A discrete simulation method for ingot additive solidification forming

Abstract

The ingot casting additive solidification forming discretization simulation method comprises the following steps: step 1, obtaining simulation experiment parameters, determining the calculation domain size according to the actual size and dividing the grid, and planning the solution path; step 2, establishing a VOF two-phase flow solidification model; step 3, defining material properties and boundary conditions; step 4, sequentially solving the Navier-Stokes equation based on the Reynolds average continuity equation and the standard k-epsilon turbulence model equation; step 5, extracting and analyzing temperature field evolution data points; step 6, using the dynamic grid technology to increase the calculation domain height to complete the multi-layer casting forming. The beneficial effects of the present application are: by simulating the evolution law in the whole casting forming process in a relatively small calculation domain, the calculation efficiency is greatly improved, and the time cost is saved; by analyzing the temperature field results obtained by numerical simulation, the evolution of the temperature field in the actual experiment process is consistent.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of ingot additive solidification forming discretization simulation method, specifically about the discretization simulation method in the ingot additive solidification process, specifically relates to the discretization simulation method in 3D metal printing process, belongs to the field of additive manufacturing. BACKGROUND

[0002] In recent years, with the rapid development of 3D printing technology, this technology is also introduced in the process of additive manufacturing, and gradually applied to industrial production. Additive manufacturing is a hot processing technology that makes materials from point to line, from line to surface accumulation to form three-dimensional entity through discrete accumulation, which has the advantages of rapid prototyping and arbitrary shaping, and can greatly improve the efficiency of solidification forming and save money and time costs.

[0003] Due to the characteristics of rapid cooling in the process of additive manufacturing, and the influence of heat accumulation and morphology in the process of accumulation and lapping, the formed parts often have defects such as pores and cracks. The causes of these defects are difficult to observe by experimental means, and a large number of experiments without theoretical guidance not only waste time and effort, but also cannot grasp the important mechanism of affecting the forming material and performance. Therefore, by constructing a reasonable numerical model, not only can the evolution process of temperature field be explored, but also the precise control of temperature field can be realized, which has important significance and application value.

[0004] The finite element numerical simulation method of additive manufacturing solidification forming usually includes the following steps: 1. Determine the size of the calculation domain; 2. Divide the structural grid; 3. Select the appropriate calculation method; 4. Define the source term through external language; 5. Define material properties and boundary conditions; 6. Solve the calculation. Through the previous experiment, the basic parameters in the model are obtained, and the simulation and experimental results are compared to verify the reliability of the model. In actual production process, due to the size of the formed parts is too large, leading to the time of numerical calculation is too long, greatly waste the time cost, which is not consistent with the original intention of numerical simulation. SUMMARY

[0005] The present application is directed to the deficiencies of the prior art, and proposes an additive manufacturing discretization numerical simulation method. This method can accurately predict the temperature evolution of the material solidification at each moment in the entire additive forming process, and lay a theoretical foundation for better controlling the forming quality.

[0006] To achieve the above technical purpose, the technical scheme adopted by the present application is:

[0007] An ingot additive solidification forming discretization simulation method, characterized in that it comprises the following steps:

[0008] Step 1, obtain the simulation experiment parameters, determine the calculation domain size according to the actual size and divide the grid, plan the solution path:

[0009] (a) According to the numerical value obtained in the casting experiment process, determine the basic process parameters of the simulation experiment, and define the thermal physical parameters of the material and the boundary conditions of the model according to the reference; wherein the basic process parameters include single nozzle casting speed, nozzle moving speed, nozzle diameter and offset of each casting layer; the boundary condition of the model is water cooling boundary condition;

[0010] (b) According to the actual size of the model, define the size of the solution domain, and divide the grid of the solution domain:

[0011] (b1) Define the discrete simulation method of ingot additive solidification forming, simulate the evolution results of the area to be observed, establish a three-dimensional solidification model, and use uniform structured grid to ensure calculation efficiency and accuracy. The structure of the grid and the size of the grid are consistent;

[0012] (b2) According to the size of the three-dimensional solidification model, the defined discrete simulation method is used to simulate the initial casting position, determine the calculation domain size and divide the grid, and plan the solution path;

[0013] Step 2, establish a VOF two-phase flow solidification model:

[0014] 1) According to the actual casting situation, there is only solidification process of molten metal in the casting process, establish a transient VOF two-phase flow model based on k-ε turbulence, calculate the volume fraction of each grid unit for the two phases added to the model, wherein the sum of the volume fractions of all phases is 1, and all phases share variables and physical parameters;

[0015] 2) Set the movement path of the transient VOF two-phase flow model based on k-ε turbulence according to the demand:

[0016] ① Use UDF programming to realize the planning control of the path, define the size of the substrate and the size of the solution domain respectively, the width is not limited, set the program control switch to control the stage of the building process; Subsequently, use dynamic grid technology to increase the calculation domain of the simulation;

[0017] ② According to the time required for the nozzle to cast a layer, the nozzle moving speed and the nozzle moving speed after casting a layer, determine the X position of the current nozzle:

[0018] T w =x*y / off-side / V n , (1);

[0019] T s =y / V n , (2);

[0020] I = t / T w , (3) ;

[0021] t s = t - I*T w , (4) ;

[0022] II = t s / T s , (5) ;

[0023] X_X = II*off_side, (6) ;

[0024] wherein: T w is the time required for the nozzle to cast a layer, in s; x, y are the substrate width and length, respectively, in mm; V n is the nozzle moving speed, in mm / s; off_side is the offset of each cast layer, in mm; T s is the time required for a single cast layer, in s; I is the layer number after rounding; t is the current time, in s; t s is the time at which the nozzle moves at the current layer; II is a specific pass of the current cast layer; X_X is the current X coordinate of the nozzle;

[0025] 3. Determine the current nozzle Y coordinate according to the time required for the nozzle to cast a layer, the nozzle moving speed, and the nozzle moving speed after casting a layer:

[0026] Y_Y = fmod(t s , T s )*V N (7) ;

[0027] Y_Y = y - fmod(t s , T s )*V N (8) ;

[0028] wherein: T s is the time required for a single cast layer, in s; x, y are the substrate width and length, respectively, in mm; t s is the time at which the nozzle moves at the current layer; V n is the nozzle moving speed, in mm / s; the fmod function is the remainder obtained by dividing the former by the latter; if it is an odd pass, the program executes formula (7), if it is an even pass, the program executes formula (8); Y_Y is the current Y coordinate;

[0029] Step 3. Define material properties and boundary conditions:

[0030] [1] Define the material properties, import the grid model in step 1 to establish the VOF two-phase flow solidification model, and select the VOF calculation method according to formulas (1)-(6), and define its material properties;

[0031] [2] Load the UDF program, define the boundary conditions and heat exchange boundary conditions, and the heat boundary condition is the room temperature, and the heat exchange coefficient of the fluid with the outside world;

[0032] [3] According to the above boundary conditions and initial data and Fourier's law, the temperature evolution process can be obtained:

[0033] T=f(y,z,t) (9);

[0034]

[0035] In the formula: x, y, z is a rectangular coordinate system, T is the temperature, unit K; t is the time, unit s; ρ is the density of the cast metal, unit Kg / m 3 ; c is the specific heat of the material J / Kg -1 ·K -1 , The heat source intensity is W;

[0036] Step 4, sequentially solve the Navier-Stokes and standard k-ε turbulence model equations based on the Reynolds-averaged continuity equation:

[0037] (i) Calculate and solve three conservation equations, namely mass conservation equation, momentum conservation equation and energy conservation equation, considering that the fluid flow is a flow system composed of incompressible fluid, wherein:

[0038] According to the mass conservation equation, the mass source term is solved to obtain the fluid volume fraction in the grid element:

[0039]

[0040]

[0041] In the formula: q represents the cast metal; ρ is the density, unit is, unit is Kg / m 3 ; α is the volume fraction; The velocity vector is m / s; t is the time, unit s; The metal liquid sprayed by the spray gun per unit time is Kg; V is the casting volume unit m 3 ;

[0042] According to the momentum conservation equation, the volume force source term is solved:

[0043]

[0044] where: for a system of n phases, the physical property parameters in the unit grid are weighted average of the volume fraction of each phase, μ is the dynamic viscosity coefficient of the fluid, unit: Kg / m -1 ·s -1 ;▽ is the Hamiltonian operator; T is the shear stress upper index; P is the pressure unit: N / m 2 , F is the equivalent volume force of surface tension, unit: N;

[0045] According to the energy conservation equation, the energy source term is solved, and the empirical correction formula of the Stirling-Boltzmann law is used for calculation:

[0046]

[0047]

[0048] where: E is the total energy, unit: J, k eff is the effective thermal conductivity, unit: W / m -1 ·K -1 ; Q is the energy source term, unit: W / m 3 ; h is the heat transfer coefficient, unit: W / m -2 .K -1 , T ref-tem is the external temperature, unit: T, V cell is the size of the grid unit, unit: m 3 , ε is the emissivity of the object (commonly known as black body), σ b is the black body radiation constant, unit: W / m -2 .K 4 ;

[0049] (2) Solve the k-ε turbulent form equation in the standard form, and get G k , get the morphology evolution under the melt flow:

[0050]

[0051]

[0052] where: G k represents the turbulent kinetic energy caused by the average velocity gradient; C lε and C 2ε are constants, k is the turbulent kinetic energy, unit: J, ε is the dissipation rate, μ is the viscosity, unit: Kg / m -1 ·s -1 ;

[0053] Step 5, extract and analyze the temperature field evolution data points:

[0054] <1> Selecting multiple points in the calculation domain for data extraction, selecting points on the edge of the calculation domain and the corresponding position above;

[0055] <2> Collecting the temperature distribution obtained by simulation after extraction, and finally obtaining the temperature field evolution curve in the casting process;

[0056] Step 6, using dynamic mesh technology to increase the height of the calculation domain to complete the multi-layer casting forming:

[0057] After the completion of the current layer casting, when the height of the calculation domain does not meet the next layer casting, the dynamic mesh technology is used to improve the position of the spray gun, and the next layer casting is continued, and the reciprocating is repeated until the casting is completed.

[0058] Further, in step (2), in order to save the calculation cost, the calculation iteration step of different time periods is defined:

[0059] When the nozzle moves to the inside of the calculation domain, the nozzle switch is turned on, and the iteration step is 1e-4; when the nozzle is at the edge of the calculation domain, the iteration step is 2e-4, which is convenient for transition; when located outside the calculation domain, the iteration step is 1e-3. Can greatly save the calculation time.

[0060] Further, in step (5)<1>, four points in the calculation domain are selected for data extraction, the first point is selected at x=14mm, y=14mm along the edge of the calculation domain, the second point is selected at x=16mm, y=16mm along the edge of the calculation domain, and the third and fourth points are selected at the corresponding position above, respectively. Increase 2mm.

[0061] The present application is based on the coupling of flow mechanics and heat transfer theory, and the temperature field evolution in the solidification forming process of additive manufacturing ingot is discretely simulated. The whole solidification can be represented by the discretely formed process. A new idea is provided for numerical simulation of solidification forming process and finite element simulation in other fields. Especially in the face of the unprecedented development of numerical simulation, improving the efficiency of simulation has great significance for mastering the theoretical mechanism in the solidification process of additive manufacturing.

[0062] The beneficial effects of the present application are: by simulating the evolution law in the whole casting forming process in a relatively small calculation domain, the calculation efficiency is greatly improved, and the time cost is saved; by analyzing the temperature field results obtained by numerical simulation, the evolution of the temperature field in the actual experiment process is analyzed. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 The present application is a casting solidification forming process flow diagram.

[0064] Figure 2a, 2b is the experimental size diagram of the casting solidification forming process of the application and the simulation calculation domain size comparison schematic diagram.

[0065] Figure 3 It is the point taking schematic diagram in the numerical simulation process of the casting forming of the application.

[0066] Figure 4a , 4b It is the solid phase forming schematic diagram in the numerical simulation process of the casting forming of the application.

[0067] Figure 5a , 5b It is the substrate position temperature field evolution in the numerical simulation process of the casting forming of the application

[0068] Figure 6a , 6b It is the temperature field data extraction schematic diagram in the numerical simulation process of the casting forming of the application.

[0069] Figure 7a , 7b It is the calculation domain size and the number of grids before and after the implementation of the dynamic grid in the process of the application. DETAILED DESCRIPTION

[0070] The specific implementation of the embodiments of the application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiments of the application, and is not used to limit the embodiments of the application.

[0071] It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other without conflict.

[0072] In the description of the application, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the application and simplify the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the application.

[0073] In addition, the terms "first", "second", etc. are used only for descriptive purposes and do not connote or imply relative importance or a quantity of the indicated technical features. Thus, a feature defined with "first" or "second" can include at least one of the features explicitly or implicitly. In the description of the present application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise explicitly specified and limited.

[0074] In the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting", "fixing" and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected or communicated with each other; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be the internal communication or interaction relationship of two elements, unless otherwise explicitly limited. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0075] In the present application, unless otherwise explicitly specified and limited, the first feature is "on" or "under" the second feature, which can be direct contact between the first and second features, or indirect contact between the first and second features through an intermediate medium. Moreover, the first feature "above", "over" and "on" the second feature can be directly above or obliquely above the first feature, or only indicate that the horizontal height of the first feature is higher than that of the second feature. The first feature "below", "under" and "under" the second feature can be directly below or obliquely below the first feature, or only indicate that the horizontal height of the first feature is less than that of the second feature.

[0076] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms is not necessarily for the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in the present application and the features of different embodiments or examples without contradiction.

[0077] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with exemplary embodiments.

[0078] The ingot casting additive solidification forming discretization simulation method described in the present application comprises the following steps:

[0079] Step 1: Obtain simulation experiment parameters, determine the computational domain size based on actual dimensions and divide the mesh, and plan the solution path:

[0080] (a) The basic process parameters of the simulation experiment were determined based on the numerical values ​​obtained from the casting experiment process, and the thermal properties of the material and the boundary conditions of the model were defined according to the references. The thermal properties of the material were obtained from the data obtained by consulting the basic properties of the material itself, as shown in Table 3. The boundary conditions of the model were based on the water-cooled boundary conditions in the actual production process. The basic process parameters include the single-nozzle casting speed, the nozzle moving speed, the nozzle diameter, and the offset of each casting layer. The single-nozzle casting speed is 1500 mm / s, the nozzle moving speed is 100 mm / s, the nozzle diameter is 1.6 mm, and the offset of each casting layer is 6 mm.

[0081] (b) Based on the actual dimensions of the model (length × width = 200mm × 150mm), define the size of the solution domain (length × width = 32mm × 32mm), and divide the solution domain into a mesh with a mesh size of length × width = 0.5mm × 0.5mm;

[0082] (b1) Define a discretization simulation method for additive solidification forming of ingots (the computational domain differs from the actual model by more than 5 times), simulate the evolution results of the region to be observed, establish a three-dimensional solidification model, and use a uniform structured mesh to ensure computational efficiency and accuracy, with consistent structured mesh and mesh size.

[0083] (b2) Based on the dimensions of the 3D solidification model (length × width = 200mm × 150mm), to increase computational stability, a defined discretization simulation method (length × width = 32mm × 32mm) was used to simulate the initial casting position, determine the computational domain size, and mesh the model. Furthermore, to improve casting efficiency, an "S"-shaped casting path was used. The computational domain size was determined based on actual conditions, and was sufficient to reach a stable state during the casting process. The experimental object in this study was a melt casting model with dimensions of 200mm × 150mm (length × width) and no width limit. The experiment used single-nozzle casting, with the path set to an S-shaped path, the width gradually increasing with the number of casting layers. Figure 1 The diagram shown is a schematic of the casting process;

[0084] The essence of discretization simulation is to ensure a accurate simulation of the actual casting process while minimizing the computational domain size. This method can be used when the computational domain size differs from the actual model size by more than five times. Figure 1 To realistically simulate the entire casting process, approximately 12 million grid cells are needed. Simulating the entire casting process comprehensively requires significant computational power, resulting in wasted time. Therefore, selective regions are simulated. A discretization simulation scheme is proposed, such as... Figure 2As shown, this calculation only uses discrete method to simulate the initial casting position, from the figure, two coordinate systems are proposed in the model, which are substrate coordinate system and calculation domain coordinate, and the calculation domain coordinate system is located in the substrate coordinate system. The substrate size is 200mmx150mm, the calculation domain selects the upper left corner position, the calculation domain center position coordinates are x=9mm, y=9mm, and the calculation domain size is 32mmx32mm. In this way, the casting process can be truly reproduced, and the time cost can be greatly shortened.

[0085] Step 2, establish a VOF two-phase flow solidification model:

[0086] 1) In order to better observe the evolution process of melt flow in the solidification process, a transient VOF two-phase flow model based on k-ε turbulence is established. For the two phases added to the model, the volume fraction of each grid element is calculated, and the sum of the volume fractions of all phases is 1, and all phases share variables and physical parameters; The model is established according to the actual casting situation. There is only a solidification process of molten metal during the casting process, so the solid-liquid two-phase flow is sufficient;

[0087] 2) According to the demand, set the motion path of the transient VOF two-phase flow model based on k-ε turbulence:

[0088] ① Use UDF programming to realize the planning control of the path using formulas (1)-(6), define the substrate size as 20mmx50mm, the solution domain size as 32mmx32mm, and the initial model width as 12mm, and set the program control switch to control the stage of the building process; Subsequently, the dynamic mesh technology is used to increase the calculation domain of the simulation;

[0089] ② According to the time required for the nozzle to cast a layer, the nozzle moving speed and the nozzle moving speed after casting a layer, determine the X position of the current nozzle:

[0090] T w = x*y / off-side / V n , (1);

[0091] T s = y / V n , (2);

[0092] I = t / T w , (3);

[0093] t s = t-I*T w , (4);

[0094] II = t s / T s , (5);

[0095] X_X = II * off_side, (6);

[0096] wherein: T w is the time required for the nozzle to cast a layer, in s; x and y are the width and length of the substrate, respectively, in mm; V n is the nozzle moving speed, in mm / s; off_side is the offset of each cast layer, in mm; T s is the time required for a single pass of casting, in s; I is the layer number after rounding; t is the current time, in s; t s is the time at which the nozzle moves to the current layer; II is a specific pass of the current cast layer; X_X is the current X coordinate of the nozzle;

[0097] III. Determining the current nozzle Y coordinate according to the time required for the nozzle to cast a layer, the nozzle moving speed, and the nozzle moving speed after casting a layer:

[0098] Y_Y = fmod(t s ,T s )*V N (7);

[0099] Y_Y = y - fmod(t s ,T s )*V N (8);

[0100] wherein: T s is the time required for a single pass of casting, in s; x and y are the width and length of the substrate, respectively, in mm; t s is the time at which the nozzle moves to the current layer; V n is the nozzle moving speed, in mm / s; the fmod function is the remainder of the former divided by the latter, obtaining the time of a specific pass; if it is an odd pass, the program executes formula (7), and if it is an even pass, the program executes formula (8); Y_Y is the current Y coordinate;

[0101] In order to save the calculation cost, the calculation iteration step length is defined for different time periods: when the nozzle moves to the inside of the calculation domain, the nozzle switch is turned on, and the iteration step length is 1e-4; when the nozzle is at the edge of the calculation domain, the iteration step length is 2e-4, facilitating the transition; when the nozzle is outside the calculation domain, the iteration step length is 1e-3. This can greatly save the calculation time.

[0102] Step 3. Defining material properties and boundary conditions:

[0103] [1] Defining material properties, importing the grid model described in step 1 into the VOF two-phase flow solidification model based on VOF calculation method, and defining the material properties thereof.

[0104] [2] Load UDF program, define the initial casting metal temperature and water cooling condition temperature, that is, define the boundary condition as water cooling boundary condition, water cooling constant temperature is 525K, and the initial temperature of molten metal is 973K;

[0105] [3] According to the above boundary conditions and initial data and Fourier's law, the temperature evolution process can be obtained:

[0106] T = f (y, z, t) (15);

[0107]

[0108] In the formula: x, y, z are the rectangular coordinate system, T is the temperature, unit K; t is the time, unit s; ρ is the density of casting metal, unit Kg / m 3 ; c is the specific heat of the material J / Kg -1 · K -1 , is the heat source intensity, unit W;

[0109] Step 4, sequentially solve the Reynolds-averaged continuity equation-based Navier-Stokes and standard k-ε turbulence model equations:

[0110] (i) Calculate and solve three conservation equations, namely mass conservation equation, momentum conservation equation and energy conservation equation, considering that the fluid flow is a flow system composed of incompressible fluid, wherein:

[0111] According to the mass conservation equation, the mass source term is solved to obtain the fluid volume fraction in the grid element:

[0112]

[0113]

[0114] In the formula: q represents the casting metal; ρ is the density, unit is, unit is Kg / m 3 ; α is the volume fraction; is the velocity vector, unit m / s; t is the time, unit s; is the metal liquid sprayed by the spray gun per unit time, unit Kg; V is the casting volume unit m 3 ;

[0115] According to the momentum conservation equation, the volume force source term is solved:

[0116]

[0117] In the formula: for a system consisting of n phases, the physical property parameters in the unit grid are weighted average of the volume fraction of each phase, μ is the dynamic viscosity coefficient of the fluid, unit: Kg / m -1 ·s -1 ;▽ is the Hamiltonian operator; T is the shear stress upper index; P is the pressure unit: N / m 2 , F is the equivalent volume force of surface tension, unit: N;

[0118] According to the energy conservation equation, the energy source term is solved, and the Staphan-Boltzmann Dinglu empirical correction formula is used for calculation:

[0119]

[0120]

[0121] In the formula: E is the total energy, unit: J, k eff is the effective thermal conductivity, unit: W / m -1 ·K -1 ; Q is the energy source term, unit: W / m 3 ; h is the heat transfer coefficient, unit: W / m -2 ·K -1 , T ref-tem is the external temperature, unit: T, V cell is the size of the grid unit, unit: m 3 , ε is the emissivity of the object (commonly known as black body), σ b is the black body radiation constant, unit: W / m -2 ·K 4 ;

[0122] (2) Solve the k-ε turbulent form equation in the standard form, get G k , get the morphology evolution under the melt flow:

[0123]

[0124]

[0125] In the formula: G k represents the turbulent kinetic energy caused by the average velocity gradient; C lε and C 2ε are constants, k is the turbulent kinetic energy, unit: J, ε is the dissipation rate, μ is the viscosity, unit: Kg / m -1 ·s -1 ;

[0126] Step 5, extract and analyze the temperature field evolution data points:

[0127] <1> In the calculation domain, select multiple points for data extraction, select points on the edge of the calculation domain and the corresponding position above; the distance between the selected point position and the edge of the calculation domain is x = 16 mm, y = 16 mm, z = 5 mm, and then the position of the point is increased by 5 mm in the z direction relative to the position of the upper point;

[0128] <2> The temperature distribution obtained by simulation is extracted and output as a Layout file, and finally the temperature field evolution curve during casting is drawn using the Origine software

[0129] Step 6, increase the height of the calculation domain using dynamic mesh technology to complete multi-layer casting molding:

[0130] After the completion of the current layer casting, if the height of the calculation domain does not meet the next layer casting, use the dynamic mesh technology to improve the position of the spray gun and continue the next layer casting, and so on until the casting is completed.

[0131] In step (5) <1>, select 4 points in the calculation domain for data extraction, select the first point along the edge of the calculation domain x = 14 mm, y = 14 mm, select the second point along the edge of the calculation domain x = 16 mm, y = 16 mm, and similarly select the third and fourth points at the corresponding position above by increasing 2 mm.

[0132] The following takes 7050 Al alloy as an example for discretization numerical simulation.

[0133] For the establishment of ingot additive solidification molding discretization simulation, taking the casting of 7050 Al alloy molten metal as an example, according to the actual casting process, the initial process parameters of the casting are determined as shown in Table 1. The material composition is shown in Table 2.

[0134] Table 1 Initial process parameters in the casting process

[0135]

[0136] Table 2 Chemical element table of 7075 aluminum alloy (%)

[0137]

[0138] A kind of ingot additive solidification molding discretization simulation is proposed, which simulates the molten metal liquid in the casting process, the material thermal physical parameters used in the model are shown in Table 3, and the calculation efficiency and calculation accuracy are improved by referring to the casting molding experimental process. The iteration time step in the calculation domain is 1e-4, the iteration time step close to the edge of the calculation domain is 2e-4, the iteration time step outside the calculation domain is 1e-3, and the grid size is 0.4 mm x 0.4 mm.

[0139] Table 3 Thermal physical parameters of discretization simulation materials

[0140]

[0141] Step 1: for numerical simulation of melt casting forming process, first, the actual size of the casting mold in the experiment process is determined, according to the actual size, the size used for simulation is judged, so as to reduce the size of the calculation domain.

[0142] Step 2, the position to be observed by the observer is determined, and the position where the center of the calculation domain is located is defined. The basic thermal physical parameters of the material and the boundary conditions are defined. The size of the casting model is as shown in Figure 2

[0143] Step 3, for the casting forming process parameters, the mass conservation equation, momentum conservation equation and energy conservation equation are solved, and the evolution of the casting melt temperature is obtained.

[0144] Step 4: for numerical model calculation in the casting process, the solved temperature data is substituted into the k-ε turbulence equation in the standard form, and the solid volume fraction of the melt casting forming is obtained as shown in Figure 4.

[0145] Step 5: for the calculation results in the casting process, the temperature change curve of different points is obtained.

[0146] Step 6: for multi-layer casting simulation, the dynamic mesh technology is used to raise the nozzle point, as shown in Figures 5 and 6, the solid volume fraction and temperature evolution curve under multi-layer casting simulation can be obtained.

[0147] The present application is aimed at discrete simulation of ingot additive solidification forming. If the simulation is completely carried out according to the experiment process, the calculation examples are wasted, and the time cost is increased. By adjusting the size of the calculation domain and using the discrete simulation method, the required temperature evolution area is simulated and the melt forming result and temperature evolution curve can be accurately obtained. When the difference between the workpiece and the nozzle diameter is more than 50 times, this method can be used to realize flexible adjustment of the calculation domain and achieve the purpose of reducing the time cost. The present application has the advantages of flexibility, simple operation, and can effectively save the simulation time of numerical simulation and improve the calculation efficiency.

[0148] Although the embodiments of the present application have been shown and described above, it should be understood that the above-mentioned embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present application.​

Claims

1. A method of discretized simulation of ingot additive solidification forming, characterized in that, Comprising the following steps: Step 1, obtaining simulation experiment parameters, determining the size of the calculation domain according to the actual size and dividing the grid, planning the solution path: (a) According to the numerical value obtained from the casting experiment process, the basic process parameters of the simulation experiment are determined, and the thermal physical parameters of the material and the boundary conditions of the model are defined according to the reference; Among them, the basic process parameters include single nozzle casting speed, nozzle moving speed, nozzle diameter and offset of each casting layer; The boundary condition of the model is the water cooling boundary condition; (b) According to the actual size of the model, the size of the solution domain is defined, and the solution domain is divided into grid: (b1) Define the discrete simulation method of ingot additive solidification forming, simulate the evolution results of the region to be observed, establish a three-dimensional solidification model, and use uniform structured grid to ensure calculation efficiency and accuracy. The structure of the grid and the size of the grid are consistent; (b2) According to the size of the three-dimensional solidification model, the defined discrete simulation method is used to simulate the initial casting position, determine the size of the calculation domain and divide the grid, and plan the solution path; Step 2, establish a VOF two-phase flow solidification model: 1) According to the actual casting situation, only the solidification process of molten metal exists in the casting process, and the k- The transient VOF two-phase flow model of turbulent flow is used to calculate the volume fraction of each phase in each grid cell for the two phases added to the model, where the sum of the volume fractions of all phases is 1, and all phases share variables and physical property parameters; 2) Set the k- Motion path of the transient VOF two-phase flow model of turbulent flow: ① Use UDF programming to realize the planning control of the path, define the size of the substrate and the size of the solution domain respectively, the width is not limited, set the program control switch to control the stage of the building process; Subsequently, the dynamic grid technology is used to increase the calculation domain; ② According to the time required for nozzle casting a layer, nozzle moving speed and nozzle moving speed after casting a layer to determine the X position of the current nozzle: ，(1)； ，(2)； ，(3)； ，(4)； ，(5)； ，(6)； In the formula: is the time required for the nozzle to cast a layer, in s; are the width and length of the substrate, respectively, in mm; is the nozzle moving speed, in mm / s; is the offset of each casting layer, in mm; is the time required for a single casting pass, in s; is the layer number after rounding the casting; is the current time, in s; is the time of the current nozzle moving position of the current layer; is the specific pass of the current casting layer; is the current X coordinate of the nozzle; ③ According to the time required for nozzle casting a layer, nozzle moving speed and nozzle moving speed after casting a layer to determine the Y coordinate of the current nozzle: （7）； （8）； In the formula: The function is the remainder of the former divided by the latter, which is the time of a specific pass; if the number of passes is odd, the program executes formula (7), and if the number of passes is even, the program executes formula (8); is the current Y coordinate; Step 3, define material properties and boundary conditions: [1] Define material properties, import the VOF two-phase flow solidification model established in step 1, and select the VOF calculation method according to formulas (1)-(6) to define its material properties; [2] Load UDF program, define thermal boundary condition and heat transfer boundary condition, thermal boundary condition is room temperature, heat transfer boundary condition is heat transfer coefficient between fluid and outside; [3] According to the thermal boundary condition, heat transfer boundary condition and initial data, as well as Fourier's law, the temperature evolution process can be obtained: （15）； (16)； wherein: , , is the spatial rectangular coordinate system, is the temperature in K; is the density of the cast metal in ; is the specific heat of the material , is the heat source intensity in ; Step 4, Sequentially solving Navier-Stokes based on Reynolds-averaged continuity equation and standard k- Turbulence model equations: (i) Calculate the three conservation equations, namely mass conservation equation, momentum conservation equation and energy conservation equation, considering that the fluid flow is composed of incompressible fluid flow system: According to the mass conservation equation, the mass source term is solved, and the fluid volume fraction in the grid cell is obtained: （9）； （10）； wherein: represents the cast metal; is the density, in kg / m3 ; is the volume fraction; is the velocity vector, in m / s; is the metal liquid sprayed by the spray gun per unit time, in kg; is the casting volume, in m3 3 ; According to the momentum conservation equation, the volume force source term is solved: （11）； where: for a system of n phases, the property parameters within the unit grid are volume fraction weighted averages of the individual phases, ; is the dynamic viscosity coefficient of the fluid, with units of ; is the Hamiltonian operator; is the upper index for shear stress; is the pressure with units of , is the equivalent volume force of surface tension with units of ; According to the energy conservation equation, the energy source term is solved, and the empirical correction of Staphan-Boltzmann is used for calculation: （12）； (13) ； wherein: is the total energy, in , is the effective thermal conductivity, in ; is the energy source term, in ; is the heat transfer coefficient, in , is the ambient temperature, in K, is the mesh cell size, in , is the emissivity of the object, is the blackbody radiation constant, in ; (2) Solving k- turbulence equations in standard form, we obtain the morphological evolution under melt flow: （14）； （15）； wherein: represents the turbulent kinetic energy caused by the mean velocity gradient; and is a constant, is the turbulent kinetic energy, in units of , is the dissipation rate; Step 5, extract and analyze temperature field evolution data points: <1> Select multiple points in the calculation domain for data extraction, select points on the edge of the calculation domain and the corresponding position above; <2> Extract the temperature distribution obtained by simulation and collect, finally get the temperature field evolution curve in the casting process; Step 6, use dynamic grid technology to increase the height of the calculation domain to complete the multi-layer casting forming: When the current layer casting is completed, and the domain height does not meet the next layer casting, the dynamic mesh technology is used to improve the position of the spray gun, and the next layer casting is continued, and the above process is repeated until the casting is completed.

2. A method of discrete simulation of ingot additive solidification forming according to claim 1, characterized in that: The calculation iteration step length of different time periods is defined in step (2): When the nozzle moves to the inside of the calculation domain, the nozzle switch is turned on, and the iteration step length is 1e-4; when the nozzle is at the edge of the calculation domain, the iteration step length is 2e-4; and when the nozzle is outside the calculation domain, the iteration step length is 1e-3.

3. A method of discrete simulation of ingot additive solidification forming according to claim 2, characterized in that: In step (5)<1>, four points are selected in the calculation domain for data extraction. The first point is selected at x=14mm, y=14mm along the edge of the calculation domain, the second point is selected at x=16mm, y=16mm along the edge of the calculation domain, and the third and fourth points are selected at the corresponding positions with an increase of 2mm above, respectively.

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