CN114912322A - Thermal behavior prediction method for selective laser melting forming process of 316L stainless steel - Google Patents

Thermal behavior prediction method for selective laser melting forming process of 316L stainless steel Download PDF

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CN114912322A
CN114912322A CN202210538138.1A CN202210538138A CN114912322A CN 114912322 A CN114912322 A CN 114912322A CN 202210538138 A CN202210538138 A CN 202210538138A CN 114912322 A CN114912322 A CN 114912322A
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郑志军
郑翔
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South China University of Technology SCUT
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    • B22F10/20—Direct sintering or melting
    • B22F10/28—Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
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Abstract

The invention discloses a thermal behavior prediction method for a selective laser melting forming process of 316L stainless steel, and belongs to the field of metal additive manufacturing. The method comprises the following steps: creating a three-dimensional model comprising the substrate and the shaped piece in the finite element software ANSYS APDL; setting solid material parameters and powder material parameters, respectively endowing the substrate and a forming area with the solid material parameters and the powder material parameters, and performing grid division; setting initial conditions and boundary conditions, and realizing interlayer powder spreading and layer-by-layer forming by a living and dead unit technology; determining a heat source control equation and a laser heat source equation, deriving a heat source command stream by using a function editor in APDL, and realizing the movement of a laser heat source by using local coordinates; and solving to obtain temperature field data for analysis. The selected area laser melting finite element simulation method provided by the invention can provide reference and theoretical basis for optimizing the forming process of the material additive manufacturing 316L stainless steel, and can effectively reduce trial and error experiments, experiment cost and the like.

Description

Thermal behavior prediction method for selective laser melting forming process of 316L stainless steel
Technical Field
The invention belongs to the field of metal additive manufacturing simulation, and particularly relates to a thermal behavior prediction method for a selective laser melting and forming process of 316L stainless steel.
Background
Additive Manufacturing (AM), commonly known as 3D printing, is a high-end, special Manufacturing technique that has been rapidly developed in recent years. The method is a manufacturing technology for rapidly preparing workpieces from bottom to top based on digital three-dimensional modeling, by combining computer-aided design, material processing and material forming technologies and utilizing metal, non-metal materials or biological materials and the like according to the discrete-accumulation principle of layer-by-layer stacking and layered manufacturing. Compared with traditional processes such as material reduction manufacturing, equal material manufacturing and the like, the additive manufacturing technology has the advantages of wide material adaptability, strong flexibility, shortening of manufacturing time, cost reduction and the like, and is widely applied to the industries of aerospace, electrical appliances, casting, building and the like.
Metal additive manufacturing technology is an important direction for developing functional parts in the future, and comprises selective laser melting, selective electron beam melting, laser melting deposition, electron beam fuse deposition, arc additive manufacturing and the like. The Selective Laser Melting (SLM) technology has the outstanding advantages of high forming precision, high efficiency, compactness and the like, and is a mature technology widely used in the field. The selective laser melting technology is a technology that high-energy laser beams are utilized to scan metal powder which is paved in advance according to a specified path, so that the metal powder is melted quickly firstly and then cooled and solidified quickly, and the metal powder is overlapped layer by layer one by one to form an entity. The control parameters of the selective laser melting technology mainly have four aspects, namely inherent parameters, material properties, processing environment and process parameters. The process parameters are key factors influencing selective laser melting forming, and directly influence the performance of a formed part to a certain extent. If the selection is not properly selected, defects such as non-melted powder, voids, or bubbles may occur in the molded article, and warpage, deformation, or cracks may also occur.
In fact, the selective laser melting forming process is complex, is a rapid non-equilibrium solidification and comprises a plurality of heat transfer and phase change physical metallurgy processes. If an experimental research method is adopted, detection equipment with higher precision is needed, and repeated experiments may be needed, which not only means a great increase in research cost, but also causes a great amount of consumption of manpower and material resources. The numerical simulation method adopted in the forming process can make up the defect, judge whether the new process parameters meet the requirements or not, and simultaneously can visually observe the temperature change in the SLM forming process, thereby being beneficial to the deep research on the forming reasons of the internal defects and the microstructures of the SLM forming piece. The finite element method is the mainstream method in the metal additive manufacturing simulation at present, but the calculation in the aspect of metal fluid flow in the printing process is usually ignored in the method at present, and the purpose is to reduce the total calculated amount and achieve the purpose of simulating larger volume; in addition, the method ignores the influence of the powder on the whole model, thereby causing a large error of the whole model from the actual condition. Therefore, the finite element method in the patent of the invention avoids the defects, fully considers the flow of the molten pool fluid and the influence of the powder on the integral model, and finally forms the novel finite element model in the patent. The novel model is used for analyzing the thermal behavior change in the forming process of the SLM 316L stainless steel, so that related data can be quickly and accurately obtained, and valuable reference is provided for optimization of process parameters.
Disclosure of Invention
The invention aims to provide a finite element simulation method for predicting the thermal behavior of 316L stainless steel formed by selective laser melting, which can simulate the distribution rule of the temperature field in a forming piece such as a single-layer single-channel, a single-layer multi-channel, a multi-layer single-channel, a multi-layer multi-channel and the like in a selective laser melting forming mode, provide a basis for optimizing the process parameters of the forming mode, and effectively reduce trial and error experiments, experiment cost and the like.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a method of predicting thermal behavior of a selective laser fusion forming process for 316L stainless steel, comprising the steps of:
step 1: creating a three-dimensional geometric model in finite element software ANSYS APDL, including the substrate and shaping layer;
step 2: setting two material parameters, namely a solid material parameter and a powder material parameter, and respectively endowing the substrate and the forming area with the two material parameters; simultaneously carrying out meshing on the substrate and the forming area, wherein free meshing and hexahedral meshing are adopted respectively;
and step 3: setting initial conditions and boundary conditions, and realizing interlayer powder spreading and layer-by-layer forming by a living and dead unit technology;
and 4, step 4: determining a heat source control equation and a laser heat source equation,
the laser heat source equation utilizes a function editor in APDL to derive a heat source command stream, and utilizes local coordinates to realize the movement of a laser heat source;
in the forming process, the total heat released by the laser comprises heat radiation between a laser heat source and the powder, heat convection between the powder and the external environment, and heat conduction between the powder and the substrate/powder; the SLM forming process has the characteristic of nonlinear transient heat conduction, and the three-dimensional transient heat conduction control differential equation is satisfied, wherein the formula is as follows:
Figure BDA0003649145870000021
where ρ is the density of the material, kg/m 3 (ii) a t is time, s; kx, ky and kz are heat conductivity coefficients in x, y and z directions, and W/m.k; c is specific heat capacity, J/kg.k; q is the heat generation per unit volume, i.e. the amount of heat the powder absorbs to melt, W/Kg; the present simulation assumes isotropy while taking into account that bath convection is using an enhanced isotropic thermal conductivity, i.e., kx-ky-kz-k when the melting point is not exceeded; when the melting point is exceeded, kx, ky, kz, kx 1.4;
the heat source implementation selects an exponentially decaying body heat source, and the laser heat source formula is as follows:
Figure BDA0003649145870000022
Figure BDA0003649145870000023
in the formula: p is laser power; x, y and z are laser focus coordinates; r is l The radius of the laser power is 40 um; h is the thickness of the printing layer, and is taken to be 0.03 mm; beta is the laser absorption rate, and is taken as 0.27;
and 5: and solving to obtain temperature field data for analysis.
Preferably, the unit type of the substrate and the shaping layer in step 1 is SOLID 70. Because the additive manufacturing belongs to micron-scale forming, the forming piece model should be subjected to grid refinement, and the grid size of the substrate far away from a forming area is gradually increased in the direction of X, Y, Z, so that the calculation efficiency is improved.
In the step 2, since the powder particles are generally spherical, pores exist in the process of stacking each layer of tiled powder, and the parameters of the powder material need to be adjusted to realize the attribute conversion between the metal powder and the solid material. The two materials need parameters including density, heat conductivity coefficient, specific heat capacity and other thermophysical parameters. Under the action of laser, when the temperature of the powder exceeds its melting point, the powder is rapidly melted and rapidly solidified to become a solid state. If the temperature does not exceed the melting point, the thermal conductivity of the powder material is 1% of that of the solid material; above the melting point, the thermal conductivity of the powder material is consistent with the thermal conductivity of the solid material. Secondly, the density of the metal powder is 0.6 of the density of the solid material, and the specific heat capacity of the metal powder is consistent with that of the solid material.
Preferably, the initial conditions of the model in the step 3 are determined according to the actual printing condition, and the initial temperature is set to be 25-70 ℃; the boundary conditions of the model mainly comprise thermal convection and thermal radiation, wherein the convection coefficient of the thermal convection is 25W/m.K, and the radiation coefficient of the thermal radiation is 0.3.
Setting all forming layers as 'dead units', activating layer by layer according to forming conditions through APDL command stream, and changing the processing layer into 'live units'; and secondly, before interlayer stacking, the powder laying time is increased by 3s, and the actual printing process is met.
And (4) calculating the scanning time, namely the scanning speed, of the simulation implementation in the step (4) according to the load step loaded by the heat source. The laser heat source equation is rewritten by an APDL function editor, then local coordinates are defined, and the laser heat source is moved by the local coordinates to enable the heat source to operate according to a specified path.
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The technical features and advantages of the present invention will be better understood by those skilled in the art with reference to the accompanying drawings, in which:
FIG. 1 is a three-dimensional model and meshing including a substrate and a molding region according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of the thermal relationship in an embodiment of the present invention.
FIG. 3 is a model of an exponentially decaying body heat source as employed in an embodiment of the present invention.
FIG. 4 is a flowchart of a finite element analysis according to an embodiment of the present invention.
FIG. 5 is a temperature profile of a heat source scanning the center of a fourth layer in an embodiment of the present invention; the laser power is 165W, the scanning speed is 1000mm/s, the scanning distance is 0.07mm, the powder laying thickness is 0.03mm, and the scanning strategy is Z-shaped.
FIG. 6 is a temperature-time curve for the processing time of each layer at the center of each layer in an embodiment of the present invention; the process parameters are as above.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiment is only one embodiment of the invention, and not all embodiments. Other embodiments used by those of ordinary skill in the art that are not inventive based on the embodiments of the present invention are within the scope of the present invention.
In the example the substrate and the shaping layer material were both 316L stainless steel.
Step 1: the three-dimensional computational model is built in finite element software ANSYS APDL.
The three-dimensional geometric model, including the substrate and shaping layers, is built up in finite element software ANSYS APDL. The substrate size was 2.6mm × 2.6mm × 1.5mm (length × width × height), and the molding layer size was 1mm × 1mm × 0.12mm (length × width × height), as shown in fig. 1. SOLID 70 is used for both the substrate and the shaping layer.
Step 2: two material parameters are set and the entire model is gridded.
Thermophysical parameters including density, thermal conductivity, specific heat capacity, etc. of the two materials (solid and powder) are set and respectively given to the substrate and the forming layer. The powder material parameters of each layer of flat powder are adjusted because of the pores in the shape, accumulation and the like of the flat powder. When the melting point is not exceeded, the heat conductivity coefficient of the powder material is 1% of that of the solid material; above the melting point, the thermal conductivity of the powder material is consistent with the thermal conductivity of the solid material. In addition, the density of the metal powder was 0.6 of the density of the solid material, and the specific heat capacity of the metal powder was consistent with that of the solid material.
After the setting is completed, the whole model is subjected to grid division. Considering the forming precision, the meshes of the forming layer need to be thinned and divided into hexagonal meshes, the size of the meshes is 0.02mm multiplied by 0.015mm, the meshes on the substrate are divided into free meshes, namely the sizes of the meshes far away from the forming area are gradually increased in X, Y, Z three directions, so that the calculation precision and the calculation efficiency are ensured. As shown in fig. 1.
And step 3: setting initial conditions and boundary conditions, setting living and dead units, and realizing layer-by-layer forming through living and dead unit technology.
The initial conditions of the model were determined from the printing practice, so the initial temperature was 25 ℃. In the additive manufacturing process, model heat dissipation is mainly carried out in a convection and radiation mode, and the formula is as follows:
q c ＝h conv (T-T 0 )
Figure BDA0003649145870000041
in the formula, q c Heat lost by convection, h conv Taking 25W/m.k, q as convection coefficient r To radiate the heat lost,. epsilon.is the emissivity of the object in the environment, taken as 0.3.
After the above conditions are added, "live unit" and "dead unit" in the live-dead unit technique are set. Firstly, all forming layers are set as 'dead units', and APDL command streams are activated layer by layer according to forming conditions, so that the processing layers become 'raw units'.
And 4, step 4: and determining a heat source control equation and a laser heat source equation, and implementing loading.
The total heat released by the laser during the forming process includes thermal radiation between the laser heat source and the powder, thermal convection between the powder and the external environment, and thermal conduction between the powder and the substrate/powder, etc., and the thermal relationship is shown in fig. 2. The SLM forming process has the characteristic of nonlinear transient heat conduction, and the three-dimensional transient heat conduction control differential equation is satisfied, wherein the formula is as follows:
Figure BDA0003649145870000042
where ρ is the density of the material, kg/m 3 (ii) a t is time, s; kx, ky and kz are heat conductivity coefficients in x, y and z directions, and W/m.k; c is specific heat capacity, J/kg.k; q is the heat generation per unit volume, i.e., the amount of heat the powder absorbs to melt, W/Kg. The present simulation assumes isotropy while taking into account that bath convection is using an enhanced isotropic thermal conductivity, i.e., kx-ky-kz-k when the melting point is not exceeded; when the melting point is exceeded, kx, ky, kz, kx 1.4.
Considering that the absorption coefficient is high due to multiple back reflection of the powder bed, the heat source implementation adopts a bulk heat source with exponential decay, and the model is shown in fig. 3, and the formula is as follows:
Figure BDA0003649145870000043
Figure BDA0003649145870000044
in the formula: p is laser power; x, y and z are laser focus coordinates; r is l The radius of the laser power is 40 um; h is the thickness of the printing layer, and is taken to be 0.03 mm; β is a laser absorptance, and is taken to be 0.27. Secondly, the scanning time, namely the scanning speed of the simulation implementation is calculated according to the load step loaded by the heat source. The laser heat source equation is rewritten by an APDL function editor, then local coordinates are defined, and the laser heat source is moved by the local coordinates to enable the heat source to operate according to a specified path.
And 5: and solving to obtain temperature field data for analysis.
The temperature field values and distribution results in the SLM forming process can be obtained by setting and solving according to the above steps, as shown in fig. 5 and 6.

Claims (7)

1. A thermal behavior prediction method for a selective laser melting forming process of 316L stainless steel is characterized by comprising the following steps:
step 1: creating a three-dimensional geometric model in finite element software ANSYS APDL, including the substrate and shaping layer;
step 2: setting two material parameters, namely a solid material parameter and a powder material parameter, and respectively endowing the substrate and the forming area with the two material parameters; simultaneously carrying out meshing on the substrate and the forming area, wherein free meshing and hexahedral meshing are adopted respectively;
and step 3: setting initial conditions and boundary conditions, and realizing interlayer powder spreading and layer-by-layer forming by a living and dead unit technology;
and 4, step 4: determining a heat source control equation and a laser heat source equation,
the laser heat source equation utilizes a function editor in APDL to derive a heat source command stream, and utilizes local coordinates to realize the movement of a laser heat source;
in the forming process, the total heat released by the laser comprises heat radiation between a laser heat source and the powder, heat convection between the powder and the external environment, and heat conduction between the powder and the substrate/powder; the SLM forming process has the characteristic of nonlinear transient heat conduction, and the three-dimensional transient heat conduction control differential equation is satisfied, wherein the formula is as follows:
Figure FDA0003649145860000011
where ρ is the density of the material, kg/m 3 (ii) a t is time, s; kx, ky and kz are heat conductivity coefficients in x, y and z directions, and W/m.k; c is specific heat capacity, J/kg.k; q is the heat generation per unit volume, i.e. the amount of heat the powder absorbs to melt, W/Kg; the present simulation assumes isotropy while taking into account that bath convection is using an enhanced isotropic thermal conductivity, i.e., kx-ky-kz-k when the melting point is not exceeded; when the melting point is exceeded, kx, ky, kz, kx 1.4;
the heat source implementation selects an exponentially decaying body heat source, and the laser heat source formula is as follows:
Figure FDA0003649145860000012
Figure FDA0003649145860000013
in the formula: p is laser power; x, y and z are laser focus coordinates; r is l The radius of the laser power is 40 um; h is the thickness of the printing layer, and is taken to be 0.03 mm; beta is the laser absorptivity, and is taken as 0.27;
and 5: and solving to acquire temperature field data for analysis.
2. A method of predicting thermal behavior of a selective laser melt forming process for 316L stainless steel according to claim 1, wherein: in step 1, SOLID 70 is adopted for the unit types of the substrate and the shaping layer.
3. A method of predicting thermal behavior of a selective laser melt forming process for 316L stainless steel according to claim 1, wherein: in the step 2, the two material parameters comprise density, heat conductivity coefficient, specific heat capacity and enthalpy value.
4. A method of predicting the thermal behavior of a selective laser melt forming process for 316L stainless steel according to claim 3, wherein:
if the temperature does not exceed the melting point, the thermal conductivity of the powder material is 1% of that of the solid material; when the melting point is exceeded, the thermal conductivity of the powder material is consistent with that of the solid material;
the density of the metal powder is 0.6 of the density of the solid material;
the specific heat capacity of the metal powder is consistent with the specific heat capacity of the solid material.
5. The method of claim 1, wherein the method comprises the following steps: in the step 3, the initial temperature in the initial condition of the model is 25-70 ℃; the boundary conditions include thermal convection, which has a convection coefficient of 25W/m.K, and thermal radiation, which has an emissivity coefficient of 0.3.
6. The method of claim 1, wherein the method comprises the following steps: setting all forming layers as 'dead units', activating layer by layer according to forming conditions through APDL command stream, and changing the processing layer into 'live units'; and secondly, before interlayer stacking, the powder laying time is increased by 3s, and the actual printing process is met.
7. A method of predicting thermal behavior of a selective laser melt forming process for 316L stainless steel according to claim 1, wherein: the scanning time, namely the scanning speed, of the simulation implementation in the step (4) is calculated according to the load step loaded by the heat source; the laser heat source equation is rewritten by an APDL function editor, then local coordinates are defined, and the laser heat source is moved by the local coordinates to enable the heat source to operate according to a specified path.
CN202210538138.1A 2022-05-18 2022-05-18 Thermal behavior prediction method for selective laser melting forming process of 316L stainless steel Pending CN114912322A (en)

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