashing behaviors of different splashing experiments.

[0047] It can be known from S200 that according to the number of particles, particle size, and particle injection speed determined by the image, combined with the set particle mass and the set particle density, the injection particle group, injection speed, and injection angle to be injected are determined to determine the initial conditions, and the particle injection simulation source emits the injection particle group at the injection speed and injection angle to meet the initial conditions.

[0048] For example, refer to Figure 2 The dimensions of the molding cavity of the LPBF equipment used in the experiment are: length (x-axis) 500mm, width (y-axis) 500mm, height (z-axis) 400mm. The splash is set to be ejected from an area 425mm away from the outlet boundary, with a length of 60mm and a width of 20mm, and a particle ejection simulation source is set in the ejection area.

[0049] In S400, refer to Figure 5 ,The discrete phase model in FLUNET software is used to track each individual splashing particle in the entire simulated flow field. ,Since the splashing of the jet has little effect on the entire inert gas flow field, ,one-way coupling is adopted to reduce the computational ,demand of the simulation.

[0050] The discrete phase model is used to calculate the acceleration of the splashing particles in combination with the parameters of the spraying particle group in the initial conditions, thereby determining the splashing trajectory of the splashing particles.

[0051] The motion of the discrete particles (splashes) follows Newton's second law in the Lagrangian reference frame. The acceleration is determined by the forces acting on the particles.

[0052] In S500, the capture size on the powder bed in the forming cavity is obtained, and one side of the injection area is used as the starting boundary. The capture boundary is determined by the capture size, and the capture area from one side of the injection area to the capture boundary is used as the capture area to form a capture boundary condition.

[0053] Since all splashes except the captured splashes escape through the outlet, the splash particles that fall into the capture area are regarded as captured splash particles, and the remaining splash particles are regarded as escaped particles. That is, the splash particles that fall into the range from the starting boundary to the capture boundary are regarded as captured splash particles.

[0054] The number of captured splash particles and the total number of ejected splashes are obtained, and the removal rate is calculated based on the number of captured splash particles and the total number of ejected splashes.

[0055] Among them, during the splashing experiment, the powder bed boundary condition is set to "capture", and the forming cavity outlet boundary condition is set to "escape".

[0056] In S600, a region of interest is set with one side of the spraying region as a starting boundary and by using a set region size.

[0057] The region of interest is within the range from the starting boundary to the capture boundary, that is, the region of interest is within the capture region.

[0058] The area of ​​interest is divided into four areas along the side away from the spraying area. The average splash diameter of the splashing particles in the four areas and the number of splashing particles in the four areas are counted to obtain the distribution trend. Through the distribution trend, the relationship between the splashing amount and the distance between the current area position and the spraying area can be analyzed.

[0059] Reference Figure 2 In some embodiments of one aspect of the present invention, in S100, the process of simulating flow field formation specifically includes: S110, setting the fluid of the simulated flow field according to the inert gas in the forming cavity, and determining the control equations of mass conservation and momentum conservation of the flow field through fluid dynamics to form a simulated flow field.

[0060] In this embodiment, a three-dimensional model is established for the forming cavity of the laser powder bed melting device used in the experiment, and fluid dynamics is used to simulate the flow field of the forming cavity. The presence of the powder bed or laser source in the forming cavity is not considered, and the inert gas in the forming cavity is set to an ideal incompressible Newtonian fluid with constant properties, which is used as the fluid for simulating the flow field. The temperature field in the simulated flow field is set to be constant and uniform, so that the control equations of mass conservation and momentum conservation of the simulated flow field are determined by fluid dynamics.

[0061]

[0062]

[0063] in, is the fluid density, is the static pressure, is the stress tensor, and are gravity and external force respectively.

[0064] S120, using standard The turbulence model simulates the turbulent airflow field formed in the forming cavity in the simulated flow field.

[0065] In this embodiment, when the inert gas flow rate in the forming cavity is too large, the Reynolds number may exceed the critical value, resulting in turbulence, and the splashing behavior will be affected by the air flow field and present different flight trajectories. Therefore, the standard Turbulence model is used to simulate the phenomenon of air flow field when the gas velocity in the forming cavity is too high to form turbulence. Turbulent kinetic energy and its dissipation rate It can be obtained from the following transport equation:

[0066]

[0067] in, is the velocity component, is the molecular viscosity of the fluid, represents the turbulent kinetic energy generation term due to the mean velocity gradient, It is the turbulent kinetic energy due to buoyancy. , and is a constant. and They are and The turbulent Prandtl number.

[0068] Calculating turbulent kinetic energy and its dissipation rate In order to simulate the phenomenon of air flow field when the gas flow velocity in the forming cavity is too high to form turbulence.

[0069] Reference Figure 3 and Figure 4 In some embodiments of one aspect of the present invention, in S200, the process of determining the particle parameters of the experimental sputtering specifically includes: S210, filtering and segmenting the splash test image, drawing the closed contours of the molten pool and the splash plume in the forming cavity, and extracting the minimum rectangular contour of the splash according to the closed contour.

[0070] In this embodiment, refer to Figure 3 , the spatter test image is median filtered to remove salt and pepper noise. The filtered image is processed by image threshold segmentation and area filter segmentation, the contours of the molten pool and spatter plume in the forming cavity are detected from the segmented image, and the closed contour is drawn. The spatter contour is extracted from the closed contour, so as to draw the minimum rectangular contour of the spatter.

[0071] S220, determining the splashing speed, splashing pixel area and total splashing quantity of the splashing according to the minimum rectangular outline and the splashing test image.

[0072] In this embodiment, refer to Figure 4 , through the minimum rectangular outline, determine the splash angle and splash speed of each splash, and identify the minimum rectangular outline of the splash , the length of the long side of the rectangle and length Angle with horizontal Respectively represent the distance and direction of the splash behavior during exposure. The sputtering velocity is obtained from the motion trajectory of the residual morphology, and the calculation formula is as follows:

[0073] in, is the speed of the detected splash, It is during the exposure time The distance the inner splash moves is the length of the long side of the rectangle.

[0074] Minimum rectangular outline , determine the splash pixel area, and through the splash experimental image, calculate the number of splashes in each frame to determine the total number of splashes.

[0075] S230, determining a scanning direction corresponding to the splash test image and an air flow velocity for performing the splash test in the forming cavity according to the splash test image.

[0076] In this embodiment, for the splash test images collected in the experiment, since during the experiment, the laser scanning area of ​​the molding cavity is limited to the scanning direction of the reverse airflow ( ) and the scanning direction along the airflow ( ) are unidirectional vectors at the two injection positions, that is, in the three-dimensional model, the scanning direction of the reverse airflow and the downstream airflow is scanned along the positive and negative directions of the x-axis. In addition, the region of interest set in the forming cavity in the experiment is also set along the x-axis direction, so the speed along the y-axis has the least effect on the number of splashes and the capture rate, so it is easier to collect images about the particle injection speed and angle in the xz plane.

[0077] In the experiment conducted in the forming cavity, splash images at different air flow velocities and different laser scanning directions were collected to obtain splash experimental images.

[0078] S240, counting the diameters of the splashing particles falling on the area of ​​interest set in the forming cavity, and determining the particle diameter data and the number of splashing particles with respect to the scanning direction and the airflow speed according to the splashing pixel area and the total number of splashes.

[0079] In this embodiment, during the experiment, the boundary condition of the powder bed is set to "capture", and the boundary condition of the molding cavity outlet is set to "escape". The spatter can be carried to the outlet by the inert gas or fall on the powder bed. When the spatter falls on the powder bed, the movement stops, and its position and spatter particle diameter and other information are recorded. The spatter is captured when it falls on the powder bed, and it is removed when it passes through the outlet.

[0080] According to the set area size, the area of ​​interest in the forming cavity is set, that is, the splash simulation process and the splash test process are divided into the same area of ​​interest.

[0081] The diameters of the splashing particles falling in the area of ​​interest set in the forming cavity are counted, and the splashing particles are divided into different groups corresponding to different air flow velocities, so that when simulating and determining the initial conditions, the particle diameter data of the splashing particles are selected for different fluid velocities to achieve inconsistent initial conditions for particle injection at different flow rates.

[0082] The particle diameter data include minimum diameter data, maximum diameter data and average diameter data, and the diameter distribution follows the Rosin-Rammler distribution.

[0083] According to the splash pixel area and the total splash number, the number of splash particles corresponding to different airflow velocities and different scanning directions is determined, so that when the initial conditions are determined by simulation, the splash particle group can be introduced into the particle injection simulation source to realize discrete phase model tracking.

[0084] The number of splashing particles is the average number of splashing particles.

[0085] S250, determining particle parameters according to the number of splashing particles, the sputtering velocity and the particle diameter data.

[0086] In some embodiments of an aspect of the present invention, in S200, the process of determining the initial condition specifically includes: S260, obtaining the current fluid velocity of the simulated flow field, and determining the number of particles, the particle injection velocity, and the particle size corresponding to the current fluid velocity according to the current fluid velocity, so as to reproduce the splashing experiment.

[0087] In this embodiment, the particle parameters include: particle number, particle injection velocity and particle size. The current fluid velocity of the simulated flow field is obtained, and according to the current fluid velocity, the particle number, particle injection velocity and particle diameter data in S250 are selected to correspond to the current fluid velocity, so as to reproduce the splashing experiment.

[0088] S270, obtaining the set particle density and the set particle mass, and determining the injection particle group, injection speed and injection angle of the particle injection simulation source according to the particle size, the number of particles and the particle injection speed, so as to determine the initial conditions.

[0089] In this embodiment, the particle mass and particle density required for simulation are obtained and used as the set particle mass and the set particle density. The injection particle group, injection velocity and injection angle of the particle injection simulation source are determined based on the particle number, particle size, particle injection velocity, the set particle mass and the set particle density. The initial conditions are formed by the injection particle group, injection velocity and injection angle of the particle injection simulation source.

[0090] In some embodiments of one aspect of the present invention, in S300, controlling the particle injection simulation source to emit particles that meet the initial condition specifically includes: S310, controlling the particle injection simulation source to emit injection particle groups according to the injection speed and injection angle to meet the initial conditions.

[0091] In this embodiment, a spray area is set in the simulated flow field, and splashing particles are sprayed from the spray area. The splashing particles are sprayed by a particle spray simulation source in the spray area. When the simulated flow field is stable, the initial conditions are used as the initial input of the particle spray simulation source to reproduce the splashing behavior of different splashing experiments.

[0092] It can be known from S200 that according to the number of particles determined by the image, the particle injection speed and the particle size (particle parameters), combined with the set particle mass and the set particle density, the injection particle group, injection speed and injection angle to be injected are determined to determine the initial conditions, and the particle injection simulation source emits the injection particle group according to the injection speed and injection angle to meet the initial conditions.

[0093] Reference Figure 5 In some embodiments of one aspect of the present invention, in S400, the process of obtaining the splash trajectory specifically includes: S410, obtaining the current fluid density of the simulated flow field, and calculating the acceleration of the splashing particles according to the current fluid velocity, fluid density and initial conditions to determine the splashing trajectory.

[0094] The acceleration of splashing particles is calculated as follows:

[0095] in, is the particle mass of the injected particle group, is the current fluid velocity, is the fluid density, is the particle density of the injected particle group, For additional force, It's resistance. is the particle relaxation time, , is the molecular viscosity of the fluid, is the particle diameter of the injected particle group, , is the relative Reynolds number.

[0096] In this embodiment, the discrete phase model in FLUNET software is used to track each individual splashing particle in the entire simulated flow field. Since the splashing of the injection has little effect on the entire inert gas flow field, a one-way coupling is used to reduce the computational requirements of the simulation.

[0097] The discrete phase model is used to calculate the acceleration of the splashing particles in combination with the parameters of the spraying particle group in the initial conditions, thereby determining the splashing trajectory of the splashing particles.

[0098] The motion of discrete particles (splashes) follows Newton's second law in the Lagrangian reference frame. The acceleration is determined by the forces acting on the particles.

[0099] The acceleration of splashing particles is calculated as follows:

[0100] in, is the particle mass of the injected particle group, is the current fluid velocity, is the fluid density, is the particle density of the injected particle group, For additional force, It's resistance. is the particle relaxation time, , is the molecular viscosity of the fluid, is the particle diameter of the injected particle group, , is the relative Reynolds number.

[0101] Reference Figure 5 and Figure 6 In some embodiments of one aspect of the present invention, in S500, the process of determining the clearance rate specifically includes: S510, obtaining a capture size on the powder bed in the forming cavity, taking one side of the injection area as a starting boundary, and setting a capture boundary according to the capture size and the starting boundary to form a capture boundary condition.

[0102] In this embodiment, according to the capture size of the powder bed in the forming cavity, one side of the injection area is used as the starting boundary, and the capture boundary is determined by the capture size. The capture area is from one side of the injection area to the capture boundary to form the capture boundary conditions.

[0103] Exemplarily, when the spray area is set to be 60 mm in length and 20 mm in width, the capture size of 330 mm is extended from the 60 mm length of the spray area to determine the capture boundary and the capture area, and splashes falling into this area are captured.

[0104] S520: According to the splashing trajectory, the splashing particles falling within the starting boundary to the capture boundary are regarded as captured splashing particles, and the remaining splashing particles are escaped particles.

[0105] In this embodiment, since all splashes except the captured splashes escape through the outlet, the splash particles falling into the capture area are regarded as captured splash particles, and the remaining splash particles are regarded as escaped particles, that is, the splash particles falling into the range from the starting boundary to the capture boundary are regarded as captured splash particles.

[0106] Through the splashing trajectory of the splashing particles, the landing point of the splashing particles can be determined, thereby determining the splashing particles that fall into the capture area.

[0107] S530, counting the number of captured splashing particles and the number of escaped particles, and calculating a clearance rate according to the number of captured splashing particles and the number of escaped particles.

[0108] In this embodiment, the number of captured splashing particles and the number of escaped particles are counted, and the clearance rate is calculated based on the number of captured splashing particles and the number of escaped particles.

[0109] The capture rate is the percentage of splashes that are successfully captured among all the splashes ejected. Since all splashes except the captured ones escape through the outlet, the capture rate is calculated. The capture rate formula is:

[0110] in, is the number of splash particles captured, is the total number of spray splashes. Since in the actual splash experiment, part of the splashes will rebound from the inner wall of the forming cavity and fall on the powder bed near the outlet, the splash removal rate is determined by subtracting the capture rate from the percentage.

[0111] Reference Figure 6 In some embodiments of one aspect of the present invention, in S600, the process of determining the distribution trend specifically includes: S610, taking one side of the spraying area as the starting boundary and setting the region of interest according to the set region size, wherein the region of interest is located within the range from the starting boundary to the capture boundary.

[0112] In this embodiment, the region of interest is set based on a set region size, with one side of the spraying region as the starting boundary.

[0113] For example, refer to Figure 6 When the spraying area is set to be 60 mm in length and 20 mm in width, according to the set area size of 120 mm × 60 mm, 60 mm is extended from the length of the spraying area of ​​60 mm to serve as the area of ​​interest. The area of ​​interest is within the starting boundary to the capture boundary, that is, the area of ​​interest is within the capture area.

[0114] S620, dividing the region of interest into four regions along a direction away from the spraying region, and counting the average diameters and numbers of splashing particles in the four regions to obtain a distribution trend.

[0115] In this embodiment, the area of ​​interest is divided into four areas along the direction away from the spraying area, and the average splashing diameters of the splashing particles in the four areas and the number of splashing particles in the four areas are counted to obtain the distribution trend. Through the distribution trend, the relationship between the splashing amount and the current area position and the distance from the spraying area can be analyzed.

[0116] For example, when the region of interest is a rectangular area of ​​120 mm × 60 mm, because more than 50% of the residual splash is located in the 60 mm long area, the entire region of interest is divided into four different areas marked as A, B, C and D, and the residual splash distribution in each area is statistically analyzed. The average diameter and number of splashes in the four different areas of A, B, C and D are counted to compare and verify the simulation results with the experimental data to verify the accuracy of the splash behavior simulation method.

[0117] Reference Figure 7 , under the condition of 1.5m / s gas flow rate, most of the residual splash falls in area D. The experimental results show that the actual proportion of splash in area D accounts for 76.6% of the total splash; the simulation results show that the proportion of splash in area D accounts for 70.8% of the total splash. The relative error is 11.17%. In addition, both the experimental and simulation results show a decreasing trend of the splash proportion from area D to area A under the condition of 1.5m / s gas flow rate.

[0118] Reference Figure 8 Under the condition of 1.5m / s gas velocity, the average diameter of the splash in area D is 140.2 m. The corresponding simulated average diameter is 124 m. The relative error is 13.1%. The rest of the regions are calculated accordingly.

[0119] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned method for simulating the spatter behavior of the laser selective melting process when executing the computer program. The electronic device can be any smart terminal including a tablet computer, a car computer, etc.

[0120] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0121] Electronic equipment includes: The processor may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory may store an operating system and other application programs. When the technical solution provided in the embodiments of this specification is implemented by software or firmware, the relevant program code is stored in the memory, and the processor is used to call and execute the method for simulating the spatter behavior of the laser selective melting process in the embodiments of this application; Input / output interface, used to realize information input and output; Communication interface, used to realize communication interaction between this device and other devices. Communication can be realized through wired methods (such as USB, network cable, etc.) or wireless methods (such as mobile network, WIFI, Bluetooth, etc.); The bus, which transfers information between the various components of the device (such as the processor, memory, input / output interfaces, and communication interfaces); The processor, memory, input / output interface and communication interface are connected to each other through a bus inside the device.

[0122] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for simulating spattering behavior in the above-mentioned selective laser melting process is implemented.

[0123] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0124] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0125] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0126] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0127] The preferred embodiments of the present invention are described in detail above, but the invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for simulating spatter behavior in a laser selective melting process, characterized in that: The method comprises: A simulated flow field is formed by using the flow field in the forming cavity of a laser powder bed melting device used in a fluid dynamics simulation experiment; Acquire a splash test image, determine the particle parameters of the experimental sputtering according to the splash test image, and determine the initial conditions of the particle simulation injection according to the particle parameters; An injection region is set in the simulated flow field, a particle injection simulation source is provided on the injection region, and the particle injection simulation source is controlled to emit particles that meet the initial conditions; Using a discrete phase model to track each splashing particle in the simulated flow field, and obtaining a splashing trajectory of the splashing particle according to the initial conditions; According to the forming cavity and the injection area, a capture boundary condition is set, and according to the splashing trajectory and the capture boundary condition, a removal rate of the splashing particles is determined; An area of ​​interest is set according to the set area size and the spraying area, and a distribution trend of the splashing particles in the area of ​​interest is counted according to the splashing trajectory.

2. The method for simulating spatter behavior in a laser selective melting process according to claim 1, characterized in that: The flow field in the forming cavity of the laser powder bed melting device used in the fluid dynamics simulation experiment is formed by: According to the inert gas in the forming cavity, the fluid of the simulated flow field is set, and the control equations of mass conservation and momentum conservation of the flow field are determined through fluid dynamics to form the simulated flow field; Adoption of standards The turbulence model simulates the turbulent airflow field formed in the forming cavity in the simulated flow field.

3. The method for simulating spattering behavior in a laser selective melting process according to claim 1, characterized in that: The step of acquiring the splash test image and determining the particle parameters of the experimental sputtering according to the splash test image specifically includes: Performing filtering and segmentation processing on the splash test image, drawing the closed contours of the molten pool and the splash plume in the forming cavity, and extracting the minimum rectangular contour of the splash according to the closed contour; Determine the splashing speed, splashing pixel area and total splashing quantity of the splashing according to the minimum rectangular outline and the splashing test image; According to the splash test image, determining a scanning direction corresponding to the splash test image and an air flow velocity for performing the splash test in the forming cavity; Counting the diameters of the splashing particles falling on the region of interest set in the forming cavity, and determining the particle diameter data and the number of splashing particles with respect to the scanning direction and the airflow speed according to the splashing pixel area and the total number of splashes; The particle parameters are determined according to the number of splashing particles, the sputtering speed and the particle diameter data.

4. The method for simulating spattering behavior in a laser selective melting process according to claim 1, characterized in that: The particle parameters include the number of particles, the particle injection speed and the particle size; the initial conditions for the particle simulation injection are determined according to the particle parameters and specifically include: Acquiring a current fluid velocity of the simulated flow field, and determining the number of particles, the particle injection velocity, and the particle size corresponding to the current fluid velocity according to the current fluid velocity, so as to reproduce a splashing experiment; The set particle density and the set particle mass are obtained, and according to the particle size, the particle quantity and the particle injection velocity, the injection particle group, injection velocity and injection angle of the particle injection simulation source are determined to determine the initial condition.

5. The method for simulating spatter behavior in a laser selective melting process according to claim 4, characterized in that: The step of using a discrete phase model to track each splashing particle in the simulated flow field and obtaining the splashing trajectory of the splashing particle according to the initial conditions specifically includes: Acquiring a current fluid density of the simulated flow field, and calculating the acceleration of the splashing particles according to the current fluid velocity, the fluid density and the initial condition to determine the splashing trajectory; The acceleration calculation formula of the splashing particles is as follows: in, is the particle mass of the injected particle group, is the current fluid velocity, is the fluid density, is the particle density of the injected particle group, For additional force, It's resistance. is the particle relaxation time, , is the molecular viscosity of the fluid, is the particle diameter of the injected particle group, , is the relative Reynolds number.

6. The method for simulating spatter behavior in a laser selective melting process according to claim 1, characterized in that: The step of setting a capture boundary condition according to the forming cavity and the injection area, and determining a removal rate of splashing particles according to the splashing trajectory and the capture boundary condition specifically includes: Acquiring a capture size on the powder bed in the forming cavity, taking one side of the injection area as a starting boundary, and setting a capture boundary according to the capture size to form the capture boundary condition; According to the splashing trajectory, the splashing particles falling within the starting boundary to the capturing boundary are regarded as captured splashing particles, and the remaining splashing particles are regarded as escaped particles; The number of the captured splashing particles and the total number of the sprayed splashes are counted, and the clearance rate is calculated according to the number of the captured splashing particles and the total number of the sprayed splashes.

7. The method for simulating spatter behavior in a laser selective melting process according to claim 6, characterized in that: The step of setting an area of ​​interest according to the set area size and the spraying area, and counting the distribution trend of the splashing particles in the area of ​​interest according to the splashing trajectory specifically includes: Taking one side of the injection area as the starting boundary, and setting the region of interest according to the set region size, wherein the region of interest is located within the range from the starting boundary to the capture boundary; The region of interest is divided into four regions along a direction away from the spraying region, and the average diameter and number of splashes of the splashing particles falling on the four regions are counted to obtain the distribution trend.

8. The method for simulating spatter behavior in a laser selective melting process according to claim 4, characterized in that: The step of controlling the particle injection simulation source to emit particles satisfying the initial condition specifically includes: The particle injection simulation source is controlled to emit the injection particle group according to the injection speed and injection angle to meet the initial condition.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the method for simulating spattering behavior in a laser selective melting process according to any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for simulating spatter behavior in a selective laser melting process according to any one of claims 1 to 8 is implemented.

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