Efficient numerical simulation method and system for laser processing molten pool-keyhole dynamic behavior

Abstract

The invention belongs to the technical field of laser manufacturing digital twinning, discloses a laser processing molten pool-keyhole dynamic behavior efficient numerical simulation method and system, and aims to solve the problem of full-weld large-scale simulation computing resource shortage, and adopts a dynamic slippage technology to reduce a large computing domain and reduce the computing resource demand. In order to solve the problem of information confusion caused by LBM high-dimensional data hybrid communication, a dimension reduction communication technology is adopted, high-dimensional data is expanded in one dimension, and efficient and unified communication between parallel processes is guaranteed. In order to solve the problem that the interface position is difficult to track, a serial and parallel mixed mode is adopted on a program architecture, phase field sequence parameters in a sub-process are collected into a host process, and accurate tracking of the interface position is achieved. Based on the lattice Boltzmann method (LBM) which is easy to parallelize, has a solid physical basis and is higher in simulation precision, the MPI parallel computing technology is combined to carry out numerical simulation on the evolution process of the full-weld-seam large-scale molten pool-keyhole in laser processing, and through efficient and accurate computing and communication, the simulation precision of the full-weld-seam large-scale molten pool-keyhole is improved. All-weld-seam large-scale laser processing numerical simulation becomes possible, and technical support is provided for shape prediction of long weld seams of large components.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital twin for laser manufacturing, and particularly relates to a method and system for efficiently numerically simulating the dynamic behavior of a laser processing molten pool-keyhole. Background Art

[0002] Laser processing is an advanced manufacturing technology integrating optics, mechanics, and electronics, with advantages such as high energy density, fast processing speed, and good processing flexibility, becoming an important means for manufacturing metal components. Laser processing can achieve rapid melting and solidification of metal materials, while ensuring processing quality and significantly improving the production efficiency of the processing process, providing effective support for the high-quality and high-efficiency manufacturing of high-performance components of major equipment in fields such as aerospace, rail transit, and marine vessels. However, the interaction process between the high-energy laser beam and the metal material is complex, especially in the molten pool-keyhole region where there is a non-linear thermal-mechanical-flow interaction, and the evolution mechanism of its dynamic behavior is unclear, resulting in some blindness in process control.

[0003] Currently, the research on the dynamic behavior of the laser processing molten pool-keyhole mainly includes experimental observation methods and digital twin numerical simulation methods. The experimental observation method is based on sensors such as sound, light, and electricity to collect various signals during the processing process, and has the following deficiencies: (1) It is difficult for the experimental device to observe the heat transfer-flow data inside the molten pool-keyhole; (2) It is impossible to simultaneously achieve data collection with high time resolution and high spatial resolution; (3) The collected signals are easily interfered by environmental noise during the processing process, and it is difficult to extract and analyze effective data. Therefore, the experimental observation method cannot comprehensively and accurately obtain the high-transient and non-linear thermal-mechanical evolution process of the molten pool-keyhole during the laser processing process.

[0004] The digital twin numerical simulation method is to analyze the physical evolution process of laser processing, establish mass, momentum, and energy conservation equations, and thus solve the temperature field and flow field information of the molten pool-keyhole during the processing process, which is the core of the digital twin technology for laser manufacturing. With the continuous development of computational fluid dynamics, high spatio-temporal resolution and high-fidelity simulation of heat transfer-flow in the molten pool-keyhole can be achieved based on digital twin numerical simulation technology. At the same time, the improvement of computer performance and the popularization and application of parallel computing technology provide an effective means to improve the computational efficiency of the numerical simulation of the dynamic behavior of the molten pool-keyhole. However, the deficiency of the existing technology is that: with the increasing demand for digital twin numerical simulation of the full-scale laser processing process of large metal components, the required number of grid numerical values and computing resources for the simulation increase linearly. Limited by the existing computer performance such as memory and the ultimate processing frequency of the processor, there are huge challenges in realizing the efficient numerical simulation of the dynamic behavior of the large-scale laser processing molten pool-keyhole.

[0005] Therefore, the key to realizing the research on the dynamic behavior mechanism of the full-size laser processing molten pool-keyhole lies in how to achieve efficient calculation based on the existing numerical simulation technology. It mainly includes: (1) How to reasonably plan the computational domain of numerical simulation for full-size calculation requirements in terms of optimizing the computational domain size; (2) How to accelerate the computational efficiency of the simulation process while ensuring the computational accuracy in the process of numerical simulation calculation.

[0006] Through the above analysis, the problems and defects existing in the prior art are as follows:

[0007] With the increasing demand for digital twin numerical simulation of the full-size laser processing process of large metal components, the number of grid values and computational resources required for simulation have increased linearly. Limited by the existing computer performance such as memory and the maximum processing frequency of the processor, there are huge challenges in realizing the efficient numerical simulation of the dynamic behavior of the large-scale laser processing molten pool-keyhole. Summary of the Invention

[0008] In view of the problems existing in the prior art, the present invention provides a method and system for efficient numerical simulation of the dynamic behavior of a laser processing molten pool-keyhole.

[0009] The present invention is implemented as follows. An efficient numerical simulation method for the dynamic behavior of a laser processing molten pool-keyhole includes:

[0010] S1: Extract the morphology of the molten pool-keyhole and perform image processing to determine the initial size of the computational domain;

[0011] S2: Realize the three-dimensional dynamic sliding computational domain: Use the dynamic sliding technology to construct a dynamic constant computational domain that follows the movement of the laser beam;

[0012] S3: Divide the numerical simulation model of the dynamic behavior of the laser processing molten pool-keyhole constructed by using the lattice Boltzmann method and the phase field method. Based on the MPI parallel computing technology, divide the numerical simulation model into a parallel computing module and a serial computing module;

[0013] The parallel computing module includes: a velocity particle distribution function calculation module, an enthalpy particle distribution function calculation module, a phase field particle distribution function calculation module, and a force calculation module; the serial computing module includes: an interface position recognition module, a laser beam multiple reflection heat source module, and a file output module;

[0014] S4: For the parallel computing module, the four-dimensional data brought by the particle distribution function introduced by the three-dimensional LBM, while scalar quantities such as the flow field, temperature field, and phase field are three-dimensional data. Therefore, there is a problem of high-dimensional data hybrid parallel computing in the calculation process;

[0015] S5: Computational post - processing: According to the calculated results, visualize the molten pool - keyhole morphology, temperature field, velocity field, and phase - field distribution during the laser processing through the Tecplot360 GUI interface.

[0016] Furthermore, for the extraction of the molten pool - keyhole morphology and image processing, determine the initial size of the computational domain;

[0017] S1.1: Obtain a video file of the dynamic changes in the molten pool - keyhole morphology during the laser processing through high - speed photography; select the molten pool - keyhole morphology in the stable processing state as the input for the image - processing steps.

[0018] S1.2: Import the image of the steady - state molten pool - keyhole morphology into MATLAB, and pre - process the images collected by the high - speed camera based on the Image Processing Toolbox in MATLAB: read the images in the folder, and change the original image format to RGB format for subsequent image - processing programs.

[0019] S1.3: Use the grayImage function in the toolbox to grayscale the extracted images; use the gaussianBlur function in the toolbox to perform Gaussian filtering on the images, smooth the images, eliminate Gaussian noise and random noise in the images, improve the image quality, and facilitate the subsequent extraction of the characteristic lines of the processed molten pool - keyhole boundary.

[0020] S1.4: Use the Sobel operator to sharpen the images, highlighting the boundary features of the processed molten pool - keyhole; extract the maximum length Smax, maximum width Wmax, and maximum depth Hmax of the molten pool - keyhole during the stable processing from the boundary - feature images.

[0021] S1.5: Determine that the length (L), width (W), and height (H) of the optimal computational domain for the laser - processing numerical simulation are 2*Smax, 2*Wmax, and 1.5*Hmax respectively, ensuring that the molten pool - keyhole is basically in the middle region of the computational domain during stable processing.

[0022] Furthermore, for the implementation of the three - dimensional dynamic sliding computational domain: use the dynamic - sliding technology to construct a dynamic constant computational domain that follows the movement of the laser beam.

[0023] S2.1: Based on the length (L), width (W), and height (H) of the computational - domain size obtained in the previous S1 step, construct the computational domain, determine the time step and grid size of the computational domain, and set the sliding - judgment conditions; extract the distance between the position of the laser - beam center and the right boundary of the computational domain at each moment. When the sliding conditions are met, perform a sliding operation on the computational domain.

[0024] S2.2: Perform a slip operation along the direction of the beam movement. According to the set number of grids, delete the part of the computational domain on the left boundary of the computational domain, and add a blank computational domain of the same size on the right boundary of the computational domain;

[0025] S2.3: After the slip operation ends, update the coordinate positions of all parameters in the computational domain, mark the end of a dynamic slip operation, and ensure that the size of the computational domain remains constant.

[0026] Furthermore, for the parallel computing module, the particle distribution function introduced by the three-dimensional LBM brings four-dimensional data, while scalar fields such as the flow field, temperature field, and phase field are three-dimensional data. Therefore, there is a problem of high-dimensional data hybrid parallel computing in the calculation process;

[0027] S4.1: In order to accurately transfer high-dimensional mixed data between parallel computing nodes, perform dimensionality reduction processing on the four-dimensional data of LBM and three-dimensional data such as temperature and velocity, and uniformly convert them into one-dimensional data to achieve accurate transfer of high-dimensional data between global processes;

[0028] S4.2: For the serial computing module, considering the problem of cross-process calculation in the position of the molten pool-keyhole gas-liquid interface, perform single-threaded serial calculation in the main process for interface position recognition and the laser beam multiple reflection heat source model (including beam tracing algorithm and energy distribution calculation); the main process first collects the phase field data of the subprocesses through MPIGather to achieve interface position recognition, and then calculates the energy distribution on the interface based on the beam tracing algorithm; finally, the main process is transmitted to each subprocess in the form of MPIBcast, and at the same time, physical quantities such as temperature and velocity of the subprocesses are collected through MPIGather and output to the dat file.

[0029] Furthermore, the dynamic slip determination condition of the three-dimensional computational domain described in S2.1 is: construct a computational domain based on the size length (L), width (W), and height (H) of the computational domain obtained in the previous S1 step, determine the time step Δt and grid size of the computational domain, and determine that the number of grids in the X, Y, and Z directions are N X = L / Δx, Ny = W / Δx, and = H / Δx. Set the dynamic slip determination condition d = 0.2*Nx; extract the distance S from the position of the laser beam center to the right boundary of the computational domain at each moment. When the slip condition S <= d is satisfied, perform a slip operation on the computational domain;

[0030] The specific implementation of the dynamic slip operation of the computational domain described in S2.2 is: when the slip determination condition of S2.1 is reached, remove the area with a length from 0 to 0.25*NX, a width of Ny, and a height of Nz along the X direction in the computational domain, and at the same time fill the right boundary along the X direction in the computational domain with a length of 0.25*N X, a blank calculation domain with a width of Ny and a height of Nz, thus ensuring that the size of the calculation domain is always Nx * Ny * Nz;

[0031] The key variable for the dynamic slip of the three-dimensional calculation domain described in S2.3 is the update formula for the real-time value S of the distance between the beam center and the right boundary of the calculation domain as follows:

[0032] S = N x -U χ *Step + m * n χ

[0033] where m is the number of times the beam cycles to the trigger position (the number of times dynamic slip occurs), with an initial value of 0, and each time a dynamic slip operation is executed, the value of m increases by 1; n is the number of grids for dynamic slip along the processing direction n χ = 0.25 * N X , Ux is the moving speed of the laser beam, Step is the real-time calculation step number of the current program; the value of S changes dynamically in real time, and when the judgment condition is met, the value of S is updated using the update formula.

[0034] Furthermore, the LBM four-dimensional data and three-dimensional data dimensionality reduction processing formulas in S4.1 are as follows:

[0035] For the coordinate values of three-dimensional data, dimensionality reduction expansion is performed:

[0036] vector3D(i, j, k) = k + j * Nz + i * Ny * Nz

[0037] For four-dimensional data:

[0038] vector4D(i, j, k, n) = (k + j * Nz + i * Ny * Nz) * Q + n

[0039] where vector3D and vector4D are the coordinates of three-dimensional and four-dimensional data in one-dimensional data, i, j, k are the current three-dimensional coordinates of the data respectively, n is the direction component of the particle distribution function, Q is the number of direction components of the particle distribution function; Ny and Nz are the maximum number of grids in the y and z directions of the calculation domain respectively; it can be proved that the above formula can ensure uniqueness when high-dimensional coordinate data is expanded into one-dimensional coordinates.

[0040] Another object of the present invention is to provide a high-efficiency numerical simulation system for the dynamic behavior of a laser processing molten pool-keyhole, including:

[0041] The image processing module is configured with MATLAB software and the Image Processing Toolbox for importing and processing the images of the steady-state molten pool-keyhole morphology in laser processing, including image format conversion, grayscale processing, Gaussian filtering, Sobel operator sharpening, and extraction of the molten pool-keyhole boundary features;

[0042] The dynamic slip module uses a judgment formula to determine when to perform boundary slip and an update formula to update the S value, thereby achieving the dynamic slip of the three-dimensional computational domain and ensuring a constant size of the computational domain during the calculation process;

[0043] The parallel computing module combines the LBM simulation technology with the MPI parallel computing technology to divide a single process into several modules, including: the velocity distribution function calculation module, the force calculation module, the phase field distribution function calculation module, the laser energy distribution calculation module, the enthalpy distribution function calculation module, and the parallel computing adjustment module, thereby completing the numerical implementation of the evolution of the molten pool-keyhole in laser processing;

[0044] The high-efficiency communication module uses the high-dimensional data dimensionality reduction communication technology to reduce three-dimensional data such as temperature, velocity, and phase field parameters and four-dimensional data particle distribution functions to one-dimensional data, uses the gradient operator and the Laplace operator to perform three-dimensional data communication tests, and uses particle distribution function migration to perform four-dimensional data communication tests to ensure high-efficiency communication of data between different processes in parallel computing;

[0045] The serial-parallel hybrid computing module collects and organizes the phase field parameter data of the subprocesses, determines the accurate position of the interface in the main process, calculates the energy distribution through the multiple reflection heat source model, and finally broadcasts the main process energy distribution data to the subprocesses;

[0046] The data output module collects physical quantities such as temperature and velocity in the subprocesses through the MPI_Gather function and outputs them as a.dat file;

[0047] The simulation result visualization module uses the visualization function of the Tecplot360 GUI interface to visualize the molten pool-keyhole morphology and the temperature field and velocity field distributions during the laser processing process.

[0048] Another object of the present invention is to provide a computer device, which includes a memory and a processor. When the computer program stored in the memory is executed by the processor, the processor executes the steps of the high-efficiency numerical simulation method for the dynamic behavior of the molten pool-keyhole in laser processing.

[0049] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to execute the steps of the efficient numerical simulation method for the dynamic behavior of a laser processing molten pool-keyhole.

[0050] Another object of the present invention is to provide an information data processing terminal for implementing the efficient numerical simulation system for the dynamic behavior of a laser processing molten pool-keyhole.

[0051] Combined with the above technical solutions and solved technical problems, the advantages and positive effects of the technical solution to be protected by the present invention are analyzed from the following aspects:

[0052] First, in view of the technical problems existing in the above prior art and the difficulty of solving the problems, closely combined with the technical solution to be protected by the present invention and the results and data in the research and development process, etc., analyze in detail and profoundly how the technical solution of the present invention solves the technical problems and the creative technical effects brought after solving the problems. The specific description is as follows:

[0053] (1) In view of the problem of tight computing resources for large-scale simulation of the entire weld, the dynamic slip technology is adopted to reduce the large computing domain and the required computing resources. In view of the problem of information chaos caused by high-dimensional data hybrid communication in LBM, the dimension reduction communication technology is adopted to expand the high-dimensional data in one dimension to ensure efficient and unified communication between parallel processes. In view of the problem of difficult interface position tracking, a serial-parallel hybrid method is adopted in the program architecture to collect the phase field sequence parameters in the subprocesses into the main process to achieve accurate tracking of the interface position.

[0054] (2) The present invention is based on the lattice Boltzmann method (LBM) which is easy to parallelize, has a solid physical basis and higher simulation accuracy, and combines the MPI parallel computing technology to numerically simulate the evolution process of the large-scale molten pool-keyhole of the entire weld in laser processing. Through efficient and accurate calculation and communication, it makes the numerical simulation of the large-scale laser processing of the entire weld possible and provides technical support for the prediction of the morphology of long welds of large components.

[0055] (3) Compared with the existing experimental methods, the present invention can effectively shorten the research cycle and reduce the research cost; compared with the existing two-dimensional macroscopic molten pool-keyhole evolution simulation and three-dimensional small-scale macroscopic molten pool-keyhole evolution simulation, through technical means such as dynamic slip, dimension reduction communication and serial-parallel hybrid, it can accurately simulate the large-scale laser processing of the entire weld with less computing resources and shorter computing time. Description of the Drawings

[0056] Figure 1 It is a flowchart of the efficient numerical simulation method for the dynamic behavior of a laser processing molten pool-keyhole provided by an embodiment of the present invention.

[0057] Figure 2 It is a structural block diagram of an efficient numerical simulation system for the dynamic behavior of a laser processing molten pool - keyhole provided by an embodiment of the present invention.

[0058] Figure 3 It is a process diagram for the determination, execution, and update of dynamic slip in a three - dimensional calculation domain of laser processing provided by an embodiment of the present invention.

[0059] Figure 4 It is a schematic diagram of a parallel computing module provided by an embodiment of the present invention.

[0060] Figure 5 It is a schematic diagram of high - dimensional data dimensionality reduction communication provided by an embodiment of the present invention

[0061] Figure 6 It is a graph of graphic understanding and program architecture using serial - parallel hybrid computing provided by an embodiment of the present invention.

[0062] Figure 7 It is a graph of the visualization simulation results of a three - dimensional laser processing molten pool - keyhole provided by an embodiment of the present invention. Detailed implementation manners

[0063] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0064] As Figure 1 shown, an efficient numerical simulation method for the dynamic behavior of a laser processing molten pool - keyhole provided by an embodiment of the present invention includes the following steps:

[0065] S1: Extract the morphology of the molten pool - keyhole and perform image processing to determine the initial size of the calculation domain;

[0066] S2: Implement a three - dimensional dynamic slip calculation domain: Use dynamic slip technology to construct a dynamic constant calculation domain that follows the movement of the laser beam;

[0067] S3: Divide the numerical simulation model of the dynamic behavior of the laser processing molten pool - keyhole constructed by using the lattice Boltzmann method and the phase - field method. Based on the MPI parallel computing technology, divide the numerical simulation model into a parallel computing module and a serial computing module;

[0068] The parallel computing module includes: a velocity particle distribution function calculation module, an enthalpy particle distribution function calculation module, a phase - field particle distribution function calculation module, and a force calculation module; the serial computing module includes: an interface position recognition module, a laser beam multiple - reflection heat source module, and a file output module;

[0069] S4: For the parallel computing module, the particle distribution function introduced by the three-dimensional LBM brings four-dimensional data, while scalar fields such as the flow field, temperature field, and phase field are three-dimensional data. Therefore, there is a problem of high-dimensional data hybrid parallel computing in the calculation process;

[0070] S5: Calculation post-processing: According to the calculation results, visualize the molten pool-keyhole morphology, temperature field, velocity field, and phase field distribution during the laser processing through the Tecplot360 GUI interface.

[0071] The molten pool-keyhole morphology extraction and image processing provided by the embodiments of the present invention determine the initial size of the calculation domain;

[0072] S1.1: Obtain a video file of the dynamic change of the molten pool-keyhole morphology during the laser processing through high-speed photography; select the molten pool-keyhole morphology in the stable processing state as the input for the image processing step;

[0073] S1.2: Import the image of the steady-state molten pool-keyhole morphology during processing into MATLAB, and preprocess the image collected by the high-speed camera based on the Image Processing Toolbox in MATLAB: read the images in the folder, and change the original image format to RGB format for subsequent image processing by the program;

[0074] S1.3: Use the grayImage function in the toolbox to grayscale the extracted image; use the gaussianBlur function in the toolbox to perform Gaussian filtering on the image, smooth the image, eliminate Gaussian noise and random noise in the image, improve the image quality, and facilitate the subsequent extraction of the characteristic line of the processed molten pool-keyhole boundary;

[0075] S1.4: Use the Sobel operator to sharpen the image, highlighting the processed molten pool-keyhole boundary features; extract the maximum length Smax, maximum width Wmax, and maximum melting depth Hmax of the molten pool-keyhole during the stable processing from the boundary feature image;

[0076] S1.5: Determine that the length (L), width (W), and height (H) of the optimal calculation domain for the laser processing numerical simulation are 2*Smax, 2*Wmax, and 1.5*Hmax respectively, ensuring that the molten pool-keyhole is basically in the middle area within the calculation domain during stable processing.

[0077] The implementation of the three-dimensional dynamic sliding calculation domain provided by the embodiments of the present invention: use the dynamic sliding technology to construct a dynamic constant calculation domain that follows the movement of the laser beam;

[0078] S2.1: Based on the length (L), width (W), and height (H) of the computational domain size obtained in the foregoing S1 step, construct the computational domain, determine the time step and grid size of the computational domain, and set the slip determination condition; extract the distance from the position of the laser beam center to the right boundary of the computational domain at each moment. When the slip condition is satisfied, perform a slip operation on the computational domain;

[0079] S2.2: Perform a slip operation along the direction of beam movement. According to the set number of grids, delete a part of the computational domain on the left boundary of the computational domain, and add a blank computational domain of the same size on the right boundary of the computational domain;

[0080] S2.3: After the slip operation is completed, update the position of all parameter coordinates in the computational domain, mark the end of a dynamic slip operation, and ensure that the size of the computational domain remains constant.

[0081] In the embodiment of the present invention, for the parallel computing module, the four-dimensional data brought by the particle distribution function introduced by the three-dimensional LBM, while scalar fields such as the flow field, temperature field, and phase field are three-dimensional data. Therefore, there is a problem of high-dimensional data hybrid parallel computing in the calculation process;

[0082] S4.1: In order to accurately transfer high-dimensional mixed data between parallel computing nodes, perform dimensionality reduction processing on the four-dimensional data of LBM and three-dimensional data such as temperature and velocity, and uniformly convert them into one-dimensional data to achieve accurate transfer of high-dimensional data between global processes;

[0083] S4.2: For the serial computing module, in view of the problem of cross-process calculation of the position of the molten pool-keyhole gas-liquid interface, for interface position recognition and the laser beam multiple reflection heat source model (including beam tracing algorithm and energy distribution calculation), perform single-threaded serial calculation in the main process; the main process first collects the phase field data of the subprocesses through MPIGather to achieve interface position recognition, and then calculates the energy distribution on the interface based on the beam tracing algorithm; finally, the main process is transmitted to each subprocess in the form of MPIBcast, and at the same time, physical quantities such as temperature and velocity of the subprocesses are collected through MPIGather and output to the dat file.

[0084] The three-dimensional computational domain dynamic slip determination condition described in S2.1 of the embodiment of the present invention is: Based on the length (L), width (W), and height (H) of the computational domain size obtained in the foregoing S1 step, construct the computational domain, determine the time step Δt and grid size of the computational domain, determine the number of grids in the X, Y, and Z directions as N X = L / Δx, Ny = W / Δx, and = H / Δx. Set the dynamic slip determination condition d = 0.2*Nx; extract the distance S from the position of the laser beam center to the right boundary of the computational domain at each moment. When the slip condition S <= d is satisfied, perform a slip operation on the computational domain;

[0085] The specific implementation of the dynamic sliding operation of the computational domain described in S2.2 is as follows: When the sliding determination condition in S2.1 is met, the grid in the computational domain is removed from 0 to 0.25*N in the X direction X for a region with a length of 0.25*N, a width of Ny, and a height of Nz, and at the same time, a blank computational domain with a length of 0.25*N, a width of Ny, and a height of Nz is filled at the right boundary in the X direction of the computational domain, so as to ensure that the size of the computational domain is always Nx*Ny*Nz; X Thereby ensuring that the size of the computational domain is always Nx*Ny*Nz;

[0086] The key variable for the dynamic sliding of the three-dimensional computational domain described in S2.3 is the update formula for the real-time value S of the distance from the beam center to the right boundary of the computational domain as follows:

[0087] S = N χ -U χ *Step + m*n x

[0088] where m is the number of times the beam cycles to the trigger position (the number of times of dynamic sliding), the initial value is 0, and each time a dynamic sliding operation is executed, the value of m increases by 1; n is the number of grids for dynamic sliding in the processing direction n χ = 0.25*N X , Ux is the moving speed of the laser beam, Step is the real-time calculation step number of the current program; the value of S changes dynamically in real time, and when the determination condition is met, the value of S is updated using the update formula.

[0089] The dimensionality reduction processing formulas for the LBM four-dimensional data and three-dimensional data in S4.1 provided by the embodiments of the present invention are as follows:

[0090] For the coordinate values of three-dimensional data, dimensionality reduction expansion is performed:

[0091] vector3D(i,j,k) = k + j*Nz + i*Ny*Nz

[0092] For four-dimensional data:

[0093] vector4D(i,j,k,n) = (k + j*Nz + i*Ny*Nz)*Q + n

[0094] where vector3D and vector4D are the coordinates of three-dimensional and four-dimensional data in one-dimensional data, i, j, k are the current three-dimensional coordinates of the data respectively, n is the direction component of the particle distribution function, Q is the number of direction components of the particle distribution function; Ny and Nz are the maximum number of grids in the y and z directions of the computational domain respectively; it can be proved that the above formula can ensure uniqueness when high-dimensional coordinate data is expanded into one-dimensional coordinates.

[0095] Such as Figure 2As shown in the figure, a high-efficiency numerical simulation system for the dynamic behavior of a laser processing molten pool-keyhole according to an embodiment of the present invention includes:

[0096] An image processing module, configured with MATLAB software and an Image Processing Toolbox image processing toolbox, for importing and processing laser processing steady-state molten pool-keyhole morphology images, including image format change, grayscale processing, Gaussian filtering, Sobel operator sharpening processing, and molten pool-keyhole boundary feature extraction;

[0097] A dynamic slip module, which uses a judgment formula to determine when to perform boundary slip and updates the S value using an update formula to achieve the dynamic slip of the three-dimensional computational domain and ensure that the size of the computational domain remains constant during the calculation process;

[0098] A parallel computing module, which combines the LBM simulation technology with the MPI parallel computing technology to divide a single process into several modules, including: a velocity distribution function calculation module, a force calculation module, a phase field distribution function calculation module, a laser energy distribution calculation module, an enthalpy distribution function calculation module, and a parallel computing adjustment module, so as to complete the numerical implementation of the evolution of the laser processing molten pool-keyhole;

[0099] A high-efficiency communication module, which uses high-dimensional data dimensionality reduction communication technology to reduce three-dimensional data such as temperature, velocity, and phase field parameters and four-dimensional data particle distribution functions to one-dimensional data, uses gradient operators and Laplace operators to perform three-dimensional data communication tests, and uses particle distribution function migration to perform four-dimensional data communication tests to ensure the high-efficiency communication of data between different processes in parallel computing;

[0100] A serial-parallel hybrid computing module, which collects and organizes the phase field parameter data of the subprocesses, determines the accurate position of the interface in the main process, calculates the energy distribution through a multiple reflection heat source model, and finally broadcasts the main process energy distribution data to the subprocesses;

[0101] A data output module, which collects physical quantities such as temperature and velocity in the subprocesses through the MPI_Gather function and outputs them as a dat file;

[0102] A simulation result visualization module, which uses the visualization function of the Tecplot360 GUI interface to visualize the molten pool-keyhole morphology and temperature field and velocity field distributions during the laser processing process.

[0103] Another object of the present invention is to provide a computer device, where the computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the high-efficiency numerical simulation method for the dynamic behavior of the laser processing molten pool-keyhole.

[0104] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to execute the steps of the efficient numerical simulation method for the dynamic behavior of the laser processing molten pool-keyhole.

[0105] Another object of the present invention is to provide an information data processing terminal for implementing the efficient numerical simulation system for the dynamic behavior of the laser processing molten pool-keyhole.

[0106] Specific implementation of the present invention:

[0107] The present invention is an efficient calculation method and system for numerical simulation of the evolution of a laser processing molten pool-keyhole. The calculation steps are specifically implemented according to the following steps:

[0108] The implementation of the dynamic sliding calculation domain of the present invention includes the following steps:

[0109] S1: Extract the morphology of the molten pool-keyhole and perform image processing to determine the initial size of the calculation domain.

[0110] S1.1: Obtain a video file of the dynamic change of the morphology of the molten pool-keyhole during the laser processing through high-speed photography. Select the morphology of the molten pool-keyhole in the stable processing state as the input for the image processing step.

[0111] S1.2: Import the image of the steady-state molten pool-keyhole morphology during processing into MATLAB, and preprocess the image collected by the high-speed camera based on the Image Processing Toolbox in MATLAB: Read the images in the folder, and change the original image format to RGB format for subsequent image processing by the program.

[0112] S1.3: Use the grayImage function in the toolbox to grayscale the extracted image. Use the gaussianBlur function in the toolbox to perform Gaussian filtering on the image, smooth the image, eliminate Gaussian noise and random noise in the image, improve the image quality, and facilitate the subsequent extraction of the characteristic line of the boundary of the processed molten pool-keyhole.

[0113] S1.4: Use the Sobel operator to sharpen the image to highlight the boundary features of the processed molten pool-keyhole. Extract the maximum length Smax, the maximum width Wmax, and the maximum depth Hmax of the molten pool-keyhole during the stable processing from the boundary feature image.

[0114] S1.5: Determine that the length (L), width (W), and height (H) of the optimal computational domain for laser processing numerical simulation are 2*Smax, 2*Wmax, and 1.5*Hmax respectively, ensuring that the molten pool-keyhole is basically in the middle region within the computational domain during stable processing.

[0115] S2: Implementation of the three-dimensional dynamic sliding computational domain: Use the dynamic sliding technology to construct a dynamic constant computational domain that follows the movement of the laser beam, as Figure 3 shown.

[0116] S2.1: Based on the length (L), width (W), and height (H) of the computational domain obtained in the previous step S1, construct the computational domain, determine the time step and grid size of the computational domain, and set the sliding judgment condition. Extract the distance from the position of the laser beam center to the right boundary of the computational domain at each moment. When the sliding condition is met, perform a sliding operation on the computational domain.

[0117] Furthermore, the three-dimensional computational domain dynamic sliding judgment condition in S2.1 is: Based on the length (L), width (W), and height (H) of the computational domain obtained in the previous step S1, construct the computational domain, determine the time step Δt and grid size of the computational domain, determine the number of grids in the X, Y, and Z directions as N X =L / Δx, Ny = W / Δx, and =H / Δx, set the dynamic sliding judgment condition d = 0.2*Nx. Extract the distance S from the position of the laser beam center to the right boundary of the computational domain at each moment. When the sliding condition S <= d is met, perform a sliding operation on the computational domain.

[0118] S2.2: Perform a sliding operation along the direction of the beam movement. According to the set number of grids, delete the part of the computational domain on the left boundary of the computational domain, and add a blank computational domain of the same size on the right boundary of the computational domain.

[0119] Furthermore, the specific implementation of the computational domain dynamic sliding operation in S2.2 is: When the sliding judgment condition of S2.1 is reached, remove the area with a length of 0 to 0.25*N X in the X direction, Ny in width, and Nz in height in the computational domain. At the same time, fill the right boundary of the computational domain in the X direction with a blank computational domain with a length of 0.25*N X in length, Ny in width, and Nz in height, so as to ensure that the size of the computational domain is always Nx*Ny*Nz.

[0120] After the sliding operation is completed, update the coordinate positions of all parameters in the computational domain, mark the end of a dynamic sliding operation, and ensure that the size of the computational domain remains constant.

[0121] Furthermore, the key variable for the three-dimensional computational domain dynamic sliding in S2.3 is the update formula for the real-time value S of the distance from the beam center to the right boundary of the computational domain as follows:

[0122] S = N χ -U χ *Step + m*n χ

[0123] Among them, m is the number of times the light beam cycles to the trigger position (the number of times of dynamic slip) with an initial value of 0. Each time a dynamic slip operation is executed, the value of m increases by 1; n is the number of grids of dynamic slip along the processing direction n χ = 0.25*N X , Ux is the moving speed of the laser beam, and Step is the number of real-time calculation steps of the current program. The value of S changes dynamically in real time. When the judgment condition is met, the value of S is updated using the update formula. The graphical understanding of the above formula is as Figure 3 shown.

[0124] S3: Model calculation process: This patent establishes a numerical model of the dynamic behavior of the laser processing molten pool-keyhole based on LBM and realizes the efficient solution of the model by combining MPI parallel computing. The parallel computing module and the serial computing module are as Figure 4 shown. The parallel computing module includes: a velocity particle distribution function calculation module, an enthalpy particle distribution function calculation module, a phase field particle distribution function calculation module, and a force calculation module; the serial computing module includes: an interface position recognition module, a laser beam multiple reflection heat source module, and a file output module.

[0125] The velocity distribution function calculation module and the force calculation module, that is, the flow field distribution calculation formula of the laser processing process is as follows:

[0126]

[0127] Among them, g i (r + e i δt, t + δt) is the particle velocity distribution function at the next time step, and g i (r, t) is the current particle velocity distribution function, is the particle equilibrium velocity distribution function, and G i (r, t) is the forced convection phase, and τ g is the relaxation time.

[0128] The laser energy distribution calculation module includes three parts: the laser beam multiple reflection model, the laser beam energy distribution, and the Fresnel energy absorption. The phase field distribution function calculation module calculates the distribution of the current phase field parameters, and realizes the accurate tracking of the molten pool-keyhole through the interface tracking formula. The calculation formula will be introduced in detail in the subsequent serial-parallel hybrid calculation part.

[0129] The enthalpy distribution function calculation module, that is, the temperature field distribution calculation formula of the laser processing process is as follows:

[0130]

[0131] Among them, h i (r + e i δt, t + δt) is the enthalpy distribution function at the next time step, h i (r, t) is the current enthalpy distribution function, is the enthalpy distribution function in the equilibrium state, ω i Qδt is the energy input term affected by the above calculation module, ω i is the weight coefficient in each direction of the particle distribution function, τ h is the relaxation time Q in is the laser energy input.

[0132] The parallel computing adjustment module uses the MPI control function to ensure that the computing progress of each process is consistent, maintain the order of the computing process, and ensure its high efficiency and unity.

[0133] S4: Processing of the computing process: The following solutions are proposed for the problems of chaotic high-dimensional data communication and low accuracy of parallel computing interface position tracking in the computing process.

[0134] Furthermore, the dimensionality reduction processing formulas for the four-dimensional data of the LBM particle distribution function and the three-dimensional data such as the temperature field, flow field, and phase field in S4.1 are as follows:

[0135] For the coordinate values of the three-dimensional data, dimensionality reduction expansion is performed:

[0136] vector3D(i, j, k) = k + j * Nz + i * Ny * Nz

[0137] For the four-dimensional data:

[0138] vector4D(i, j, k, n) = (k + j * Nz + i * Ny * Nz) * Q + n

[0139] Among them, vector3D and vector4D are the coordinates of the three-dimensional and four-dimensional data in one-dimensional data. i, j, and k are the current three-dimensional coordinates of the data, n is the direction component of the particle distribution function, and Q is the number of direction components of the particle distribution function. Ny and Nz are the maximum grid numbers in the y and z directions of the computing domain respectively. It can be proved that the above formula can ensure uniqueness when the high-dimensional coordinate data is expanded into one-dimensional coordinates.

[0140] Furthermore, the program uses the gradient operator and Laplace operator to perform three-dimensional data communication tests, and uses particle distribution function migration to perform four-dimensional data communication tests to ensure accurate data communication between different processes in parallel computing. The graphical understanding of high-dimensional data dimensionality reduction communication is as Figure 5 shown.

[0141] S4.2: To address the problem of low accuracy in tracking the position of the parallel computing interface, serial-parallel hybrid computing is performed on the data in the computing domain. The interface position recognition, beam tracking algorithm, and energy distribution calculation are carried out in the main process using single-threaded serial computing. The main process transmits the beam tracking results and energy distribution data to each sub-process in the form of MPI Bcast, and at the same time collects physical quantities such as temperature and velocity of the sub-processes through MPI Gather and outputs them to the dat file. The program architecture of the serial-parallel hybrid computing is as shown in Figure 6 shown below.

[0142] The interface tracking formula is as follows:

[0143]

[0144] where is the phase field order parameter, u is the velocity vector, M is the interface diffusion coefficient, n is the normal vector of the current interface, W is the interface thickness, generally taking [3,5] grid sizes. The phase field order parameter is set to a constant of [0,1]. In this patent, the material phase order parameter is set to 1 and the gas phase is set to 0. is the order parameter constant, set to 0.5.

[0145] The formula for calculating the beam reflection direction vector in the beam multiple reflection heat source model is as follows:

[0146]

[0147] where is the beam reflection direction vector, N i is the incident beam direction vector, and n is the normal vector of the reflection interface. The model assumes that the laser beam stops reflecting when it reflects 10 times or reaches the boundary of the computing domain. It is assumed that the energy of the laser beam belongs to a Gaussian distribution.

[0148] Then the light intensity distribution function of each laser beam is as follows:

[0149]

[0150] where I 0 (r) is the light intensity of the laser beam at the reflection point, with the unit of W / mm 2 , P is the laser processing power, is the radius constant of the laser beam focal plane, and r is the distance from the reflection point to the origin of the laser beam plane.

[0151] The energy absorbed by the material irradiated by the laser beam is calculated using the Fresnel energy absorption rate, and the calculation formula considering only reflection is as follows:

[0152]

[0153] where αF where \( \alpha \) is the laser beam energy absorption rate of the reflection point material, and \( \varepsilon \) is the Fresnel absorption coefficient of the material. is the angle between the incident beam and the normal of the reflection interface. The energy at the reflection point can be calculated by the following formula:

[0154] Q = I 0 (r) * \( \alpha \) F

[0155] S5: Post - processing calculation: The numerical simulation exports a dat file containing the calculation results and visualizes the melt pool - keyhole morphology, temperature field, and velocity field distribution during the laser processing through the Tecplot360 GUI interface. The high - efficiency numerical simulation results of the dynamic behavior of the laser - processed melt pool - keyhole are as Figure 7 shown.

[0156] Example 1

[0157] In this example, it is assumed that the processing material is TC4 titanium alloy, the Fresnel absorption coefficient is 0.2, the heat source model is a Gaussian heat source model, and the laser beam is perpendicular to the material surface. According to the modeling steps of the high - efficiency numerical simulation system for the dynamic behavior of the laser - processed melt pool - keyhole, the evolution behavior of the melt pool - keyhole during the laser processing is numerically simulated, and the large - scale melt pool - keyhole simulation results of the full weld seam are obtained as Figure 7 shown. Figure 7 In (a) - (c), there are pictures of the temperature field and flow field distributions at different times of the central longitudinal section of the calculation domain, showing the changes of the melt pool - keyhole in the central section. Figure 7 In (d) - (f), there are pictures of the morphology evolution of the melt pool - keyhole at different times from a three - dimensional perspective. In this case, the dynamic slip technology is used to complete the large - scale weld seam simulation of the full weld seam with a small amount of computing resources occupied, proving the feasibility and superiority of this technology. In this case, the high - dimensional data reduction communication technology is used to ensure the efficient and unified communication of data between different processes, and the serial - parallel hybrid calculation method is used to ensure the accuracy of interface position tracking and energy calculation. The gas - liquid interface and solid - liquid interface are clear and smooth, achieving the simulation effect. Therefore, the high - efficiency numerical simulation method and system for the dynamic behavior of the laser - processed melt pool - keyhole proposed by the present invention effectively solve the problems of large computing resources for full weld seam simulation, chaotic high - dimensional data communication, and low accuracy of parallel solution of interface position.

[0158] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those of ordinary skill in the art can understand that the above devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and their modules of the present invention can be implemented by hardware circuits of programmable hardware devices such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above hardware circuits and software, such as firmware.

[0159] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. An efficient numerical simulation method for the dynamic behavior of laser processing molten pool-keyhole, characterized in that: The efficient numerical simulation method for dynamic behavior of laser processing molten pool-keyhole comprises the following steps: S1: Molten pool-keyhole morphology extraction and image processing to determine the initial size of the calculation domain; S2: Implementation of three-dimensional dynamic sliding computational domain: Using dynamic sliding technology to construct a dynamic constant computational domain that moves with the laser beam; S3: The numerical simulation model of the dynamic behavior of the laser processing molten pool-keyhole constructed by the lattice Boltzmann method and the phase field method is divided into modules, and the numerical simulation model is divided into parallel computing modules and serial computing modules based on the MPI parallel computing technology; The parallel calculation module includes: velocity particle distribution function calculation module, enthalpy particle distribution function calculation module, phase field particle distribution function calculation module and force calculation module; the serial calculation module includes: interface position recognition module, laser beam multiple reflection heat source module and file output module; S4: For the parallel computing module, the particle distribution function introduced by the three-dimensional LBM brings four-dimensional data, while the scalars such as flow field, temperature field, and phase field are three-dimensional data. Therefore, the calculation process has the problem of high-dimensional data mixed parallel computing; S5: Post-processing: Based on the calculation results, the molten pool-keyhole morphology and temperature field, velocity field and phase field distribution during laser processing are visualized through the Tecplot360GUI interface.

2. The efficient numerical simulation method for dynamic behavior of laser processing molten pool-keyhole according to claim 1, characterized in that: The molten pool-keyhole morphology extraction and image processing are performed to determine the initial size of the calculation domain; S1.1: Video files of dynamic changes of molten pool-keyhole morphology during laser processing are obtained by high-speed video recording; The molten pool-keyhole morphology in the stable state of machining is selected as the input of the image processing step; S1.2: Import the image of the processing steady-state molten pool-keyhole morphology into MATLAB, and pre-process the image collected by the high-speed camera based on the ImageProcessing Toolbox in MATLAB: read the image in the folder, and change the original image format to RGB format to facilitate image processing in subsequent programs; S1.3: grayImage function in the toolkit is used to grayscale the extracted image; gaussianBlur function in the toolkit is used to perform Gaussian filtering on the image, smooth the image, eliminate Gaussian noise and random noise in the image, improve image quality, and facilitate subsequent extraction of characteristic lines of the processing molten pool-keyhole boundary; S1.4: Use the Sobel operator to sharpen the image and highlight the boundary features of the molten pool and keyhole. Extract the longest value Smax and the widest value Wmax of the molten pool and keyhole in the stable processing process, and the maximum value Hmax of the melting depth through the boundary feature image. S1.5: Determine the length (L), width (W) and height (H) of the optimal calculation domain for numerical simulation of laser processing as 2*Smax, 2*Wmax and 1.5*Hmax, respectively, to ensure that the molten pool-keyhole is basically in the middle area of ​​the calculation domain during stable processing.

3. The efficient numerical simulation method for dynamic behavior of laser processing molten pool-keyhole according to claim 1, characterized in that: The realization of the three-dimensional dynamic sliding calculation domain: using dynamic sliding technology to construct a dynamic constant calculation domain that moves with the laser beam; S2.1: Construct a computational domain based on the computational domain dimensions length (L), width (W) and height (H) obtained in the above step S1, determine the computational domain time step and grid size, and set the slip judgment condition; extract the distance between the position of the laser beam center and the right boundary of the computational domain at each moment, and perform a slip operation on the computational domain when the slip condition is met; S2.2: Perform a sliding operation along the direction of beam movement. According to the set number of grids, delete the computational domain on the left boundary of the computational domain, and add a blank computational domain of the same size on the right boundary of the computational domain. S2.3: After the sliding operation is completed, the coordinate positions of all parameters in the calculation domain are updated, marking the end of a dynamic sliding operation and ensuring that the size of the calculation domain remains constant.

4. The efficient numerical simulation method for dynamic behavior of laser processing molten pool-keyhole according to claim 1, characterized in that: For the parallel computing module, the particle distribution function introduced by the three-dimensional LBM brings four-dimensional data, while the scalars such as flow field, temperature field, and phase field are three-dimensional data. Therefore, the calculation process has the problem of mixed parallel computing of high-dimensional data; S4.1: In order to accurately transfer high-dimensional mixed data between parallel computing nodes, dimensionality reduction processing is performed on LBM four-dimensional data and three-dimensional data such as temperature and speed, and they are uniformly converted into one-dimensional data to achieve accurate transfer of high-dimensional data between global processes; S4.2: For the serial calculation module, in view of the difficulty of cross-process calculation in the position of the molten pool-keyhole gas-liquid interface, single-thread serial calculation is adopted in the main process for interface position identification and laser beam multiple reflection heat source model (including beam tracing algorithm and energy distribution calculation); the main process first collects the phase field data of the sub-process through MPIGather and realizes interface position identification, and then calculates the energy distribution on the interface based on the beam tracing algorithm; finally, the main process is transmitted to each sub-process through MPIBcast broadcast, and at the same time, the temperature, speed and other physical quantities of the sub-process are collected through MPIGather and output to the dat file.

5. The efficient numerical simulation method for dynamic behavior of laser processing molten pool-keyhole according to claim 1, characterized in that: The dynamic slip judgment condition of the three-dimensional calculation domain in step S2.1 is as follows: construct the calculation domain based on the length (L), width (W) and height (H) of the calculation domain obtained in step S1 above, determine the time step Δt and grid size of the calculation domain, and determine the number of grids in the X, Y and Z directions to be N respectively. X =L / Δx, Ny=W / Δx and =H / Δx to set the dynamic slip judgment condition d=0.2*Nx; extract the distance S between the position of the laser beam center and the right boundary of the calculation domain at each moment, and when the slip condition S<=d is met, perform a slip operation on the calculation domain; The specific implementation of the dynamic sliding operation of the computational domain described in S2.2 is: when the sliding judgment condition of S2.1 is met, the grid in the computational domain is moved from 0 to 0.25*N along the X direction. X The area with a length of Ny, a width of Ny, and a height of Nz is removed, and the right border along the X direction in the calculation domain is filled with a length of 0.25*N X , a blank computational domain with a width of Ny and a height of Nz, thus ensuring that the computational domain size is always Nx*Ny*Nz; The key variable of the dynamic sliding of the three-dimensional calculation domain described in S2.3 is the real-time value S of the distance between the center of the beam and the right boundary of the calculation domain. The update formula is as follows: S=N x -U x *Step+m*nx Where m is the number of times the beam cycles to the trigger position (the number of times dynamic slip occurs), the initial value is 0, and the value of m increases by 1 each time a dynamic slip operation is performed; n is the number of grids that dynamically slip along the processing direction. x =0.25*N X , Ux is the moving speed of the laser beam, Step is the number of real-time calculation steps of the current program; the S value changes dynamically in real time, and the S value is updated using the update formula when the judgment condition is met.

6. The efficient numerical simulation method for dynamic behavior of laser processing molten pool-keyhole according to claim 4, characterized in that: The dimensionality reduction processing formulas for LBM four-dimensional data and three-dimensional data in S4.1 are as follows: Perform dimensionality reduction on the coordinate values ​​of three-dimensional data: vector3D(i,j,k)=k+j*Nz+i*Ny*Nz For 4D data: vector4D(i,j,k,n)=(k+j*Nz+i*Ny*Nz)*Q+n Among them, vector3D and vector4D are the coordinates of three-dimensional and four-dimensional data in one-dimensional data, i, j, k are the current three-dimensional coordinates of the data, n is the direction component of the particle distribution function, Q is the number of direction components of the particle distribution function; Ny and Nz are the maximum number of grids in the calculation domain in the y and z directions respectively; it can be proved that the above formula can ensure uniqueness when the high-dimensional coordinate data is expanded into one-dimensional coordinates.

7. A system for efficiently simulating the dynamic behavior of a molten pool and a keyhole in laser processing, which implements the method for efficiently simulating the dynamic behavior of a molten pool and a keyhole in laser processing as claimed in any one of claims 1 to 6, characterized in that: The laser processing molten pool-keyhole dynamic behavior efficient numerical simulation system comprises: Image processing module, equipped with MATLAB software and Image Processing Toolbox, is used to import and process laser processing steady-state molten pool-keyhole morphology images, including image format change, grayscale processing, Gaussian filtering, Sobel operator sharpening processing, and molten pool-keyhole boundary feature extraction; The dynamic sliding module uses the judgment formula to determine when to perform boundary sliding and uses the update formula to update the S value, thereby realizing the dynamic sliding of the three-dimensional calculation domain and ensuring that the size of the calculation domain is constant during the calculation process; The parallel computing module uses LBM simulation technology combined with MPI parallel computing technology to divide a single process into several modules, including: velocity distribution function calculation module, force calculation module, phase field distribution function calculation module, laser energy distribution calculation module, enthalpy distribution function calculation module, and parallel computing adjustment module, so as to complete the numerical realization of laser processing molten pool-keyhole evolution; The efficient communication module uses high-dimensional data dimension reduction communication technology to reduce the three-dimensional data such as temperature, velocity, phase field parameters, and the four-dimensional data particle distribution function to one-dimensional data. It uses the gradient operator and Laplace operator to perform three-dimensional data communication tests, and uses the particle distribution function migration to perform four-dimensional data communication tests, ensuring efficient communication of data between different parallel computing processes; The serial-parallel hybrid calculation module collects and organizes the phase field parameter data of the sub-process, determines the exact position of the interface in the main process, calculates the energy distribution through the multi-reflection heat source model, and finally broadcasts the energy distribution data of the main process to the sub-process; The data output module collects physical quantities such as temperature and speed in the subprocess through the MPI_Gather function and outputs them as dat files; The simulation result visualization module uses the visualization function of the Tecplot360GUI interface to visualize the molten pool-keyhole morphology and the temperature field and velocity field distribution during the laser processing process.

8. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the efficient numerical simulation method for the dynamic behavior of the laser processing molten pool-keyhole as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the method for efficient numerical simulation of the dynamic behavior of a laser processing molten pool-keyhole as claimed in any one of claims 1 to 6.

10. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the efficient numerical simulation system for the dynamic behavior of the laser processing molten pool-keyhole as described in claim 7.

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