Fatigue performance evaluation method and system of orthotropic steel bridge deck U rib

Abstract

The invention provides a fatigue performance evaluation method and system for a U rib of an orthotropic steel bridge deck slab, and relates to the technical field of U rib fatigue performance evaluation, and the method comprises the steps: constructing a U rib model, setting a load and environmental parameter working condition combination, simulating residual stress evolution, and screening out main control parameters; a residual stress change coefficient theoretical equation is constructed, and a final formula is obtained through processing; the main control parameters are combined, the welding process without cyclic load is simulated, and initial values of the characteristic parameters are extracted; finding out the most unfavorable combination, simulating stress evolution under the action of the most unfavorable combination, extracting a final value, comparing the final value with an initial value to obtain a variable quantity, generating a fatigue comprehensive index, and comparing the fatigue comprehensive index with a preset threshold value to evaluate the fatigue performance of the U rib. The method disclosed by the invention reveals a core mechanism that residual stress, load and environmental factors cooperatively change the stress state of the U rib, provides a solid theoretical support for evaluation of the fatigue performance of the U rib, accurately quantifies the influence of main control parameters on the fatigue performance of the U rib, and remarkably improves the evaluation result of the fatigue performance.

Description

Technical Field

[0001] The present invention relates to the technical field of U-rib fatigue performance evaluation, and in particular to a fatigue performance evaluation method and system for U-ribs of orthotropic steel bridge decks. Background Art

[0002] Orthotropic steel decks (OSDs) are widely used in steel bridges due to their light weight, high strength, and ease of construction and fabrication. Among various fatigue diseases in OSDs, fatigue cracks occur most frequently in the welds between the faceplate and the U-ribs. Considering that the residual stresses in the OSD faceplate-U-rib welds approach or even exceed the material's yield limit, the stresses generated by external loads are superimposed on the residual stresses within the component, and this superposition effect alters the stress distribution within the component. During service, the wheel loads borne by OSDs exhibit significant randomness in terms of operating position and load amplitude. Therefore, the superposition effect of residual stress and external loads is also highly random. Therefore, it is essential to understand the interaction mechanism between residual stress and external loads and to accurately understand the local stress state of the welds under the superposition of residual stress and external loads.

[0003] In the prior art, publication number CN118133606A provides a fatigue performance evaluation method for steel bridge decks after U-rib internal welding reinforcement, which includes the following steps: obtaining a fatigue load spectrum of an actual bridge, and using finite element crack propagation simulation on the structural details of the longitudinal ribs and top plate to obtain the stress history of each important fatigue failure mode; using the rain flow counting method or the water discharge method to process the stress history and obtain the fatigue damage accumulation of each important fatigue failure mode; determining the design parameters of the structural details of the longitudinal ribs and top plate, and designing and conducting steel bridge deck fatigue tests based on the stress characteristics of the fatigue-prone details. The actual fatigue resistance of the structural system under each important fatigue failure model is obtained; welding process tests are carried out on the structural details after U-rib internal welding reinforcement, and a theoretical analysis model of defect degradation effect is established using metallographic analysis. Combined with the fatigue damage accumulation of each important fatigue failure mode and the actual fatigue resistance of the structural system, the fatigue resistance degradation effect of microcracks after U-rib internal welding reinforcement on each important fatigue failure mode is quantified; the evaluation standards of finite element calculation, fatigue test and welding process test are unified, and the cumulative damage degree is used as an indicator to evaluate the fatigue resistance and remaining life of the structural system after U-rib internal welding reinforcement.

[0004] However, there are still the following deficiencies. As can be seen from the above statements, on the one hand, the existing technology only studies the influence of fatigue load or welding process on U-rib fatigue in isolation, and does not consider the coupling effect of residual stress, load amplitude, and ambient temperature (such as the relaxation effect of cyclic load on residual stress under high temperature environment). As a result, it is impossible to quantify the stress redistribution mechanism under the synergistic effect of the three, and there is a deviation between the evaluation model and the actual service status; on the other hand, the existing technology relies on single finite element simulation or test data, lacks data-driven iterative optimization of theoretical models, and it is difficult to accurately quantify the nonlinear influence of parameters such as load cycle number and temperature on residual stress attenuation, resulting in inaccurate evaluation results.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] The object of the present invention is to provide a fatigue performance evaluation method and system for U-ribs of orthotropic steel bridge decks to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions: A fatigue performance evaluation method for U-ribs of orthotropic steel bridge decks is provided, comprising the following steps: S1. Construct a U-rib model, set the load and environmental parameter ranges and gradients to form a working condition combination, simulate the residual stress evolution under each working condition, record the simulation data of the weld at each time, extract the load and environmental parameter matrix and residual stress decay rate, and use the Pearson coefficient to select the number of load cycles, cyclic load amplitude, and ambient temperature as the main control parameters; S2. Fit the main control parameters to construct a theoretical equation for the residual stress variation coefficient, divide the set into training and test sets, use the training set to fit the equation parameters to obtain a preliminary empirical formula, and then iteratively optimize the test set to obtain the final formula; S3. Combine the master control parameters to form a master control parameter combination, input the final formula to calculate the residual stress variation coefficient, simulate the U-rib welding process without cyclic loading using a thermo-elastic-plastic finite element model, and extract the initial value of the weld residual stress characteristic parameter; S4. Traverse the parameter combinations to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient. Input the thermo-elasto-plastic finite element model to simulate the evolution of weld residual stress under cyclic load and ambient temperature. Extract the final value of the characteristic parameter and compare it with the initial value to obtain the variation. Process the variation with the residual stress variation coefficient corresponding to the most unfavorable combination to generate a fatigue comprehensive index. Compare it with the preset threshold to evaluate the fatigue performance status of the U-rib.

[0008] Furthermore, the simulation data includes stress peak, stress gradient, residual stress evolution curve, and temperature field distribution data; the load parameters include the number of load cycles, cyclic load amplitude, and stress ratio; the environmental parameters include ambient temperature, ambient humidity, and ambient pH; and the characteristic parameters include the maximum residual stress value of the weld, the center point residual stress, and the average residual stress.

[0009] Furthermore, the specific steps of S2 are as follows: Clearly take the number of load cycles, cyclic load amplitude, and ambient temperature as input variables, and the residual stress variation coefficient as output variable to form a one-to-one corresponding sample data. The sample data is ,in, Respectively The number of load cycles, cyclic load amplitude, ambient temperature, and residual stress variation coefficient of each sample are is the index of the sample, is the number of samples; The sample data set is divided into training set and test set in a ratio of 7:3; Define basic function library: including addition, subtraction, multiplication, division, exponent, logarithm, power function, trigonometric function and variables; Using the particle swarm optimization algorithm, we randomly combine basic functions and variables to generate a large number of candidate expressions; The fitness is used to measure the degree of fit between the candidate equation and the training set data, where a higher fitness means a smaller fitting error; Retain candidate equations with high fitness and eliminate equations with low fitness; Perform function term crossover and random mutation on the retained candidate equations to generate a new generation of candidate equations, and stop the iteration when the preset number of iterations is reached; The data in the test set are input into the candidate equation after selection, crossover and mutation to calculate the prediction error. The mean square error is used as the loss function. For multiple sets of candidate equations, the equation with the smallest error in the test set is selected as the final formula of the residual stress variation coefficient. The final formula for the residual stress variation coefficient is: ; in, is the residual stress variation coefficient; Where, 、 、 are the number of load cycles, cyclic load amplitude, and ambient temperature, respectively. 、 、 are the weight coefficients of load cycle number, cyclic load amplitude and ambient temperature respectively. On this basis, .

[0010] Furthermore, the specific steps of S3 are as follows: Combine the main control parameters to form a main control parameter combination, and build a main control parameter data set based on the main control parameter combination ,in, Respectively The number of load cycles, cyclic load amplitude, and ambient temperature of the main control parameter combination are is the index of the main control parameter combination, is the number of master control parameter combinations; For each combination of main control parameters, the thermoelastic finite element model is used to simulate the U-rib welding process without cyclic load and calculate the The initial residual stress distribution of the weld corresponding to the main control parameter combination ,in Weld Axis coordinates, Axis coordinates, axis coordinates; Extract the initial values ​​of the maximum residual stress value, center point residual stress, and average residual stress of the weld from the initial residual stress distribution; ; in, For the The initial value of the maximum residual stress of the weld corresponding to the main control parameter combination; ; in, For the The initial value of residual stress at the center of the weld corresponding to the main control parameter combination is: The center point of the weld Axis coordinates, Axis coordinates, axis coordinates; ; in, For the The average initial residual stress value of the weld corresponding to the main control parameter combination is is the total volume of the weld.

[0011] Furthermore, the final value of the characteristic parameter is compared with the initial value to calculate the change in the characteristic parameter according to the following formula: ; ; ; in, 、 、 are the changes in the maximum residual stress, center point residual stress, and average residual stress of the weld, respectively. is the final value of the maximum residual stress of the weld corresponding to the most unfavorable combination, is the final value of the residual stress at the center of the weld corresponding to the most unfavorable combination, is the final value of the average residual stress of the weld corresponding to the most unfavorable combination, is the initial value of the maximum residual stress of the weld corresponding to the most unfavorable combination, is the initial value of residual stress at the center of the weld corresponding to the most unfavorable combination, is the initial value of the average residual stress of the weld corresponding to the most unfavorable combination; The variation of characteristic parameters and the residual stress variation coefficient corresponding to the most unfavorable combination are processed to generate the fatigue comprehensive index based on the following formula: ; ; ; ; in, 、 、 They are the first fatigue comprehensive index, the second fatigue comprehensive index, and the third fatigue comprehensive index. is the residual stress variation coefficient corresponding to the most unfavorable combination, that is, the maximum value of the residual stress variation coefficient, is the residual stress variation coefficient corresponding to the most unfavorable combination.

[0012] Furthermore, the fatigue comprehensive index is compared with the preset threshold to evaluate the fatigue performance status of the U-rib. The specific steps are as follows: When all fatigue comprehensive indices are less than or equal to the preset threshold, that is, and and When , the fatigue performance of the U rib is excellent; When at least one fatigue comprehensive index is greater than the preset threshold, or or When , the fatigue performance of the U rib is poor; in, 、 、 They are the thresholds of the first fatigue comprehensive index, the second fatigue comprehensive index, and the third fatigue comprehensive index respectively.

[0013] A fatigue performance evaluation system for U-ribs of orthotropic steel bridge decks, the system being used to execute any of the above-mentioned fatigue performance evaluation methods for U-ribs of orthotropic steel bridge decks, comprising: The simulation module is used to build the U-rib model, set the load and environmental parameter ranges and gradients to form working condition combinations, simulate the residual stress evolution under various working conditions, record the simulation data of the weld at each moment, extract the load and environmental parameter matrix and residual stress decay rate, and select the number of load cycles, cyclic load amplitude, and ambient temperature as the main control parameters through the Pearson coefficient; The fitting module is used to fit the main control parameters to construct the theoretical equation of the residual stress variation coefficient, divide the training set into a training set and a test set, use the training set to fit the equation parameters to obtain a preliminary empirical formula, and then obtain the final formula through iterative optimization of the test set; The feature extraction module is used to combine the main control parameters to form a main control parameter combination, input the final formula to calculate the residual stress variation coefficient, simulate the U-rib welding process without cyclic loading through the thermo-elastic finite element model, and extract the initial value of the weld residual stress characteristic parameter; The data evaluation module is used to traverse the parameter combinations to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient, input the thermo-elasto-plastic finite element model to simulate the evolution of weld residual stress under cyclic load and ambient temperature, extract the final value of the characteristic parameter, compare it with the initial value to obtain the change, and process the change with the residual stress variation coefficient corresponding to the most unfavorable combination to generate a fatigue comprehensive index, which is compared with the preset threshold to evaluate the fatigue performance status of the U-rib.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention constructs a U-rib model, simulates the residual stress evolution process with load and environmental parameters as variables, records the simulation data of the weld at each moment, extracts the parameter matrix and residual stress decay rate of the working condition combination, selects the main control parameters through the Pearson coefficient, fits the main control parameters, constructs a theoretical equation for the residual stress variation coefficient, and obtains its final formula after optimization. This reveals the core mechanism by which residual stress, load and environmental factors synergistically change the stress state of the U-rib, overcomes the defect of the existing technical evaluation lacking a theoretical basis, and provides a solid theoretical support for the fatigue performance evaluation of the U-rib. By inputting the main control parameter combination into the final formula of the residual stress variation coefficient, the residual stress variation coefficient is calculated, the U-rib welding is simulated through the fatigue damage model, the initial value of the characteristic parameter of the weld residual stress is extracted, the main control parameter combination is traversed, and the main control parameter combination corresponding to the maximum value of the residual stress variation coefficient is found. The change of the characteristic parameter is obtained, and the change of the characteristic parameter and the residual stress variation coefficient corresponding to the most unfavorable combination are processed to generate a fatigue comprehensive index. The fatigue comprehensive index is compared with the preset threshold to evaluate the fatigue performance status of the U-rib. The deep integration of theoretical derivation and data mining is achieved, the influence of the main control parameters on the fatigue performance of the U-rib is comprehensively and accurately quantified, and the fatigue performance evaluation results are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the overall method flow of the present invention; Figure 2 It is a block diagram of the module composition of the present invention; Figure 3 Schematic diagram of the fitting of the load cycle number and the residual stress variation coefficient of the present invention; Figure 4 Schematic diagram of the fitting of the cyclic load amplitude and the residual stress variation coefficient of the present invention; Figure 5 Schematic diagram of the fitting of the ambient temperature and the residual stress variation coefficient of the present invention. DETAILED DESCRIPTION

[0016] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0018] Example 1: See also Figures 1 to 5 , the present invention provides a technical solution: A fatigue performance evaluation method for U-ribs of orthotropic steel bridge decks is provided, comprising the following steps: S1. Construct a U-rib model based on the cyclic plastic constitutive model. Set the load and environmental parameter ranges and gradients to form a combination of working conditions. Simulate the residual stress evolution under each working condition. Record the simulation data of the weld at each time. Extract the load and environmental parameter matrix and residual stress decay rate. Use the Pearson coefficient to select the number of load cycles, cyclic load amplitude, and ambient temperature as the main control parameters. Based on the above embodiment, the simulation data includes stress peak value, stress gradient, residual stress evolution curve, and temperature field distribution data; the load parameters include the number of load cycles, cyclic load amplitude, and stress ratio; and the environmental parameters include ambient temperature, ambient humidity, and ambient pH. On this basis, it should be noted that: Simulation data, load parameters, and environmental parameters must all be normalized, and subsequent data processing and analysis will all be based on normalized data.

[0019] On the basis of the above embodiment, a U-rib model is constructed based on the cyclic plastic constitutive method. The specific steps are as follows: Based on the actual engineering dimensions of the U-rib of the orthotropic steel bridge deck, the cross-sectional parameters of the U-rib, including height, thickness, web slope, cover plate thickness, and weld geometry, are determined. The weld geometry includes weld leg dimensions and groove angle. A cyclic plastic constitutive theory model suitable for fatigue analysis of steel structures should be selected. This model should include kinematic hardening and isotropic hardening parameters to reflect the plastic accumulation, Bauschinger effect, and stress amplitude attenuation characteristics of the material under cyclic loading. Based on the steel grade of the U-rib and cover plate, basic mechanical parameters such as elastic modulus and Poisson's ratio are input; combined with material cyclic test data, key parameters in the cyclic plastic constitutive model are determined, including yield strength, cyclic hardening coefficient, and saturated plastic strain amplitude; The geometric model was meshed, with a focus on improving the mesh accuracy of welds and stress concentration areas. Based on the actual stress state of the U-rib in the steel bridge deck, constraint boundary conditions were set, including fixing the displacement of the cover plate edge and restricting the rotation of the U-rib end, to simulate its connection with the overall structure. By applying monotonic tensile load or simple cyclic load, the stress-strain curve of the model is calculated and compared with the material test data. The constitutive parameters are adjusted until the deviation between the simulation results and the test results is within the allowable range.

[0020] On the basis of the above embodiment, the load and environmental parameter ranges and gradient forming working condition combinations are set, the residual stress evolution under each working condition is simulated, and the simulation data of the weld part at each moment is recorded. The specific steps are as follows: The load type focuses on cyclic loads, which are used to simulate vehicle loads; Load cycle number: Based on the design life of the bridge and the average daily traffic volume, Second, divided into 5-8 levels according to the logarithmic gradient; Cyclic load amplitude: Refer to the actual vehicle load standard value (such as 100-500kN), and divide it into 4-6 levels according to the arithmetic gradient (such as 100kN, 200kN...); Stress ratio: Based on the load distribution characteristics of the bridge deck, take 0.1-0.5 and divide the gradient into 0.1 intervals; According to the bridge service environment, key environmental parameters are selected: Ambient temperature: covers the extreme temperature difference in the project area (e.g. -30°C to 60°C), divided into 8-10 levels at 10°C intervals; Ambient humidity: Considering atmospheric humidity fluctuations (e.g. 30%-90%), the humidity is divided into four levels at 20% intervals; Environmental pH: simulates industrial environment or acid rain impact, takes 4.0-8.0, divided into 5 levels at intervals of 1.0; The orthogonal test method is used to reduce the test volume and select representative combinations from the gradient of load and environmental parameters to ensure uniform coverage of each parameter level; Each working condition includes a set of load parameters (number of load cycles + cyclic load amplitude + stress ratio) and a set of environmental parameters (ambient temperature + ambient humidity + ambient pH), forming a complete working condition matrix; The combined working condition parameters are input into the U-rib model, and numerical simulation is performed for each working condition combination. During the simulation, the evolution of the residual stress in the U-rib weld under the combined effects of cyclic loading and environmental factors is calculated. Simultaneously, the simulation data at each moment is recorded in real time: Stress peak and location; stress gradient, which is the rate of change of stress along the length of the weld; Residual stress evolution curve with time; Temperature field distribution data, that is, the instantaneous temperature values ​​of the weld and surrounding areas.

[0021] Based on the above embodiment, the parameter matrix and residual stress decay rate are extracted from the simulation data of the weld at each moment, and the number of load cycles, cyclic load amplitude and ambient temperature are selected as the main control parameters through the Pearson coefficient. The specific steps are as follows: For each combination of working conditions, the specific values ​​of load and environmental parameters are sorted out from the recorded simulation data to form a structured parameter matrix. Each row of the matrix corresponds to a set of working conditions, and the columns contain the number of load cycles (such as times), cyclic load amplitude (e.g., 100kN), stress ratio (e.g., 0.1), ambient temperature (e.g., -30°C), ambient humidity (e.g., 30%), and ambient pH (e.g., 4.0). Ensure that the parameter values ​​correspond to the working condition combinations and fully reflect the input conditions of the test group; From the residual stress evolution curve of the weld, extract the residual stress value at the initial moment (before cyclic loading) and the residual stress value at each moment. Calculate the attenuation rate for each working condition using the formula "Residual stress attenuation rate = (Residual stress value at the initial moment - Residual stress value at each moment) / Residual stress value at the initial moment × 100%." ​​If there are multiple monitoring points, take the average of the attenuation rates of each point as the representative attenuation rate for that working condition to quantify the degree of residual stress attenuation with cyclic loading and environmental effects. The six parameters in the parameter matrix (number of load cycles, cyclic load amplitude, stress ratio, ambient temperature, ambient humidity, and ambient pH) are used as independent variables, and the corresponding residual stress decay rate is used as the dependent variable. The Pearson correlation coefficient r between each independent variable and the dependent variable is calculated. The closer the absolute value of the coefficient r is to 1, the stronger the correlation between the parameter and the residual stress decay; the closer it is to 0, the weaker the correlation. Compare the absolute values ​​of the Pearson coefficients of the six parameters, sort them from large to small, and select the top three with absolute values ​​of coefficients ≥ The parameters, namely the number of load cycles, cyclic load amplitude and ambient temperature, are determined as the main control parameters, among which, is the preset Pearson coefficient threshold.

[0022] S2. Fit the main control parameters to construct a theoretical equation for the residual stress variation coefficient, divide the set into training and test sets, use the training set to fit the equation parameters to obtain a preliminary empirical formula, and then iteratively optimize the test set to obtain the final formula; Based on the above embodiment, the specific steps of S2 are as follows: Clearly take the number of load cycles, cyclic load amplitude, and ambient temperature as input variables, and the residual stress variation coefficient as output variable to form a one-to-one corresponding sample data. The sample data is ,in, Respectively The number of load cycles, cyclic load amplitude, ambient temperature, and residual stress variation coefficient of each sample are is the index of the sample, is the number of samples; The sample data set is divided into training set and test set in a ratio of 7:3; Define basic function library: including addition, subtraction, multiplication, division, exponent, logarithm, power function, trigonometric function and variables; Using the particle swarm optimization algorithm, we randomly combine basic functions and variables to generate a large number of candidate expressions; The fitness is used to measure the degree of fit between the candidate equation and the training set data, where a higher fitness means a smaller fitting error; Retain candidate equations with high fitness and eliminate equations with low fitness; Perform function term crossover and random mutation on the retained candidate equations to generate a new generation of candidate equations, and stop the iteration when the preset number of iterations is reached; The data in the test set are input into the candidate equation after selection, crossover and mutation to calculate the prediction error. The mean square error is used as the loss function. For multiple sets of candidate equations, the equation with the smallest error in the test set is selected as the final formula of the residual stress variation coefficient. Table 1. Variation of residual stress coefficient with load cycle number, cyclic load amplitude, and ambient temperature

[0023] According to Table 1, the residual stress variation coefficient shows a significant positive correlation with the number of load cycles, cyclic load amplitude, and ambient temperature, as shown in the following: As the number of load cycles increases from 200 to 10,000, the cyclic load amplitude increases from 10 to 50, and the ambient temperature rises from 0°C to 40°C, the residual stress variation coefficient gradually increases from 6 to 56.5, showing an overall continuous upward trend; The synergistic effect of the three factors causes the residual stress variation coefficient to increase significantly with the increase of each parameter, reflecting that the more load cycles, the larger the load amplitude, and the higher the ambient temperature, the more obvious the residual stress attenuation of the U-rib weld, the more serious the degradation of the material fatigue performance, and the higher the risk of fatigue failure.

[0024] according to Figure 3-Figure 5 As can be seen, the black squares represent the "residual stress variation coefficient" data points, and the black straight line is the fitted line between the corresponding parameters and the residual stress variation coefficient, indicating that all three parameters are significantly positively correlated with the residual stress variation coefficient. The higher the number of load cycles, the cyclic load amplitude, and the ambient temperature, the greater the residual stress variation coefficient, the more significant the residual stress attenuation in the U-rib weld, and the higher the fatigue performance degradation and fatigue failure risk of the material.

[0025] Based on the above examples, the final formula for the residual stress variation coefficient is: ; in, is the residual stress variation coefficient. The residual stress variation coefficient is used to evaluate the degree of residual stress degradation of the U-rib weld under cyclic load and environmental conditions by combining three index parameters: the number of load cycles, the cyclic load amplitude, and the ambient temperature. The larger the residual stress variation coefficient, the more significant the residual stress attenuation of the U-rib weld under the corresponding load and environmental conditions, the more serious the fatigue performance degradation of the material, and the higher the risk of fatigue failure. Where, 、 、 are the number of load cycles, cyclic load amplitude, and ambient temperature respectively; On this basis, it should be noted that: The number of load cycles refers to the total number of cyclic loads a U-rib weld experiences during service. Essentially, this is the accumulation of material fatigue damage through repeated stress. From a physical perspective, each load cycle causes tiny plastic deformation within the weld. As the number of cycles increases, this plastic deformation accumulates, leading to an increase in the dislocation density within the material, which in turn triggers the cyclic softening effect. This effect involves the material's ability to resist deformation decreasing with increasing cycles, making it difficult for the residual stress originally generated by welding to maintain a stable state. Instead, the residual stress exhibits a trend of continuous release. This attenuation increases with the accumulation of cycles, directly leading to an increase in the residual stress variation coefficient. The cyclic load amplitude refers to the maximum load variation within each cycle. Its core function is to determine the damage depth of a single cycle through the magnitude of the stress amplitude. As the amplitude increases, the alternating stress amplitude experienced by the weld increases. When the amplitude exceeds the fatigue limit of the material, it accelerates the initiation and expansion of internal microscopic defects. These defects, acting as stress concentration points, disrupt the equilibrium state of residual stress, prompting stress redistribution to the defective area and accelerating the relaxation of residual stress. Therefore, the larger the cyclic load amplitude, the faster the residual stress decays, and the residual stress variation coefficient increases accordingly.

[0026] Ambient temperature refers to the temperature of the U-rib's service environment, which affects the stability of residual stress through the coupling of thermal and mechanical stresses. Based on the principle of thermoelasticity, rising temperature intensifies the thermal motion of steel atoms, reducing the material's yield strength and weakening its ability to maintain residual stress. At the same time, the superposition of thermal stresses generated by thermal expansion and contraction with load stress increases the total stress level in the weld, further promoting dislocation motion and microdefect expansion, and accelerating the release of residual stress. Therefore, as the ambient temperature rises, the residual stress decay process is intensified, leading to an increase in the residual stress variation coefficient.

[0027] Therefore, the residual stress variation coefficient is positively correlated with the number of load cycles, cyclic load amplitude, and ambient temperature.

[0028] From the perspective of physical mechanism, although the effects of load cycles, cyclic load amplitude, and ambient temperature on residual stress are coupled, the core is to act on the residual stress attenuation process through independent paths: the number of cycles dominates the "accumulated damage amount", the cyclic load amplitude dominates the "single damage intensity", and the temperature dominates the "degree of material performance weakening". The linear function is calculated through the weight coefficient 、 、 Quantifying the contributions of the three parameters separately reflects the independent influence of each parameter and reflects the total effect of multiple factors in an additive form, which is consistent with the fatigue theory logic that "damage accumulation is additive"; In the previous article, three linear parameters (number of load cycles, cyclic load amplitude, and ambient temperature) that are strongly correlated with residual stress decay were screened out through the Pearson coefficient, indicating that the basic relationship between the three and the residual stress variation coefficient is closer to a linear correlation.

[0029] Therefore, the above-mentioned function form is used to express the functional relationship between the residual stress variation coefficient and the number of load cycles, cyclic load amplitude, and ambient temperature.

[0030] Where, 、 、 are the weight coefficients of load cycle number, cyclic load amplitude, and ambient temperature respectively; The amplitude of the cyclic load directly determines the magnitude of the alternating stress amplitude borne by the weld, and is the core factor that triggers the initiation and expansion of material micro-defects. When the amplitude exceeds the fatigue limit of the material, a single cycle can cause significant residual stress relaxation, and its effect on the attenuation of residual stress is "strength-dominated" - even if the number of cycles is small, high-amplitude loads can still rapidly aggravate the degradation of residual stress. Therefore, As a coefficient to quantify this "high-intensity damage", it is usually taken to be the largest value.

[0031] The number of load cycles affects the attenuation of residual stress through a cumulative effect, and its effect depends on "number superposition": when the amplitude does not exceed the fatigue limit, it takes a sufficient number of cycles to significantly attenuate the residual stress; when the amplitude is high, the cumulative effect of the number will be amplified. However, compared with the "single strong impact" of the amplitude, the influence of the number of cycles is more inclined to "gradual accumulation", so its weight coefficient Less than , but it is greater than the influence of ambient temperature.

[0032] Ambient temperature affects residual stress indirectly mainly by weakening material properties. Its effect can only be manifested by coupling with load. The effect of simple temperature change (without load) on residual stress is weak. Even under load, the effect of temperature is more of an "auxiliary strengthening" rather than a "dominant trigger". Therefore, its independent contribution to the attenuation of residual stress is the lowest, and the weight coefficient is Minimum.

[0033] Therefore, in On this basis, .

[0034] As an implementation method, The value range is 0.3-0.4, The value range is 0.4-0.6, The value range is 0.1-0.2. The specific value is set by technical personnel according to actual conditions and is not limited here.

[0035] S3. Combine the master control parameters to form a master control parameter combination, input the final formula to calculate the residual stress variation coefficient, simulate the U-rib welding process without cyclic loading using a thermo-elastic-plastic finite element model, and extract the initial value of the weld residual stress characteristic parameter; Based on the above embodiment, the specific steps of S3 are as follows: Combine the main control parameters to form a main control parameter combination, and construct a main control parameter data set based on the main control parameter combination ,in, Respectively The number of load cycles, cyclic load amplitude, and ambient temperature of the main control parameter combination are is the index of the main control parameter combination, is the number of master control parameter combinations; For each combination of main control parameters, the thermoelastic finite element model is used to simulate the U-rib welding process without cyclic loading. The purpose is to eliminate the subsequent load and environmental interference and obtain the initial residual stress distribution of the weld caused by the welding process itself. The welding process will produce inherent residual stress due to uneven cooling from high temperature. This is the "original state" for evaluating fatigue performance. The subsequent cyclic load and ambient temperature changes need to be calculated based on this initial state. For the The initial residual stress distribution of the weld corresponding to the main control parameter combination is: Weld Axis coordinates, Axis coordinates, axis coordinates; The initial values ​​of the maximum residual stress, center point residual stress, and average residual stress of the weld are extracted from the initial residual stress distribution. The maximum residual stress reflects the initial stress level at the stress concentration point of the weld, which is the key location where fatigue cracks are prone to initiation. The geometric center of the weld is selected as a representative monitoring point to obtain the center point residual stress. The center point residual stress reflects the average initial state of the core area of ​​the weld. The overall stress mean is calculated by volume integration as the average residual stress. The average residual stress reflects the macroscopic distribution characteristics of the residual stress in the weld. ; in, For the The initial value of the maximum residual stress of the weld corresponding to the main control parameter combination; ; in, For the The initial value of residual stress at the center of the weld corresponding to the main control parameter combination is: The center point of the weld Axis coordinates, Axis coordinates, axis coordinates; ; in, For the The average initial residual stress value of the weld corresponding to the main control parameter combination is is the total volume of the weld; The formula is obtained by triple integral , the stress values ​​of each point in the three-dimensional space are accumulated, which is essentially to calculate the "total effect" of the residual stress in the weld volume, and then divided by the total volume of the weld , and the average stress value per unit volume is obtained, that is, the initial value of the average residual stress at the macro level.

[0036] S4. Traverse the parameter combinations to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient. Input the thermo-elasto-plastic finite element model to simulate the evolution of weld residual stress under cyclic load and ambient temperature. Extract the final value of the characteristic parameter and compare it with the initial value to obtain the variation. Process the variation with the residual stress variation coefficient corresponding to the most unfavorable combination to generate a fatigue comprehensive index. Compare it with the preset threshold to evaluate the fatigue performance status of the U-rib.

[0037] Based on the above embodiment, the parameter combinations are traversed to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient. The thermoelastic finite element model is input to simulate the evolution of weld residual stress under cyclic load and ambient temperature, and the final value of the characteristic parameter is extracted. The specific steps are as follows: Traverse the master parameter data set , substitute each combination into the final formula of residual stress variation coefficient and calculate the corresponding , filter out the combination with the largest residual stress variation coefficient , defined as the most unfavorable combination - this combination represents the load and environmental conditions that have the most significant impact on residual stress degradation; The most unfavorable combination parameters are input into the thermo-elasto-plastic finite element model, and the boundary conditions and loading system are set: the number of cyclic loads, the cyclic load amplitude, and the ambient temperature are respectively , simulate the dynamic evolution of weld residual stress under the coupling effect of the two, and record the residual stress distribution at the end of the evolution , The end time of the cycle; From the final residual stress distribution Extract the maximum residual stress value , center point residual stress , the final value of the average residual stress .

[0038] Based on the above embodiment, the final value of the characteristic parameter is compared with the initial value to calculate the change in the characteristic parameter, according to the following formula: ; ; ; in, 、 、 are the changes in the maximum residual stress, center point residual stress, and average residual stress of the weld, respectively. is the final value of the maximum residual stress of the weld corresponding to the most unfavorable combination, is the final value of the residual stress at the center of the weld corresponding to the most unfavorable combination, is the final value of the average residual stress of the weld corresponding to the most unfavorable combination, is the initial value of the maximum residual stress of the weld corresponding to the most unfavorable combination, is the initial value of residual stress at the center of the weld corresponding to the most unfavorable combination, is the initial value of the average residual stress of the weld corresponding to the most unfavorable combination; The variation of characteristic parameters and the residual stress variation coefficient corresponding to the most unfavorable combination are processed to generate the fatigue comprehensive index based on the following formula: ; ; ; ; in, 、 、 They are the first fatigue comprehensive index, the second fatigue comprehensive index, and the third fatigue comprehensive index. is the residual stress variation coefficient corresponding to the most unfavorable combination, that is, the maximum value of the residual stress variation coefficient, is the residual stress variation coefficient corresponding to the most unfavorable combination; The first fatigue comprehensive index is used to evaluate the fatigue damage degree of the stress concentration part of the weld by combining the change of the maximum residual stress of the weld and the maximum value of the residual stress variation coefficient. The larger the first fatigue comprehensive index is, the more significant the residual stress change at the stress concentration part of the weld is under the most unfavorable combination of action, the more serious the fatigue damage at this part is, and the higher the risk of fatigue failure. The second fatigue comprehensive index is used to evaluate the fatigue damage degree of the core area of ​​the weld by combining the two index parameters: the change in residual stress at the center point of the weld and the maximum value of the residual stress variation coefficient. The larger the second fatigue comprehensive index, the more obvious the change in residual stress in the core area of ​​the weld under the most unfavorable combined influence, the more prominent the fatigue performance degradation in this area, and the greater the possibility of fatigue failure. The third fatigue comprehensive index is used to evaluate the fatigue damage degree of the entire weld by combining two indicator parameters: the change in the average residual stress of the weld and the maximum value of the residual stress variation coefficient. The larger the third fatigue comprehensive index, the more significant the change in the overall residual stress distribution of the weld under the most unfavorable combination. The greater the decline in the fatigue performance of the overall structure, the higher the risk of overall fatigue problems.

[0039] On this basis, it should be noted that: The maximum value of the residual stress variation coefficient corresponding to the most unfavorable combination is used as the "quantitative benchmark of the most unfavorable conditions". The variation of the characteristic parameters is compared with this benchmark. The fatigue comprehensive index obtained is essentially the "relative quantitative value of the actual stress change under the most unfavorable conditions". If the variation of characteristic parameters is smaller, it means that the residual stress state of the U-rib weld under extreme conditions is more stable and the ability to resist external adverse factors is stronger, that is, the fatigue performance of the U-rib is better; conversely, the fatigue performance of the U-rib is worse; Therefore, in the formula of the first fatigue comprehensive index, the change in the maximum residual stress of the weld is used as the numerator, and the maximum value of the residual stress variation coefficient is used as the denominator.

[0040] In the formula of the second fatigue comprehensive index, the change in residual stress at the center point of the weld is used as the numerator, and the maximum value of the residual stress variation coefficient is used as the denominator.

[0041] In the formula of the third fatigue comprehensive index, the change in the average residual stress of the weld is used as the numerator, and the maximum value of the residual stress variation coefficient is used as the denominator.

[0042] Based on the above embodiment, the fatigue comprehensive index is compared with a preset threshold value to evaluate the fatigue performance status of the U rib. The specific steps are as follows: When all fatigue comprehensive indices are less than or equal to the preset threshold, that is, and and When , the fatigue performance of the U rib is excellent; When at least one fatigue comprehensive index is greater than the preset threshold, or or When , the fatigue performance of the U rib is poor; in, 、 、 They are the threshold values ​​of the first fatigue comprehensive index, the second fatigue comprehensive index, and the third fatigue comprehensive index respectively; For the threshold value of the first fatigue comprehensive index: Fatigue tests on U-rib welds were carried out, and the maximum residual stress changes and the corresponding maximum residual stress variation coefficients under different cycle numbers were recorded. The comprehensive fatigue index under each state was calculated. The "first appearance of macro cracks" was used as the failure judgment criterion, and the index distribution range at the time of failure was statistically analyzed. The lower limit of the distribution was taken as the threshold to ensure that the threshold had a failure warning accuracy of more than 95%.

[0043] For the threshold value of the second fatigue comprehensive index: When conducting fatigue tests on U-rib welds, the focus is on the residual stress changes in the core area (center point) of the weld. The changes in residual stress at the center point are recorded for different numbers of cycles. The second fatigue comprehensive index is calculated based on the maximum value of the corresponding residual stress variation coefficient. The "first appearance of macrocracks" is used as the failure criterion, and the distribution characteristics of the second fatigue comprehensive index for all failure cases are statistically analyzed. For example, if 85% of the failure cases in the test occurred when the second fatigue comprehensive index was greater than 0.65, it means that the failure risk increases significantly after this index exceeds 0.65. Therefore, the second threshold can be initially set at 0.65.

[0044] For the threshold value of the third fatigue comprehensive index: The test focused on the average residual stress change across the weld and calculated the third fatigue composite index at different cycle stages, again using the first appearance of macrocracks as the failure criterion. If statistics show that the third fatigue composite index exceeds 0.75 in 90% of failure cases, indicating that the overall structure has entered a high-risk state, the third threshold can be tentatively set at 0.75.

[0045] See also Figure 2 , the present invention also provides a technical solution: A fatigue performance evaluation system for U-ribs of orthotropic steel bridge decks, the system being used to execute any of the above-mentioned fatigue performance evaluation methods for U-ribs of orthotropic steel bridge decks, comprising: The simulation module is used to build the U-rib model, set the load and environmental parameter ranges and gradients to form working condition combinations, simulate the residual stress evolution under various working conditions, record the simulation data of the weld at each moment, extract the load and environmental parameter matrix and residual stress decay rate, and select the number of load cycles, cyclic load amplitude, and ambient temperature as the main control parameters through the Pearson coefficient; The fitting module is used to fit the main control parameters to construct the theoretical equation of the residual stress variation coefficient, divide the training set into a training set and a test set, use the training set to fit the equation parameters to obtain a preliminary empirical formula, and then obtain the final formula through iterative optimization of the test set; The feature extraction module is used to combine the main control parameters to form a main control parameter combination, input the final formula to calculate the residual stress variation coefficient, simulate the U-rib welding process without cyclic loading through the thermo-elastic finite element model, and extract the initial value of the weld residual stress characteristic parameter; The data evaluation module is used to traverse the parameter combinations to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient, input the thermo-elasto-plastic finite element model to simulate the evolution of weld residual stress under cyclic load and ambient temperature, extract the final value of the characteristic parameter, compare it with the initial value to obtain the change, and process the change with the residual stress variation coefficient corresponding to the most unfavorable combination to generate a fatigue comprehensive index, which is compared with the preset threshold to evaluate the fatigue performance status of the U-rib.

[0046] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0047] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by computer software, electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0048] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0049] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A fatigue performance evaluation method for U-ribs of orthotropic steel bridge decks, characterized in that: The specific steps include: S1. Construct a U-rib model, set the load and environmental parameter ranges and gradients to form a working condition combination, simulate the residual stress evolution under each working condition, record the simulation data of the weld at each time, extract the load and environmental parameter matrix and residual stress decay rate, and use the Pearson coefficient to select the number of load cycles, cyclic load amplitude, and ambient temperature as the main control parameters; S2. Fit the main control parameters to construct a theoretical equation for the residual stress variation coefficient, divide the set into training and test sets, use the training set to fit the equation parameters to obtain a preliminary empirical formula, and then iteratively optimize the test set to obtain the final formula; S3. Combine the master control parameters to form a master control parameter combination, input the final formula to calculate the residual stress variation coefficient, simulate the U-rib welding process without cyclic loading using a thermo-elastic-plastic finite element model, and extract the initial value of the weld residual stress characteristic parameter; S4. Traverse the parameter combinations to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient. Input the thermo-elasto-plastic finite element model to simulate the evolution of weld residual stress under cyclic load and ambient temperature. Extract the final value of the characteristic parameter and compare it with the initial value to obtain the variation. Process the variation with the residual stress variation coefficient corresponding to the most unfavorable combination to generate a fatigue comprehensive index. Compare it with the preset threshold to evaluate the fatigue performance status of the U-rib.

2. The fatigue performance evaluation method of U-rib of orthotropic steel bridge deck according to claim 1, characterized in that: The simulation data includes stress peak, stress gradient, residual stress evolution curve, and temperature field distribution data; the load parameters include the number of load cycles, cyclic load amplitude, and stress ratio; the environmental parameters include ambient temperature, ambient humidity, and ambient pH; and the characteristic parameters include the maximum residual stress value of the weld, the center point residual stress, and the average residual stress.

3. The fatigue performance evaluation method of U-rib of orthotropic steel bridge deck according to claim 2, characterized in that: The specific steps of S2 are as follows: The number of load cycles, cyclic load amplitude, and ambient temperature are used as input variables, and the residual stress variation coefficient is used as the output variable to form a one-to-one corresponding sample data. The sample data is ,in, Respectively The number of load cycles, cyclic load amplitude, ambient temperature, and residual stress variation coefficient of each sample are is the index of the sample, is the number of samples; The sample data set is divided into training set and test set in a ratio of 7:3; Define basic function library: including addition, subtraction, multiplication, division, exponent, logarithm, power function, trigonometric function and variables; Using the particle swarm optimization algorithm, we randomly combine basic functions and variables to generate a large number of candidate expressions; The fitness is used to measure the degree of fit between the candidate equation and the training set data, where a higher fitness means a smaller fitting error; Retain candidate equations with high fitness and eliminate equations with low fitness; Perform function term crossover and random mutation on the retained candidate equations to generate a new generation of candidate equations, and stop the iteration when the preset number of iterations is reached; The data in the test set are input into the candidate equation after selection, crossover and mutation to calculate the prediction error. The mean square error is used as the loss function. For multiple sets of candidate equations, the equation with the smallest error in the test set is selected as the final formula of the residual stress variation coefficient. The final formula for the residual stress variation coefficient is: ； in, is the residual stress variation coefficient; Where, 、 、 are the number of load cycles, cyclic load amplitude, and ambient temperature, respectively. 、 、 are the weight coefficients of load cycle number, cyclic load amplitude and ambient temperature respectively. On this basis, .

4. The fatigue performance evaluation method of U-rib of orthotropic steel bridge deck according to claim 3 is characterized in that: The specific steps of S3 are as follows: Combine the main control parameters to form a main control parameter combination, and build a main control parameter data set based on the main control parameter combination ,in, Respectively The number of load cycles, cyclic load amplitude, and ambient temperature of the main control parameter combination are is the index of the main control parameter combination, is the number of master control parameter combinations; For each combination of main control parameters, the thermoelastic finite element model is used to simulate the U-rib welding process without cyclic load and calculate the The initial residual stress distribution of the weld corresponding to the main control parameter combination ,in Weld Axis coordinates, Axis coordinates, axis coordinates; Extract the initial values ​​of the maximum residual stress value, center point residual stress, and average residual stress of the weld from the initial residual stress distribution; ； in, For the The initial value of the maximum residual stress of the weld corresponding to the main control parameter combination; ； in, For the The initial value of residual stress at the center of the weld corresponding to the main control parameter combination is: The center point of the weld Axis coordinates, Axis coordinates, axis coordinates; ； in, For the The average initial residual stress value of the weld corresponding to the main control parameter combination is is the total volume of the weld.

5. The fatigue performance evaluation method of U-rib of orthotropic steel bridge deck according to claim 4, characterized in that: The final value of the characteristic parameter is compared with the initial value to calculate the change in the characteristic parameter. The formula is as follows: ； ； ； in, 、 、 are the changes in the maximum residual stress, center point residual stress, and average residual stress of the weld, respectively. is the final value of the maximum residual stress of the weld corresponding to the most unfavorable combination, is the final value of the residual stress at the center of the weld corresponding to the most unfavorable combination, is the final value of the average residual stress of the weld corresponding to the most unfavorable combination, is the initial value of the maximum residual stress of the weld corresponding to the most unfavorable combination, is the initial value of residual stress at the center of the weld corresponding to the most unfavorable combination, is the initial value of the average residual stress of the weld corresponding to the most unfavorable combination; The variation of characteristic parameters and the residual stress variation coefficient corresponding to the most unfavorable combination are processed to generate the fatigue comprehensive index based on the following formula: ； ； ； ； in, 、 、 They are the first fatigue comprehensive index, the second fatigue comprehensive index, and the third fatigue comprehensive index. is the residual stress variation coefficient corresponding to the most unfavorable combination, that is, the maximum value of the residual stress variation coefficient, is the residual stress variation coefficient corresponding to the most unfavorable combination.

6. The fatigue performance evaluation method of U-rib of orthotropic steel bridge deck according to claim 5, characterized in that: The fatigue comprehensive index is compared with the preset threshold to evaluate the fatigue performance status of the U-rib. The specific steps are as follows: When all fatigue comprehensive indices are less than or equal to the preset threshold, that is, and and When , the fatigue performance of the U rib is excellent; When at least one fatigue comprehensive index is greater than the preset threshold, or or When , the fatigue performance of the U rib is poor; in, 、 、 They are the thresholds of the first fatigue comprehensive index, the second fatigue comprehensive index, and the third fatigue comprehensive index respectively.

7. A fatigue performance evaluation system for U-ribs of orthotropic steel bridge decks, the system being used to execute the fatigue performance evaluation method for U-ribs of orthotropic steel bridge decks according to any one of claims 1 to 6, characterized in that: include: The simulation module is used to build the U-rib model, set the load and environmental parameter ranges and gradients to form working condition combinations, simulate the residual stress evolution under various working conditions, record the simulation data of the weld at each moment, extract the load and environmental parameter matrix and residual stress decay rate, and select the number of load cycles, cyclic load amplitude, and ambient temperature as the main control parameters through the Pearson coefficient; The fitting module is used to fit the main control parameters to construct the theoretical equation of the residual stress variation coefficient, divide the training set into a training set and a test set, use the training set to fit the equation parameters to obtain a preliminary empirical formula, and then obtain the final formula through iterative optimization of the test set; The feature extraction module is used to combine the main control parameters to form a main control parameter combination, input the final formula to calculate the residual stress variation coefficient, simulate the U-rib welding process without cyclic loading through the thermo-elastic finite element model, and extract the initial value of the weld residual stress characteristic parameter; The data evaluation module is used to traverse the parameter combinations to find the most unfavorable combination corresponding to the maximum value of the residual stress variation coefficient, input the thermo-elasto-plastic finite element model to simulate the evolution of weld residual stress under cyclic load and ambient temperature, extract the final value of the characteristic parameter, compare it with the initial value to obtain the change, and process the change with the residual stress variation coefficient corresponding to the most unfavorable combination to generate a fatigue comprehensive index, which is compared with the preset threshold to evaluate the fatigue performance status of the U-rib.

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