Method for regulating and controlling residual stress of additive high-strength steel through cooperation of thermal cycle and martensite phase transformation

Abstract

The invention relates to the technical field of steel production, and discloses a method for regulating and controlling residual stress of additive high-strength steel through cooperation of thermal cycle and martensite phase transformation, and the method comprises the following steps: S1, collecting process information; s2, establishing a digital twinborn model according to the process information and predicting a residual stress field; s3, cooperative control parameters are generated through a control algorithm; s4, the heat source output device is controlled to melt the raw materials to form a new layer of geometric structure; and S5, on the basis of the cooperative control parameters, residual stress generated by thermal shrinkage is compensated or counteracted through the volume expansion effect of martensite phase transformation. According to the method, the residual stress is predicted through the digital twinborn model, the control parameters are generated to control non-melting thermal cycle to trigger martensite phase transformation at a precise time-space point, thermal shrinkage stress is compensated through phase transformation volume expansion, and therefore the precision and predictability of stress regulation and control are improved.

Description

Technical Field

[0001] This invention relates to the field of steel production technology, specifically to a method for controlling residual stress in additive high-strength steel through thermal cycling-assisted martensitic phase transformation. Background Technology

[0002] Metal additive manufacturing is a manufacturing method for creating three-dimensional solid parts. Based on the principle of layer-by-layer deposition, additive manufacturing can directly transform a three-dimensional digital model into a physical entity, thereby enabling it to be integrally formed into a structural component.

[0003] However, in the additive manufacturing process of high-strength steel, the localized melting of metal powder or wire by a high-energy heat source followed by rapid solidification and cooling results in an uneven temperature field. Since metal expands when heated and contracts when cooled, this leads to localized expansion and contraction, inevitably generating internal stress. If this internal stress exceeds the material's yield strength, it can cause macroscopic defects such as warping and cracking in the workpiece, severely affecting the dimensional accuracy and reliability of the parts, and even causing the manufacturing process to fail entirely.

[0004] In existing technologies, internal stress is suppressed by adjusting the scanning strategy of the heat source, reducing the scanning speed, or preheating the substrate. However, existing methods are often passive or open-loop control strategies, and are based on experience or preset fixed parameters. Therefore, they are difficult to handle workpieces with complex shapes and cannot predict the stress distribution caused by unsteady heat accumulation, which in turn leads to a decrease in the mechanical properties of the workpiece. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for controlling residual stress in additive high-strength steel through thermal cycling-assisted martensitic phase transformation. This method solves the problem that existing technologies, which rely on experience or preset fixed parameters, are unable to handle workpieces with complex shapes and cannot predict the stress distribution caused by unsteady thermal accumulation, thus leading to a decline in the mechanical properties of the workpiece.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling residual stress in additive high-strength steel through thermal cycling-assisted martensitic phase transformation, comprising the following steps:

[0007] Step S1: Collect process information during additive manufacturing;

[0008] Step S2: Establish a digital twin model based on the collected process information and predict the residual stress field;

[0009] Step S3: Using the predicted residual stress field and target stress state, generate cooperative control parameters through a control algorithm;

[0010] Step S4: Based on the aforementioned coordinated control parameters, control the heat source output device to melt the raw materials to form a new layer of geometric structure;

[0011] Step S5: Based on the aforementioned coordinated control parameters, control the heat source output device to apply a non-melting heat cycle to the new layer or the adjacent area of ​​the new layer to regulate the cooling path of the deposited layer, trigger the martensitic phase transformation at a specified time and location, and use the volume expansion effect of the martensitic phase transformation to compensate for or offset the residual stress generated by thermal shrinkage.

[0012] Preferably, in step S1, the process information includes: power, scanning speed, substrate temperature, and raw material composition.

[0013] Preferably, in step S2, the digital twin model calculates the local cooling rate and stress state during the prediction process, and uses the cooling rate and stress state together with the raw material composition as input through a functional relationship to dynamically determine the martensitic phase transformation initiation temperature.

[0014] Preferably, in step S3, the control algorithm uses the target stress state as input to calculate the spatiotemporal distribution parameters of the non-melting thermal cycle required to achieve the target stress state.

[0015] Preferably, the digital twin model also outputs the stress tensor of the residual stress field and determines the direction of the principal tensile stress;

[0016] In step S3, the control algorithm also plans the scanning vector field of the control heat source output device according to the direction of the principal tensile stress, which is used to control the preferred orientation of the grains during solidification and form a preset crystal texture.

[0017] Preferably, the orientation of the preset crystal texture is used to generate maximum anisotropic volume expansion along the direction of principal tensile stress during post-martensitic phase transformation.

[0018] Preferably, step S3 further includes, when the predicted residual stress field exceeds a preset threshold, the control algorithm also generates an alloying instruction, which is used to adjust the composition of the raw materials supplied to the melting region in real time to adjust the inherent martensitic phase transformation characteristics of the deposited layer, including the martensitic phase transformation initiation temperature and the phase transformation volume expansion rate.

[0019] Preferably, the non-melting heat cycle is used to heat and cool the region that has completed solidification but is still in the austenitic state, so as to control the timing of the martensitic phase transformation.

[0020] Preferably, the set of coordinated control parameters includes: the spatiotemporal distribution parameters of the non-melting thermal cycle, the scanning vector field, and the alloying command.

[0021] A residual stress control system for additive high-strength steel with thermal cycling-assisted martensitic phase transformation includes:

[0022] The data acquisition module is used to collect process information during the additive manufacturing process;

[0023] Heat source output device; used to output heat source;

[0024] Raw material component supply device; used for supplying raw materials;

[0025] Memory is used to store computer program instructions;

[0026] The processor is connected to the acquisition module, the raw material component supply device and the heat source output device, and establishes a digital twin model based on the process information acquired by the acquisition module, and predicts the residual stress field that will be generated in the new layer and the adjacent area when the new layer is manufactured in additive manufacturing through the digital twin model.

[0027] Using the predicted residual stress field and target stress state as input, a collaborative control parameter is generated through a control algorithm;

[0028] Based on the aforementioned coordinated control parameters, the heat source output device and the raw material component supply device are controlled to:

[0029] The heat source output device is controlled according to the heat source scanning vector field to melt the raw materials to form the geometry of the new layer;

[0030] Adjust the raw material composition supplied to the melting zone by the raw material composition supply device;

[0031] The heat source output device controls the application of non-melting heat circulation to the new layer or the area adjacent to the new layer to regulate the cooling path of the deposited layer, thereby triggering the martensitic phase transformation at a specified time and location, and using the volume expansion effect of the martensitic phase transformation to compensate for or offset the residual stress generated by thermal shrinkage.

[0032] This invention provides a method for controlling residual stress in additive high-strength steel through thermal cycling-assisted martensitic phase transformation.

[0033] It has the following beneficial effects:

[0034] 1. This invention predicts the residual stress field by collecting process information and establishing a digital twin model, and finally generates control parameters. It uses non-melting thermal cycling to trigger the martensitic phase transformation at a precise time and location. In this way, the phase transformation volume expansion of the material itself can be used to actively compensate for and offset the thermal shrinkage stress, thereby significantly improving the accuracy and predictability of stress control.

[0035] 2. This invention uses non-melting thermal cycling to control the phase transition time point and pre-sets the crystal texture through a planned scanning vector field, maximizing the anisotropic volume expansion generated by the phase transition along the principal tensile stress direction. Furthermore, by dynamically adjusting the raw material composition, the inherent phase transition characteristics of the material can be optimized online, allowing for multi-faceted stress control and improving control efficiency.

[0036] 3. This invention calculates the influence of stress state on the initiation temperature of martensitic phase transformation using a digital twin model. At the same time, it introduces alloying instructions to adjust the composition of raw materials supplied to the melting zone in real time. Therefore, it can achieve the purpose of adjusting material properties online to meet specific stress control requirements. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0038] Figure 2 This is a schematic diagram of the system architecture of the present invention.

[0039] Among them, 10 is the acquisition module; 20 is the processor; 30 is the memory; 40 is the heat source output device; and 50 is the raw material component supply device. Detailed Implementation

[0040] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] To better understand the present invention, the above content will be described in detail below with reference to specific embodiments.

[0042] Refer to the attached Figure 1 , attached Figure 1 This is a schematic flowchart of a method for controlling residual stress in additive high-strength steel by thermal cycling synergistic martensitic phase transformation according to an embodiment of the present invention.

[0043] Step S1: Acquire process information during additive manufacturing. In this step, parameters used to define the physical boundary conditions and energy input of the manufacturing process are obtained. Specifically, these parameters include the power output of the heat source, the scanning speed, the workpiece substrate temperature, and the initial chemical composition of the supplied raw materials;

[0044] Step S2: Establish a digital twin model based on the collected process information and predict the residual stress field. In this step, calculations are performed using a multiphysics coupling model based on the finite element method. This model is pre-set and stored in a computer-readable medium. First, the nonlinear transient heat conduction equation is solved to calculate the temperature field of the workpiece in three-dimensional space as a function of time. Based on the calculated temperature field, the mechanical response is further solved. The model decomposes the total strain increment into the sum of elastic strain increment, plastic strain increment, thermal strain increment, and phase transformation strain increment. The phase transformation strain increment includes isotropic volumetric strain caused by lattice structure changes, as well as phase transformation-induced plastic strain induced by applied stress. The phase transformation kinetics module in the model is used to determine the evolution of the martensite volume fraction. The martensitic phase transformation initiation temperature is influenced by the local cooling rate, local stress tensor, and chemical composition.

[0045] Step S3: Generate cooperative control parameters using the predicted residual stress field and target stress state. In this step, the residual stress field predicted in step S1 is compared with the preset target stress state (e.g., zero stress or a specific compressive stress state), and solved using a control algorithm (e.g., model predictive control or inverse optimization algorithm) to generate a set of time-varying cooperative control parameters.

[0046] Step S4: Based on the coordinated control parameters, a heat source output device is controlled to melt the raw material to form a new layer of geometry. In this step, according to the heat source scanning vector value and heat source output power command in the parameter set, the heat source output device is controlled to move on the workpiece surface and output a high-energy beam. Simultaneously, according to the raw material component supply rate command, the raw material component supply device is controlled to supply powder or filament. By melting the supplied raw material, the physical deposition and geometric shaping of the new layer of material are completed.

[0047] Finally, in step S5, based on the coordinated control parameters, the heat source output device is controlled to apply a non-melting thermal cycle to the new layer or its adjacent area. In this step, according to the non-melting thermal cycle instructions in the parameter set, the heat source output device is controlled to adjust its output power to a level that will not melt the material, and controlled heating and cooling are performed on the designated area to precisely control the cooling path of the area, triggering a martensitic phase transformation at a predetermined time and location, and using its volume expansion to compensate for and offset the residual stress generated by thermal contraction.

[0048] In one specific embodiment, in the initial step S1, process information during additive manufacturing is collected. This provides accurate, real-time initial and boundary condition data for subsequent digital twin model calculations.

[0049] Specifically, preset process parameters are obtained. These parameters include: the power of the energy beam output from the heat source output device 40 to the workpiece surface, which can be measured by a power meter connected to the power controller of the heat source output device 40; the scanning speed and scanning path of the energy beam on the workpiece surface, which can be directly read from the controller of the system controlling the movement of the heat source output device 40 (such as a galvanometer or CNC platform); and the initial temperature of the workpiece substrate and the ambient temperature, which can be measured by thermocouples installed in the manufacturing chamber or on the substrate.

[0050] In one embodiment, non-contact temperature measurement is also included, such as one or more pyrometers whose optical axes are aligned with the molten pool and its adjacent area. The pyrometers can be used to monitor the temperature of the molten pool and the newly deposited layer in real time during the manufacturing process, and transmit the acquired temperature data stream to processor 20 for calibration of the calculation results of the digital twin model or as input to the digital twin model.

[0051] In addition, this step also includes acquiring the initial chemical composition information of the raw materials used. This information, such as the mass percentage of each alloying element (e.g., carbon, manganese, chromium, molybdenum, etc.) in high-strength steel, is input as an initial parameter set and stored in memory 30 for the processor 20 to retrieve in subsequent calculations. The acquisition module 10 integrates all the above-mentioned acquired process information into a dataset and sends it to the processor 20.

[0052] After information acquisition is completed in step S1, the process proceeds to step S2. In this step, based on the acquired process information, a digital twin model is established and computed to predict the residual stress field that will be generated in the new layer and adjacent areas during additive manufacturing.

[0053] In one specific embodiment, the digital twin model is a multiphysics coupled model based on the finite element method. The processor 20 first generates a finite element mesh based on the geometric data of the component to be manufactured and the geometry of the newly deposited layer. Subsequently, the processor 20 solves a set of coupled, nonlinear partial differential equations on this mesh.

[0054] First, the thermal analysis module in the model calculates the temperature field (T(x,y,z,t)) of the entire workpiece in three-dimensional space (x,y,z) as a function of time (t) by solving the nonlinear transient heat conduction equation. The formula for this equation is:

[0055]

[0056] In the formula, ρ(T,ξ) represents the density of the material, and its value is a function of temperature T and phase composition ξ; C p(T,ξ) represents the specific heat capacity of the material, which is a function of temperature T and phase composition ξ; k(T,ξ) represents the thermal conductivity of the material, which is a function of temperature T and phase composition ξ; T represents temperature, which is a scalar field and a function of spatial position and time; t represents time; ξ represents the phase composition of the material, such as the volume fraction of each phase (austenite, martensite, etc.). This represents the partial derivative of temperature with respect to time. Representing the temperature gradient, it is a vector pointing in the direction of the fastest increase in temperature; Q v This indicates the heat source within the volume, with power per unit volume, representing the heat generated inside the material by an additive manufacturing heat source (such as a laser or electron beam).

[0057] Based on the temperature field calculated at each time step, the mechanical analysis module in the model further solves for the mechanical response. The core of this module is to decompose the total strain increment d∈ into the sum of multiple components, calculated using the following formula:

[0058] d∈=d∈ e +d∈ p +d∈ th +d∈ tr ;

[0059] In the formula, d∈ e The elastic strain increment follows Hooke's law; d∈ p For the plastic strain increment, it follows temperature-dependent flow laws and hardening models; d∈ th The thermal strain increment; d∈ tr This represents the phase transition strain increment;

[0060] Phase transition strain increment d∈ tr This includes isotropic volumetric strain caused by changes in lattice structure, and phase transformation-induced plastic strain induced by applied stress. The formula for the increment is:

[0061]

[0062] In the formula, I is the second-order unit tensor; ΔV is the inherent volumetric expansion rate of the material as it transforms from the parent phase (austenite) to the martensite phase; dξ m ξ is the volume fraction of martensite. m The increment; K p X is the phase transformation-induced plasticity coefficient of the material; S is the deviatoric stress tensor; X tr ξ is the back stress tensor associated with phase transformation hardening. m Martensite volume fraction

[0063] The phase transformation kinetics module in the model is used to determine the martensite volume fraction ξ. m Evolution of martensitic phase transformation. Martensitic phase transformation initiation temperature M. s Local cooling rate Local stress tensor σ ij and chemical component C k The combined influence has the following functional relationship:

[0064]

[0065] In the formula, C k The concentration or mass fraction of the k-th alloying element in the material is represented by f(,,,), which indicates the functional relationship, indicating that M s It is determined by the variables within the parentheses.

[0066] When the temperature T calculated by processor 20 drops to M s The following is the martensite volume fraction ξ m The evolution follows the Koistinen-Marburger relation:

[0067] ξ m =1-exp[-α(M s -T)];

[0068] In the formula, α represents a material-related constant that determines the rate of phase transition. This parameter is determined experimentally; exp[.] represents the natural exponential function.

[0069] Finally, by iteratively solving the aforementioned heat conduction equation, mechanical constitutive equation, and phase transition kinetic equation within each time increment step, the spatial distribution of the residual stress field formed inside the workpiece after the newly deposited layer has completely cooled to room temperature is calculated. This stress field, as the output of this step, is passed to the next step.

[0070] After the residual stress field is predicted in step S2, the method proceeds to step S3. In this step, the processor 20 executes computer program instructions stored in the memory 30, using the residual stress field predicted in step S2 and the preset target stress state as input, and generates a set of cooperative control parameters through a control algorithm.

[0071] Specifically, processor 20 constructs the generation process of the cooperative control parameters as an optimization problem. The goal of this optimization problem is to solve for a set of optimal time-varying control parameters U(t) to minimize the final residual stress field σ. final With respect to the preset target stress field σ target The deviation between them. Optimization objective. The function formula is:

[0072]

[0073] Where σ final(U(t)) represents the residual stress field obtained after applying the control parameter U(t); σ target The target stress field is a preset stress field, such as a zero stress field or a compressive stress field with a specific distribution; ∥.∥ represents the norm used to measure the deviation between two stress fields, such as the L2 norm.

[0074] The set of coordinated control parameters U(t) includes: the heat source output power command P(t) and the scan vector command v(t) for step S4, and the raw material component supply rate command for step S4. And the spatiotemporal distribution instruction H(x,t) for the non-melting thermal cycle in step S5. The specific expression formula is:

[0075]

[0076] In one specific embodiment, the processor 20 generates the following types of control parameters by solving this optimization problem:

[0077] First, processor 20 determines the spatiotemporal distribution instruction H(x,t) for the non-melting thermal cycle in step S5. This instruction defines which spatial regions (x) of the workpiece and at which time points the non-melting thermal cycle is applied, and specifies the specific temperature-time curve of the thermal cycle. The solution is based on finding the optimal temperature history through reverse calculation to control the martensitic phase transformation volume fraction ξ. m The evolution process, thereby maximizing the use of phase change volume expansion to offset thermal shrinkage stress.

[0078] Secondly, processor 20 generates the scan vector instruction v(t) for step S4. Processor 20 first analyzes the residual stress field σ predicted in step S2. predictedt The direction of the principal tensile stress is determined. Subsequently, the control algorithm plans a scanning vector field based on this direction to control the preferred orientation of grains during solidification, forming a predetermined crystal texture. This is because the macroscopic phase transition strain tensor ∈ tr The phase transformation strain ∈ for all N martensitic variants p tr,p According to its volume fraction f p The weighted average is calculated using the following formula:

[0079]

[0080] Third, the processor 20 generates a raw material component supply rate instruction for step S4. The processor 20 first determines whether the amplitude of the residual stress field predicted in step S2 exceeds a preset threshold. If it exceeds the threshold, the control algorithm generates a corresponding alloying instruction, which is manifested as the supply rate of raw material components to the melting region. Adjustments were made to change the chemical composition (C) of the sedimentary layers in this area.k The aim is to adjust the inherent martensitic transformation initiation temperature M of the material in this region. s M s The relationship between temperature and chemical composition can be described by the following empirical formula:

[0081] M s (°C)=A0-∑ k A k C k ;

[0082] In the formula, A0 is the phase transformation temperature constant of pure iron; C k A represents the mass percentage of the k-th alloying element. k is the regression coefficient corresponding to the k-th alloying element.

[0083] Finally, the processor 20 will output the set of cooperative control parameters U(t) containing the above instructions for subsequent manufacturing and control steps.

[0084] After generating the collaborative control parameters in step S3, the process proceeds to step S4. In this step, based on the collaborative control parameters, the heat source output device 40 is controlled to melt the raw material to form a new layer of geometry.

[0085] Specifically, processor 20 extracts instructions for the main manufacturing process from the cooperative control parameter set U(t) generated in step S3. These instructions include the heat source output power instruction P(t), the scan vector instruction v(t), and the raw material component supply rate instruction.

[0086] Processor 20 sends the heat source output power command P(t) and the scan vector command v(t) to the controller of heat source output device 40. Heat source output device 40, such as a laser or electron beam source and its associated scanning system (e.g., a galvanometer or CNC platform), executes the operation according to the received commands. The output power is adjusted to the value of P(t), while the focus of its energy beam moves along the spatial path and velocity defined by v(t).

[0087] The scan vector command v(t) is based on the route planned in step S3 to control the crystal texture.

[0088]

[0089] At the same time, the processor 20 sends the raw material component supply rate instruction. The raw material is sent to the raw material component supply device 50. The raw material component supply device 50, such as a multi-channel powder feeder or a multi-filament supply system, accurately supplies the raw material to the area where the heat source energy beam acts, according to the instruction.

[0090] In one implementation, if the raw material component supply rate instruction Including the alloying instruction generated in step S3, the raw material component supply device 50 will adjust the supply rate ratio of different hoppers to form a molten pool with the target chemical composition C. k The alloy melt.

[0091] Therefore, in summary, the heat source output device 40 melts the raw materials supplied by the raw material composition supply device 50, and the molten metal solidifies along a preset path, thereby completing the physical deposition of a new layer of material with a specific geometry, crystal texture, and chemical composition. This, in turn, provides support for subsequent non-melting thermal cycles or the deposition of the next layer.

[0092] After the physical deposition of the new layer of material is completed in step S4, the process proceeds to step S5. In this step, based on the cooperative control parameters, the heat source output device 40 is controlled to apply a non-melting heat cycle to the new layer or its adjacent area.

[0093] Specifically, the processor 20 extracts the spatiotemporal distribution instruction H(x,t) of the non-melting heat cycle from the cooperative control parameter set U(t) generated in step S3, and sends the instruction to the heat source output device 40.

[0094] Upon receiving an instruction, the heat source output device 40 adjusts its output power to a preset temperature parameter below the material's melting point. Simultaneously, the scanning system of the heat source output device 40 guides the heat source output end of the device to one or more designated areas on the workpiece based on the spatial coordinate information contained in the instruction H(x,t). The controller of the heat source output device 40 controls the application duration and interruption of the heat source output end in these areas according to the instruction H(x,t), thereby forming a temperature-time curve. This temperature-time curve is used to regulate the cooling path of the forming area, ensuring that austenite undergoes a martensitic solid-state phase transformation within a predetermined time and temperature range.

[0095] Since martensitic phase transformation leads to volume change (i.e., volume expansion), and this phase transformation process generates a compressive stress field or expansion strain within the forming region, the compressive stress field or expansion strain can be used to compensate for and counteract the tensile stress generated by thermal contraction during the melting and solidification process in step S4 and subsequent cooling.

[0096] Furthermore, during additive manufacturing, the melting, solidification, and cooling processes of materials result in a non-uniform temperature field that leads to uncoordinated thermal shrinkage, which in turn generates residual tensile stress. This invention utilizes the volume expansion effect that accompanies the transformation of steel from the parent phase (austenite) to the martensite phase in the solid state. By actively controlling the timing and spatial location of this phase transformation, an endogenous compressive stress field with a specific direction and magnitude is generated to compensate for and counteract the tensile stress caused by thermal shrinkage.

[0097] Whether a phase transformation occurs and its process are determined by the change in Gibbs free energy ΔG. (Austenite γ to martensite α) ′ The transformation only occurs when the total Gibbs free energy changes ΔGγ→α. ′ The phase transition only occurs when the value is negative; the magnitude of this negative value represents the driving force of the phase transition. The total driving force of the phase transition consists of two parts: chemical driving force and mechanical driving force.

[0098] The formula for the total change in Gibbs free energy is expressed as:

[0099]

[0100] In the formula, This represents the total change in free energy; This represents the change in chemical free energy; ΔG mech The mechanical work done by the stress field on the phase transition.

[0101] Chemical free energy change It is a function of temperature and chemical composition, and is negative only when the temperature is below the two-phase equilibrium temperature T0. It decreases as the temperature decreases, thus providing the basic driving force for phase change.

[0102] Mechanical driving force ΔG chem This originates from the interaction between the internal stress field of the material and the phase transformation strain. When an external or internal stress field exists, it couples with the strain generated by the phase transformation, thereby changing the total free energy. This term can be expressed as:

[0103]

[0104] In the formula, V m σ is the molar volume; ij This refers to the stress tensor acting in the phase transition region. This is the phase transition strain tensor.

[0105] Using this formula, when there is tensile stress inside the material (σ) ij (Positive), the stress field will tend to drive those that can produce the maximum expansion strain in the tensile direction ( Martensitic variants with a positive nucleation rate preferentially nucleate and grow. This interaction manifests externally as providing an additional driving force for the phase transition (making ΔGi) mech (negative), thereby increasing the critical temperature at which the phase transformation begins, i.e., the martensitic phase transformation initiation temperature M. s .

[0106] Therefore, in step S5, a non-melting heat cycle is applied, and the temperature-time curve of a specific area of ​​the workpiece is precisely controlled, thereby actively adjusting the temperature T and stress state σ of that area. ijThis allows the total phase change driving force in the region to be at the point when stress compensation is most needed (e.g., when the tensile stress caused by thermal shrinkage reaches its peak). If the critical driving force threshold required for the phase transformation is reached or exceeded, the martensitic phase transformation can be triggered. The volume expansion generated by the phase transformation is precisely used to offset the tensile stress, thereby achieving effective control over the final residual stress.

[0107] Refer to the attached Figure 2 , attached Figure 2 This is a schematic diagram of the system architecture of a thermal cycling-assisted martensitic transformation additive high-strength steel residual stress control system according to another embodiment of the present invention, including:

[0108] The data acquisition module is used to collect process information during the additive manufacturing process;

[0109] Heat source output device; used to output heat source;

[0110] Raw material component supply device; used for supplying raw materials;

[0111] Memory is used to store computer program instructions;

[0112] The processor is connected to the acquisition module, the raw material component supply device and the heat source output device, and establishes a digital twin model based on the process information acquired by the acquisition module. It also uses the digital twin model to predict the residual stress field that will be generated in the new layer and the adjacent area when a new layer is manufactured in additive manufacturing.

[0113] Using the predicted residual stress field and target stress state as inputs, a collaborative control parameter is generated through a control algorithm;

[0114] Based on coordinated control parameters, the heat source output device and the raw material component supply device are controlled to:

[0115] The heat source output device is controlled by the heat source scanning vector field to melt the raw materials to form a new layer of geometric structure;

[0116] Adjust the raw material composition supplied to the melting zone by the raw material composition supply device;

[0117] The heat source output control device applies a non-melting heat cycle to the new layer or the area adjacent to the new layer to regulate the cooling path of the deposited layer, which is used to trigger the martensitic phase transformation at a specified time and location, and to use the volume expansion effect of the martensitic phase transformation to compensate for or offset the residual stress generated by thermal shrinkage.

[0118] In this embodiment, the system includes a data acquisition module 10, a processor 20, a memory 30, a heat source output device 40, and a raw material component supply device 50. The processor 20 is communicatively connected to the data acquisition module 10, the memory 30, the heat source output device 40, and the raw material component supply device 50.

[0119] The data acquisition module 10 is used to acquire preset process information in real time during the additive manufacturing process. This includes the output power of the heat source output device 40, the scanning speed, the workpiece substrate temperature, and the chemical composition of the raw materials used. The data acquisition module 10 transmits the acquired data to the processor 20 as the initial and boundary conditions for model calculation.

[0120] The memory 30 stores computer program instructions and data required by the processor 20 to perform its functions. Specifically, the memory 30 stores the algorithm for the digital twin model and the control algorithm for generating control parameters.

[0121] The processor 20 executes computer program instructions stored in the memory 30. First, the processor 20 establishes and calculates a digital twin model based on the process information acquired by the acquisition module 10. Using this model, the processor 20 predicts the spatial distribution of the residual stress field that will form in the new layer and its adjacent area after the deposition of a new layer of material.

[0122] Next, the processor 20 compares the predicted residual stress field with the target stress state stored in the memory 30. Using a control algorithm, the processor 20 generates a set of coordinated control parameters, which are used to drive the final stress state of the workpiece to approach the preset target stress state through subsequent physical operations.

[0123] Finally, based on the generated collaborative control parameters, the processor 20 sends specific execution instructions to the heat source output device 40 and the raw material component supply device 50. The execution of these instructions includes the following collaborative operations: First, controlling the power and scanning path of the heat source output device 40 to melt the raw material and form a predetermined geometry for a new layer. The scanning path is determined according to the scanning vector field instruction in the collaborative control parameters, used to preset the crystal texture of the deposited layer, thereby affecting the anisotropy of subsequent phase transformation strain. Second, controlling the raw material component supply device 50 to adjust the chemical composition ratio of the raw material supplied to the melting region. The purpose of this adjustment is to locally change the inherent martensitic phase transformation initiation temperature of the deposited material, creating more favorable conditions for subsequent thermal cycling control. Third, controlling the heat source output device 40 to scan and heat the newly deposited layer or its adjacent region at a power lower than the material's melting point, i.e., applying a non-melting thermal cycle. The temperature-time curve of this thermal cycle is determined according to the collaborative control parameters, and its function is to precisely trigger the martensitic solid-state phase transformation at a specific time and location, using the volume expansion generated by the phase transformation to compensate for or offset the tensile residual stress caused by thermal contraction.

[0124] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling residual stress in additive high-strength steel through thermal cycling-assisted martensitic phase transformation, characterized in that, Includes the following steps: Step S1: Collect process information during additive manufacturing; Step S2: Establish a digital twin model based on the collected process information and predict the residual stress field; Step S3: Using the predicted residual stress field and target stress state, generate cooperative control parameters through a control algorithm; Step S4: Based on the aforementioned coordinated control parameters, control the heat source output device to melt the raw materials to form a new layer of geometric structure; Step S5: Based on the aforementioned coordinated control parameters, control the heat source output device to apply a non-melting heat cycle to the new layer or the adjacent area of ​​the new layer to regulate the cooling path of the deposited layer, trigger the martensitic phase transformation at a specified time and location, and use the volume expansion effect of the martensitic phase transformation to compensate for or offset the residual stress generated by thermal shrinkage.

2. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 1, characterized in that, In step S1, the process information includes: power, scanning speed, substrate temperature, and raw material composition.

3. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 1, characterized in that, In step S2, the digital twin model calculates the local cooling rate and stress state during the prediction process, and uses the cooling rate and stress state together with the raw material composition as inputs through a functional relationship to dynamically determine the martensitic phase transformation initiation temperature.

4. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 1, characterized in that, In step S3, the control algorithm uses the target stress state as input to calculate the spatiotemporal distribution parameters of the non-melting thermal cycle required to achieve the target stress state.

5. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 4, characterized in that, The digital twin model also outputs the stress tensor of the residual stress field and determines the direction of the principal tensile stress; In step S3, the control algorithm also plans the scanning vector field of the control heat source output device according to the direction of the principal tensile stress, which is used to control the preferred orientation of the grains during solidification and form a preset crystal texture.

6. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 5, characterized in that, The pre-defined crystal texture orientation is used to generate maximum anisotropic volume expansion along the direction of principal tensile stress during post-martensitic phase transformation.

7. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 5, characterized in that, Step S3 further includes the following: when the predicted residual stress field exceeds a preset threshold, the control algorithm generates an alloying instruction. The alloying instruction is used to adjust the composition of the raw materials supplied to the melting region in real time to adjust the inherent martensitic phase transformation characteristics of the deposited layer. The characteristics include the martensitic phase transformation initiation temperature and the phase transformation volume expansion rate.

8. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 4, characterized in that, The non-melting heat cycle is used to heat and cool regions that have completed solidification but are still in the austenitic state, in order to control the timing of the martensitic phase transformation.

9. The method for controlling residual stress in additive high-strength steel by thermal cycling-assisted martensitic phase transformation according to claim 7, characterized in that, The set of coordinated control parameters includes: the spatiotemporal distribution parameters of the non-melting thermal cycle, the scanning vector field, and the alloying command.

10. A residual stress control system for additive high-strength steel with thermal cycling synergistic martensitic transformation, based on the residual stress control method for additive high-strength steel with thermal cycling synergistic martensitic transformation as described in any one of claims 1-9, characterized in that, include: The data acquisition module is used to collect process information during the additive manufacturing process; Heat source output device; Used to output heat source; Raw material component supply device; Used for supplying raw materials; Memory is used to store computer program instructions; The processor is connected to the acquisition module, the raw material component supply device and the heat source output device, and establishes a digital twin model based on the process information acquired by the acquisition module, and predicts the residual stress field that will be generated in the new layer and the adjacent area when the new layer is manufactured in additive manufacturing through the digital twin model. Using the predicted residual stress field and target stress state as input, a collaborative control parameter is generated through a control algorithm; Based on the aforementioned coordinated control parameters, the heat source output device and the raw material component supply device are controlled to: The heat source output device is controlled according to the heat source scanning vector field to melt the raw materials to form the geometry of the new layer; Adjust the raw material composition supplied to the melting zone by the raw material composition supply device; The heat source output device controls the application of non-melting heat circulation to the new layer or the area adjacent to the new layer to regulate the cooling path of the deposited layer, thereby triggering the martensitic phase transformation at a specified time and location, and using the volume expansion effect of the martensitic phase transformation to compensate for or offset the residual stress generated by thermal shrinkage.

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