Method and system for determining the rapid propagation threshold of a weld seam crack

Abstract

The embodiment of the application provides a method and system for determining a weld crack rapid expansion threshold, comprising: receiving original data obtained through a plurality of sets of material mechanics tests, wherein the original data contains fracture strain and corresponding stress triaxiality of a target material under different stress states; calling a data fitting algorithm module to process the original data to establish a digital material damage model representing material damage accumulation rules; inputting the digital material damage model as material properties into a finite element simulation calculation module, setting boundary conditions and load steps of simulation, running a simulation program and calculating mechanical response and damage evolution of the material under virtual service conditions; monitoring and judging damage variables of each unit of the material in the calculation process of the simulation program until the damage variable reaches a critical value, triggering a fracture judgment, and outputting a corresponding strain value at this moment as a crack rapid expansion threshold. The application can quantitatively determine the crack rapid expansion threshold.

Description

Technical Field

[0001] This application relates to the technical field of metal material simulation, specifically to a method and system for determining the rapid propagation threshold of weld cracks. Background Technology

[0002] In the production system of a thermal power plant, steam pipelines are the core equipment for transporting high-temperature and high-pressure steam. Their operating environment is extremely harsh—they are subjected to alternating loads of high temperature and high pressure for a long time, and the steam medium may carry impurities that cause corrosion of the inner wall of the pipeline. The connection parts of these pipelines are generally made using welding technology. However, as the bonding area between dissimilar materials (base material and filler metal), the weld seam has a significantly different microstructure and mechanical properties from the base material, making it a weak link in the entire pipeline system.

[0003] Current methods for assessing the lifespan of steam pipe welds in thermal power plants have limitations:

[0004] The shortcomings of traditional testing methods: Existing technologies mostly involve cutting pipe welds to obtain samples and then using a universal testing machine in the laboratory to perform single mechanical property tests such as tensile and bending tests. However, the cutting process destroys the original stress state of the weld, and the sample size and stress conditions cannot reproduce the high temperature, high pressure, and complex stress fields (such as multi-directional tensile and shear combined effects) of the pipeline in actual service, resulting in a large deviation between the test results and the actual working conditions.

[0005] Limitations of operating condition simulation: Some methods simulate high-temperature environments through heating devices, but it is difficult to simultaneously reproduce comprehensive operating conditions such as high pressure and alternating loads, and it is even more impossible to capture the micro-damage evolution process of welds caused by fatigue, creep and corrosion during long-term service.

[0006] Insufficient data acquisition: Traditional testing can only obtain the macroscopic stress-strain curve of the sample, which cannot intuitively present the full-field strain distribution on the weld surface. It is difficult to accurately identify the critical position and propagation trend of crack initiation, resulting in a large error in judging the threshold of rapid crack propagation in the weld.

[0007] Therefore, given the unique service environment of steam pipeline welds in thermal power plants, there is an urgent need for a solution that can simulate actual working conditions, comprehensively capture damage evolution, and quantitatively determine the threshold for rapid crack propagation, in order to ensure the safe operation of the pipeline system and scientifically guide maintenance cycles. Summary of the Invention

[0008] This application proposes a method and system for determining the rapid propagation threshold of weld cracks, in order to overcome the deficiencies of the prior art.

[0009] According to a first aspect of the embodiments of this application, a method for determining the rapid propagation threshold of weld cracks is provided, comprising:

[0010] Receive raw data obtained through multiple sets of material mechanics tests, the raw data including the fracture strain and corresponding stress triaxiality of the target material under different stress states;

[0011] The data fitting algorithm module is invoked to process the raw data in order to establish a digital material damage model that characterizes the cumulative law of material damage.

[0012] The digital material damage model is input into the finite element simulation calculation module as a material property, and the boundary conditions and load steps of the simulation are set. The simulation program is run and the mechanical response and damage evolution of the material under virtual service conditions are calculated.

[0013] The simulation program monitors and judges the damage variables of each material element during the calculation process until the damage variables reach a critical value, triggering a fracture determination and outputting the strain value corresponding to this moment as the crack rapid propagation threshold.

[0014] In some embodiments, the method further includes:

[0015] Identify the test types of the multiple sets of material mechanics tests, and classify the heterogeneous raw data according to their corresponding target stress triaxiality levels based on the test types;

[0016] The categorized raw data is then converted to a standardized data format to generate standardized data of the raw data.

[0017] The test types include tensile tests for obtaining material response under low stress triaxiality, shear tests for obtaining material response under medium stress triaxiality, and tensile tests for obtaining material response under high stress triaxiality.

[0018] In some implementations, the step of calling the data fitting algorithm module to process the raw data to establish a digital material damage model characterizing the cumulative law of material damage includes:

[0019] Based on the reference strain rate and reference temperature conditions, the stress triaxiality data and its corresponding fracture strain data are extracted from the standardized data, and the relationship between the stress triaxiality data and the fracture strain data is constructed.

[0020] A nonlinear regression algorithm is used to fit the relationship between the triaxiality data and the fracture strain data, and the first set of core parameters is obtained to characterize the dependence of the material failure strain on the stress triaxiality data.

[0021] In some implementations, setting the boundary conditions and load steps for the simulation includes:

[0022] The computing device sets the boundary conditions and load steps for the simulation by parsing the input load profile. The load profile includes pressure load data for simulating the internal pressure of the pipe and temperature field data for simulating the temperature gradient.

[0023] In some implementations, before running the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions, the following steps are also included:

[0024] Based on the key dimensional parameters of the input sample, a three-dimensional finite element model containing a V-shaped notch is automatically generated, enabling the simulation program to construct a geometric entity and computational domain for applying boundary conditions, loads, and defining material properties.

[0025] The key dimensional parameters include width, thickness, pin hole spacing, notch angle, and depth.

[0026] In some embodiments, the method further includes:

[0027] According to the preset mesh generation strategy, a dense hexahedral element mesh is automatically generated for the crack region of the three-dimensional finite element model, and the mesh density is controlled to decrease gradually from the crack region to the model boundary.

[0028] In some implementations, running the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions includes:

[0029] The simulation program is executed based on the solver kernel in the computing device and explicit or implicit integration algorithms to calculate the mechanical response and damage evolution of the material under virtual service conditions.

[0030] The simulation program iteratively calculates the element strain, stress, and damage variables for each increment step and updates the simulation program's status in real time.

[0031] In some implementations, after outputting the strain value corresponding to this moment as the crack rapid propagation threshold, the method further includes:

[0032] Based on the computing device's call to the graphics drawing module, a correlation curve is automatically generated with overall strain as the horizontal axis and stress and crack tip opening displacement as the two vertical axes.

[0033] In some embodiments, the method further includes:

[0034] Based on the aforementioned correlation curve, the global maximum value of the stress data is located by the peak-finding algorithm, and the maximum value of the rate of change of the crack tip opening displacement data is located by differential calculation.

[0035] Based on the global maximum point and the maximum rate of change point, the critical value of the crack rapid propagation threshold is determined by machine interpretation.

[0036] According to a second aspect of this application, a system for determining the rapid propagation threshold of weld cracks is provided, comprising:

[0037] The raw data acquisition module is used to receive raw data obtained through multiple sets of material mechanics tests. The raw data includes the fracture strain and corresponding stress triaxiality of the target material under different stress states.

[0038] The material damage model building module is used to call the data fitting algorithm module to process the raw data in order to establish a digital material damage model that characterizes the cumulative law of material damage.

[0039] The simulation calculation module is used to input the digital material damage model as material properties into the finite element simulation calculation module, set the boundary conditions and load steps of the simulation, run the simulation program, and calculate the mechanical response and damage evolution of the material under virtual service conditions.

[0040] The crack threshold confirmation module is used to monitor and determine the damage variables of each material element during the simulation program's calculation process, until the damage variables reach a critical value, triggering a fracture determination, and outputting the strain value corresponding to this moment as the crack rapid propagation threshold.

[0041] The beneficial effects of the method and system for determining the rapid propagation threshold of weld cracks in this application include at least the following:

[0042] This application embodiment receives raw data including stress triaxiality and fracture strain from multiple sets of material mechanics tests, systematically covering the fracture behavior of materials under different stress states, laying a complete data foundation for establishing accurate damage models. By calling data fitting algorithms to process these data to establish a digital material damage model, it achieves a quantitative characterization of the material damage accumulation law, significantly improving the model's accuracy in describing complex stress states. By inputting the established model as an attribute into a finite element simulation module and setting loads and boundary conditions, the simulation can reproduce the material's response process under actual service conditions in a virtual environment, realizing dynamic tracking and visual analysis of damage evolution behavior. By monitoring the damage variables of material elements during the simulation and triggering fracture judgment and outputting strain thresholds when critical values ​​are reached, the critical state of crack instability propagation can be accurately identified, providing key criteria for structural life prediction and safety assessment. In summary, this application embodiment, through a closed-loop technology chain of experimentation, modeling, simulation, and judgment, achieves accurate and reliable prediction of material fracture thresholds, overcoming the limitations of traditional methods such as single-condition simulation and insufficient data acquisition, and providing a systematic solution for life management of critical parts of complex structures. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the method for determining the rapid propagation threshold of weld cracks according to an embodiment of this application.

[0044] Figure 2 This is a schematic diagram illustrating the operation of the digital material damage model in an embodiment of this application;

[0045] Figure 3 This is a diagram showing the sample mesh division effect of an embodiment of this application;

[0046] Figure 4 This is a line graph of stress versus CTOD under overall strain in an embodiment of this application;

[0047] Figure 5 This is a schematic diagram of the structure of the system for determining the rapid propagation threshold of weld cracks according to an embodiment of this application. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0049] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed embodiments of the present application, but merely to illustrate selected embodiments of the present application. Other embodiments obtained by those skilled in the art based on the embodiments of the present application without inventive effort are all within the scope of protection of the embodiments of the present application.

[0050] It can 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 will not be further defined and explained in subsequent figures according to the embodiments of this application.

[0051] This application discloses a method for determining the rapid crack propagation threshold of welds. This method is based on a system for determining the rapid crack propagation threshold of welds. The purpose of this method is to solve the problem of predicting the service life of welds in long-term pipelines, and to obtain the stress and strain fields of the specimen during the process, thereby determining the mechanical properties of the specimen. Furthermore, this method is applicable to the service life prediction of materials after welding, and can obtain a reliable prediction of the service life of the measured weld. (See attached figure.) Figure 1 As shown, the method includes steps 110-140.

[0052] Step 110: Receive the raw data obtained through multiple sets of material mechanics tests.

[0053] In some implementations, the raw data includes the fracture strain and corresponding stress triaxiality of the target material under different stress states.

[0054] In some implementations, the test types of the multiple sets of material mechanics tests are identified, and the heterogeneous raw data are classified according to their corresponding target stress triaxiality levels based on the test type; the classified raw data is then converted to a standardized data format, and standardized data of the raw data is generated.

[0055] For example, the test types include tensile tests for obtaining the material response under low stress triaxiality, shear tests for obtaining the material response under medium stress triaxiality, and tensile tests for obtaining the material response under high stress triaxiality.

[0056] For example, in the embodiments of this application, the sample model size can be selected based on standards and a model can be built using modeling software before the above steps. Specifically, the test and simulation model can be built based on test specifications and standards. Among them, the specifications for key parameters can be, for example, that the sample width (W) is 25 mm, the sample thickness (B) is between W / 2 and W / 4, and the distance between pin holes / 2 (L) is 2W.

[0057] Step 120: Call the data fitting algorithm module to process the raw data in order to establish a digital material damage (Johnson-Cook, JC) model that characterizes the cumulative law of material damage.

[0058] The digital material damage model can cover different stress states (tension, compression, shear) and different strain rates, thereby obtaining the material flow stress parameters (constitutive) and damage evolution parameters (damage) required by the model.

[0059] In some implementations, the data fitting algorithm module is invoked to process the raw data to establish a digital material damage model characterizing the cumulative law of material damage. This includes: extracting stress triaxiality data and its corresponding fracture strain data from the standardized data based on reference strain rate and reference temperature conditions, and constructing the relationship between stress triaxiality data and fracture strain data; using a nonlinear regression algorithm to fit the relationship between the triaxiality data and fracture strain data, and obtaining a first set of core parameters used to characterize the dependence of material failure strain on the stress triaxiality data.

[0060] In one exemplary embodiment, a data fitting algorithm module is invoked to process the raw data and establish a digital material damage model characterizing the cumulative damage law of the material, including: uniaxial tensile test, uniaxial compression test, and shear test. The uniaxial tensile test is used to obtain flow and damage data under tensile stress, the uniaxial compression test is used to obtain flow and damage data under compressive stress, and the shear test is used to obtain flow and damage data under shear stress.

[0061] For example, performing a uniaxial tensile test includes: applying an axial load to a standard tensile specimen, recording the load-displacement curve, converting it into a stress-strain curve, and capturing the strain at fracture.

[0062] For example, preferred conditions for uniaxial tensile testing include: using round bar tensile specimens (or plate specimens) conforming to ASTM E8 standards, with a gauge length diameter of 5 mm / 10 mm. This gauge length is five to ten times the gauge length, and this gauge length diameter range ensures uniform stress distribution within the gauge length, avoids stress concentration at the clamping end, and guarantees that deformation is concentrated within the gauge length. Furthermore, a rounded transition is preferred for the transition section to prevent breakage at the junction of the clamping end and the gauge length. The preferred equipment is an electronic universal testing machine (quasi-static, strain rate 10). -4 ~10 - ²s - ¹) and hydraulic servo testing machine (dynamic, strain rate 10) - ¹~10³s - ¹) Force measurement can be performed using a force sensor built into the testing machine (accuracy ≤0.5%). Deformation measurement can be performed using digital image correlation (DIC) to capture strain across the entire field (including the necking region). Loading control can be achieved using displacement control (e.g., a rate of 0.1~10 mm / min).

[0063] For example, the purpose of uniaxial compression testing is to simulate the deformation behavior of materials under compressive stress, supplementing constitutive and damage parameters under compression and avoiding deviations in tensile data from those under compression. Preferred conditions for uniaxial compression testing include: using short cylindrical compression specimens conforming to ASTM E9 standards, with a diameter of 10mm / 15mm to ensure sufficient specimen stiffness and prevent instability; controlling the aspect ratio to 1.5–2; polishing the upper and lower end faces of the specimen (roughness Ra ≤ 0.8μm) and applying lubricant (such as molybdenum disulfide) to reduce bulging distortion caused by end-face friction; using equipment consistent with tensile testing, such as equipped with an anti-buckling guide device to prevent buckling of specimens with slightly larger aspect ratios; force measurement via a force sensor built into the testing machine; deformation measurement based on DIC capturing radial / axial full-field strain to monitor the degree of bulging distortion; and load control using displacement control (e.g., a rate of 0.05–5mm / min).

[0064] For example, the purpose of a shear test is to simulate the deformation and fracture of a material under pure shear stress, such as when tension and compression are not dominant, the stress state is closer to engineering scenarios like impact and cutting. Preferred conditions for conducting a shear test include: applying torque to a thin-walled circular tube specimen to place the tube wall under pure shear stress (e.g., shear stress dominant, normal stress 0), recording the torque-torsion angle curve, and converting it to a shear stress-shear strain curve. Using a thin-walled circular tube specimen conforming to ASTM D2344 standards, for example, with an outer diameter of 10-20 mm, ensures the tube wall is thin and uniform. Controlling the wall thickness to a ratio greater than ten ensures uniform stress distribution across the tube wall cross-section (approximately pure shear). A gauge length of 3-5 times the outer diameter avoids torque interference at the clamping ends. End face treatment requires machining splines or threads at both ends to match the torsion fixture, ensuring coaxial torque transmission. The equipment used is a torsion testing machine (quasi-static, shear strain rate 10). -4 ~10 - ²s - ¹). Torque measurement is achieved using a torque sensor built into the testing machine (accuracy ≤0.5%). Deformation measurement is achieved by capturing the shear deformation (e.g., full-field shear strain distribution) on the gauge length surface using digital image correlation. Loading control is achieved using quasi-static "torsion angle control" (rate 1~10° / min).

[0065] Step 130: Input the digital material damage model as material properties into the finite element simulation calculation module, set the boundary conditions and load steps for the simulation, run the simulation program, and calculate the mechanical response and damage evolution of the material under virtual service conditions.

[0066] In some implementations, setting the boundary conditions and load steps for the simulation includes setting the boundary conditions and load steps for the simulation based on a computing device by parsing an input load profile, the load profile including pressure load data for simulating the internal pressure of the pipe and temperature field data for simulating the temperature gradient.

[0067] In some implementations, refer to the appendix. Figure 3 As shown, before running the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions, the process also includes: automatically generating a three-dimensional finite element model containing a V-notch based on the key dimensional parameters of the input specimen, so that the simulation program can construct the geometric entity and computational domain for applying boundary conditions, loads and defining material properties.

[0068] For example, the key dimensional parameters include width, thickness, pin hole spacing, notch angle, and depth.

[0069] In some implementations, the method further includes: automatically generating a dense hexahedral element mesh for the crack region of the three-dimensional finite element model according to a preset meshing strategy, and controlling the mesh density to decrease gradually from the crack region to the model boundary.

[0070] In some implementations, running the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions includes: executing the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions based on the solver kernel in the computing device and an explicit or implicit integration algorithm; iteratively calculating the element strain, stress, and damage variables for each increment step, and updating the state of the simulation program in real time.

[0071] For example, simulations using ABAQUS software are used to obtain curves of overall strain and crack strain, thereby identifying the strain value at which cracks surge, i.e., the threshold for rapid crack propagation. For instance, a preferred specimen shape and size with fixed holes, suitable for both testing machines and simulations, is characterized by a spacing of 100mm, a width of 30mm, a thickness of 12.5mm, a transition of 2mm to the connecting section, a 60mm length for the intermediate connecting section, a slot width of 3mm, an angle of 60°, and a depth of 2mm. For example, based on the aforementioned uniaxial tensile, uniaxial compression, and shear tests, the required triaxial stress state data (tension, compression, and shear) for the JC model can be comprehensively covered, ensuring the model's predictive accuracy in complex engineering scenarios.

[0072] Among them, refer to the appendix Figure 2 As shown, the digital material damage model is divided into a constitutive model (Jc constitutive) and a damage model (Jc damage). The constitutive model is used to represent the changes in the plastic stage of the material, while the damage model is used to describe the cumulative law of damage in the material during plastic deformation and to determine the timing of crack propagation.

[0073] For example, the basic formulas for constitutive and damage models are as follows:

[0074] ;

[0075] in, This represents the initial yield stress at the reference strain rate and reference temperature. and These represent the material's strain hardening modulus and hardening index, respectively. This represents the strain rate strengthening parameter of the reference material. Indicates the thermal softening index of the material. This refers to flow stress, which is the stress that a material experiences during plastic deformation. It represents the equivalent plastic strain and is used to measure the degree of plastic deformation in a material; This represents the current strain rate, i.e., the rate at which the material deforms; For reference strain rate, This represents dimensionless temperature. In tensile simulations, the default temperature setting is used, meaning it has no effect on the model.

[0076] For example, dimensionless temperature It can be calculated using the following formula:

[0077]

[0078] in, Indicates the current temperature. Indicates reference temperature. Indicates the melting point of a material. Dimensionless temperature. It is used to reflect the magnitude of the current temperature relative to the material's melting point and a reference temperature.

[0079] For example, when the effects of strain rate and temperature are not considered, i.e., when temperature and strain rate are set to 1, the basic formula of the constitutive model can be simplified to:

[0080] ;

[0081] In this process, material properties can be substituted into the equation to calculate the result. , and The parameters are determined experimentally (e.g., tensile, shear, dynamic tests) to determine constitutive parameters and damage parameters. , , , , and failure criterion parameters ).

[0082] For example, damage models use failure strain The expression describing material failure is as follows:

[0083]

[0084] in, This represents the current actual strain rate. Indicates the reference strain rate. Indicates stress triaxiality, Representing dimensionless temperature, the strain under different stresses and triaxialities obtained from tensile, shear, and tensile tests is calculated. The effects of strain rate and temperature on the damage model are determined by varying the specific working conditions.

[0085] For example, when the strain rate and temperature terms are ignored, i.e., when temperature and strain rate are set to 1, the damage model band can be simplified to:

[0086]

[0087] Among them, different Below Data, fitted using nonlinear regression , , .

[0088] For example, referring to the parameter meanings shown in Table 1 and the triaxial strain reference values ​​for different types of specimens shown in Table 2, strains under three triaxial conditions can be obtained through tensile tests, compression tests, and shear (three-point bending) tests. Substituting these values ​​into the formula yields... arrive First, determine arrive To avoid interference between strain rate and temperature.

[0089] Table 1: Physical meaning and typical value range of the parameters

[0090]

[0091] Table 2: Reference values ​​for triaxial strain of different types of specimens

[0092]

[0093] For example, based on fixed , , (as shown in the following formula) ), in the same Calibration is performed by changing the strain rate at the specified temperature. (Strain rate sensitivity). For example, calibrated by the following formula. :

[0094]

[0095] For example, based on fixing other parameters (as expressed in the following formula) ), in the same Calibration was performed by changing the temperature under the strain rate and strain rate. (Temperature sensitivity). For example, calibrated using the following formula. :

[0096]

[0097] in, Indicates reference temperature. This indicates the current temperature or the test temperature. For example, it can be obtained through linear fitting. and .

[0098] Step 140: Monitor and determine the damage variables of each material element during the simulation program's calculation process until the damage variable reaches a critical value, triggering a fracture determination, and outputting the strain value corresponding to this moment as the crack rapid propagation threshold.

[0099] In some implementations, after outputting the strain value corresponding to this moment as the crack rapid propagation threshold, the method further includes: automatically generating a correlation curve with the overall strain as the horizontal axis and the stress and crack tip opening displacement as the two vertical axes based on the call of the graphics drawing module of the computing device.

[0100] In some implementations, the method further includes: based on the correlation curve, locating the global maximum point of stress data using a peak-finding algorithm, and locating the maximum point of the rate of change of crack tip opening displacement data by calculating differentially; and determining the critical value of the crack rapid propagation threshold based on the global maximum point and the maximum point of the rate of change using machine interpretation.

[0101] In some implementations, the crack tip opening displacement (CTOD) observation point is selected at the point on the 60° edge of the crack tip center point that coincides with the crack wall.

[0102] The physical definition of crack tip opening displacement focuses on the opening behavior of the crack tip. Essentially, it measures the relative displacement of the two surfaces of the crack tip along the crack opening direction under external load. This displacement directly determines whether the crack will propagate unstably. A highly concentrated stress-strain field exists at the crack tip, and the displacement gradient decays rapidly outwards from the tip. Only the region near the tip can accurately reflect this critical deformation state; regions far from the tip are affected by the overall deformation of the specimen. Therefore, it is necessary to avoid stress concentration areas not caused by the crack, such as specimen edges, loading fixture contact points, and pre-fabricated holes. Observation points should be selected near the tip to capture the "local opening displacement" directly related to crack propagation. Simultaneously, by adding auxiliary points outside the core observation points, the influence of overall deformation on local data is calibrated, avoiding distortion of the crack tip opening displacement value calculation due to external interference, thus ensuring that the data is consistent with the physical definition of crack tip opening displacement. The selection of observation points for crack tip opening displacement aims to meet the goal of "accurately and reliably obtaining the true displacement of the crack tip," and is formed by combining material mechanical properties and measurement technology limitations. (See Appendix) Figure 4As shown, this embodiment selects a point on the 60° angle edge of the crack tip center point that coincides with the crack wall as the observation point for crack tip opening displacement. This makes the point closer to the tip and less affected by overall deformation, avoiding inaccurate observations caused by longitudinal displacement of the point due to deformation. For load application, pressure and temperature loads are applied to the pipe wall, selected according to the analysis type and pipe wall geometry. The pressure load is applied to the inner surface of the pipe wall to simulate the internal pressure of the pipe. A temperature load is also applied to simulate the gradient temperature field of the pipe wall, creating a temperature difference between the inner and outer walls. For mesh generation, hexagonal elements C3D8R are used, and the mesh is further subdivided for the crack, with the density gradually decreasing from the crack to the clamping end. For the post-processing curves, a comparison of stress, strain, and crack tip opening displacement is used to explore the relationship between these three factors at different stages of the material, thus locking in the threshold for rapid crack initiation.

[0103] In this embodiment of the application, when a crack has already appeared, the correlation between overall strain, stress, and crack tip opening displacement was found, and the threshold for rapid crack propagation was obtained by using a line graph.

[0104] This application embodiment receives raw data including stress triaxiality and fracture strain from multiple sets of material mechanics tests, systematically covering the fracture behavior of materials under different stress states, laying a complete data foundation for establishing accurate damage models. By calling data fitting algorithms to process these data to establish a digital material damage model, it achieves a quantitative characterization of the material damage accumulation law, significantly improving the model's accuracy in describing complex stress states. By inputting the established model as an attribute into a finite element simulation module and setting loads and boundary conditions, the simulation can reproduce the material's response process under actual service conditions in a virtual environment, realizing dynamic tracking and visual analysis of damage evolution behavior. By monitoring the damage variables of material elements during the simulation and triggering fracture judgment and outputting strain thresholds when critical values ​​are reached, the critical state of crack instability propagation can be accurately identified, providing key criteria for structural life prediction and safety assessment. In summary, this application embodiment, through a closed-loop technology chain of experimentation, modeling, simulation, and judgment, achieves accurate and reliable prediction of material fracture thresholds, overcoming the limitations of traditional methods such as single-condition simulation and insufficient data acquisition, and providing a systematic solution for life management of critical parts of complex structures.

[0105] This application also discloses a system for determining the rapid propagation threshold of weld cracks. (Refer to the attached document.) Figure 5 As shown, the system includes: a raw data acquisition module 510, a material damage model building module 520, a simulation calculation module building module 530, and a crack threshold confirmation module 540.

[0106] For example, the raw data acquisition module 510 is used to receive raw data obtained through multiple sets of material mechanics tests, which includes the fracture strain and corresponding stress triaxiality of the target material under different stress states.

[0107] For example, the material damage model building module 520 is used to call the data fitting algorithm module to process the original data in order to establish a digital material damage model that characterizes the cumulative law of material damage.

[0108] For example, the simulation calculation module building module 530 is used to input the digital material damage model as material properties into the finite element simulation calculation module, to set the boundary conditions and load steps of the simulation, and to run the simulation program and calculate the mechanical response and damage evolution of the material under virtual service conditions.

[0109] For example, the crack threshold confirmation module 540 is used to monitor and determine the damage variables of each element of the material during the simulation program's calculation process, until the damage variable reaches a critical value, triggering a fracture determination, and outputting the strain value corresponding to this moment as the crack rapid propagation threshold.

[0110] This application's embodiments design and execute multiple sets of mechanical tests on the target material, and acquire fracture characteristic data under different stress states based on a system for determining the rapid propagation threshold of weld cracks. For example, uniaxial tensile tests simulate the stress state of the material under low-stress triaxiality (tension-dominated) conditions, recording the strain data of the material throughout the entire process from elastic deformation, plastic yielding to final fracture; shear tests construct a medium-stress triaxiality environment, focusing on capturing the plastic flow and critical fracture strain of the material under shear loads; simultaneously, tensile tests under high-stress triaxiality conditions are supplemented to obtain the fracture strain characteristics of the material under high hydrostatic pressure. Through the above multi-dimensional tests, a complete fracture strain database covering low, medium, and high stress triaxiality ranges is formed. Based on the correlation between stress triaxiality and fracture strain obtained from the tests, this invention further establishes a Johnson-Cook damage model suitable for the target material. Regression analysis of the experimental results is performed using a data fitting algorithm to determine the optimal values ​​of key parameters in the JC damage model. The finally constructed JC damage model quantitatively characterizes the damage accumulation process of the material under complex stress states, laying a core theoretical foundation for the digital modeling of materials. After completing the digital modeling of the material, this invention utilizes finite element simulation technology to perform in-depth analysis of the material properties. By embedding the aforementioned JC damage model into the simulation platform, the mechanical response of the material under different service conditions is simulated, with a focus on tracking the evolution of damage variables: when the damage variables accumulate to a critical value, the material is determined to fracture, and the threshold conditions for rapid crack propagation are extracted. Compared with traditional empirical formulas or single experiments, this simulation process can reproduce the entire process of material from microscopic damage initiation to macroscopic crack propagation, and by adjusting simulation parameters, refined analysis of complex structural details can be achieved. Therefore, the obtained crack propagation threshold has higher accuracy and engineering reference value.

[0111] In summary, the embodiments of this application, through a complete technical chain of "multi-condition testing - damage model construction - digital simulation - life assessment", break through the bottleneck of single stress state and limited assessment accuracy in traditional material performance testing. It is especially suitable for life prediction of key parts such as welds in complex structures, and provides a systematic and efficient solution for the safe service and life management of engineering materials.

[0112] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of this application, and this application is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this application, and these modifications and improvements are also considered to be within the scope of protection of this application.

Claims

1. A method of determining a rapid expansion threshold of a weld crack, characterized by, include: Receive raw data obtained through multiple sets of material mechanics tests, the raw data including the fracture strain and corresponding stress triaxiality of the target material under different stress states; The test types of the multiple sets of material mechanics tests are identified, and the heterogeneous raw data are classified according to their corresponding target stress triaxiality levels based on the test types. The classified raw data is then converted to a standardized data format to generate standardized data of the raw data. The test types include tensile tests for obtaining material response under low stress triaxiality, shear tests for obtaining material response under medium stress triaxiality, and tensile tests for obtaining material response under high stress triaxiality. The data fitting algorithm module is invoked to process the raw data in order to establish a digital material damage model that characterizes the cumulative law of material damage. The digital material damage model is input into the finite element simulation calculation module as a material property, and the boundary conditions and load steps of the simulation are set. The simulation program is run and the mechanical response and damage evolution of the material under virtual service conditions are calculated. The simulation program monitors and judges the damage variables of each material element during the calculation process until the damage variables reach a critical value, triggering a fracture determination and outputting the strain value corresponding to this moment as the crack rapid propagation threshold. Based on the computing device's call to the graphics drawing module, an automatic correlation curve is generated with overall strain as the horizontal axis and stress and crack tip opening displacement as the two vertical axes. Based on the aforementioned correlation curve, the global maximum value of the stress data is located by the peak-finding algorithm, and the maximum value of the rate of change of the crack tip opening displacement data is located by differential calculation. Based on the global maximum point and the maximum rate of change point, the critical value of the crack rapid propagation threshold is determined by machine interpretation.

2. The method of claim 1, wherein, The process of calling the data fitting algorithm module to process the raw data and establish a digital material damage model characterizing the cumulative law of material damage includes: Based on the reference strain rate and reference temperature conditions, the stress triaxiality data and its corresponding fracture strain data are extracted from the standardized data, and the relationship between the stress triaxiality data and the fracture strain data is constructed. A nonlinear regression algorithm is used to fit the relationship between the triaxiality data and the fracture strain data, and the first set of core parameters is obtained to characterize the dependence of the material failure strain on the stress triaxiality data.

3. The method of claim 1, wherein, The setting of boundary conditions and load steps for the simulation includes: The computing device sets the boundary conditions and load steps for the simulation by parsing the input load profile. The load profile includes pressure load data for simulating the internal pressure of the pipe and temperature field data for simulating the temperature gradient.

4. The method of claim 1, wherein, Before running the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions, the following steps are also included: Based on the key dimensional parameters of the input sample, a three-dimensional finite element model containing a V-shaped notch is automatically generated, enabling the simulation program to construct a geometric entity and computational domain for applying boundary conditions, loads, and defining material properties. The key dimensional parameters include width, thickness, pin hole spacing, notch angle, and depth.

5. The method of claim 4, wherein, The method further includes: According to the preset mesh generation strategy, a dense hexahedral element mesh is automatically generated for the crack region of the three-dimensional finite element model, and the mesh density is controlled to decrease gradually from the crack region to the model boundary.

6. The method according to claim 1, characterized in that, The process of running the simulation program and calculating the mechanical response and damage evolution of the material under virtual service conditions includes: The simulation program is executed based on the solver kernel in the computing device and explicit or implicit integration algorithms to calculate the mechanical response and damage evolution of the material under virtual service conditions. The simulation program iteratively calculates the element strain, stress, and damage variables for each increment step and updates the simulation program's status in real time.

7. A system for determining the threshold of rapid crack propagation in welds, characterized in that, include: The raw data acquisition module is used to receive raw data obtained through multiple sets of material mechanics tests. The raw data includes the fracture strain and corresponding stress triaxiality of the target material under different stress states. The test types of the multiple sets of material mechanics tests are identified, and the heterogeneous raw data are classified according to their corresponding target stress triaxiality levels based on the test types. The classified raw data is then converted to a standardized data format to generate standardized data of the raw data. The test types include tensile tests for obtaining material response under low stress triaxiality, shear tests for obtaining material response under medium stress triaxiality, and tensile tests for obtaining material response under high stress triaxiality. The material damage model building module is used to call the data fitting algorithm module to process the raw data in order to establish a digital material damage model that characterizes the cumulative law of material damage. The simulation calculation module is used to input the digital material damage model as material properties into the finite element simulation calculation module, set the boundary conditions and load steps of the simulation, run the simulation program, and calculate the mechanical response and damage evolution of the material under virtual service conditions. The crack threshold confirmation module monitors and judges the damage variables of each material element during the simulation program's calculation process until the damage variables reach a critical value, triggering fracture judgment and outputting the corresponding strain value at this moment as the crack rapid propagation threshold. Based on the computing device's invocation of the graphics drawing module, it automatically generates a correlation curve with overall strain as the horizontal axis and stress and crack tip opening displacement as the two vertical axes. Based on the correlation curve, it locates the global maximum value of stress data using a peak-finding algorithm and the maximum value of the rate of change of crack tip opening displacement data using differential calculation. Based on the global maximum value and the maximum value of the rate of change, and using machine interpretation, it determines the critical value of the crack rapid propagation threshold.

Images