A method and system for predicting residual stress in hot-rolled strip steel based on finite element model

Abstract

This invention provides a method and system for predicting residual stress in hot-rolled strip steel based on a finite element model, belonging to the field of hot rolling process control. The method acquires historical production data and strip steel properties, constructs a finite element model and a three-dimensional unsteady-state heat transfer equation, and solves for the temperature field distribution. Then, a thermo-mechanical-phase transformation coupled model is constructed. Feature points are selected in the finite element model, and their thermo-mechanical history data are extracted and used as boundary conditions to solve for the microstructure evolution history data of the feature points, calculating the phase transformation strain increment. Using the final rolled strip temperature, cooling temperature, and fluid rate as feature parameters, a feature parameter-phase transformation strain increment coupled model is constructed and fitted to solve the parameters. Finally, the current process conditions are input into the feature parameter-phase transformation strain increment coupled model to obtain the phase transformation strain increment, which is then inverted and substituted into the thermo-mechanical-phase transformation coupled model to predict the residual stress under the current process conditions. This invention improves the accuracy of residual stress calculation.

Description

Technical Field

[0001] This invention belongs to the field of hot rolling process control, specifically relating to a method and system for predicting residual stress in hot-rolled strip steel based on a finite element model. Background Technology

[0002] Hot rolling is a crucial step in strip steel production, encompassing heating, rolling, and laminar flow cooling. During rolling and laminar flow cooling, uneven rolling force and cooling temperature can lead to spatial and temporal uneven thermal deformation, uneven thermal expansion, uneven phase transformation, and uneven grain size, resulting in uneven volume changes and microstructure transformations, ultimately forming macroscopic residual stress. This residual stress is a key factor contributing to strip steel shape defects (such as warping, edge waviness, and center waviness), severely affecting dimensional accuracy and performance, and may even cause cracks and fatigue during subsequent processing or use, reducing the material's service life and reliability.

[0003] In existing technologies, residual stress in hot-rolled strip steel is generally predicted using models, and the process is optimized based on the prediction results to reduce residual stress. Currently, models for predicting residual stress in hot-rolled strip steel typically employ macroscopic finite element simulations. This type of method, by establishing a thermo-mechanical coupling model, can predict the distribution of temperature and stress-strain fields to a certain extent and perform preliminary optimization of the cooling process; however, macroscopic finite element models usually highly simplify the phase transformation process, making it difficult to accurately describe the microscopic mechanisms involved. Some models employ multi-scale coupling, adding a micro-mesoscopic model to the macroscopic finite element model and coupling various microscopic mechanisms, including dislocations, slip, twinning, and phase transformations, to establish a temperature-stress-microstructure coupled physical model. However, these models still rely on the temperature field distribution calculated under the macroscopic model. The microstructure analysis in this case is based on the transfer results of the macroscopic model, rather than directly from process parameters. Predictions of microstructures related to residual stress, such as changes in grain size and martensitic phase transformation, are inaccurate and cannot truly reflect the dynamics and variability of the actual production process, resulting in inaccurate predictions of residual stress. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a method and system for predicting residual stress in hot-rolled strip steel based on a finite element model. The method constructs a thermo-mechanical-phase transformation coupled model using the finite element model, and then builds a characteristic parameter-phase transformation strain increment coupled model based on the preliminary solution results of the finite element model. This strengthens the influence of characteristic parameters in residual stress generation, thereby improving the accuracy of residual stress calculation.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows: In a first aspect, embodiments of the present invention provide a method for predicting residual stress in hot-rolled strip steel based on a finite element model, the method comprising the following steps: Step S1: Obtain historical production data of the current production line's laminar flow cooling process, as well as the physical property parameters of the corresponding strip steel produced; Step S2: Construct a finite element model of the strip and a three-dimensional unsteady heat transfer equation of the strip finite element model based on the final rolled strip dimensions, and solve the heat transfer equation to obtain the temperature field distribution. Step S3: Construct a thermo-mechanical-phase transition coupled model based on the finite element model; Step S4: Select feature points in the finite element model and extract the thermo-mechanical history data of the feature points from the solved temperature field distribution; based on the thermo-mechanical-phase transition coupling model, use the thermo-mechanical history data as boundary conditions to solve the microstructure evolution history data of the feature points, and calculate the phase transition strain increment at the corresponding feature points. Step S5: Using the final strip temperature, cooling temperature, and fluid rate as characteristic parameters, construct a characteristic parameter-phase transformation strain incremental coupling model. Step S5: Using the final strip temperature, cooling temperature, and fluid rate as characteristic parameters, construct a characteristic parameter-phase transformation strain incremental coupling model. Step S6: Based on historical production data and the phase transformation strain increment at the corresponding feature point, fit and solve the parameters of the feature parameter-phase transformation strain increment coupling model, and substitute them into the model; Step S7: Input the current process conditions into the characteristic parameter-phase transformation strain increment coupling model to obtain the phase transformation strain increment under the current process conditions; Step S8: Substitute the phase transformation strain increment inversion into the thermo-mechanical-phase transformation coupled model to predict the residual stress under the current process conditions.

[0006] As a preferred embodiment of the present invention, the characteristic parameter-phase transformation strain increment coupling model in step S5 is as follows: (7) In equation (7), T C , T E , v c These represent the cooling temperature, the final strip temperature, and the fluid rate, respectively. This represents the increase in strain during phase transition. This is the incremental adjustment constant. , , and These are the phase transformation strain increment coefficients. and β The power exponent.i Indicates the first i 1 feature point.

[0007] In a preferred embodiment of the present invention, in step S1, the historical production data includes strip composition, final rolled strip size, final rolled strip temperature, cooling temperature, and fluid rate; the physical properties of the strip include thermal conductivity, specific heat, and density.

[0008] In a preferred embodiment of the present invention, the heat transfer parameters of the three-dimensional unsteady heat transfer equation are defined using the Nusselt number in step S2, and the formula is as follows: (1) In equation (1), Represents the Nusel number, Representing the Grashof number, The Prandtl number represents the boundary layer fluid. This represents the heat transfer coefficient of the strip cooling surface. Indicates the characteristic length. Expressed as the thermal conductivity of the boundary layer fluid, C , n It is a constant.

[0009] As a preferred embodiment of the present invention, the three-dimensional unsteady-state heat transfer equation of the strip finite element model is as follows: Internal node A: (3) Boundary line node B: (4) Boundary surface node C: (5) In equations (3)-(5), and They represent x The direction and the temperature values ​​at the two corresponding neighboring nodes of internal node A; and They represent y The direction and the temperature values ​​at the two corresponding neighboring nodes of internal node A; and They represent z The direction and the temperature values ​​at the two corresponding neighboring nodes of internal node A; This indicates that nodes A, B, and C pass through Δ t Temperature change over time; Density, unit: kg / m³ 3 ; T Temperature, unit: K ; Specific heat, expressed in J / (kg·K); is the thermal conductivity, with units of W / (m·K).

[0010] In a preferred embodiment of the present invention, when constructing the thermo-mechanical-phase transformation coupling model in step S3, the phase transformation volume fraction of the transformation from austenite to other microstructures is calculated according to the lever principle.

[0011] In a preferred embodiment of the present invention, the lever principle formula is as follows: (6) In equation (6), This indicates the volume fraction of austenite. Indicates the austenitizing initiation temperature. Indicates the temperature at which complete austenitization occurs. T This indicates the real-time temperature.

[0012] In a preferred embodiment of the present invention, the phase transformation strain increment in step S4 includes phase transformation volumetric strain and phase transformation induced plastic strain.

[0013] In a preferred embodiment of the present invention, the thermo-mechanical history data includes temperature-time history data and stress-time history data.

[0014] Secondly, embodiments of the present invention provide a system for implementing the above-described method for predicting residual stress in hot-rolled strip steel based on a finite element model. The system includes: a data acquisition module, a heat transfer equation construction module, a temperature field distribution solution module, a thermo-mechanical-phase transformation coupled model construction module, a phase transformation strain increment solution module, a characteristic parameter-phase transformation strain increment coupled model construction module, a fitting solution module, and a residual stress prediction module; wherein... The data acquisition module is used to acquire historical production data of the laminar flow cooling process of the current production line, as well as the physical property parameters of the corresponding strip steel produced. The heat transfer equation construction module is used to construct the finite element model of the strip and the three-dimensional unsteady heat transfer equation of the strip finite element model based on the final rolled strip size. The temperature field distribution solution module is used to solve the heat transfer equation to obtain the temperature field distribution; The thermo-mechanical-phase transition coupling model construction module is used to construct a thermo-mechanical-phase transition coupling model based on the finite element model; The phase transformation strain increment solution module is used to select feature points in the finite element model and extract the thermo-mechanical history data of the feature points from the solved temperature field distribution; based on the thermo-mechanical-phase transformation coupled model, the microstructure evolution history data of the feature points is solved using the thermo-mechanical history data as boundary conditions, and the phase transformation strain increment at the corresponding feature points is calculated. The characteristic parameter-phase transformation strain incremental coupling model construction module is used to construct a characteristic parameter-phase transformation strain incremental coupling model using the final rolled strip temperature, cooling temperature and fluid rate as characteristic parameters. The fitting and solving module is used to fit and solve the parameters of the characteristic parameter-phase transformation strain increment coupled model based on historical production data and the phase transformation strain increment at the corresponding characteristic points, and then substitute them into the model; The residual stress prediction module is used to input the current process conditions into the characteristic parameter-phase transformation strain increment coupling model to obtain the phase transformation strain increment under the current process conditions; and to substitute the phase transformation strain increment into the thermo-mechanical-phase transformation coupling model to predict the residual stress under the current process conditions.

[0015] The solutions of the embodiments of the present invention have the following beneficial effects: The hot-rolled strip residual stress prediction method and system based on the finite element model provided in this invention constructs a finite element model of the strip and its three-dimensional unsteady heat transfer equation based on historical production data of the laminar cooling process of the current production line and the physical property parameters of the corresponding strip. The heat transfer equation is solved to obtain the temperature field distribution. A thermo-mechanical-phase change coupled model based on the finite element model is then constructed. Feature points are selected in the finite element model, and the thermo-mechanical history data of these feature points is extracted from the solved temperature field distribution. Based on the thermo-mechanical-phase change coupled model, the thermo-mechanical history data is... The data used is the microstructure evolution history data of characteristic points solved for boundary conditions, and the phase transformation strain increment at the corresponding characteristic points is calculated. Simultaneously, using the final rolled strip temperature, cooling temperature, and fluid rate as characteristic parameters, a coupled model of characteristic parameters and phase transformation strain increment is constructed, and the model parameters are solved by fitting historical production data and corresponding phase transformation strain increments. Finally, the current process conditions are input into the coupled model of characteristic parameters and phase transformation strain increment to obtain the phase transformation strain increment under the current process conditions. The phase transformation strain increment is then inverted and substituted into the thermo-mechanical-phase transformation coupled model to predict the residual stress under the current process conditions. When performing residual stress reduction, the predicted residual stress under all process conditions is compared, and the process condition corresponding to the minimum residual stress is selected as the optimal one. This invention fully leverages the full-parameter capabilities of the finite element model. By constructing a thermo-mechanical-phase transformation coupled model within the finite element model, process parameters are transferred to the final phase transformation strain increment calculation. Then, relying on the calculation of the finite element model, the relationship between characteristic parameters and strain increment is fitted, and this mapping relationship is fed back into the calculation of residual stress. This amplifies and fully reflects the influence of characteristic parameters on residual stress, fully explores the relationship between data, improves the accuracy of residual stress calculation, and optimizes the residual stress reduction scheme.

[0016] Of course, implementing any product or method of the present invention does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method for predicting residual stress in hot-rolled strip steel based on the finite element model, as described in an embodiment of the present invention. Detailed Implementation

[0019] After discovering the aforementioned problems, the inventors of this application conducted a detailed study on the existing residual stress prediction process for hot-rolled strip steel. The study found that during the laminar cooling stage, the uneven distribution of fluid velocity along the width direction significantly leads to spatial and temporal differences in phase transformation behavior. This is a key factor inducing uneven volume changes and microstructural transformation in the strip steel product, playing a dominant role in the final formation of macroscopic residual stress. The main factors involved in the laminar cooling stage include parameters such as the final rolled strip temperature, strip speed, cooling temperature, and fluid velocity, as well as the relationships between these parameters. These parameters are directly related to the austenite-to-martensite phase transformation, grain nucleation and growth behavior, and phase transformation plasticity in the strip steel. By constructing a direct correlation function between characteristic parameters and microstructure, and then inversely correcting the temperature field data obtained from the macroscopic finite element model, the influence of characteristic parameters on residual stress can be more accurately reflected, thus improving the accuracy of prediction.

[0020] It should be noted that the defects in the above-mentioned prior art solutions are all the result of the inventors' practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed by the embodiments of the present invention in the following text should be the inventors' contributions to the present invention.

[0021] The technical solutions of 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 a part of the embodiments of the present invention, and not all of them. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can also be combined with each other.

[0022] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In the description of this invention, the terms "first," "second," "third," "fourth," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0023] Based on the above in-depth analysis, this invention provides a method and system for predicting residual stress in hot-rolled strip steel based on a finite element model. A finite element model of the strip steel is established based on the process parameters of laminar cooling. The temperature field of the strip steel entering the laminar cooling process after hot rolling is simulated from a macroscopic perspective. Based on the thermo-mechanical coupling relationship of the finite element model, the temperature-stress field is solved. Then, a stress-microstructure coupling model is constructed, and the relationship parameters of the stress-microstructure coupling model are determined according to the solved temperature-stress field. Finally, a characteristic parameter-microstructure coupling model is established, and the parameters of the characteristic parameter-microstructure coupling model are solved based on experimental data. When predicting residual stress, the residual stress solved in the macroscopic temperature field is corrected using the microstructure parameters solved by the characteristic parameters, thereby obtaining a residual stress value close to the actual production value. The optimal process parameters are then selected based on the predicted residual stress value.

[0024] like Figure 1 As shown in the embodiment of the present invention, a method for predicting residual stress in hot-rolled strip steel based on a finite element model includes the following steps: Step S1: Obtain historical production data of the laminar flow cooling process of the current production line, as well as the physical property parameters of the corresponding strip steel produced.

[0025] In this step, the historical production data includes strip composition, final rolled strip dimensions, final rolled strip temperature, cooling temperature, and fluid rate; the physical properties of the strip include thermal conductivity, specific heat, density, etc.

[0026] Step S2: Construct a finite element model of the strip and a three-dimensional unsteady heat transfer equation of the strip finite element model based on the final rolled strip dimensions, and solve the heat transfer equation to obtain the temperature field distribution.

[0027] In this step, the geometric finite element model of the strip steel mainly achieves cooling through convective heat transfer during the laminar cooling stage. In order to calculate the temperature field, stress field, and phase transition field at each node by arranging the temperature fields solved by the heat transfer model, the following assumptions are made: The final rolled strip is uniform, and rolling abnormalities are not considered. The strip steel is used as a flat plate, and unsteady heat transfer is carried out under the action of cooling water; The heat transfer boundary conditions of thermal radiation and thermal convection are transformed into a comprehensive heat transfer coefficient. The thermal deformation of the upper and lower surfaces of the strip and the changes in thermal properties caused by the thermal deformation are ignored. The ambient air temperature remains constant during the cooling process of the strip steel.

[0028] Preferably, in this embodiment, the Nusselt number is used to define the heat transfer parameters, and the formula is: (1) In equation (1), Represents the Nusel number, Representing the Grashof number, The Prandtl number represents the boundary layer fluid. This represents the heat transfer coefficient of the strip cooling surface. Indicates the characteristic length. Expressed as the thermal conductivity of the boundary layer fluid, C , n It is a constant. The overall heat transfer coefficient in the boundary conditions can be obtained using the above formula.

[0029] Based on the above assumptions, the three-dimensional unsteady heat conduction partial differential governing equation in the rectangular coordinate system is: (2)

[0030] In equation (2), Density, unit: kg / m³ 3 ; T Temperature, unit: K ; Specific heat, expressed in J / (kg·K); is the thermal conductivity, with units of W / (m·K); For heat source items, there is no heat source for the strip steel during the laminar flow cooling stage. =0.

[0031] In a Cartesian coordinate system, the side lengths of the grid in the three directions are Δ x Δ y Δ z The heat transfer at different locations is handled by the finite difference method. The internal nodes meet the first type of boundary conditions, while the boundary line nodes and boundary surface nodes meet the third type of boundary conditions. Based on the boundary conditions and locations, a three-dimensional unsteady heat transfer equation including internal nodes, boundary line nodes, and boundary surface nodes is constructed, thereby constructing a closed heat transfer equation and solving it to obtain the temperature field distribution.

[0032] The three-dimensional unsteady-state heat transfer equations for the finite element model of the strip are as follows: Internal node A: (3) Boundary line node B: (4) Boundary surface node C: (5) In equations (3)-(5), and They represent x The direction and the temperature values ​​at the two corresponding neighboring nodes of internal node A; and They represent y The direction and the temperature values ​​at the two corresponding neighboring nodes of internal node A; and They represent z The direction and the temperature values ​​at the two corresponding neighboring nodes of internal node A; This indicates that nodes A, B, and C pass through Δ t Temperature change over time.

[0033] Solving the three solutions simultaneously yields the temperature field distribution.

[0034] Step S3: Construct a thermo-mechanical-phase change coupled model based on the finite element model.

[0035] In this step, when constructing the thermo-mechanical-phase transformation coupling model, the phase transformation volume fraction of the transformation from austenite to other microstructures is calculated based on the lever principle.

[0036] The lever principle formula is as follows: (6) In equation (6), This indicates the volume fraction of austenite. Indicates the austenitizing initiation temperature. Indicates the temperature at which complete austenitization occurs. T This indicates the real-time temperature.

[0037] The transformations of austenite to ferrite, pearlite, bainite, and martensite are calculated using their respective classical models. For example, the transformation from austenite to ferrite uses the classical JMAK equation, while the transformation from austenite to martensite uses the classical KM equation or a modified KM equation.

[0038] Step S4: Select feature points in the finite element model and extract the thermo-mechanical history data of the feature points from the solved temperature field distribution; based on the thermo-mechanical-phase transition coupling model, use the thermo-mechanical history data as boundary conditions to solve the microstructure evolution history data of the feature points, and calculate the phase transition strain increment at the corresponding feature points.

[0039] In this step, the microstructure evolution data includes austenite grain size changes, martensite transformation points, and martensite volume fraction evolution. The phase transformation strain increment includes phase transformation volumetric strain and phase transformation-induced plastic strain. Specifically, this can be achieved by writing Python or MATLAB scripts to automatically read the finite element model output file (such as ODB or VTK format), extract the required data, and convert it to standard text or HDF5 format for subsequent calculations.

[0040] The selection of the feature points includes at least two edge regions and a middle region in the strip width direction.

[0041] The thermo-mechanical history data includes temperature-time history data (Tt) and stress-time history data (σ-t).

[0042] Step S5: Using the final strip temperature, cooling temperature, and fluid rate as characteristic parameters, construct a characteristic parameter-phase transformation strain increment coupling model.

[0043] In this step, the characteristic parameter-phase transformation strain increment coupling model is as follows: (7) In equation (7), T C , T E , v c These represent the cooling temperature, the final strip temperature, and the fluid rate, respectively. This represents the increase in strain during phase transition. This is the incremental adjustment constant. , , and These are the phase change strain increment coefficients. The historical production data and the corresponding phase change strain increments are substituted into formula (7) for fitting to obtain the phase change strain increment coefficients. and β The exponent is a power-law exponent, which is specified empirically or solved as a fitting parameter during the fitting process. i Indicates the first i 1 feature point.

[0044] This step involves constructing a coupled model of characteristic parameters and phase transformation strain increments. In the solution process of the thermo-mechanical-phase transformation coupled model based on the finite element model, the influence of all elements on residual stress is reflected. In this model, the influence of three characteristic parameters—final rolling strip temperature, cooling temperature, and fluid rate—on laminar cooling of the strip is further enhanced, thereby obtaining a more accurate relationship between process parameters and residual stress and improving the accuracy and precision of prediction.

[0045] Step S6: Based on historical production data and the phase transformation strain increment at the corresponding feature point, fit and solve the parameters of the feature parameter-phase transformation strain increment coupling model, and substitute them into the model.

[0046] In this step, characteristic parameter values ​​from historical production data are obtained and combined with the corresponding phase transformation strain increments to form an array. This array is then substituted into the model's equations for fitting, ultimately yielding the unknown parameters of the characteristic parameter-phase transformation strain increment coupled model. These unknown parameters include... , , and and incremental adjustment constant For the power exponent, it can be specified according to empirical formulas or obtained through fitting during simulation. When performing exponential fitting, corresponding algorithmic formulas or software can also be used.

[0047] Step S7: Input the current process conditions into the characteristic parameter-phase transformation strain increment coupling model to obtain the phase transformation strain increment under the current process conditions.

[0048] Step S8: Substitute the phase transformation strain increment inversion into the thermo-mechanical-phase transformation coupled model to predict the residual stress under the current process conditions.

[0049] When performing residual stress reduction, the process conditions corresponding to the minimum residual stress are selected as the preferred conditions by comparing the predicted residual stress under all process conditions.

[0050] Based on the same idea, this invention also provides a residual stress prediction system for hot-rolled strip steel based on a finite element model. The system includes: a data acquisition module, a heat transfer equation construction module, a temperature field distribution solution module, a thermo-mechanical-phase transformation coupled model construction module, a phase transformation strain increment solution module, a characteristic parameter-phase transformation strain increment coupled model construction module, a fitting solution module, and a residual stress prediction module; wherein... The data acquisition module is used to acquire historical production data of the laminar flow cooling process of the current production line, as well as the physical property parameters of the corresponding strip steel produced. The heat transfer equation construction module is used to construct the finite element model of the strip and the three-dimensional unsteady heat transfer equation of the strip finite element model based on the final rolled strip size. The temperature field distribution solution module is used to solve the heat transfer equation to obtain the temperature field distribution; The thermo-mechanical-phase transition coupling model construction module is used to construct a thermo-mechanical-phase transition coupling model based on the finite element model; The phase transformation strain increment solution module is used to select feature points in the finite element model and extract the thermo-mechanical history data of the feature points from the solved temperature field distribution; based on the thermo-mechanical-phase transformation coupled model, the microstructure evolution history data of the feature points is solved using the thermo-mechanical history data as boundary conditions, and the phase transformation strain increment at the corresponding feature points is calculated. The characteristic parameter-phase transformation strain incremental coupling model construction module is used to construct a characteristic parameter-phase transformation strain incremental coupling model using the final rolled strip temperature, cooling temperature and fluid rate as characteristic parameters. The fitting and solving module is used to fit and solve the parameters of the characteristic parameter-phase transformation strain increment coupled model based on historical production data and the phase transformation strain increment at the corresponding characteristic points, and then substitute them into the model; The residual stress prediction module is used to input the current process conditions into the characteristic parameter-phase transformation strain increment coupling model to obtain the phase transformation strain increment under the current process conditions; and to substitute the phase transformation strain increment into the thermo-mechanical-phase transformation coupling model to predict the residual stress under the current process conditions.

[0051] In this embodiment, each module is implemented using a processor, with additional memory added as needed for storage. The processor can be, but is not limited to, a microprocessor (MPU), a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), other programmable logic devices, discrete gates, transistor logic devices, discrete hardware components, etc. The memory can include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory can also be at least one storage device located remotely from the aforementioned processor.

[0052] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0053] It should also be noted that the hot-rolled strip residual stress prediction system based on the finite element model described in this embodiment corresponds to the hot-rolled strip residual stress prediction method based on the finite element model. The description and limitations of the method also apply to the system, and will not be repeated here.

[0054] As can be seen from the above technical solutions, this invention fully utilizes the full-parameter function of the finite element model. By constructing a thermo-mechanical-phase transformation coupled model in the finite element model, the process parameters are transferred to the final phase transformation strain increment calculation. Then, relying on the calculation of the finite element model, the relationship between characteristic parameters and strain increment is fitted, and this mapping relationship is fed back to the calculation of residual stress. This amplifies and fully reflects the influence of characteristic parameters on residual stress, fully explores the relationship between data, improves the accuracy of residual stress calculation, and optimizes the residual stress reduction scheme.

[0055] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed, and is not intended to limit the scope of the claimed invention, but merely to illustrate preferred embodiments of the invention. Those skilled in the art should understand that the scope of the invention is not limited to the specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A method for predicting residual stress in hot-rolled strip steel based on a finite element model, characterized in that, The method includes the following steps: Step S1: Obtain historical production data of the current production line's laminar flow cooling process, as well as the physical property parameters of the corresponding strip steel produced; Step S2: Construct a finite element model of the strip and a three-dimensional unsteady heat transfer equation of the strip finite element model based on the final rolled strip dimensions, and solve the heat transfer equation to obtain the temperature field distribution. Step S3: Construct a thermo-mechanical-phase transition coupled model based on the finite element model; Step S4: Select feature points in the finite element model and extract the thermo-mechanical history data of the feature points from the solved temperature field distribution; Based on the thermo-mechanical-phase transition coupling model, the microstructure evolution process data of feature points are solved using thermo-mechanical history data as boundary conditions, and the phase transition strain increment at the corresponding feature points is calculated. Step S5: Using the final strip temperature, cooling temperature, and fluid rate as characteristic parameters, construct a characteristic parameter-phase transformation strain incremental coupling model; the characteristic parameter-phase transformation strain incremental coupling model is as follows: (7) In equation (7), T C T E v c These represent the cooling temperature, the final strip temperature, and the fluid rate, respectively. This represents the increase in strain during phase transition. This is the incremental adjustment constant. , , and These are the phase transformation strain increment coefficients, α and β are power exponents, and i represents the i-th characteristic point; Step S6: Based on historical production data and the phase transformation strain increment at the corresponding feature point, fit and solve the parameters of the feature parameter-phase transformation strain increment coupling model, and substitute them into the model; Step S7: Input the current process conditions into the characteristic parameter-phase transformation strain increment coupling model to obtain the phase transformation strain increment under the current process conditions; Step S8: Substitute the phase transformation strain increment inversion into the thermo-mechanical-phase transformation coupled model to predict the residual stress under the current process conditions.

2. The method according to claim 1, characterized in that, In step S1, the historical production data includes strip composition, final rolled strip size, final rolled strip temperature, cooling temperature, and fluid rate; the physical properties of the strip include thermal conductivity, specific heat, and density.

3. The method according to claim 1, characterized in that, In step S2, the Nusselt number is used to define the heat transfer parameters of the three-dimensional unsteady heat transfer equation, and the formula is as follows: (1) In equation (1), Represents the Nusel number, Representing the Grashof number, The Prandtl number represents the boundary layer fluid. This represents the heat transfer coefficient of the strip cooling surface. Indicates the characteristic length. It is expressed as the thermal conductivity of the boundary layer fluid, where C and n are constants.

4. The method according to claim 3, characterized in that, The three-dimensional unsteady-state heat transfer equations for the finite element model of the strip are as follows: Internal node A: (3) Boundary line node B: (4) Boundary surface node C: (5) In equations (3)-(5), and These represent the temperature values ​​at two adjacent nodes of the internal node A in the x-direction; and These represent the temperature values ​​at two adjacent nodes of the internal node A in the y-direction; and These represent the temperature values ​​at two adjacent nodes of the internal node A in the z-direction; This represents the temperature change values ​​of nodes A, B, and C after a time interval Δt. Density, unit: kg / m³ 3 T represents temperature, in Kelvin (K). Specific heat, expressed in J / (kg·K); is the thermal conductivity, with units of W / (m·K).

5. The method according to claim 1, characterized in that, When constructing the thermo-mechanical-phase transformation coupled model in step S3, the phase transformation volume fraction of the transformation from austenite to other microstructures is calculated based on the lever principle.

6. The method according to claim 5, characterized in that, The lever principle formula is as follows: (6) In equation (6), This indicates the volume fraction of austenite. Indicates the austenitizing initiation temperature. The temperature at which the austenitization is complete is represented, and T represents the real-time temperature.

7. The method according to claim 1, characterized in that, The phase transformation strain increment mentioned in step S4 includes phase transformation volumetric strain and phase transformation-induced plastic strain.

8. The method according to claim 1, characterized in that, The thermo-mechanical history data includes temperature-time history data and stress-time history data.

9. A system for implementing the method for predicting residual stress in hot-rolled strip steel as described in any one of claims 1-8, characterized in that, The system includes: a data acquisition module, a heat transfer equation construction module, a temperature field distribution solution module, a thermo-mechanical-phase transition coupled model construction module, a phase transition strain increment solution module, a characteristic parameter-phase transition strain increment coupled model construction module, a fitting solution module, and a residual stress prediction module; wherein... The data acquisition module is used to acquire historical production data of the laminar flow cooling process of the current production line, as well as the physical property parameters of the corresponding strip steel produced. The heat transfer equation construction module is used to construct the finite element model of the strip and the three-dimensional unsteady heat transfer equation of the strip finite element model based on the final rolled strip size. The temperature field distribution solution module is used to solve the heat transfer equation to obtain the temperature field distribution; The thermo-mechanical-phase transition coupling model construction module is used to construct a thermo-mechanical-phase transition coupling model based on the finite element model; The phase transformation strain increment solution module is used to select feature points in the finite element model and extract the thermo-mechanical history data of the feature points from the solved temperature field distribution; based on the thermo-mechanical-phase transformation coupled model, the microstructure evolution history data of the feature points is solved using the thermo-mechanical history data as boundary conditions, and the phase transformation strain increment at the corresponding feature points is calculated. The characteristic parameter-phase transformation strain incremental coupling model construction module is used to construct a characteristic parameter-phase transformation strain incremental coupling model using the final rolled strip temperature, cooling temperature, and fluid rate as characteristic parameters; the characteristic parameter-phase transformation strain incremental coupling model is as follows: (7) In equation (7), T C T E v c These represent the cooling temperature, the final strip temperature, and the fluid rate, respectively. This represents the increase in strain during phase transition. This is the incremental adjustment constant. , , and These are the phase transformation strain increment coefficients, α and β are power exponents, and i represents the i-th characteristic point; The fitting and solving module is used to fit and solve the parameters of the characteristic parameter-phase transformation strain increment coupled model based on historical production data and the phase transformation strain increment at the corresponding characteristic points, and then substitute them into the model; The residual stress prediction module is used to input the current process conditions into the characteristic parameter-phase transformation strain increment coupling model to obtain the phase transformation strain increment under the current process conditions; and to substitute the phase transformation strain increment into the thermo-mechanical-phase transformation coupling model to predict the residual stress under the current process conditions.

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