Method and apparatus for simulating spatter behavior in a laser selective melting process, medium

Abstract

The application provides a splash behavior simulation method and device of a laser selective melting process, and a medium, and belongs to the field of metal material additive technology. The method comprises the following steps: forming a simulation flow field by simulating the flow field in a forming cavity used in a fluid dynamics simulation experiment; determining particle parameters of an experimental splash according to a splash experiment image, and determining initial conditions of particle simulation spraying according to the particle parameters; setting a spraying area in the simulation flow field, and controlling a particle spraying simulation source to emit particles meeting the initial conditions; tracking each splash particle in the simulation flow field by using a discrete phase model, and obtaining a splash trajectory of the splash particle according to the initial conditions; setting a capture boundary condition, and determining a removal rate of the splash particle according to the splash trajectory and the capture boundary condition; setting a region of interest, and statistically analyzing a distribution trend of the splash particle in the region of interest according to the splash trajectory. The splash behavior in an LPBF processing process is simulated and analyzed, so that the influence of the splash on the quality of a formed part is reduced.

Description

Technical Field

[0001] This invention relates to the technical field of additive manufacturing of metallic materials, and in particular to a method, equipment, and medium for simulating the spatter behavior of laser selective melting processes. Background Technology

[0002] Laser powder bed melting (LPBF) is a major technology in additive manufacturing of metal materials. It uses a laser as an energy source and scans the metal powder bed layer by layer according to the path planned in the 3D CAD slicing model. The scanned metal powder melts and solidifies to achieve metallurgical bonding and finally obtain the metal parts designed in the model.

[0003] However, the large forming cavity in large laser powder bed melting (LPBF) equipment leads to a high rate of residual spatter, which adversely affects the quality of the formed parts. Although the circulating inert gas flow can effectively remove spatter, residual spatter still affects the quality of the formed parts, and existing technologies rarely simulate the trajectory and residence of residual spatter under the action of the gas flow for a comprehensive study. Summary of the Invention

[0004] The main objective of this application is to propose a method, equipment, and medium for simulating spatter behavior during selective laser melting (LPBF) to simulate, predict, and analyze spatter behavior during LPBF processing, thereby reducing the impact of spatter on the quality of formed parts during LPBF processing.

[0005] To achieve the above objectives, one aspect of this application proposes a method for simulating the spatter behavior of a laser selective melting process, the method comprising:

[0006] A simulated flow field is formed by analyzing the flow field within the forming cavity of the laser powder bed melting equipment used in the fluid dynamics simulation experiment.

[0007] Acquire splash experiment images, determine the particle parameters of the experimental sputtering based on the splash experiment images, and determine the initial conditions for the simulated particle ejection based on the particle parameters;

[0008] A jetting region is set in the simulated flow field, and a particle jetting simulation source is provided on the jetting region. The particle jetting simulation source is controlled to emit particles that meet the initial conditions.

[0009] A discrete phase model is used to track each splashing particle in the simulated flow field, and the splash trajectory of the splashing particle is obtained according to the initial conditions.

[0010] Based on the forming cavity and the spraying area, capture boundary conditions are set, and based on the splash trajectory and the capture boundary conditions, the removal rate of splash particles is determined;

[0011] Based on the set area size and the spray area, a region of interest is set, and based on the splash trajectory, the distribution trend of the splash particles in the region of interest is statistically analyzed.

[0012] Furthermore, the flow field within the forming cavity of the laser powder bed melting equipment used in the fluid dynamics simulation experiment, specifically including:

[0013] Based on the inert gas in the forming cavity, the fluid of the simulated flow field is set, and the governing equations for mass conservation and momentum conservation of the flow field are determined through fluid dynamics to form the simulated flow field;

[0014] Adopting standards A turbulence model is used to simulate the turbulent airflow field formed within the forming cavity in the simulated flow field.

[0015] Furthermore, the acquisition of the splash experiment image and the determination of the particle parameters of the experimental sputtering based on the splash experiment image specifically include:

[0016] The splash experiment image is filtered and segmented to draw the closed contour of the molten pool and splash plume in the forming cavity. Based on the closed contour, the minimum rectangular contour of the splash is extracted.

[0017] Based on the minimum rectangular contour and the splash experiment image, determine the splashing speed, splash pixel area, and total number of splashes;

[0018] Based on the splash test image, determine the scanning direction corresponding to the splash test image and the airflow velocity for the splash test in the forming cavity;

[0019] The diameter of the splashed particles falling into the region of interest within the forming cavity is statistically analyzed, and based on the splashed pixel area and the total number of splashes, particle diameter data and the number of splashed particles with respect to the scanning direction and the airflow velocity are determined.

[0020] The particle parameters are determined based on the number of splashed particles, the splashing velocity, and the particle diameter data.

[0021] Furthermore, the particle parameters include particle number, particle ejection velocity, and particle size; determining the initial conditions for simulated particle ejection based on the particle parameters specifically includes:

[0022] The current fluid velocity of the simulated flow field is obtained, and the number of particles, the particle ejection velocity, and the particle size corresponding to the current fluid velocity are determined to reproduce the splash experiment.

[0023] The set particle density and set particle mass are obtained, and the ejection particle swarm, ejection velocity and ejection angle of the particle ejection simulation source are determined according to the particle size, the particle number and the particle ejection velocity, so as to determine the initial conditions.

[0024] Furthermore, the step of using a discrete phase model to track each splashing particle in the simulated flow field and obtaining the splash trajectory of the splashing particles based on the initial conditions specifically includes:

[0025] Obtain the current fluid density of the simulated flow field, and calculate the acceleration of the splashing particles based on the current fluid velocity, the fluid density, and the initial conditions to determine the splash trajectory;

[0026] The acceleration formula for the splashed particles is as follows:

[0027]

[0028] in, The particle mass of the jet particle swarm is... The current fluid velocity, The fluid density is... The particle density of the jet particle swarm. For additional force, It is resistance. Let be the particle relaxation time. , The molecular viscosity of the fluid. The diameter of the jet particle swarm is given. , This is the relative Reynolds number.

[0029] Furthermore, the step of setting capture boundary conditions based on the forming cavity and the spraying area, and determining the removal rate of splash particles based on the splash trajectory and the capture boundary conditions specifically includes:

[0030] The capture size on the powder bed in the forming cavity is obtained. Taking one side of the spraying area as the starting boundary, the capture boundary is set according to the capture size to form the capture boundary condition.

[0031] According to the splash trajectory, splash particles that fall within the range from the starting boundary to the capture boundary are considered captured splash particles, and the remaining splash particles are considered escape particles.

[0032] The number of captured splash particles and the total number of jet splashes are counted, and the clearance rate is calculated based on the number of captured splash particles and the total number of jet splashes.

[0033] Furthermore, the step of setting a region of interest based on the set area size and the spray area, and statistically analyzing the distribution trend of the splash particles in the region of interest based on the splash trajectory, specifically includes:

[0034] Using one side of the spray area as the starting boundary, the region of interest is set according to the set area size, wherein the region of interest is located within the range from the starting boundary to the capture boundary;

[0035] The region of interest is divided into four regions along the direction away from the spray area. The average diameter and number of splash particles in each of the four regions are counted to obtain the distribution trend.

[0036] Furthermore, the specific steps of controlling the particle jet simulation source to emit particles that satisfy the initial conditions include:

[0037] The particle jet simulation source is controlled to emit the jet particle swarm according to the jet speed and jet angle to satisfy the initial conditions.

[0038] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned method for simulating the spatter behavior of the laser selective melting process.

[0039] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for simulating the spatter behavior of the laser selective melting process.

[0040] The embodiments of this application include at least the following beneficial effects: This application provides a method, device, and medium for simulating the spatter behavior of laser selective melting (LPBF). This scheme simulates the flow field through fluid dynamics and uses a discrete phase model to track each individual spatter particle in the simulated flow field. Based on the coupled simulation of fluid dynamics and the discrete phase model, an interaction model between the airflow field and the jet spatter during LPBF forming is established. The initial conditions for the simulated particle jetting are determined through spatter experimental images to reproduce the spatter behavior during the experiment. According to the initial conditions and the discrete phase model, the spatter trajectory of the spatter particles during the simulation experiment is predicted. The capture boundary conditions and region of interest are set, the spatter removal rate is calculated, and the distribution trend of residual spatter is recorded to analyze and verify the accuracy of the model. By simulating and predicting the spatter behavior during LPBF processing, it is convenient to analyze the spatter behavior and minimize the impact of spatter on the quality of large-size laser powder bed fused parts. Attached Figure Description

[0041] Figure 1 This is a schematic flowchart of a method for simulating the spatter behavior of a laser selective melting process according to an embodiment of this application;

[0042] Figure 2 This is a schematic diagram of a three-dimensional model of a forming cavity for simulating the spatter behavior of a laser selective melting process according to an embodiment of this application;

[0043] Figure 3 This is a schematic diagram of the spatter feature extraction of a method for simulating the spatter behavior of a laser selective melting process according to an embodiment of this application;

[0044] Figure 4 This is a schematic diagram illustrating the calculation of the splash velocity in a method for simulating the splash behavior of a laser selective melting process according to an embodiment of this application.

[0045] Figure 5 This is a schematic diagram of the splash trajectory under different conditions in a simulation method for simulating the splash behavior of a laser selective melting process according to an embodiment of this application;

[0046] Figure 6 This is a comparison of the splash capture rate at different gas flow rates in the simulation results of a method for simulating the splash behavior of a laser selective melting process according to an embodiment of this application.

[0047] Figure 7 This is a comparison chart of the percentage of splashes in the sensing area under experimental and simulated conditions under a gas flow rate of 1.5 m / s, based on an embodiment of the present application, of a method for simulating the splash behavior of a laser selective melting process.

[0048] Figure 8 This is a comparison of the average diameter distribution of splashes in the sensing area under experimental and simulated conditions at a gas flow rate of 1.5 m / s, according to an embodiment of this application, which provides a method for simulating the splash behavior of a laser selective melting process. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying 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 those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0050] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0051] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0053] To facilitate understanding of the inventive concept of this application, before providing a detailed description of the embodiments of this application, the English abbreviations (terms) / related concepts involved in the embodiments of this application will first be explained. The English abbreviations (terms) / related concepts involved in the embodiments of this application are subject to the following interpretations.

[0054] The fundamental axioms of fluid dynamics (CFD) are conservation laws, especially the conservation of mass, the conservation of momentum (also known as Newton's second and third laws), and the conservation of energy.

[0055] The Reynolds number can be used to estimate the effect of fluid viscosity on the description of a problem.

[0056] Discrete Phase Model (DPM) is used to describe the trajectories of a small number of discrete particles (such as particles, droplets, etc.) in a flow field and their interactions with the continuous phase (gas or liquid).

[0057] Laser Powder Bed Fusion (LPBF) is an additive manufacturing technology. Using a laser as the energy source, it scans layer by layer through a metal powder bed following a pre-planned path in a 3D CAD slicing model. The scanned metal powder melts and solidifies to achieve a metallurgical bond, ultimately yielding the metal part designed in the model.

[0058] As described in the background section, the large forming cavity in large laser powder bed melting (LPBF) equipment leads to a high rate of residual spatter, which adversely affects the quality of the formed parts. Although circulating inert airflow can effectively remove spatter, residual spatter still affects the quality of the formed parts, and existing technologies rarely simulate the trajectory and residence of residual spatter under the action of airflow for a comprehensive study.

[0059] Based on this, embodiments of the present invention propose a method, equipment, and medium for simulating spatter behavior during laser selective melting (LPBF) to simulate, predict, and analyze spatter behavior during LPBF processing, thereby reducing the impact of spatter on the quality of formed parts during LPBF processing.

[0060] Figure 1 This is an optional flowchart of the method for simulating the spatter behavior of the laser selective melting process provided in the embodiments of this application. Figure 1 The methods may include, but are not limited to, S100 to S600.

[0061] S100 forms a simulated flow field by utilizing the flow field within the forming cavity of the laser powder bed melting equipment used in fluid dynamics simulation experiments;

[0062] S200: Acquire splash experiment images; determine the particle parameters of the experimental sputtering based on the splash experiment images; and determine the initial conditions for the simulated particle ejection based on the particle parameters.

[0063] S300 sets up a jetting area in the simulated flow field, and a particle jetting simulation source is set on the jetting area. The particle jetting simulation source is controlled to emit particles that meet the initial conditions.

[0064] S400 uses a discrete phase model to track each splashing particle in the simulated flow field and obtains the splash trajectory of the splashing particles based on the initial conditions.

[0065] S500 sets capture boundary conditions based on the forming cavity and the spray area, and determines the removal rate of splash particles based on the splash trajectory and capture boundary conditions;

[0066] S600 sets the region of interest based on the set area size and spray area, and statistically analyzes the distribution trend of splash particles in the region of interest based on the splash trajectory.

[0067] In the embodiments of this application, steps S100 to S600 simulate the flow field through fluid dynamics and use a discrete phase model to track each individual splash particle in the simulated flow field. Based on the coupled simulation of fluid dynamics and the discrete phase model, an interaction model between the airflow field and the jet splash during LPBF forming is established. The initial conditions for simulated particle jetting are determined through splash experiment images to reproduce the splash behavior during the experiment. According to the initial conditions and the discrete phase model, the splash trajectory of the splash particles during the simulation experiment is predicted. The capture boundary conditions and region of interest are set, the splash removal rate is calculated, and the distribution trend of residual splash is recorded to analyze and verify the accuracy of the model. By simulating and predicting the splash behavior during LPBF processing, it is convenient to analyze the splash behavior and minimize the impact of splash on the quality of large-size laser powder bed fused parts.

[0068] In S100, a three-dimensional model is established for the forming cavity of the laser powder bed melting equipment used in the experiment, and the flow field of the forming cavity is simulated using fluid dynamics. The presence of the powder bed or laser source within the forming cavity is ignored, and the inert gas within the forming cavity is set as an ideal incompressible Newtonian fluid with constant properties, serving as the fluid for the simulated flow field. The temperature field within the simulated flow field is set to be constant and uniform, thereby determining the governing equations for mass conservation and momentum conservation of the simulated flow field through fluid dynamics.

[0069] When the inert gas velocity within the forming cavity is too high, the Reynolds number may exceed the critical value, leading to turbulence. Splashing behavior is influenced by the airflow field, resulting in different flight trajectories. Therefore, a standard... A turbulence model is used to simulate the phenomenon of airflow field when the gas velocity in the forming cavity is too high, resulting in turbulence.

[0070] For example, refer to Figure 2 A 1:1 three-dimensional model of the forming 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 forming cavity. The presence of a powder bed or laser source within the forming cavity was ignored, and the inert gas within the forming cavity was assumed to be an ideal incompressible Newtonian fluid with constant properties, serving as the fluid for the simulated flow field. Heat transfer was neglected, and the temperature field within the simulated flow field was assumed to be constant and uniform. Thus, the governing equations for mass conservation and momentum conservation of the simulated flow field were determined through fluid dynamics.

[0071] In this embodiment, through fluid dynamics and standards By combining turbulence models, the airflow field inside the forming cavity can be simulated more accurately, thereby improving the simulation accuracy and the accuracy of determining the flight trajectory of splashed particles in subsequent steps.

[0072] In S200, for the splash experiment images acquired during the experiment, since the laser scanning area of ​​the forming cavity is limited to the scanning direction against the airflow during the experiment ( ) and scanning direction with airflow ( The unidirectional vectors at these two injection positions, i.e., the reference vectors... Figure 2 In the 3D model, the scanning directions of the reverse and forward airflows are along the positive and negative x-axis. Furthermore, the region of interest set within the forming cavity in the experiment is also set along the x-axis. Therefore, the velocity along the y-axis has the least impact on the number of splashes and the capture rate, making it easier to acquire images of particle ejection velocity and angle in the xz plane.

[0073] In the experiment conducted inside the forming cavity, splash images were acquired at different airflow velocities and different laser scanning directions to obtain splash experimental images.

[0074] Reference Figure 3 and Figure 4 The splash experiment images are filtered, segmented, and identified to extract splash features and determine the minimum rectangular contour of each splash. Using this minimum rectangular contour, the splash angle, splash velocity, and splash pixel area of ​​each splash are determined. The number of splashes in each frame is calculated from the splash experiment images to determine the total number of splashes.

[0075] The diameter of the splash particles falling into the region of interest set in the forming cavity is statistically analyzed. Based on the splash particle diameter, the splash particles are divided into different groups corresponding to different airflow velocities, so that the particle diameter data of the splash particles can be selected for different fluid velocities when the initial conditions of the simulation are determined.

[0076] Based on the splash pixel area and the total number of splashes, the number of splash particles corresponding to different airflow velocities and different scanning directions is determined so that when the initial conditions are determined in the simulation, the splash particle swarm can be introduced into the particle jet simulation source to achieve discrete phase model tracking.

[0077] Particle parameters are determined by using data on the number of splashed particles, splash velocity, and particle diameter.

[0078] Particle parameters include: number of particles, particle ejection velocity, and particle size.

[0079] Obtain the current fluid velocity of the simulated flow field. Based on the current fluid velocity, select the particle number, particle ejection velocity, and particle size corresponding to the current fluid velocity from the data on the number of splashed particles, splash velocity, and particle diameter, in order to reproduce the splash experiment.

[0080] Obtain the required particle mass and particle density, and use them as the set particle mass and particle density. Based on the particle number, particle size, particle ejection velocity, set particle mass and set particle density, determine the ejection particle group, ejection velocity and ejection angle of the particle ejection simulation source. The initial conditions are thus formed by the ejection particle group, ejection velocity and ejection angle of the particle ejection simulation source.

[0081] In this embodiment, by using splash experimental images of different flow rates and scanning directions obtained during the experiment, splash particle data related to flow rate and scanning direction are determined. Based on the particle parameters determined by the splash particle data and the particle mass and particle density to be simulated, the parameters of the jet particle swarm, jet velocity and jet angle input to the particle jet simulation source during the simulation are determined, thereby determining the initial conditions.

[0082] In S300, a jetting region is set in the simulated flow field, from which splash particles are ejected. The splash particles are ejected by a particle jetting simulation source in the jetting region. The initial conditions are used as the initial input to the particle jetting simulation source to reproduce the splashing behavior of different splashing experiments.

[0083] As can be seen from S200, based on the number of particles, particle size, and particle ejection speed determined from the image, combined with the set particle mass and set particle density, the ejection particle group, ejection speed, and ejection angle to be ejected are determined to determine the initial conditions. The particle ejection simulation source then emits the ejection particle group according to the ejection speed and ejection angle to satisfy the initial conditions.

[0084] 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, and height (z-axis) 400mm. The splash is set to originate 425mm from the exit boundary, within an area 60mm long and 20mm wide, with a particle spray simulation source located in the spray area.

[0085] In S400, refer to Figure 5 The discrete phase model in FLUNET software is used to track each individual splash particle in the entire simulated flow field. Since the impact of the ejected splash on the entire inert gas flow field is small, unidirectional coupling is used to reduce the computational requirements of the simulation.

[0086] By using a discrete phase model and combining the parameters of the ejected particle swarm in the initial conditions, the acceleration of the splashing particles is calculated, thereby determining the splash trajectory of the splashing particles.

[0087] The motion of discrete particles (splashes) follows Newton's second law in a Lagrange frame of reference. Acceleration is determined by the forces acting on the particles.

[0088] In S500, the capture size on the powder bed in the forming cavity is obtained. Taking one side of the spray area as the starting boundary, the capture boundary is determined by the capture size. The area from one side of the spray area to the capture boundary is the capture area, thus forming the capture boundary conditions.

[0089] Since all splashes except those that are captured escape through the exit, splash particles that fall into the capture area are considered captured splash particles, and the remaining splash particles are considered escaped particles. Splash particles that fall between the starting boundary and the capture boundary are also considered captured splash particles.

[0090] Obtain the number of captured splash particles and the total number of spray splashes, and calculate the clearance rate based on the number of captured splash particles and the total number of spray splashes.

[0091] In the splashing experiment, the powder bed boundary condition was set to "capture" and the forming cavity outlet boundary condition was set to "escape".

[0092] In the S600, the region of interest is set by taking one side of the spray area as the starting boundary and setting the area size.

[0093] The region of interest is located between the starting boundary and the capture boundary, meaning the region of interest is within the capture area.

[0094] The region of interest is divided into four regions along the side away from the spray area. The average diameter of the splash particles in each of the four regions and the number of splash particles in each of the four regions are counted to obtain the distribution trend. By analyzing the distribution trend, the relationship between the amount of splash and the distance between the current region position and the spray area can be analyzed.

[0095] Reference Figure 2 In some embodiments of this invention, in S100, the simulated flow field formation process specifically includes:

[0096] S110: Based on the inert gas in the forming cavity, the fluid of the simulated flow field is set, and the governing equations for mass conservation and momentum conservation of the flow field are determined through fluid dynamics to form the simulated flow field.

[0097] In this embodiment, a three-dimensional model is established for the forming cavity of the laser powder bed melting equipment used in the experiment, and the flow field of the forming cavity is simulated using fluid dynamics. The presence of the powder bed or laser source within the forming cavity is disregarded. The inert gas within the forming cavity is set as an ideal incompressible Newtonian fluid with constant properties, and is used as the fluid in the simulated flow field. The temperature field within the simulated flow field is set to be constant and uniform, thereby determining the governing equations for mass conservation and momentum conservation of the simulated flow field through fluid dynamics.

[0098]

[0099]

[0100] in, For fluid density, For static pressure, For stress tensor, and These are gravity and external forces, respectively.

[0101] S120, adopts standard The turbulence model simulates the turbulent airflow field formed within the forming cavity in the simulated flow field.

[0102] In this embodiment, when the inert gas flow rate within the forming cavity is too high, the Reynolds number may exceed a critical value, leading to turbulence. Since the splashing behavior is affected by the airflow field and exhibits different flight trajectories, a standard... A turbulence model is used to simulate the airflow field phenomenon when the gas velocity inside the forming cavity is too high, resulting in turbulence. Turbulent kinetic energy. and its dissipation rate It can be obtained from the following transport equations:

[0103]

[0104]

[0105] in, It is the velocity component. It is the molecular viscosity of the fluid. This represents the turbulent kinetic energy generation term due to the average velocity gradient. It is the turbulent kinetic energy generated by buoyancy. , and It is a constant. and They are and The Prandtl number for turbulence.

[0106] Calculate turbulent kinetic energy and its dissipation rate To simulate the phenomenon of airflow field when the gas flow velocity in the forming cavity is too high and turbulence is formed.

[0107] Reference Figure 3 and Figure 4 In some embodiments of this invention, in step S200, the process of determining the particle parameters of the experimental sputtering specifically includes:

[0108] S210: Filter and segment the splash experiment image to draw the closed contour of the molten pool and splash plume in the forming cavity. Based on the closed contour, extract the minimum rectangular contour of the splash.

[0109] In this embodiment, reference is made to Figure 3 Median filtering was applied to the splash experiment images to remove salt-and-pepper noise. The filtered images were then processed using image thresholding and area filtering. The contours of the molten pool and splash plumes in the forming cavity were detected in the segmented images, closed contours were drawn, and the splash contours were extracted from the closed contours, thus drawing the minimum rectangular contour of the splash.

[0110] S220 determines the splashing speed, splashing pixel area, and total number of splashes based on the minimum rectangular profile and the splashing experiment image.

[0111] In this embodiment, reference is made to Figure 4 By using the minimum rectangular profile, the splash angle and splash velocity of each splash are determined, and the minimum rectangular profile of the splash is identified. The length of the long side of the rectangle and length Angle with the horizontal line These represent the distance and direction of the splashing behavior during exposure, respectively. The sputtering velocity is obtained from the motion trajectory manifested by the residual morphology, calculated using the following formula:

[0112]

[0113] in, It is the detected splash speed. During the exposure time The distance the splash travels is the length of the long side of the rectangle.

[0114] Using the smallest rectangular outline The area of ​​the splash pixels is determined, and the number of splashes in each frame is calculated using the splash experiment images, thereby determining the total number of splashes.

[0115] S230, based on the splash test image, determine the scanning direction corresponding to the splash test image and the airflow velocity for the splash test in the forming cavity.

[0116] In this embodiment, for the splash experiment images acquired during the experiment, since the laser scanning area of ​​the forming cavity is limited to the scanning direction against the airflow during the experiment ( ) and scanning direction with airflow ( The unidirectional vectors at these two injection positions, i.e., in the 3D model, represent the scanning directions of the reverse and forward airflows along the positive and negative x-axis. Furthermore, since the region of interest within the forming cavity in the experiment is also set along the x-axis, the velocity along the y-axis has the least impact on the number of splashes and the capture rate. Therefore, it is easier to acquire images of particle ejection velocity and angle in the xz plane.

[0117] In the experiment conducted inside the forming cavity, splash images were acquired at different airflow velocities and different laser scanning directions to obtain splash experimental images.

[0118] S240: Calculate the diameter of the splashed particles falling into the region of interest set in the forming cavity, and determine the particle diameter data and the number of splashed particles with respect to the scanning direction and airflow velocity based on the splashed pixel area and the total number of splashes.

[0119] In this embodiment, during the experiment, the powder bed boundary condition is set to "capture," and the forming cavity outlet boundary condition is set to "escape." Splashes can be carried to the outlet by inert gas or fall onto the powder bed. When a splash falls onto the powder bed, its movement stops, and its position and the diameter of the splash particles are recorded. Splashes falling onto the powder bed are considered captured, while splashes passing through the outlet are considered removed.

[0120] Based on the set area size, the region of interest within the forming cavity is set, that is, the same region of interest is divided for the splash simulation process and the splash experiment process.

[0121] The diameter of the splashed particles falling into the region of interest set in the forming cavity is statistically analyzed. The splashed particles are divided into different groups according to different airflow velocities. In order to select the particle diameter data of splashed particles for different fluid velocities when determining the initial conditions in the simulation, so as to achieve inconsistent initial conditions for particle jetting under different flow rates.

[0122] The particle diameter data includes minimum diameter data, maximum diameter data, and average diameter data, and the diameter distribution follows the Rosin-Rammler distribution.

[0123] Based on the splash pixel area and the total number of splashes, the number of splash particles corresponding to different airflow velocities and different scanning directions is determined so that when the initial conditions are determined in the simulation, the splash particle swarm can be introduced into the particle jet simulation source to achieve discrete phase model tracking.

[0124] The number of splashed particles is the average number of splashed particles.

[0125] S250 determines particle parameters based on data on the number of splashed particles, splash velocity, and particle diameter.

[0126] In some embodiments of this invention, in step S200, the process of determining the initial conditions specifically includes:

[0127] S260: Obtain the current fluid velocity of the simulated flow field. Based on the current fluid velocity, determine the number of particles, particle ejection velocity, and particle size corresponding to the current fluid velocity to reproduce the splash experiment.

[0128] In this embodiment, the particle parameters include: particle number, particle ejection velocity, and particle size. The current fluid velocity of the simulated flow field is obtained. Based on the current fluid velocity, the particle number, particle ejection velocity, and particle size corresponding to the current fluid velocity are selected from the splash particle number, ejection velocity, and particle diameter data in S250 to reproduce the splash experiment.

[0129] S270: Obtain the set particle density and set particle mass, and determine the ejected particle swarm, ejection velocity and ejection angle of the particle ejection simulation source according to the particle size, particle number and particle ejection velocity, so as to determine the initial conditions.

[0130] In this embodiment, the particle mass and particle density to be simulated are obtained and used as the set particle mass and set particle density. Based on the particle number, particle size, particle ejection speed, set particle mass and set particle density, the ejection particle group, ejection speed and ejection angle of the particle ejection simulation source are determined. The initial conditions are thus formed by the ejection particle group, ejection speed and ejection angle of the particle ejection simulation source.

[0131] In some embodiments of this invention, in S300, controlling the particle jet simulation source to emit particles that satisfy the initial conditions specifically includes:

[0132] S310 controls the particle jet simulation source to emit a swarm of jet particles according to the jet speed and jet angle to meet the initial conditions.

[0133] In this embodiment, a jetting region is set in the simulated flow field, from which splash particles are ejected. The splash particles are ejected by a particle jetting simulation source in the jetting region. Once the simulated flow field stabilizes, the initial conditions are used as the initial input to the particle jetting simulation source to reproduce the splashing behavior of different splashing experiments.

[0134] As can be seen from S200, based on the number of particles, particle ejection speed, and particle size (particle parameters) determined from the image, combined with the set particle mass and set particle density, the ejection particle group, ejection speed, and ejection angle to be ejected are determined to determine the initial conditions. The particle ejection simulation source then emits the ejection particle group according to the ejection speed and ejection angle to satisfy the initial conditions.

[0135] Reference Figure 5In some embodiments of this invention, in step S400, the process of obtaining the splash trajectory specifically includes:

[0136] S410: Obtain the current fluid density of the simulated flow field. Based on the current fluid velocity, fluid density, and initial conditions, calculate the acceleration of the splashing particles to determine the splash trajectory.

[0137] The formula for calculating the acceleration of splash particles is as follows:

[0138]

[0139] in, Let be the mass of the ejected particle swarm. Given the current fluid velocity, For fluid density, The particle density of the jet particle swarm. For additional force, It is resistance. Let be the particle relaxation time. , The molecular viscosity of the fluid. Where is the diameter of the ejected particle swarm. , This is the relative Reynolds number.

[0140] In this embodiment, the discrete phase model in FLUNET software is used to track each individual splash particle in the entire simulated flow field. Since the impact of the ejected splash on the entire inert gas flow field is small, unidirectional coupling is used to reduce the computational requirements of the simulation.

[0141] By using a discrete phase model and combining the parameters of the ejected particle swarm in the initial conditions, the acceleration of the splashing particles is calculated, thereby determining the splash trajectory of the splashing particles.

[0142] The motion of discrete particles (splashes) follows Newton's second law in a Lagrange frame of reference. Acceleration is determined by the forces acting on the particles.

[0143] The formula for calculating the acceleration of splash particles is as follows:

[0144]

[0145] in, Let be the mass of the ejected particle swarm. Given the current fluid velocity, For fluid density, The particle density of the jet particle swarm. For additional force, It is resistance. Let be the particle relaxation time. , The molecular viscosity of the fluid. Where is the diameter of the ejected particle swarm. , This is the relative Reynolds number.

[0146] Reference Figure 5 and Figure 6 In some embodiments of this invention, in step S500, the process of determining the clearance rate specifically includes:

[0147] S510: Obtain the capture size on the powder bed in the forming cavity, take one side of the spraying area as the starting boundary, and set the capture boundary according to the capture size and the starting boundary to form the capture boundary conditions.

[0148] In this embodiment, based on the capture size of the powder bed in the forming cavity, the capture boundary is determined by taking one side of the spraying area as the starting boundary and the capture size as the capture boundary. The area from one side of the spraying area to the capture boundary is the capture area, thus forming the capture boundary conditions.

[0149] For example, when the spray area is set to be 60mm in length and 20mm in width, the capture dimension is extended by 330mm from the 60mm length of the spray area to determine the capture boundary and the capture area. Splashes falling into this area are captured.

[0150] S520: Based on the splash trajectory, splash particles that fall within the range from the starting boundary to the capture boundary are considered captured splash particles, while the remaining splash particles are considered escape particles.

[0151] In this embodiment, since all splashes except those that are captured escape through the exit, the splash particles that fall into the capture area are considered captured splash particles, and the remaining splash particles are considered escaped particles. Specifically, splash particles that fall between the starting boundary and the capture boundary are considered captured splash particles.

[0152] By observing the trajectory of the splashing particles, we can determine their landing point and thus identify the splashing particles that have fallen into the capture area.

[0153] S530 counts the number of splash particles captured and the number of escaped particles, and calculates the clearance rate based on the number of splash particles captured and the number of escaped particles.

[0154] In this embodiment, the number of captured splash particles and the number of escaped particles are counted, and the clearance rate is calculated based on the number of captured splash particles and the number of escaped particles.

[0155] The capture rate is the percentage of all ejected splashes that are successfully captured. Since all splashes except those captured escape through the exit, the capture rate is calculated using the following formula:

[0156]

[0157] in, It's about the number of splash particles captured. This is the total number of jet splashes. Since in actual splash experiments, some splashes will bounce off the inner wall of the forming cavity and fall onto the powder bed near the outlet, the splash removal rate is determined by subtracting the capture rate from the percentage.

[0158] Reference Figure 6 In some embodiments of this invention, in step S600, the process of determining the distribution trend specifically includes:

[0159] S610, taking one side of the spray area as the starting boundary, sets the region of interest according to the set area size, wherein the region of interest is located within the range from the starting boundary to the capture boundary.

[0160] In this embodiment, the region of interest is set according to the size of the area, with one side of the spraying area as the starting boundary.

[0161] For example, refer to Figure 6 When the spray area is set to be 60mm in length and 20mm in width, based on the set area size of 120mm×60mm, the region of interest is defined as 60mm extending from the 60mm length of the spray area. The region of interest lies within the area between the starting boundary and the capture boundary, i.e., within the capture area.

[0162] S620 divides the region of interest into four regions along the direction away from the spray area, and counts the average diameter and number of splashed particles in the four regions to obtain the distribution trend.

[0163] In this embodiment, the region of interest is divided into four regions along the direction away from the spray area. The average diameter of the splash particles in each of the four regions and the number of splash particles in each of the four regions are counted to obtain the distribution trend. By analyzing the distribution trend, the relationship between the amount of splash and the distance between the current region position and the spray area can be analyzed.

[0164] For example, when the region of interest is a rectangular area of ​​120mm × 60mm, since more than 50% of the residual splashes are located within this 60mm long area, the entire region of interest is divided into four different regions labeled A, B, C, and D. Statistical analysis is performed on the residual splash distribution in each region, and the average splash diameter and number of splashes in the four different regions A, B, C, and D are statistically analyzed to compare and verify the simulation results with experimental data, thereby verifying the accuracy of the splash behavior simulation method.

[0165] Reference Figure 7 Under a gas flow rate of 1.5 m / s, most of the residual splash landed in region D. Experimental results showed that the actual proportion of splash in region D was 76.6% of the total splash; simulation results showed that the proportion of splash in region D was 70.8% of the total splash. The relative error was 11.17%. Furthermore, both experimental and simulation results showed a decreasing trend in the proportion of splash from region D to region A under a gas flow rate of 1.5 m / s.

[0166] Reference Figure 8 Under a gas flow velocity of 1.5 m / s, the average diameter of the splash in region D was experimentally measured to be 140.2 mm. m. The corresponding simulated average diameter is 124. m. The relative error is 13.1%. The corresponding calculations are performed for the remaining regions.

[0167] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method for simulating the spatter behavior of the laser selective melting process. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0168] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment 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.

[0169] Electronic devices include:

[0170] The processor can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to achieve the technical solutions provided in the embodiments of this application.

[0171] The memory can be implemented in the form of read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory and called by the processor to execute the spatter behavior simulation method for the laser selective melting process of the embodiments of this application.

[0172] Input / output interfaces are used to implement information input and output;

[0173] The communication interface is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0174] A bus is used to transfer information between various components of a device, such as processors, memory, input / output interfaces, and communication interfaces.

[0175] The processor, memory, input / output interfaces, and communication interfaces communicate with each other within the device via a bus.

[0176] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for simulating the spatter behavior of the laser selective melting process.

[0177] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0178] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0179] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0180] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0181] The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A method for simulating the spatter behavior of a laser selective melting process, characterized in that, The method includes: A simulated flow field is formed by analyzing the flow field within the forming cavity of the laser powder bed melting equipment used in the fluid dynamics simulation experiment. Acquire splash experiment images, determine the particle parameters of the experimental sputtering based on the splash experiment images, and determine the initial conditions for the simulated particle ejection based on the particle parameters; A jetting region is set in the simulated flow field, and a particle jetting simulation source is provided on the jetting region. The particle jetting simulation source is controlled to emit particles that meet the initial conditions. A discrete phase model is used to track each splashing particle in the simulated flow field, and the splash trajectory of the splashing particle is obtained according to the initial conditions. Based on the forming cavity and the spraying area, capture boundary conditions are set, and based on the splash trajectory and the capture boundary conditions, the removal rate of splash particles is determined; Based on the set area size and the spray area, a region of interest is set, and the distribution trend of the splash particles in the region of interest is statistically analyzed based on the splash trajectory. The flow field within the forming cavity of the laser powder bed melting equipment used in the fluid dynamics simulation experiment, specifically including: Based on the inert gas in the forming cavity, the fluid of the simulated flow field is set, and the governing equations for mass conservation and momentum conservation of the flow field are determined through fluid dynamics to form the simulated flow field; Adopting standards A turbulence model is used to simulate the turbulent airflow field formed within the forming cavity in the simulated flow field. The step of using a discrete phase model to track each splashing particle in the simulated flow field and obtaining the splash trajectory of the splashing particles based on the initial conditions specifically includes: Obtain the current fluid density of the simulated flow field, and calculate the acceleration of the splashing particles based on the current fluid velocity, the fluid density, and the initial conditions to determine the splash trajectory; The acceleration formula for the splashed particles is as follows: in, Let be the mass of the ejected particle swarm. The current fluid velocity, The fluid density is... The particle density of the jet particle swarm. For additional force, It is resistance. Let be the particle relaxation time. , The molecular viscosity of the fluid. Where is the diameter of the ejected particle swarm. , This is the relative Reynolds number.

2. The method for simulating spatter behavior in laser selective melting process according to claim 1, characterized in that, The process of acquiring splash experiment images and determining the particle parameters of the experimental sputtering based on these images specifically includes: The splash experiment image is filtered and segmented to draw the closed contour of the molten pool and splash plume in the forming cavity. Based on the closed contour, the minimum rectangular contour of the splash is extracted. Based on the minimum rectangular contour and the splash experiment image, determine the splashing speed, splash pixel area, and total number of splashes; Based on the splash test image, determine the scanning direction corresponding to the splash test image and the airflow velocity for the splash test in the forming cavity; The diameter of the splashed particles falling into the region of interest within the forming cavity is statistically analyzed, and the particle diameter data and the number of splashed particles are determined based on the splashed pixel area and the total number of splashes, with respect to the scanning direction and the airflow velocity. The particle parameters are determined based on the number of splashed particles, the splashing velocity, and the particle diameter data.

3. The method for simulating spatter behavior in laser selective melting process according to claim 1, characterized in that, The particle parameters include particle number, particle ejection velocity, and particle size; determining the initial conditions for simulated particle ejection based on the particle parameters specifically includes: The current fluid velocity of the simulated flow field is obtained, and the number of particles, the particle ejection velocity, and the particle size corresponding to the current fluid velocity are determined to reproduce the splash experiment. The set particle density and set particle mass are obtained, and the ejection particle swarm, ejection velocity and ejection angle of the particle ejection simulation source are determined according to the particle size, the particle number and the particle ejection velocity, so as to determine the initial conditions.

4. The method for simulating spatter behavior in laser selective melting process according to claim 1, characterized in that, The step of setting capture boundary conditions based on the forming cavity and the spraying area, and determining the removal rate of splash particles based on the splash trajectory and the capture boundary conditions specifically includes: The capture size on the powder bed in the forming cavity is obtained. Taking one side of the spraying area as the starting boundary, the capture boundary is set according to the capture size to form the capture boundary condition. According to the splash trajectory, splash particles that fall within the range from the starting boundary to the capture boundary are considered captured splash particles, and the remaining splash particles are considered escape particles. The number of captured splash particles and the total number of jet splashes are counted, and the clearance rate is calculated based on the number of captured splash particles and the total number of jet splashes.

5. The method for simulating spatter behavior in laser selective melting process according to claim 4, characterized in that, The step of setting a region of interest based on the set area size and the spray area, and statistically analyzing the distribution trend of the splash particles in the region of interest based on the splash trajectory, specifically includes: Using one side of the spray area as the starting boundary, the region of interest is set according to the set area 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 the direction away from the spray area. The average diameter and number of splash particles landing on the four regions are counted to obtain the distribution trend.

6. The method for simulating spatter behavior in laser selective melting process according to claim 3, characterized in that, The specific components of controlling the particle jet simulation source to emit particles that satisfy the initial conditions include: The particle jet simulation source is controlled to emit the jet particle swarm according to the jet speed and jet angle to satisfy the initial conditions.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the method for simulating the spatter behavior of the laser selective melting process according to any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for simulating the spatter behavior of the laser selective melting process as described in any one of claims 1 to 6.

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