Temperature field numerical simulation method and system in H13 hot work die steel SLM forming process

Abstract

The invention discloses a temperature field numerical simulation method and system in the SLM forming process of H13 hot work die steel, and belongs to the technical field of additive manufacturing. Mesh generation is conducted on a constructed three-dimensional geometric model of a formed part and a substrate, and refined mesh units consistent with hexahedron units in direction are generated; the forming power and the scanning speed range of materials used by the forming piece and the substrate are determined, the time step length of scanning is simulated in advance to establish a heat source model, and the lower limit and the upper limit of the technological parameter range of the forming piece and the substrate are simulated; according to the upper limit, the lower limit and the refined grid units, the maximum allowable calculation time step length is obtained, and the optimal technological parameter combination of the forming piece and the substrate SLM forming process is obtained by analyzing the temperature changes of the key nodes under different forming powers and scanning speeds and the maximum allowable calculation time step length. According to the method, the temperature field change in the SLM forming process can be comprehensively simulated.

Description

Technical Field

[0001] The present invention relates to the technical field of additive manufacturing, and more particularly to a numerical simulation method and system for the temperature field during the SLM forming process of H13 hot work die steel. Background Art

[0002] Due to its excellent comprehensive properties, such as good toughness, outstanding thermal fatigue performance, and relatively high strength, H13 hot work die steel plays a crucial role in modern manufacturing and is widely used in the manufacturing of various hot work dies, such as die-casting dies and hot forging dies. With the continuous development of manufacturing towards high-precision and complex-shaped die manufacturing, traditional manufacturing processes face many challenges in meeting these requirements. As an advanced additive manufacturing technology, selective laser melting (SLM) technology has emerged, bringing new opportunities for the manufacturing of H13 hot work die steel.

[0003] However, the SLM forming process is a highly complex physical metallurgical process, involving multiple coupled physical phenomena such as the absorption and conversion of laser energy, heat transfer, melting and solidification of materials, etc. During this process, the distribution of the temperature field is extremely complex and changes rapidly, and its variation law directly affects the quality and performance of the formed parts. For example, if the temperature is too high, it may lead to defects such as excessive melting of the material, generation of cracks or residual stresses; if the temperature is too low, it may cause incomplete melting of the powder, affecting the interlayer bonding strength and the density of the formed part.

[0004] Traditional experimental research methods have many limitations in studying the temperature field during the SLM forming process. On the one hand, obtaining temperature field data requires high-precision detection equipment, and it is often only possible to measure at a limited number of points, making it difficult to comprehensively and real-time monitor the temperature field changes during the entire forming process. On the other hand, experimental research is costly, and conducting a large number of repeated experiments requires a large amount of manpower, material resources, and time. Therefore, numerical simulation methods have become an important means for studying the temperature field during the SLM forming process.

[0005] Although there are currently some numerical simulation methods for studying the SLM forming process, there are still many deficiencies. When establishing models, some simulation methods fail to fully consider the material properties of the formed part and the substrate as well as the actual processing environment, resulting in a large deviation between the model and the actual situation. There is a lack of systematicness and accuracy in determining process parameters, and it is difficult to find the optimal process parameter combination. Summary of the Invention

[0006] Aiming at the problems existing in the above fields, the present invention proposes a numerical simulation method and system for the temperature field during the SLM forming process of H13 hot work die steel, by establishing a heat source model, determining the reasonable range of process parameters, optimizing the process parameters, and deeply exploring the complex temperature field change law of H13 hot work die steel during the SLM forming process, providing a solid theoretical basis and technical support for optimizing the forming process and improving the quality of formed parts.

[0007] To solve the above technical problems, the present invention discloses a numerical simulation method for the temperature field during the SLM forming process of H13 hot work die steel, including the following steps:

[0008] Construct a three-dimensional geometric model of the formed part and the substrate according to the dimensional parameters and boundary conditions of the formed part and the substrate;

[0009] Through meshing the three-dimensional geometric model of the formed part and the substrate, generate regular hexahedron elements of the three-dimensional geometric model; and re-mesh the hexahedron elements to generate refined mesh elements that are consistent with the direction of the hexahedron elements;

[0010] Determine the forming power and scanning speed range of the materials used for the formed part and the substrate, establish a heat source model through the pre-simulated time step of scanning, and simulate the process parameter range of the formed part and the substrate; take the forming state of the first layer when the laser scans to the second layer of the forming layer as the evaluation criterion. When the surface temperature of the forming layer at the same position of the first layer fails to reach the melting point of H13 hot work die steel, determine the forming state of the first layer as the lower limit of the process parameter range; based on the range of the interlayer overlap rate of the forming layer, determine the upper limit of the process parameter range by measuring the depth of the molten pool;

[0011] According to the upper and lower limits of the process parameter range and the refined mesh elements, obtain the maximum allowable calculation time step by determining the time step of each layer of mesh elements of the forming layer scanned by the laser and optimizing the scanning strategy;

[0012] Select the midpoint of each track of each layer in the forming layer as the key node, and obtain the optimal process parameter combination for the SLM forming process of the formed part and the substrate by analyzing the temperature change of the key node and the maximum allowable calculation time step under different forming powers and scanning speeds.

[0013] Preferably, the construction of the three-dimensional geometric model of the formed part and the substrate specifically includes:

[0014] Determine the dimensional parameters of the formed part and the substrate according to the actual process requirements;

[0015] Based on the physical properties of H13 hot work die steel, endow the corresponding properties to the material characteristics of the formed part and the substrate, and determine the thermophysical parameters of the powder material of H13 hot work die steel;

[0016] According to the actual processing environment and material properties of the formed part and the substrate, boundary conditions are set. During the SLM processing, a heat convection model is constructed between the side surface of the substrate, the upper surface except the powder bed, and the upper surface of the powder bed and the surrounding environment. The heat convection exchange situation is represented by the formula q:

[0017]

[0018] Among them, k e is the thermal conductivity coefficient of the powder bed, α is the heat convection coefficient of the workpiece surface, T a is the temperature of the surrounding medium, T s is the temperature of the workpiece surface, σ is the Potsdam constant, ε is the heat radiation coefficient, and q is the laser heat flux density;

[0019] Each parameter in the formula q needs to be determined according to the actual processing environment and material properties;

[0020] According to the dimensional parameters of the formed part and the substrate and the set boundary conditions, a three-dimensional geometric model of the formed part and the substrate is constructed in the three-dimensional modeling software.

[0021] Preferably, the generation of refined grid cells that are consistent with the direction of the hexahedral cells includes the following steps:

[0022] According to the three-dimensional geometric model of the formed part and the substrate, the three-dimensional geometric model is discretized in the three directions of its length, width, and height, and divided into regular hexahedral cells M;

[0023] Among them, the hexahedral cells M in the substrate area need to be segmented by selecting grid cells with a fixed size according to actual needs. The hexahedral cells M in the formed part area are further divided by the grid cells m to generate refined grid cells that are consistent with the direction of the hexahedral cells;

[0024] The selection of the grid cell size needs to comprehensively consider the balance between calculation accuracy and calculation efficiency.

[0025] Preferably, the establishment of the heat source model by pre-simulating the time step of the scan includes:

[0026] Input the heat source model in the software ANSYS function editor to generate the APDL command stream:

[0027]

[0028] Among them, q(x, y, z, t) is the instantaneous heat flux density at the local coordinate point (x, y, z) of the laser, P is the scanning power of the laser, r b is the laser spot radius, x 2 +y 2is the square of the distance from any point on the powder bed to the center of the laser spot, v is the laser scanning speed, and δ is the thermal diffusion model of the material;

[0029] The thermal diffusion model δ of the material is:

[0030]

[0031] where k is the thermal conductivity, ρ is the density, and c p is the specific heat capacity.

[0032] Preferably, determining the forming state of the first layer as the lower limit of the process parameter range specifically includes:

[0033] Calculating the scanning time step through the speed, inputting the heat source model to simulate the parameters, and obtaining the simulation results;

[0034] According to the simulation results, taking the forming state of the first layer when the laser scans to the second layer as the evaluation criterion, when the surface temperature of the formed layer at the same position of the first layer fails to reach the melting point of H13 hot work die steel, it is determined that this is the lower limit of the process parameter range, indicating that the laser power is low or the scanning speed is fast, and the formed layer fails to form a sufficient molten pool;

[0035] where the melting point of H13 hot work die steel is determined through experiments.

[0036] Preferably, determining the upper limit of the process parameter range specifically includes:

[0037] Based on the range of the interlayer overlap rate of the formed layer, it is discriminated by measuring the depth of the molten pool. When the overlap rate exceeds the upper limit of the range of the interlayer overlap rate, it indicates that the laser power is high or the scanning speed is low, and the formed layer has an over-melting phenomenon;

[0038] Among them, the overlap range in the SLM formation process of SLM H13 steel should be between 30% and 60%.

[0039] Preferably, obtaining the maximum allowable calculation time step specifically includes:

[0040] According to the lower and upper limits of the determined process parameter range, determining the time step of each layer of grid cells of the formed layer scanned by the laser and optimizing the scanning strategy;

[0041] The scanning strategy adopts a 90° rotation scanning path between layers;

[0042] The time step of each layer of grid cells is the time when all the current formed layers are scanned plus the powder spreading time t reserved at the end of the scanning of each layer of grid cells;

[0043] When the speed is changed, by adjusting the corresponding time of each formed layer, the position change formula is optimized to:

[0044] F(x, y, z, t) = F(o ± vt, y, nd, t)

[0045] Wherein, o is the starting position of the forming layer of each layer, v is the laser scanning speed, n is the number of scanning layers, and d is the powder layer thickness;

[0046] After optimization, when changing the speed value, by designing the loading time related to its heat source model, we get:

[0047]

[0048] Wherein, x 0 is the x - coordinate at the scanning starting point, and y 0 is the y - coordinate during the scanning process;

[0049] Combined with the dimensions of the hexahedron element M and the mesh element m, as well as the detailed thermal physical property parameters of the formed part, substrate, and powder material, the maximum allowable computational time step is determined through calculation and analysis.

[0050] Preferably, the obtaining of the optimal process parameter combination for the formation process of the formed part and the substrate by SLM includes the following steps:

[0051] According to the constructed heat source model and scanning strategy, the SLM forming process is simulated through the finite element analysis software ANSYS;

[0052] During the calculation process, the "element birth and death" technology is introduced. By setting the activation and inactivation conditions of the birth and death elements, whenever a new layer of forming starts, the corresponding mesh elements are activated, and after each layer of forming is completed, some elements are inactivated, so as to capture the temperature changes of each node during the SLM forming process;

[0053] According to the temperature changes of each node during the SLM forming process, the mid - point of each track of each layer in the forming layer is selected as the key node. By analyzing the temperature change trend and distribution characteristics of the key nodes, the optimal process parameter combination is determined.

[0054] Preferably, it further includes a temperature field numerical simulation system for the SLM formation process of H13 hot - working die steel, including:

[0055] A mesh element generation module for the formed part and the substrate, which is used to construct a three - dimensional geometric model of the formed part and the substrate according to the size parameters and boundary conditions of the formed part and the substrate; through meshing the three - dimensional geometric model of the formed part and the substrate, regular hexahedron elements of the three - dimensional geometric model are generated; and the hexahedron elements are further divided to generate refined mesh elements that are consistent with the direction of the hexahedron elements;

[0056] The process parameter range determination module is used to determine the forming power and scanning speed ranges of the materials used for the formed part and the substrate. A heat source model is established through the time step of the pre-simulated scan to simulate the process parameter ranges of the formed part and the substrate. Using the forming state of the first layer when the laser scan reaches the second layer of the formed layer as the evaluation criterion, when the surface temperature of the formed layer at the same position in the first layer fails to reach the melting point of H13 hot work die steel, the forming state of the first layer is determined as the lower limit of the process parameter range. Based on the range of the interlayer overlap rate of the formed layer, it is discriminated by measuring the depth of the molten pool to determine the upper limit of the process parameter range.

[0057] The optimal process parameter combination acquisition module is used to obtain the maximum allowable calculation time step according to the upper and lower limits of the process parameter range and the refined grid cells by determining the time step of each grid cell of the formed layer scanned by the laser and optimizing the scanning strategy. The midpoint of each track of each layer in the formed layer is selected as the key node, and by analyzing the temperature changes of the key nodes and the maximum allowable calculation time step under different forming powers and scanning speeds, the optimal process parameter combination for the SLM formation process of the formed part and the substrate is obtained.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The numerical simulation method of the temperature field in the SLM forming process of H13 hot work die steel proposed by the present invention divides the three-dimensional geometric models of the formed part and the substrate into grids to generate refined grid units for the formed part and the substrate. The selection of the grid size needs to comprehensively consider the balance between calculation accuracy and calculation efficiency. On the premise of ensuring the accuracy of the simulation results, the calculation speed should be increased as much as possible, so as to optimize the calculation resources and time of the entire simulation process. By constructing a heat source model, precise process parameter ranges are determined through a rigorous pre-simulation process, and the approximate forming power and scanning speed ranges of the materials used for the formed part and the substrate are determined. The simulation is carried out by accurately calculating the scanning time step through the speed. The simulation results are observed and evaluated comprehensively and from multiple angles. The forming state of the first layer when the laser scans to the second layer is used as the key evaluation criterion. When the surface temperature of the formed layer at the same position in the first layer fails to reach the exact melting point of H13 hot work die steel, it is determined that this is the lower limit of the process parameter range, indicating that the laser power is low or the scanning speed is fast, and the formed layer fails to form a sufficient molten pool, which will seriously affect the interlayer lap quality; the upper limit of the process parameter range is selected based on the precise range of the interlayer lap rate, and is judged by accurately measuring the depth of the molten pool. When the lap rate exceeds the upper limit, it means that the laser power is high or the scanning speed is low, and the formed layer will have an over-melting phenomenon, seriously affecting the forming quality and efficiency. After determining a reasonable process parameter range, representative parameter combinations are carefully selected, and then the precise time step for each pass and the optimized scanning strategy are determined. The numerical simulation of the temperature field in the SLM forming process of H13 hot work die steel is carried out to capture the interaction between the heat source and the material in real time, which can ensure the calculation accuracy in the heat conduction simulation process and ensure the high convergence of the numerical solution, thus providing a reliable basis for the subsequent temperature field analysis. By analyzing the temperature changes of key nodes, the process parameters are optimized. The numerical simulation method proposed by the present invention deeply reveals the variation law of the temperature field and provides a theoretical basis for the optimization of the process parameters in the SLM forming process. Description of the Drawings

[0060] Figure 1 It is a flowchart of the numerical simulation method of the temperature field in the SLM forming process of H13 hot work die steel proposed by the present invention;

[0061] Figure 2 It is the architecture of the numerical simulation method of the temperature field in the SLM forming process of H13 hot work die steel proposed by the present invention;

[0062] Figure 3 It is a diagram of the three-dimensional geometric model construction and grid division of the present invention;

[0063] Figure 4 It is the front view of the size division of the temperature field simulation model of the present invention;

[0064] Figure 5Top view of the size division of the temperature field simulation model of the present invention;

[0065] Figure 6 The 90° interlayer rotation scanning strategy of the present invention. Specific embodiments

[0066] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying Figure 1 - Figure 6 drawings in the embodiments of the present invention. It should be understood that the terms described in the present invention are only for describing specific embodiments and are not used to limit the present invention.

[0067] As Figure 1 shown, the present invention proposes a numerical simulation method for the temperature field during the SLM forming process of H13 hot work die steel, including the following steps:

[0068] S1: According to the size parameters and boundary conditions of the formed part and the substrate, construct a three-dimensional geometric model of the formed part and the substrate; through meshing the three-dimensional geometric model of the formed part and the substrate, generate regular hexahedral elements of the three-dimensional geometric model; and re-divide the hexahedral elements to generate refined mesh elements that are consistent with the direction of the hexahedral elements.

[0069] S2: Determine the forming power and scanning speed range of the materials used for the formed part and the substrate, establish a heat source model through the pre-simulated scanning time step, and simulate the process parameter range of the formed part and the substrate; use the forming state of the first layer when the laser scans to the second layer of the formed layer as the evaluation criterion. When the surface temperature of the formed layer at the same position in the first layer fails to reach the melting point of H13 hot work die steel, determine the forming state of the first layer as the lower limit of the process parameter range; based on the range of the interlayer overlap rate of the formed layer, determine the upper limit of the process parameter range by measuring the depth of the molten pool.

[0070] S3: According to the upper and lower limits of the process parameter range and the refined mesh elements, obtain the maximum allowable calculation time step by determining the time step of each layer of mesh elements of the formed layer scanned by the laser and optimizing the scanning strategy.

[0071] S4: Select the midpoint of each track of each layer in the formed layer as the key node, and obtain the optimal process parameter combination for the SLM forming process of the formed part and the substrate by analyzing the temperature changes of the key nodes and the maximum allowable calculation time step under different forming powers and scanning speeds.

[0072] Specifically, in step S1, constructing the three-dimensional geometric model of the formed part and the substrate specifically includes:

[0073] In a professional three-dimensional modeling software, accurately construct the three-dimensional geometric model of the formed part and the substrate, that is, the temperature field simulation model, as Figure 3shown.

[0074] According to the actual process requirements, the size parameters of the molded part and the substrate are determined. For example, the length, width and height of the molded part are x, y, and z respectively. The size of the substrate is also determined as X, Y, and Z according to the experimental or production requirements.

[0075] For formed parts and substrates, the thermophysical parameters of the materials are accurately assigned based on the physical properties of H13 hot working die steel. The material properties of the substrate include thermal conductivity, density, specific heat capacity and enthalpy values ​​that are dynamically adjusted with temperature changes. All these parameters can be obtained by experimental measurement using high-precision differential scanning calorimetry (DSC), and the material properties are calculated using complex physical formulas determined experimentally.

[0076] For parameters such as thermal conductivity, density, specific heat capacity and enthalpy, the acquisition method is limited to high-precision experimental measurement operations or accurate queries from authoritative professional material databases, in order to ensure that the constructed model can meet high accuracy standards. At the same time, the molded parts are in powder form, and their material properties are obtained by calculation and deduction based on specific formulas. Each parameter involved in this specific formula must be determined by accurate measurement methods or meticulous calculation processes. Only in this way can the unique characteristics inherent in powder materials be accurately reflected, thereby building a solid foundation for subsequent simulation analysis work and ensuring the scientificity and reliability of the entire simulation process.

[0077] The powder density is calculated by the following formula:

[0078] ρ(T)=ρ 0 ·(1-α·(TT 0 ))

[0079] Where ρ(T) is the powder density at temperature T, ρ 0 is the reference temperature T 0 is the density at room temperature (usually the density at room temperature), α is the temperature-dependent linear expansion coefficient, which indicates the change of density with temperature, T 0 is the reference temperature (can be room temperature or another suitable temperature); the thermal conductivity of the powder is determined by the following formula:

[0080] k(T)=k 0 ·(1+β·(TT 0 ))

[0081] Where k(T) is the thermal conductivity at temperature T, K 0 is the reference temperature T 0The thermal conductivity under (the value at room temperature), β is the linear coefficient of the change of thermal conductivity with temperature, and T 0 is the reference temperature. Each parameter has a clear physical meaning and needs to be accurately measured or calculated.

[0082] At the same time, according to the actual processing environment and material properties of the formed part and the substrate, boundary conditions are set. During the SLM processing, a heat convection model is constructed between the side surface of the substrate, the upper surface except the powder bed, and the upper surface of the powder bed and the surrounding environment. The heat convection exchange situation is characterized by a specific formula, and each parameter in this formula must be accurately set according to the actual processing environment conditions and the material's own properties. In this way, the heat exchange process can be accurately simulated to ensure that the simulation results can truly reflect the heat transfer situation in actual processing, providing necessary conditions for accurately analyzing the variation law of the temperature field in the subsequent stage, and further providing a reliable basis for optimizing the forming process to ensure a high degree of consistency between the simulation and the actual processing process.

[0083] The heat convection exchange situation is accurately represented by the formula q:

[0084]

[0085] Among them, k e is the powder bed thermal conductivity coefficient, α is the workpiece surface heat convection coefficient, T a is the surrounding medium temperature, T s is the workpiece surface temperature, σ is the Boltzmann constant, ε is the thermal radiation coefficient, and q is the laser heat flux density. Each parameter in the formula q needs to be determined according to the actual processing environment and material properties.

[0086] Generate refined mesh elements that are consistent with the hexahedral element direction, including the following steps:

[0087] According to the three-dimensional geometric model of the formed part and the substrate, discretize the three-dimensional geometric model in the three directions of its length, width, and height, and divide it into regular hexahedral elements M as Figure 3 shown. During this process, it is particularly necessary to ensure that the division of the model in the Y direction is consistent with the single-pass width and the diameter of the laser spot, so as to ensure the high accuracy of the temperature field simulation results.

[0088] For the substrate part, further refine the division using the hexahedral element M to generate the refined mesh elements m. At this time, the sizes of the refined mesh elements m are x, y, and z respectively, and the x, y, and z directions must be strictly consistent with the X, Y, and Z directions of the overall model to ensure the unity and accuracy of the entire model.

[0089] During the mesh generation process, the hexahedral element M in the substrate area can be divided by selecting mesh elements m of a specific size according to actual requirements (such as (X, Y, Z)); the hexahedral element M in the formed part area is divided by finer mesh elements m (such as (x, y, z)). The selection of the mesh size needs to comprehensively consider the balance between calculation accuracy and calculation efficiency. On the premise of ensuring accurate simulation results, the calculation speed should be increased as much as possible, so as to optimize the calculation resources and time of the entire simulation process.

[0090] In step S2, determining the forming state of the first layer as the lower limit of the process parameter range specifically includes:

[0091] Formulating an accurate process parameter range through a rigorous pre-simulation process. This process needs to comprehensively consider various factors. First, determine the approximate forming power and scanning speed ranges of the materials used for the formed part and the substrate based on rich experience and previous research. Then, accurately calculate the scanning time step through the speed, and initially input reasonable parameters for simulation. The scanning strategy is as Figure 6 shown. After that, conduct comprehensive and multi-angle key observations and accurate evaluations on the simulation results, and use the forming state of the first layer when the laser scanning reaches the second layer as the key evaluation criterion.

[0092] When the surface temperature of the formed layer at the same position of the first layer fails to reach the melting point of H13 hot work die steel, it is determined that this is the lower limit of the process parameter at this time, indicating that the laser power is low or the scanning speed is fast, and the formed layer fails to fully form a molten pool, which will seriously affect the interlayer lap quality. Among them, the melting point of H13 hot work die steel is determined by experiment to be 1460 °C.

[0093] Determine the upper limit of the process parameter range, specifically including:

[0094] Based on the range of the interlayer lap rate, judge by measuring the depth of the molten pool, the interlayer lap rate, etc. When the depth of the molten pool is too deep and the lap rate exceeds the upper limit of the interlayer lap rate range, it indicates that the laser power is high or the scanning speed is low, and the formed layer has an over-melting phenomenon, seriously affecting the forming quality and efficiency. Throughout the process, high-precision measurement means and accurate judgment methods are required to determine various states and parameters to ensure that the formulated process parameter range is accurate and reliable, providing a solid foundation for subsequent accurate simulation and optimization of the forming process.

[0095] After determining a reasonable process parameter range, carefully select representative parameter combinations, and then determine the accurate time step of each formed layer and optimize the scanning strategy.

[0096] Among them, the lap range of the SLM formation process of SLM H13 steel should be between 30% and 60%.

[0097] Considering the characteristics of the laser energy distribution of the laser, a Gaussian moving heat source model is established. The heat source model is input into the function editor of the software ANSYS to generate an APDL command stream:

[0098]

[0099] Among them, q(x, y, z, t) is the instantaneous heat flux density at the local coordinate point (x, y, z) of the laser, P is the scanning power of the laser, r b is the radius of the laser spot, x 2 +y 2 is the square of the distance from any point on the powder bed to the center of the spot, v is the laser scanning speed, and δ is the thermal diffusion model of the material. Each parameter needs to be determined through experiments or accurately set according to the equipment parameters to accurately simulate the laser heat source.

[0100] The thermal diffusion model δ of the material is:

[0101]

[0102] Among them, k is the thermal conductivity, ρ is the density, and c p is the specific heat capacity.

[0103] In step S3, the maximum allowable calculation time step is obtained, specifically including:

[0104] According to the lower and upper limits of the determined process parameter range, the time step of each layer of the formed layer of laser scanning and the optimized scanning strategy are determined.

[0105] As Figure 6 shown, the scanning strategy adopts a 90° rotation scanning path between layers. The aim is to make the scanning directions between each layer perpendicular to each other through this specific scanning method, so that during the layer-by-layer forming process, the heat is more evenly dispersed, reducing local overheating or deformation problems caused by heat accumulation, and thus improving the overall quality and accuracy of the formed part. The analysis time step of each layer is determined as the time when all the currently formed layers are scanned plus the powder spreading time t reserved at the end of each layer. Among them, the determination of the powder spreading time must be accurately calculated based on the unique material properties of H13 hot work die steel and specific process requirements. This is because different materials have different behaviors during the powder spreading process. Only by accurately determining the powder spreading time can the uniformity and stability of the powder laying of each layer be ensured, providing good basic conditions for subsequent laser melting forming.

[0106] When changing the scanning speed, it is necessary to precisely adjust the corresponding time of each forming layer, because the change in scanning speed will directly affect the residence time of the laser on the powder bed surface and the energy input density, thereby changing the temperature field distribution during the forming process. By precisely adjusting the time of each forming layer, it is possible to maintain the relative stability of the temperature field under the condition of speed change, ensure the accuracy and reliability of the simulation results, and provide effective data support for process optimization.

[0107] Optimize the position change formula to:

[0108] F(x,y,z,t)=F(o±vt,y,nd,t)

[0109] Where, o is the starting position of each forming layer, v is the laser scanning speed, n is the number of scanning layers, and d is the powder layer thickness.

[0110] When changing the speed value after optimization, it is necessary to cleverly design and associate the loading time of its heat source model:

[0111]

[0112] Where, x 0 is the x coordinate at the scanning starting point, y 0 is the y coordinate during the scanning process.

[0113] To ensure the efficiency of the scanning process and the accuracy of the simulation results.

[0114] Combined with the sizes of the hexahedron element M and the mesh element m, as well as the detailed thermal physical properties of the formed part, the substrate, and the powder material, through a series of complex calculations and analyses, determine the maximum allowable calculation time step. This process is crucial, as it can ensure the calculation accuracy during the heat conduction simulation process and the high convergence of the numerical solution, thereby providing a reliable basis for subsequent temperature field analysis. Through this precise calculation method, numerical instability can be effectively avoided, and while ensuring the calculation efficiency, the accuracy of the simulation results can be maximally improved.

[0115] In step S4, obtain the optimal process parameter combination for the formation process of the formed part and the substrate SLM, including the following steps:

[0116] According to the temperature changes of each node during the SLM forming process, select the midpoint of each forming layer and other representative positions as key nodes, and analyze the temperature change trend and distribution characteristics through the key nodes to determine the optimal process parameter combination.

[0117] Specifically, when calculating the temperature field, strictly based on the previously constructed Gaussian moving heat source model and scanning strategy, simulate the SLM forming process through the finite element analysis software ANSYS.

[0118] As Figure 2 shown, in this process, the characteristics of the SLM process are fully considered, especially the unique process of material additive manufacturing layer by layer. Therefore, the "element birth and death" technology is introduced in the calculation process. By accurately setting the activation and inactivation conditions of the birth and death elements, the true reproduction of the material additive manufacturing process layer by layer is realized. Specifically, whenever a new layer of forming starts, the corresponding mesh elements are activated, and after each layer of forming is completed, some elements are inactivated. Through this method, the layer-by-layer growth process of the powder material can be highly simulated, making the numerical simulation results closer to the thermal behavior of the actual process. This calculation process not only accurately captures the temperature changes of each node during the SLM forming process, but also provides comprehensive and reliable data support for subsequent process optimization and performance analysis, ensuring that the simulation results can accurately reflect the temperature field changes in the actual process.

[0119] In the temperature field analysis stage, an in-depth study is carried out based on the accurate temperature change history recorded by each node element during the entire forming process. In a scientific and reasonable way, representative key nodes are selected, such as the midpoints of each layer and each pass, etc. These positions are crucial for reflecting the characteristics of the temperature field, and their data can effectively characterize the temperature change trend and distribution characteristics during the entire forming process. A comprehensive and detailed analysis and comparison are carried out on numerous temperature-related parameters under different power and different speed conditions to deeply explore the sensitivity of each parameter to the temperature field.

[0120] Among them, the parameters analyzed and compared cover multiple key aspects, including the trend of the temperature change curve under different power settings and speed conditions. For the temperature change curve, its trend is accurately tracked, and the rates of temperature rise and fall over time, as well as the specific time nodes when the peak temperature appears, are detailedly recorded. In terms of the temperature characteristics of the molten pool, the accurate numerical value of its peak temperature and the accurate duration of the molten pool existence are precisely measured to evaluate the stability of the molten pool and its impact on the forming quality; the analysis of the temperature gradient of the melt depth focuses on its accurate distribution in the melt depth direction to clarify the heat transfer law and judge whether there are local overheating or overcooling regions. For the overlapping edge, its accurate state is carefully observed, including whether there is incomplete fusion, the distribution and size of pores and other defect conditions at the edge. In terms of the cooling rate, its accurate numerical value is obtained, which reflects the cooling speed of the formed part after solidification and understands the heat exchange rate of the formed part during the cooling process. At the same time, the ratio of the width-depth ratio is accurately calculated to evaluate the impact of the molten pool shape on the forming quality.

[0121] After meticulous and precise analysis and comparison of these parameters, a quantitative relationship between each parameter and the forming quality can be established, thus providing a comprehensive and accurate basis for the precise optimization of process parameters. Based on these bases, process parameters such as power and speed can be adjusted in a targeted manner to achieve precise control of the temperature field of the forming process, thereby ensuring that the final formed parts have excellent quality and performance to meet the needs of actual engineering applications. The reasonable process parameter range of laser forming power and scanning speed for the materials used for the formed parts and substrates can be accurately determined. This result provides a scientific and reliable process guidance basis for actual production, ensuring that the formed parts have excellent quality and performance, such as high density, good mechanical properties and precise dimensional accuracy, etc., thereby effectively promoting the high-quality application and development of H13 hot working die steel in the field of selective laser melting forming technology.

[0122] The present invention also proposes a temperature field numerical simulation system for the SLM forming process of H13 hot working die steel, comprising:

[0123] The mesh unit generation module of the formed part and the substrate is used to construct a three-dimensional geometric model of the formed part and the substrate according to the size parameters and boundary conditions of the formed part and the substrate; generate regular hexahedral units of the three-dimensional geometric model by meshing the three-dimensional geometric model of the formed part and the substrate; and divide the hexahedral units again to generate refined mesh units that are consistent with the direction of the hexahedral units;

[0124] The process parameter range determination module is used to determine the forming power and scanning speed range of the materials used for the formed parts and substrates. The heat source model is established by pre-simulating the scanning time step to simulate the process parameter range of the formed parts and substrates. The forming state of the first layer when the laser scanning reaches the second layer of the forming layer is used as the evaluation standard. When the surface temperature of the forming layer at the same position of the first layer does not reach the melting point of H13 hot working die steel, the forming state of the first layer is determined as the lower limit of the process parameter range. According to the range of the interlayer overlap rate of the forming layer, the upper limit of the process parameter range is determined by measuring the depth of the molten pool.

[0125] The optimal process parameter combination acquisition module is used to obtain the maximum allowable calculation time step by determining the time step of each layer of grid units of the laser scanned forming layer and optimizing the scanning strategy according to the upper and lower limits of the process parameter range and the refined grid units. The main view and top view of the obtained temperature field simulation model correspond to the following: Figure 4 and Figure 5 shown.

[0126] The optimal process parameter combination acquisition module is used to select the midpoint of each pass in each layer of the formed layer as the key node, and by analyzing the temperature change and the maximum allowable calculation time step of the key node under different forming powers and scanning speeds, the optimal process parameter combination for the SLM formation process of the formed part and the substrate is obtained.

[0127] The method proposed by the present invention deeply reveals the variation law of the temperature field and provides a theoretical basis for the optimization of the SLM process.

[0128] In order to verify the effectiveness of the method proposed by the present invention, the present invention will be analyzed through the following 3 specific examples.

[0129] As shown in Table 1 and Table 2, they correspond to the main chemical components of H13 steel and the thermal physical properties of H13 steel powder.

[0130] Table 1 Main chemical components of H13 steel

[0131] Element Content / wt.% Iron (Fe) Equilibrium amount Chromium (Cr) 4.75-5.5％ Molybdenum (Mo) 1.1-1.75％ Vanadium (V) 0.8-1.2％ Manganese (Mn) 0.2-0.6％ Silicon (Si) 0.8-1.2％ Carbon (C) 0.32-0.45％

[0132] Table 1 Thermal physical properties of H13 steel powder

[0133]

[0134]

[0135] Example 1

[0136] 1) Establish a temperature field simulation model

[0137] The size of the formed part is set to 5mm × 5mm × 0.2mm, and it is evenly divided into 5 layers with a height of 0.04mm for each layer. The size of the substrate is determined to be 10mm × 10mm × 5mm. The material of the formed part is selected as H13 hot work die steel powder with a specific particle size range (such as 15 - 53μm), and its material properties are obtained through precise experimental measurements and complex formula calculations. The material properties of the substrate are obtained through high-precision experiments. The preheating temperature is set to 200°C.

[0138] 2) Divide the unit and refine the mesh

[0139] The formed part is divided into a hexahedral unit M mesh with a size of 0.05mm × 0.05mm × 0.05mm. This mesh size can accurately capture the internal temperature change of the formed part while ensuring a certain calculation efficiency. The substrate is divided into a refined hexahedral unit m mesh with a size of 0.02mm × 0.02mm × 0.02mm. The finer mesh helps to more accurately simulate the heat conduction process between the substrate and the formed part, and can also reflect the subtle changes in the substrate temperature.

[0140] 3) Establish a heat source model

[0141] By querying a large amount of information and conducting preliminary tests in the early stage, the approximate forming power range of the materials used for the formed part and the substrate is determined to be 100 - 500 W, and the scanning speed range is 400 - 1200 mm / s. Taking a laser power of 100 W and a scanning speed of 500 mm / s as an example for pre-simulation, the scanning time step is calculated to be 0.01 s. According to the pre-simulation results, when the laser scans to the second layer, if the surface temperature of the formed layer at the same position in the first layer does not reach the melting point of the material (the melting point of H13 hot work die steel is 1460 °C), the power is appropriately increased or the speed is decreased; if there is an over-melting phenomenon (such as too large a melt pool depth, too wide a width, etc.), the power is appropriately decreased or the speed is increased. After multiple tests, the lower limit of the process parameters is determined to be a laser power of 150 W and a scanning speed of 300 mm / s, and the upper limit is a laser power of 500 W and a scanning speed of 1000 mm / s. A formal simulation is carried out with a laser power of 500 W and a scanning speed of 900 mm / s. The Gaussian moving heat source equation is established, and the maximum allowable calculation time step is calculated to be 0.01 s. The scanning strategy adopts a 90° rotation scanning path between layers, and the analysis step for each layer is the time when all the current formed tracks are scanned plus the reserved powder spreading time of 5 s at the end of each layer. During the process of determining the process parameter range and scanning strategy, various factors such as laser energy distribution, powder melting characteristics, and interlayer bonding requirements are fully considered to ensure that the model can accurately reflect the actual forming process.

[0142] 4) Calculate the temperature field

[0143] According to the above carefully determined parameters and strategies, simulation calculations are carried out in the finite element analysis software ANSYS to obtain the numerical simulation results of the temperature field, and the temperature change process of each node element is recorded in detail. During the simulation process, physical laws and mathematical models are strictly followed to ensure the accuracy and reliability of the calculation. Through the simulation results, the distribution of temperature in the formed part and the substrate can be intuitively observed, as well as the temperature change trend over time, providing a rich data basis for subsequent analysis.

[0144] 5) Temperature field analysis

[0145] The midpoint of each track in each layer is selected as the key node, and parameters such as the temperature change of the key node, the melt pool temperature and its existence time, the melt depth temperature gradient, the lap edge, the cooling rate, and the width-depth ratio are analyzed under different powers (such as 150 W, 300 W, 450 W) and different speeds (500 mm / s, 700 mm / s, 900 mm / s). For example, when the power is 150 W and the speed is 900 mm / s, the melt pool temperature reaches a maximum of 2100 °C, the existence time is 0.05 s, the melt depth temperature gradient is 1000 °C / mm, the lap edge condition is good (judged by observing the temperature distribution and fusion at the edge in the simulation results), the cooling rate is 106 °C / s, and the width-depth ratio is 1.5.

[0146] By comparing and analyzing these parameters under different parameter combinations, it is concluded that under these process parameters, the quality of the formed part is good, but the existence time of the molten pool is slightly short. The scanning speed can be appropriately reduced to extend the existence time of the molten pool and improve the forming quality. At the same time, according to the analysis results, the process parameters can be further optimized, such as adjusting the combination of power and speed, to obtain a more ideal forming effect.

[0147] Example 2

[0148] 1) Establish a temperature field simulation model

[0149] The size of the formed part is adjusted to 10mm×10mm×0.24mm, divided into 6 layers, each layer being 0.04mm. The size of the substrate remains unchanged. The material properties of the formed part and the substrate are the same as in Example 1, but during the actual measurement process, considering the slight differences in material batches and processing environments, some parameters are calibrated more precisely. Some parameters in the boundary conditions are adjusted to: k(T) = 27W / (m·K), δ = 18 / (mm 2 ·K), and the other parameters remain unchanged. These adjustments are based on a more in-depth study of the heat conduction and heat convection conditions during the actual processing process, aiming to improve the accuracy of the model.

[0150] 2) Divide the unit and refine the mesh

[0151] The formed part is divided into hexahedral elements with an M mesh of 0.04mm×0.04mm×0.04mm. Compared with Example 1, a finer mesh division helps to study the distribution of the temperature field inside the formed part more carefully, especially in the molten pool area and the interlayer transition area. The mesh division of the substrate remains unchanged, and the refined mesh of 0.02mm×0.02mm×0.02mm is still used to ensure the accuracy of the heat transfer simulation between the substrate and the formed part.

[0152] 3) Establish a heat source model

[0153] The process parameter range is fine-tuned according to the results of Example 1. The lower limit is adjusted to a laser power of 200W and a scanning speed of 600mm / s, and the upper limit is adjusted to a laser power of 500W and a scanning speed of 1000mm / s. This is because, based on Example 1, the influence of the change in the size of the formed part on the process parameters is further considered. A laser power of 400W and a scanning speed of 850mm / s are selected for simulation, the calculated scanning time step is 0.01s, and the maximum allowable calculation time step is 0.015s. The scanning strategy remains unchanged, and the 90° rotation scanning path between layers is still used. The analysis step size for each layer is calculated according to the new parameters to ensure that the forming process can be accurately simulated.

[0154] 4) Calculate the temperature field

[0155] Perform simulation calculations to obtain the numerical simulation results of the temperature field. During the calculation process, closely monitor the convergence and stability of the model to ensure the reliability of the calculation results. Through the simulation results, the distribution of the temperature field under the new process parameters and model settings can be seen. Compared with Example 1, the change trend and distribution characteristics of the temperature field are different, which provides an important basis for further analyzing the influence of process parameters on the quality of the formed parts.

[0156] 5) Temperature field analysis

[0157] Similarly, select key nodes to analyze various parameters under different power and speed combinations. For example, when the power is 500 W and the speed is 450 mm / s, the highest temperature of the molten pool reaches 3000 °C, the existence time is 0.04 s, the temperature gradient of the melting depth is 1500 °C / mm, the quality of the overlapping edge is better (judged by more detailed simulation result analysis, such as indicators like temperature uniformity and fusion degree at the edge), the cooling rate is 106 °C / s, and the width-depth ratio is 1.3. Comparing these results with those of Example 1, it is found that the temperature of the molten pool decreases slightly, but the temperature gradient of the melting depth is more uniform, the quality of the overlapping edge is better, the cooling rate is moderate, and the width-depth ratio is closer to the ideal value.

[0158] It shows that under these process parameters, the internal quality of the formed parts has been improved to a certain extent, but the overall temperature is relatively low. The power can be appropriately increased to further optimize the forming quality. For example, increase the power to about 300 W while keeping the speed unchanged, and perform simulation analysis again to observe the change of the quality of the formed parts.

[0159] Example 3

[0160] 1) Establish a temperature field simulation model

[0161] The size of the formed part is 12 mm × 12 mm × 0.28 mm, divided into 7 layers, each layer being 0.04 mm. The size of the substrate remains unchanged. The boundary condition parameters are adjusted to: k(T) = 27.5 W / (m·K), δ = 20 / (mm 2 ·K), with the other parameters remaining unchanged. These adjustments are based on the study of the heat exchange characteristics of different formed part sizes, aiming to improve the fitting degree of the model to the actual situation. For the assignment of material properties, the most realistic values are obtained by referring to authoritative materials science literature and conducting targeted experimental tests.

[0162] 2) Divide elements and refine the mesh

[0163] The formed part is divided into M hexahedral elements with a grid size of 0.06 mm × 0.06 mm × 0.06 mm. This relatively large grid size can improve the calculation efficiency while ensuring a certain calculation accuracy, and is suitable for simulating formed parts with smaller sizes. The substrate is divided into m refined hexahedral elements with a grid size of 0.02 mm × 0.02 mm × 0.02 mm, which can not only accurately simulate the thermal interaction between the substrate and the formed part, but also avoid waste of computing resources caused by excessive refinement. When dividing the grid, the geometric shape of the model and the characteristics of the temperature field change are fully considered, and local grid encryption is performed in areas with large temperature gradients (such as near the molten pool) to improve the accuracy of the simulation results. Use professional finite element preprocessing software (such as HyperMesh, etc.) for grid division operations to ensure the quality of the grid and the rationality of the element shape, and avoid the influence of deformed elements on the calculation results.

[0164] 3) Establish a heat source model

[0165] Through the result analysis of Examples 1 and 2 and further theoretical research, determine the new process parameter range. The lower limit is adjusted to a laser power of 300 W and a scanning speed of 750 mm / s, and the upper limit is adjusted to a laser power of 500 W and a scanning speed of 1000 mm / s. Select a laser power of 300 W and a scanning speed of 750 mm / s for simulation, calculate the scanning time step as 0.015 s and the maximum allowable calculation time step as 0.015 s. The scanning strategy still adopts a 90° rotation scanning path between layers. Use the function editor of software such as ANSYS to accurately input the heat source equation and generate an APDL command stream to achieve accurate loading and movement simulation of the heat source.

[0166] 4) Calculate the temperature field

[0167] Use the advanced finite element analysis software ANSYS to perform simulation calculations according to the optimized parameters and strategies. During the calculation process, make full use of the parallel computing function of the software to improve the calculation speed. At the same time, closely monitor the convergence and stability during the calculation process, and ensure the reliability of the calculation results by adjusting calculation parameters (such as relaxation factors, etc.). The simulation results are presented in various forms such as cloud maps and curves, intuitively showing the distribution changes of the temperature field in space and time. For example, through the temperature cloud map, the shape, size and temperature distribution of the molten pool can be clearly seen, and the temperature-time change curve can reflect the temperature history of different nodes during the forming process.

[0168] 5) Temperature field analysis

[0169] Select key nodes (such as the midpoints and edge points of each layer and each pass, etc.), and comprehensively analyze various parameters under different power and speed combinations. In addition to the conventional parameters such as temperature change, molten pool temperature and residence time, melt depth temperature gradient, lap joint edge, cooling rate, and width-depth ratio, the analysis of thermal stress distribution is also added. For example, when the power is 300 W and the speed is 750 mm / s, the molten pool temperature reaches a maximum of 2500 °C, the residence time is 0.03 s, the melt depth temperature gradient is 1200 °C / mm, the lap joint edge quality is good (judged by observing the temperature continuity and fusion degree at the edge), the cooling rate is 106 °C / s, the width-depth ratio is 1.2, and the thermal stress distribution is within the acceptable range (judged by calculating the thermal stress tensor and comparing it with the yield strength of the material).

[0170] By comparing with the first two embodiments, it is found that as the size of the formed part becomes smaller, at the same power and speed, the molten pool temperature is relatively lower, but the thermal stress also decreases. Based on these analysis results, further optimize the process parameters, such as appropriately reducing the power to reduce energy consumption while ensuring the forming quality, and at the same time adjusting the scanning speed to optimize the molten pool stability and interlayer bonding strength.

[0171] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

[0172] In addition, unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention belongs. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods related to the documents. In case of conflict with any incorporated document, the content of this specification shall prevail.

Claims

1. A numerical simulation method for temperature field of H13 hot working die steel SLM forming process, characterized in that: The following steps are involved: Constructing a three-dimensional geometric model of the formed part and the substrate according to the size parameters and boundary conditions of the formed part and the substrate; By meshing the three-dimensional geometric model of the formed part and the substrate, regular hexahedral units of the three-dimensional geometric model are generated; and the hexahedral units are further divided to generate refined mesh units that are consistent with the directions of the hexahedral units; Determine the forming power and scanning speed range of the materials used for the formed parts and substrates, establish a heat source model by pre-simulating the scanning time step, and simulate the process parameter range of the formed parts and substrates; take the forming state of the first layer when the laser scanning reaches the second layer of the forming layer as the evaluation standard, and when the surface temperature of the forming layer at the same position of the first layer does not reach the melting point of H13 hot working die steel, determine the forming state of the first layer as the lower limit of the process parameter range; According to the range of the interlayer overlap rate of the forming layer, the upper limit of the process parameter range is determined by measuring the depth of the molten pool; According to the upper and lower limits of the process parameter range and the refined grid units, the maximum allowable calculation time step is obtained by determining the time step of each grid unit of the laser scanned forming layer and optimizing the scanning strategy; The midpoint of each layer and each track in the forming layer is selected as the key node. The optimal process parameter combination of the formed part and the substrate SLM forming process is obtained by analyzing the temperature changes of the key nodes under different forming powers and scanning speeds and the maximum allowable calculation time step.

2. The method for numerically simulating the temperature field of the H13 hot working die steel SLM forming process according to claim 1 is characterized in that: The three-dimensional geometric model of the building block and the substrate specifically includes: Determine the size parameters of the formed parts and substrate according to actual process requirements; According to the physical properties of H13 hot working die steel, the material characteristics of the formed part and the substrate are assigned corresponding attributes, and the thermal physical property parameters of the powder material of H13 hot working die steel are determined; According to the actual processing environment and material properties of the formed parts and substrates, boundary conditions are set. During the SLM processing, a heat convection model is constructed between the side of the substrate, the upper surface excluding the powder bed, and the upper surface of the powder bed and the surrounding environment. The heat convection exchange is expressed by formula q: Among them, k e is the thermal conductivity coefficient of the powder bed, α is the thermal convection coefficient of the workpiece surface, T a is the ambient medium temperature, T s is the workpiece surface temperature, σ is the Potsdam constant, ε is the thermal radiation coefficient, and q is the laser heat flux density; The parameters in formula q need to be determined according to the actual processing environment and material characteristics; According to the size parameters of the molded part and the substrate and the set boundary conditions, a three-dimensional geometric model of the molded part and the substrate is constructed in the three-dimensional modeling software.

3. The method for numerically simulating the temperature field during the SLM forming process of H13 hot working die steel according to claim 2, characterized in that: The generating of the refined mesh unit having the same orientation as the hexahedral unit comprises the following steps: According to the three-dimensional geometric model of the formed part and the substrate, the three-dimensional geometric model is discretized according to its length, width and height, and divided into regular hexahedral units M; Among them, the hexahedral unit M in the substrate area needs to be divided by selecting a fixed-size grid unit according to actual needs, and the hexahedral unit M in the formed part area is divided again by the grid unit m to generate a refined grid unit that is consistent with the direction of the hexahedral unit; The selection of grid cell size requires a comprehensive consideration of the balance between computational accuracy and computational efficiency.

4. The method for numerical simulation of temperature field during SLM forming process of H13 hot working die steel according to claim 3, characterized in that: The heat source model is established by pre-simulating the time step of the scan, comprising: Enter the heat source model in the ANSYS function editor to generate the APDL command stream: Where q(x,y,z,t) is the instantaneous heat flux density at the local coordinate point (x,y,z) of the laser, P is the scanning power of the laser, r b is the laser spot radius, x 2 +y 2 is the square of the distance from any point on the powder bed to the center of the light spot, v is the laser scanning speed, and δ is the thermal diffusion model of the material; The thermal diffusion model δ of the material is: Where k is the thermal conductivity, ρ is the density, c p is the specific heat capacity.

5. The method for numerically simulating the temperature field during the SLM forming process of H13 hot working die steel according to claim 4, characterized in that: Determining the forming state of the first layer as the lower limit of the process parameter range specifically includes: The scanning time step is calculated by the speed, and the heat source model is input to simulate the parameters to obtain the simulation results; According to the simulation results, the forming state of the first layer when the laser scanning reaches the second layer is used as the evaluation standard. When the surface temperature of the forming layer at the same position of the first layer does not reach the melting point of H13 hot working die steel, it is determined that this is the lower limit of the process parameter range, indicating that the laser power is low or the scanning speed is fast, and the forming layer cannot fully melt the pool; Among them, the melting point of H13 hot working die steel was determined by experiment.

6. The method for numerical simulation of temperature field during SLM forming process of H13 hot working die steel according to claim 5, characterized in that: The upper limit of the process parameter range is determined, specifically including: According to the range of the interlayer overlap rate of the forming layer, the depth of the molten pool is measured for judgment. When the overlap rate exceeds the upper limit of the range of the interlayer overlap rate, it indicates that the laser power is high or the scanning speed is low, and the forming layer is over-melted. Among them, the overlap range of the SLM forming process of SLM H13 steel should be between 30% and 60%.

7. The method for numerically simulating the temperature field during the SLM forming process of H13 hot working die steel according to claim 6, characterized in that: The obtaining of the maximum allowable calculation time step specifically includes: According to the determined lower limit and upper limit of the process parameter range, determine the time step of each grid unit of the laser scanning forming layer and optimize the scanning strategy; The scanning strategy uses a 90° rotation scanning path between layers; The time step of each grid unit is the time when all current forming layers are scanned plus the powder spreading time t reserved after the scanning of each grid unit is completed; When the speed is changed, the position change formula is optimized to: F(x,y,z,t)=F(o±vt,y,nd,t) Among them, o is the starting position of each forming layer, v is the laser scanning speed, n is the number of scanning layers, and d is the powder layer thickness; After optimization, when the speed value is changed, the loading time of the heat source model is associated with the design, and the following is obtained: Among them, x0 is the x coordinate of the scanning starting point, and y0 is the y coordinate of the scanning process; The maximum allowable calculation time step is determined by calculation and analysis based on the sizes of the hexahedral unit M and the mesh unit m, as well as the detailed thermophysical properties of the formed part, substrate and powder material.

8. The method for numerically simulating the temperature field during the SLM forming process of H13 hot working die steel according to claim 7, characterized in that: The method of obtaining the optimal process parameter combination for the SLM forming process of the formed part and the substrate comprises the following steps: According to the constructed heat source model and scanning strategy, the SLM forming process was simulated using the finite element analysis software ANSYS; The "unit life and death" technology is introduced in the calculation process. By setting the activation and deactivation conditions of the life and death units, each time a new layer of forming begins, the corresponding grid unit is activated, and after each layer of forming is completed, some units are deactivated to capture the temperature changes of each node during the SLM forming process; According to the temperature changes of each node during the SLM forming process, the midpoint of each layer and each channel in the forming layer is selected as the key node. The temperature change trend and distribution characteristics are analyzed through the key nodes to determine the optimal process parameter combination.

9. A numerical simulation system for temperature field of H13 hot working die steel SLM forming process, characterized in that: include: The mesh unit generation module of the formed part and the substrate is used to construct a three-dimensional geometric model of the formed part and the substrate according to the size parameters and boundary conditions of the formed part and the substrate; generate regular hexahedral units of the three-dimensional geometric model by meshing the three-dimensional geometric model of the formed part and the substrate; and divide the hexahedral units again to generate refined mesh units that are consistent with the direction of the hexahedral units; The process parameter range determination module is used to determine the forming power and scanning speed range of the materials used for the formed parts and substrates. The heat source model is established by pre-simulating the scanning time step to simulate the process parameter range of the formed parts and substrates. The forming state of the first layer when the laser scanning reaches the second layer of the forming layer is used as the evaluation standard. When the surface temperature of the forming layer at the same position of the first layer does not reach the melting point of H13 hot working die steel, the forming state of the first layer is determined as the lower limit of the process parameter range. According to the range of the interlayer overlap rate of the forming layer, the upper limit of the process parameter range is determined by measuring the depth of the molten pool; The optimal process parameter combination acquisition module is used to obtain the maximum allowable calculation time step by determining the time step of each layer of grid units in the laser scanned forming layer and optimizing the scanning strategy according to the upper and lower limits of the process parameter range and the refined grid units; the midpoint of each layer and each channel in the forming layer is selected as the key node, and the temperature change of the key node under different forming power and scanning speed and the maximum allowable calculation time step are analyzed to obtain the optimal process parameter combination of the SLM forming process of the formed part and the substrate.

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