CN110472355B - 3D printing preview method based on multi-field coupling modeling and simulation solving - Google Patents

3D printing preview method based on multi-field coupling modeling and simulation solving Download PDF

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CN110472355B
CN110472355B CN201910771451.8A CN201910771451A CN110472355B CN 110472355 B CN110472355 B CN 110472355B CN 201910771451 A CN201910771451 A CN 201910771451A CN 110472355 B CN110472355 B CN 110472355B
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printing
structural part
printing process
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CN110472355A (en
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占小红
高转妮
颜廷艳
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Nanjing University of Aeronautics and Astronautics
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Nanjing University of Aeronautics and Astronautics
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/20—Apparatus for additive manufacturing; Details thereof or accessories therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
    • G06F3/1203—Improving or facilitating administration, e.g. print management
    • G06F3/1208—Improving or facilitating administration, e.g. print management resulting in improved quality of the output result, e.g. print layout, colours, workflows, print preview
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1223—Dedicated interfaces to print systems specifically adapted to use a particular technique
    • G06F3/1237—Print job management
    • G06F3/1253—Configuration of print job parameters, e.g. using UI at the client
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1278—Dedicated interfaces to print systems specifically adapted to adopt a particular infrastructure
    • G06F3/1279—Controller construction, e.g. aspects of the interface hardware
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y10/00—Processes of additive manufacturing

Abstract

The invention discloses a 3D printing preview method based on multi-field coupling modeling and simulation solving, which aims at the 3D printing process of a structural part, utilizes a computer programming language and an interpolation algorithm to establish a multi-physical coupling model of a temperature field, a stress strain field, a flow field, a tissue field, a solute field and a defect field, solves and calculates the model by a finite element method, and carries out post-processing on the result to obtain the performance parameters of the 3D printing structural part under the mutual influence of different physical fields. The performance parameters of the 3D printing structure part in different physical fields are compared with the test results in real time and are judged and analyzed, so that the purposes of accurate preview and real-time regulation and control of the 3D printing process are achieved. According to the method, more reasonable 3D printing process parameters are worked out through judging and solving of the multi-field coupling model, the quality of the 3D printing structural part is improved, the 3D printing cost is effectively reduced, and the test efficiency is greatly improved.

Description

3D printing preview method based on multi-field coupling modeling and simulation solving
Technical Field
The invention relates to the technical field of 3D printing, in particular to a 3D printing preview method based on multi-field coupling modeling and simulation solving, and particularly relates to a digital preview and regulation and control technology of a 3D printing process.
Background
The 3D printing (also called Additive manufacturing, AM) technology is used as a rapid forming technology, and has the characteristics of integrated forming, high material utilization rate, high digitalization and the like, so that the method has a wide prospect in the field of manufacturing of precise and complex parts.
Whether a structural part formed using 3D printing techniques can be used in product manufacturing depends directly on the quality of the part. In order to obtain structural parts with required performance, parameter planning is required to be carried out before 3D printing so as to achieve the purpose of final preview, and real-time regulation and control are carried out in the 3D printing process so as to improve the production efficiency and the product quality. The traditional experimental method achieves the purpose of accumulating data by developing a large number of experiments, and has high cost, time and labor waste and difficulty in ensuring accuracy. The 3D printing process is an irreversible process, and the lack of a real-time regulation and control technology not only increases the time cost, but also has high requirements on the printing fault tolerance rate. With the improvement of computer simulation technology and related basic theory, there is a case of realizing preview of casting and welding process by simulating temperature field, stress strain field, microstructure field, etc. The 3D printing process is a process of rapid melting and rapid cooling, the existing time of a molten pool is very short, but the physical process of the molten pool is very complex, and the 3D printing process is simulated to realize 3D printing preview and regulation and control, which is a new challenge.
Disclosure of Invention
Aiming at the problems, the invention aims to design a 3D printing preview method based on multi-field coupling modeling and simulation solving so as to realize multi-field multi-scale visual preview of a 3D printing process. By means of carrying out multi-field coupling simulation of a temperature field, a flow field, a stress strain field, a microstructure, a defect field and the like in the 3D printing process of the structural part, the 3D printing technology and finite element analysis are comprehensively applied, the tissue, stress and performance prediction of the 3D printed structural part is achieved, and the purpose of 3D printing preview and regulation and control of the structural part is achieved.
In order to achieve the above object, the 3D print preview method based on multi-field coupling modeling and simulation solving in the present invention includes the following specific contents:
(1) constructing a multi-field coupling model of a 3D printing process of the structural part: establishing a three-dimensional geometric model and a grid model, defining material parameters, completing pretreatment of a solver, and completing establishment of a multi-field coupling model of a macroscopic temperature field, a stress strain field, a flow field, a microstructure field, a solute field and a defect field by adopting a computer programming language and finite element analysis software;
(2) establishing a solving algorithm of a multi-field coupling model: the macroscopic temperature field and the stress strain field adopt a finite element method, the macroscopic flow field adopts a finite volume method, the viscosity is realized by writing a User-defined function, the microstructure field, the solute field and the defect field adopt a specific Cellular Automata (CA) method, the conversion of a macroscopic physical field calculation result and microscopic physical field data is completed by an interpolation coupling algorithm, and the solving calculation of a multi-physical field coupling model is completed by applying an iterative algorithm;
(3) obtaining optimized 3D printing process parameters: and comparing and analyzing the calculation result of the multi-field coupling model with the preliminary test result in real time, judging that the multi-field coupling model returns to adjustment or continues to calculate according to the comparison result, obtaining the macroscopic and microscopic changes of the 3D printing process of the structural part when the performance parameters of the 3D printing structural part obtained by simulation completely accord with the test result, and outputting the 3D printing process parameters to achieve accurate preview and accurate guidance of the 3D printing process.
Preferably, in the step (1), the established three-dimensional geometric model close to reality is measured, analyzed and integrated based on partial experimental results, the geometric model is gridded by adopting a density-sparse combination gridding method, the material parameters comprise liquidus temperature, liquidus slope, solute distribution coefficient, liquid phase diffusion coefficient, solid phase diffusion coefficient, Gibbs-Thomson coefficient, initial concentration, cell size, time step, specific heat capacity, heat conductivity, young modulus, yield strength, density and the like, the thermosensitive material is defined as a function changing along with temperature, such as the specific heat capacity and the heat conductivity are defined as functions changing along with temperature, and the simulation software A, B, C, D and the programming software E are used for establishing the multi-field coupling model of the 3D printing structural part.
Preferably, the step (2) is to consider the calculation of the macroscopic flow field, approximate the flow variable to be solved by using a simple function in the finite element software C, substitute the approximate relation into the control equation of continuity to form a discrete equation system, and then solve the algebraic equation system. The CA method comprises a nucleation model, a dendrite growth model and a solute diffusion model, wherein the nucleation model is a uniform nucleation model and a non-uniform nucleation model which correspond to different algorithms and coexist. The coupled interpolation algorithm firstly discretizes a calculation region, divides the region into a limited number of grid nodes, each grid node is provided with a corresponding coordinate (i, j), then discretizes an equation by a finite difference method, approximately solves by using points around the coordinates, and changes continuous variables into discrete points; and finally, replacing the solution of the partial differential equation by an interpolation polynomial and the differential thereof to realize approximate solution. The iterative algorithm determines whether to continue the calculation by determining whether the state variables of all the cells are all "1".
Preferably, the macro-change in step (3) includes temperature field distribution, thermal cycle curve, residual stress distribution, residual deformation distribution, flow field distribution, etc. of the 3D printing process of the structural part, the micro-change includes microstructure distribution law, microstructure evolution, phase change, solute distribution evolution, defect distribution, formation law, etc., and 3D printing preview of the structural part can be realized according to the macro-and micro-changes and based on the 3D printed structural part performance parameters including porosity, crack distribution, deformation, microstructure size, etc. of the structural part. The judgment process of the comparison result on the multi-field coupling model starts from the judgment of the temperature field, the stress strain field and the flow field are in a mutual judgment relation, the calculation of the microscopic physical field can enter the next step only when the simulation results of the temperature field, the stress strain field and the flow field are matched with the preliminary test result, the microscopic tissue field, the solute field and the defect field adopt a sequential judgment sequence, when the final microscopic defect field is matched with the preliminary test result, 3D printing process parameters including laser power, powder feeding rate, laser scanning speed and layering thickness are output, the gradual realization of the judgment process of the multi-field coupling model through the comparison result can achieve the purpose of accurately regulating and controlling the 3D printing process.
The invention has the beneficial effects that:
aiming at the problem that the product quality and the production efficiency are difficult to meet the actual production requirements due to a plurality of factors such as low fault-tolerant rate, high time cost and the like in the current 3D printing process, the aims of accurate preview and accurate regulation and control of the 3D printing process of the structural part can be fulfilled by establishing a multi-physical-field coupling model and solving the model by adopting a specific algorithm. The model can well simulate the temperature field, can consider the influence of the temperature field change on the microscopic physical field, the macroscopic flow field and the stress strain field, establishes the coupling of the macroscopic physical field and the microscopic physical field, and realizes the multi-field coupling simulation of the powder melting and solidifying processes in the 3D printing process of the structural part. The simulation process can be compared with the preliminary experiment result in real time, so that model regulation and control and optimization of 3D printing process parameters are completed. The simulation result can accord with the macro and micro appearance of the 3D printing structure part in the laboratory.
Drawings
FIG. 1 is a flow diagram of an implementation of a three-dimensional finite element modeling and simulation method for a macroscopic temperature field and a stress-strain field of a 3D print preview model based on multi-field coupling solution;
FIG. 2 is a flow chart of an implementation of a three-dimensional finite element modeling and simulation method for a macroscopic flow field of a 3D print preview model based on multi-field coupling solution;
FIG. 3 is a flow diagram of an implementation of a microscopic simulation for a 3D print preview model based on multi-field coupling solution;
FIG. 4 is a flow diagram of a simulation algorithm implementation for a 3D print preview model based on multi-field coupling solution;
FIG. 5 is a flow diagram of an implementation of a 3D print preview model for multi-field coupling based solution.
Detailed Description
The following describes a 3D print preview method based on multi-field coupling modeling and simulation solving in detail with reference to the accompanying drawings.
The working flow of the method of the invention is shown in figures 1-3.
FIG. 1 is an implementation flow diagram of a three-dimensional finite element modeling and simulation method for macroscopic temperature and stress-strain fields of a 3D print preview model based on multi-field coupling solution.
Step 1, establishing a 3D printing structure part geometric model, wherein the specific steps comprise establishing the 3D geometric model in finite element modeling software A or L according to the actual structure size of the 3D printing structure part;
and 2, establishing a grid model, and performing grid division on the geometric model of the 3D printing structure part in the finite element software B in a density transition grid division mode to ensure the efficiency and the accuracy of calculation.
Step 3-5 is to establish a 3D printing finite element model of the structural part in finite element software D finite element analysis software, which comprises the following steps:
(1) applying the material property. Defining the relation among the variables such as elastic modulus, yield strength, thermal expansion coefficient, thermal conductivity, specific heat capacity and temperature, defining Poisson's ratio and density of the material, and applying the defined material performance to the corresponding unit;
(2) a laser scan path is defined. The 3D printing process of the structural part is generally multilayer and multichannel laser scanning, so that a plurality of laser scanning paths need to be set, the paths are set by adopting a node method, the laser pointing method adopts a node method, and nodes are selected according to the relation between the previously set laser scanning paths and the laser irradiation direction;
(3) thermodynamic boundary conditions are imposed. The thermal boundary condition firstly selects a proper heat source model to characterize the action of the laser beam, and sets heat source parameters, wherein the heat source parameters comprise: welding energy, effective power coefficient, heat source width, heat source depth, heat source front half ellipsoid length, heat source rear half ellipsoid length, Gaussian heat source parameters: setting a welding speed after finishing setting heat source model parameters, selecting a welding path corresponding to the parameters, selecting a unit range which can be included by a heat source, applying convection boundary conditions of a workpiece and an external environment, setting the convection coefficient of the workpiece and the external environment to be 40, setting the temperature of the ambient environment to be 20 ℃, and selecting all surfaces capable of radiating to set radiating boundary conditions; the mechanical boundary condition setting is mainly to prevent the object from generating rigid displacement, and the constraint applying principle can ensure that the object does not generate rigid displacement, but can not add redundant rigid constraint. And (5) carrying out displacement constraint on the structural units in X, Y and Z directions to complete the setting of mechanical boundary conditions.
And 6, after the finite element model is established, calculating the temperature field and the stress field by adopting a finite element method.
Step 7, judging whether to continue calculating by judging whether the laser scanning path is finished, if so, entering step 5 to reapply the heat source model, otherwise, outputting a simulation result;
FIG. 2 is a flow chart of an implementation of a three-dimensional finite element modeling and simulation method for a macroscopic flow field of a 3D print preview model based on multi-field coupling solution.
Step 8 is the solver setup. Before step 8, completing the operation of step 1-2, reading the established mesh model into the finite element software C and checking the mesh. In the finite element software C, a flow variable to be solved is approximated by using a simple function, the approximate relation is substituted into a control equation of continuity to form a discrete equation set, and then an algebraic equation set is solved.
Step 9 is defining material properties, comprising: the density, specific heat capacity and heat transfer coefficient are equal to temperature-related parameters, liquidus temperature and solidus temperature, and viscosity are realized by compiling a User-defined function;
step 10, for defining boundary conditions, setting velocity and scalar velocity entry boundary conditions for defining flow entry boundaries, comprising: defining the inflow velocity, setting the temperature (in solving the energy equation, the static temperature of the flow needs to be set at the velocity entrance boundary in the temperature field), and defining the outflow standard pressure. Setting pressure outlet boundary conditions for defining the static pressure (including other scalars in the return flow) of the flow outlet, the setting of the pressure outlet boundary conditions requiring input parameters including: static pressure, reflux conditions, total temperature, i.e. stagnation temperature (for energy calculations), turbulence parameters (for turbulence calculations), volume fraction of secondary phase (for calculations of multiphase flow), discrete phase boundary conditions (for discrete phase calculations);
step 11, solving the flow velocity of each point of a turbulence equation and the overall flow field distribution through iterative calculation;
and step 12, outputting a numerical simulation result.
FIG. 3 is a flow diagram of an implementation of a microscopic simulation for a 3D print preview model based on multi-field coupling solution.
Step 13, inputting temperature, solute fraction and material physical parameters of the 3D printing structural part used in the simulation, wherein the physical parameters comprise liquidus temperature, liquidus slope, solute distribution coefficient, liquid phase diffusion coefficient, solid phase diffusion coefficient, Gibbs-Thomson coefficient, initial concentration, cell size, time step and the like;
step 14-16 macroscopic microscopic temperature field coupling process. And (3) simulating the macroscopic temperature field and the microscopic structure by using two kinds of software, namely finite element software D and programming software E respectively, and adopting a weak coupling mode in the process of realizing the coupling of the macroscopic temperature field and the microscopic temperature field. In the weak coupling mode, the temperature of each unit cell is in a unique solidification path, the macroscopic time step is obtained by macroscopic node temperature interpolation, and the CA nucleation and growth model is circularly called to complete simulation.
Step 17 is to establish a nucleation growth model, which gives each cell the following information: temperature, solute concentration, grain color variation, grain growth orientation, and grain state variation. The grain color variation is used to represent different solid phase grains, each nucleated solid phase grain having a random growth orientation. The state change of the unit cell is expressed by continuous variables. "1" represents a solid phase, "0" represents a liquid phase, and a solid/liquid interface is represented between "0" and "1", and the cellular elements in the interface state can be nucleated and grown up.
Step 18 is a calculation process of the nucleation growth model, firstly, whether the supercooling degree (delta T) is greater than the critical supercooling degree (delta Tn) or not is judged, and when the supercooling degree (delta T) is greater than the critical supercooling degree (delta Tn), solidification and nucleation occur in the liquid metal; once the core is formed, the crystal nucleus continues to grow to form crystal grains, so that after the core is formed, the model judges whether the crystal nucleus grows, when a growth signal returned to the program is sent, the program updates the state variable of the cell, and the state variable of the cell is changed from '0' to '1';
step 19, judging whether to continue calculating by judging whether the state variables of all the cells are all '1', judging whether the state variables of all the cells are all '1' by continuously returning the state variables of the cells, finishing the solidification process when all the cells are changed into solid phase, and outputting a simulation result; if the cells are in the liquid phase, carrying out secondary judgment to judge whether the time limit is reached, if the time limit is reached, directly outputting a simulation result, and if the time limit is not reached, entering the simulation of the next moment until all the cycles are finished, and outputting the simulation result;
FIG. 4 is a flow chart of a simulation algorithm implementation for a 3D print preview model based on multi-field coupling solution.
Step 20 is the calculation of a macroscopic temperature field, a stress strain field and a flow field, and steps 1 to 12 are the specific implementation flow of step 20;
step 21 is the calculation of the microscopic temperature field and the flow field, and the process is realized by carrying out an interpolation algorithm on the macroscopic temperature field. First, a regular (usually orthogonal equidistant) meshing of the computed regions is required, and the basic steps include:
(1) calculating area discretization: the calculation region is divided into an M × N grid. Dividing the region into a finite number of mesh nodes, each mesh node having a corresponding coordinate (i, j);
(2) approximate substitution: discretizing an equation by a finite difference method, and according to a difference format, approximately solving by using points around coordinates, wherein continuous variables are changed into discrete points through the processing;
(3) and (3) approximation solving: this process can be seen as a process of replacing the solution of the partial differential equation with an interpolation polynomial and its differential, and the interpolation rule can be simply expressed as:
Figure BSA0000188439040000061
step 22 is multi-field coupling calculation of a micro temperature field, a micro flow field, a micro tissue field, a defect field and a solute field, the micro coupling calculation is carried out based on the simulation results of the first three models, and a multi-field coupling model is firstly required to be established. The method comprises the following steps:
(1) dividing a grid: the calculation area is divided by adopting orthogonal grids, and the principle is mainly followed when the orthogonal grids are divided: 1) the grid adopts a square regular grid with the same size; 2) each grid is endowed with different characteristic variables and states, such as temperature, concentration, liquid phase, solid phase and the like; 3) the state change of the grid is determined according to the state of the neighbor grid; 4) the grid size is selected, and the calculation capability of the equipment and the instability caused by calculation are comprehensively considered;
(2) definition of thermophysical parameters: thermophysical parameters used include: density, liquidus temperature, solidus temperature, thermal conductivity, latent heat of solidification, specific heat capacity, and the like;
numerical value processing: the multi-field coupling numerical calculation model mainly comprises pretreatment, numerical calculation and post-treatment. 1) Preprocessing (initialization process of program): the thermal physical parameters, the temperature and the solute fraction are written into a program, one or more grain growth core points are arranged in a calculation area at the beginning of calculation, and the states of the rest grid points are respectively assigned to be solid-phase cells, liquid-phase cells or interface-layer cells according to the position of a growth core and a capture rule; 2) numerical value processing: and (4) calculating a control equation, and combining the initial condition and the interface judgment condition to iteratively solve the dispersed equation. After the initialization is completed, heat and mass transfer exists in each time step, and heat and mass transfer exists in the whole calculation area, so that heat and mass transfer calculation needs to be carried out on the grids in the whole area. According to the capture principle of the unit cell, when the unit cell meets the following two conditions, the unit cell becomes an interface layer unit cell, wherein whether at least one unit cell is a solid phase in the adjacent unit cell or not is judged, and whether the unit cell node is positioned in the interface layer or not is judged. In the multi-field coupling micro model, one or more grains which are arranged in advance are selected in the initial stage and are endowed with a preferential growth direction of 0-90 degrees. Then calculating the growth of the crystal grains, and using a new capture rule to make the interface continuously move towards the liquid phase and the crystal grains continuously grow up; 3) and (3) post-treatment: after the calculation is completed, a series of data files can be generated, and when the set conditions are met, the data stops being output. And (4) sorting and analyzing the simulation results, and performing certain processing on the results by using the visual software F to visually display the simulation results.
FIG. 5 is a flow diagram of an implementation of a 3D print preview model for multi-field coupling based solution.
Step 23, inputting the technological parameters of the designed 3D printing structural part, wherein the technological parameters comprise: layer height, print speed, print temperature, scan power, scan spacing, etc.
And 24, calculating a temperature field, a stress strain field, a flow field, a solute field, a microstructure field and a microscopic defect field in sequence, wherein the steps 1 to 22 are a specific calculation process of the multi-physical field in the step 24. Firstly, calculating a temperature field to obtain the temperature field distribution characteristic of the structural part in the 3D printing process, comparing and judging the temperature field distribution characteristic with the physical property parameters of the actual structural part in the 3D printing process, if the temperature field distribution characteristic is consistent with the actual result, continuing the next step of calculation, if the temperature field distribution characteristic is not consistent with the actual result, redesigning the process parameters of the 3D printing structural part, and returning to the step 23; finishing temperature field judgment, performing stress-strain field calculation, comparing and judging a stress-strain characteristic result in the 3D printing process of the structural part with physical property parameters of the 3D printing process of the actual structural part, continuing the next step of calculation if the result is consistent with an actual result, redesigning the process parameters of the 3D printed structural part if the result is not consistent with the actual result, and returning to the step 23; and (5) finishing layer-by-layer calculation and judgment of the flow field, the solute field, the microstructure field and the microscopic defect field in sequence, and finally entering step 25 if all results are consistent with physical parameters of the actual structural part in the 3D printing process, outputting process parameters of the 3D printed structural part, and performing an actual 3D printing experiment on the structural part.
The foregoing is only a preferred embodiment of this invention and it should be noted that modifications can be made by those skilled in the art without departing from the principle of the invention and these modifications should also be considered as the protection scope of the invention.

Claims (3)

1. A3D printing preview method based on multi-field coupling modeling and simulation solving is characterized by comprising the following steps:
(1) constructing a multi-field coupling model of a 3D printing process of the structural part: establishing a three-dimensional geometric model and a grid model, defining material parameters, completing pretreatment of a solver, and completing establishment of a multi-field coupling model of a macroscopic temperature field, a stress strain field, a flow field, a microstructure field, a solute field and a defect field by adopting a computer programming language and finite element analysis software;
(2) establishing a solving algorithm of a multi-field coupling model: the macroscopic temperature field and the stress strain field adopt a finite element method, the macroscopic flow field adopts a finite volume method, the viscosity is realized by writing a User-defined function, the microstructure field, the solute field and the defect field adopt a specific Cellular Automata (CA) method, the conversion of a macroscopic physical field calculation result and microscopic physical field data is completed by an interpolation coupling algorithm, and the solving calculation of a multi-physical field coupling model is completed by applying an iterative algorithm;
(3) obtaining optimized 3D printing process parameters: comparing and analyzing the calculation result of the multi-field coupling model with the preliminary test result in real time, judging that the multi-field coupling model returns to adjustment or continues to calculate according to the comparison result, obtaining the macroscopic and microscopic changes of the 3D printing process of the structural part when the performance parameters of the 3D printing structural part obtained by simulation completely accord with the test result, and outputting the 3D printing process parameters to achieve accurate preview and accurate guidance of the 3D printing process;
the macroscopic change in the step (3) comprises temperature field distribution, a thermal cycle curve, residual stress distribution, residual deformation distribution and flow field distribution of the structural part in the 3D printing process, the microscopic change comprises a microstructure distribution rule, a microstructure evolution rule, phase change, solute distribution evolution, defect distribution and a formation rule, and 3D printing preview of the structural part can be realized according to the macroscopic change and the microscopic change and based on the performance parameters of the 3D printed structural part, including porosity, crack distribution, deformation and microstructure size of the structural part; the judgment process of the comparison result on the multi-field coupling model starts from the judgment of the temperature field, the stress strain field and the flow field are in a mutual judgment relation, the calculation of the microscopic physical field can enter the next step only when the simulation results of the temperature field, the stress strain field and the flow field are matched with the preliminary test result, the microscopic tissue field, the solute field and the defect field adopt a sequential judgment sequence, when the final microscopic defect field is matched with the preliminary test result, 3D printing process parameters including laser power, powder feeding rate, laser scanning speed and layering thickness are output, the gradual realization of the judgment process of the multi-field coupling model through the comparison result can achieve the purpose of accurately regulating and controlling the 3D printing process.
2. The 3D printing preview method based on multi-field coupling modeling and simulation solving of claim 1, wherein the step (1) is to integrate the established three-dimensional geometric model close to reality based on partial experimental result measurement and analysis, to perform grid division on the geometric model by adopting a density-sparse combination grid division method, to define the thermal sensitive material as a function varying with temperature, to establish the multi-field coupling model of the 3D printing structural part by using simulation software CATIA, Hypermesh, Fluent, MSC.
3. The 3D print preview method based on multi-field coupling modeling and simulation solution as claimed in claim 1, wherein the step (2) is to consider the calculation of the macroscopic flow field, approximate the flow variables to be solved in Fluent by using simple functions, substitute the approximate relationship into the control equation of continuity to form a discrete equation system, and then solve the algebraic equation system; the cellular automata method comprises a nucleation model, a dendrite growth model and a solute diffusion model, wherein the nucleation model is a uniform nucleation model and a non-uniform nucleation model which are corresponding to different algorithms and are coexisted; the interpolation coupling algorithm firstly discretizes a calculation region, divides the region into a limited number of grid nodes, each grid node is provided with a corresponding coordinate (i, j), then discretizes an equation by a finite difference method, approximately solves by using points around the coordinates, and changes continuous variables into discrete points; finally, an interpolation polynomial and the differential thereof are used for replacing the solution of a partial differential equation to realize approximate solution; the iterative algorithm determines whether to continue the calculation by determining whether the state variables of all the cells are all "1".
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