A fatigue life prediction method and system for truss-chord composite beams

Abstract

The present invention provides a fatigue life prediction method and system for a truss-chord composite beam, relating to the field of data processing technology. The method comprises: establishing a finite element model of the connection node between a corrugated steel web and a concrete-filled steel tube chord, and using the corrugated steel web's oblique web inclination angle, curved connection radius, plate thickness, as well as the chord tube diameter, steel tube wall thickness, and the concrete filling state within the tube as key structural parameters; analyzing the influence of key structural parameters on hotspot stress distribution and stress concentration factor through numerical simulation, and determining the structural parameter combination of the corrugated steel web and chord based on existing concrete-filled steel tube truss composite beam structural characteristic data. The present invention quantifies the fatigue life of a truss-chord composite beam through a comprehensive process of multi-parameter modeling, numerical-experimental correction, load spectrum equivalence, and S-N curve prediction, providing a basis for structural fatigue resistance design and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a fatigue life prediction method and system for a truss-chord composite beam. Background Art

[0002] The fatigue failure mode of conventional concrete-filled steel tube (CFST) truss composite beams primarily manifests as fatigue cracks initiating in the welds or parent material at the truss web member nodes. These cracks propagate with increasing load cycles, ultimately leading to node failure or even complete structural damage. Existing improvements to the fatigue performance of CFST truss composite beams have primarily focused on optimizing the local structure of the web member nodes (e.g., strengthening welds, adding stiffening ribs, etc.). However, practice has demonstrated the following limitations of these approaches:

[0003] Local structural optimization is difficult to fundamentally eliminate geometric discontinuities in node areas, and the reduction of stress concentration factors (SCF) is limited. In some projects, the negative effect of "the stronger, the weaker" even occurs.

[0004] The residual stress distribution at the node is significantly affected by the component size, and the test results of small-scale models are difficult to truly reflect the fatigue performance evolution law of the actual structure. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a fatigue life prediction method and system for a truss-chord composite beam, which solves the problem of fatigue life prediction of a new type of truss-chord composite beam and improves the prediction accuracy and engineering applicability.

[0006] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0007] In a first aspect, a fatigue life prediction method for a truss-chord composite beam is provided, the method comprising:

[0008] Step 1: Establish a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord, and use the corrugated steel web inclined web inclination angle, curved connection radius, plate thickness, chord diameter, steel tube wall thickness, and concrete filling state as key structural parameters;

[0009] Step 2: Analyze the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation, and determine the structural parameter combination of corrugated steel web and chord based on the structural characteristic data of existing steel tube concrete truss composite beams;

[0010] Step 3: Based on the optimized combination of structural parameters, a solid model is constructed. The actual hotspot stress distribution data is obtained through static loading. The stress concentration factor in the numerical simulation is corrected by combining the stiffness degradation characteristics and crack initiation locations under repeated loading to obtain the corrected stress concentration factor.

[0011] Step 4: Based on the corrected stress concentration factor and the measured load spectrum data, the equivalent stress amplitude of the corrugated steel web-chord connection area is calculated by load spectrum equivalent conversion;

[0012] Step 5: Determine the fatigue life prediction value of the truss-chord composite beam based on the equivalent stress amplitude.

[0013] Furthermore, a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord was established, and the inclination angle of the corrugated steel web, the curve connection radius, the plate thickness, the chord tube diameter, the steel tube wall thickness, and the concrete filling state in the tube were used as key structural parameters, including:

[0014] Finite element analysis software was used to construct a three-dimensional solid model of the connection between the corrugated steel web and the chord. The corrugated steel web and weld area were divided using hexahedral elements. The steel tube of the concrete-filled steel tube chord was modeled using shell elements, and the concrete was modeled using solid elements. The interface contact behavior between the steel tube and concrete was also defined.

[0015] The key structural parameters are the inclined web inclination angle, curve connection radius, plate thickness of the corrugated steel web, as well as the tube diameter of the chord, the wall thickness of the steel tube, and the state of the concrete filled in the tube.

[0016] Furthermore, the influence of key structural parameters on hot spot stress distribution and stress concentration factor was analyzed through numerical simulation. Combined with the structural characteristic data of existing steel tube concrete truss composite beams, the structural parameter combination of corrugated steel web and chord was determined, including:

[0017] Based on the value range of key structural parameters, the inclined web angle, curved connection radius, plate thickness and chord tube diameter are used as experimental factors, and multiple levels are assigned to each factor to generate an experimental matrix containing different parameter combinations.

[0018] Finite element static loading simulation was performed for each parameter combination. The loading method was symmetrical loading at two points in the mid-span, the boundary condition was simply supported, and the vertical load was applied step by step to the target stress amplitude. The hot spot stress distribution and stress concentration factor in the connection area between the corrugated steel web and the chord were recorded.

[0019] According to the stress concentration factor, the influence of each parameter on the stress concentration factor is calculated to determine the degree of influence on the stress distribution, and the structural parameters whose change exceeds the preset threshold are regarded as the sensitivity parameter combination;

[0020] Based on the sensitivity parameter combination, the finite element simulation results corresponding to the sensitivity parameter combination are compared with the measured data of the node stress of the existing steel tube concrete truss composite beam. The parameter combination whose spatial distribution trend of the simulated stress concentration factor is consistent with the measured data and whose deviation is within the preset range is taken as the optimized construction parameter combination.

[0021] Furthermore, based on the optimized combination of structural parameters, a solid model was constructed, and actual hotspot stress distribution data was obtained through static loading. Combined with the stiffness degradation characteristics and crack initiation locations under repeated loading, the stress concentration factor in the numerical simulation was corrected to obtain the corrected stress concentration factor, including:

[0022] Based on the optimized combination of structural parameters, a solid model of a composite beam with corrugated steel web and concrete-filled steel tube chord was constructed. The weld geometry and dimensional parameters of the connection area between the corrugated steel web and the chord corresponded to those of the finite element model.

[0023] A symmetrical static load test was applied to the solid model at two points in the mid-span, loading the target stress amplitude in stages. The measured values ​​of the stress concentration factor at the actual hotspot were collected using gradient strain sensors placed at the junction of the arc transition section of the corrugated steel web and the chord weld.

[0024] The measured value of the actual hot spot stress concentration coefficient is compared with the stress concentration coefficient of the same parameter combination in the test matrix. When the deviation between the measured value and the stress concentration coefficient of the same parameter combination is less than a first preset threshold, the original stress concentration coefficient is maintained; when the deviation exceeds the first preset threshold and is less than a second preset threshold, the stress concentration coefficient is corrected according to the proportional relationship between the measured value and the stress concentration coefficient of the same parameter combination to generate an intermediate correction value; when the deviation exceeds the second preset threshold, the finite element model parameters are adjusted and the stress concentration coefficient is recalculated;

[0025] Based on the intermediate correction value, a constant-amplitude cyclic load is applied to the solid model, where the load amplitude is set according to the hot spot stress amplitude corresponding to the intermediate correction value; the stiffness degradation process is monitored, and when the stiffness degradation rate reaches the critical point, phased array ultrasonic scanning is used to locate the coordinates of the crack initiation position;

[0026] The coordinates of the crack initiation position are compared with the coordinates of the maximum hot spot stress area corresponding to the intermediate correction threshold. If the spatial position deviation between the crack position coordinates and the stress area coordinates is within the preset range, the intermediate correction value is output as the corrected stress concentration factor; if the deviation exceeds the preset range, the process of adjusting the finite element model parameters based on the crack position coordinates, recalculating the stress concentration factor and verifying the spatial position deviation is iteratively executed until the deviation is within the preset range, and the final corrected stress concentration factor is output.

[0027] Furthermore, based on the corrected stress concentration factor and combined with the measured load spectrum data, the equivalent stress amplitude of the corrugated steel web-chord connection area is calculated through load spectrum equivalent conversion, including:

[0028] Obtain the measured dynamic strain time history data of the target bridge chord node and generate the nominal stress time history curve through material elastic modulus conversion;

[0029] Extract stress cycle events from the nominal stress time history curve to generate a nominal stress amplitude sequence;

[0030] Each stress value in the nominal stress amplitude sequence is fused with the corrected stress concentration factor to generate the actual stress amplitude sequence of the hotspot area;

[0031] The actual stress amplitude series is processed by rain flow counting method, and the number of cycles corresponding to each stress amplitude level is counted to construct the stress amplitude-cycle number distribution spectrum;

[0032] Based on each stress amplitude level and number of cycles in the stress amplitude-cycle number distribution spectrum, the fatigue damage degree corresponding to each stress amplitude level is calculated, and the fatigue damage degrees of all stress amplitude levels are accumulated to obtain the total cumulative damage value;

[0033] Taking the total cumulative damage value equal to the critical damage state as the benchmark, the benchmark stress amplitude that produces equivalent damage under the action of constant amplitude load is reversed as the final equivalent stress amplitude.

[0034] Furthermore, based on each stress amplitude level and the number of cycles in the stress amplitude-cycle number distribution spectrum, the fatigue damage degree corresponding to each stress amplitude level is calculated, and the fatigue damage degrees of all stress amplitude levels are accumulated to obtain the total cumulative damage value, including:

[0035] Determine the corresponding number of fatigue life cycles based on the current stress amplitude level;

[0036] The actual number of cycles corresponding to the current stress amplitude level and the number of fatigue life cycles are proportionally combined to obtain the single-level damage degree;

[0037] The single-level damage degree of each stress amplitude level is accumulated to generate the total cumulative damage value.

[0038] Furthermore, the fatigue life prediction value of the truss-chord composite beam is determined based on the equivalent stress amplitude, including:

[0039] Based on the final equivalent stress amplitude, the target fatigue detail category is determined, and the corresponding characteristic constant and slope index are obtained according to the fatigue detail category;

[0040] Based on the characteristic constant and slope index, the SN curve model is constructed, and the final equivalent stress amplitude is input into the SN curve model. According to the relationship between the final equivalent stress amplitude and the characteristic constant, the theoretical number of failure cycles is obtained;

[0041] The theoretical failure cycles are used as the fatigue life prediction value of the truss-chord composite beam.

[0042] In a second aspect, a fatigue life prediction system for a truss-chord composite beam includes:

[0043] The finite element modeling module is used to establish a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord. The key structural parameters are the inclined web angle of the corrugated steel web, the curve connection radius, the plate thickness, the chord diameter, the steel tube wall thickness, and the concrete filling state inside the tube.

[0044] The parameter analysis module is used to analyze the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation. It is also used to determine the structural parameter combination of corrugated steel web and chord based on the structural characteristic data of existing concrete-filled steel tube truss composite beams.

[0045] The model correction module is used to construct a solid model based on the optimized combination of structural parameters, obtain the actual hot spot stress distribution data through static loading, and correct the stress concentration factor in the numerical simulation by combining the stiffness degradation characteristics and crack initiation location under repeated loading to obtain the corrected stress concentration factor;

[0046] The stress calculation module is used to calculate the equivalent stress amplitude of the corrugated steel web-chord connection area through load spectrum equivalent conversion based on the corrected stress concentration factor and the measured load spectrum data;

[0047] The life prediction module is used to determine the fatigue life prediction value of the truss-chord composite beam according to the equivalent stress amplitude.

[0048] According to a third aspect, a computing device includes:

[0049] one or more processors;

[0050] The storage device is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method.

[0051] In a fourth aspect, a computer-readable storage medium stores a program, which implements the method when executed by a processor.

[0052] The above solution of the present invention includes at least the following beneficial effects:

[0053] The geometric parameters of the corrugated steel web (inclination angle, curve radius, plate thickness) and chord parameters (tube diameter, wall thickness, concrete filling status) are incorporated into the model to fully reflect the spatial stress characteristics of the composite beam and avoid the deviation in the calculation of the stress concentration factor caused by traditional simplified modeling. Through orthogonal test matrices and numerical simulations, the influence of key parameters on the stress concentration factor is quantified (for example, increasing the curve radius can reduce the stress concentration factor), reducing design blindness and determining the final structural parameter combination. Real hot spot stress data is obtained through static load testing. Combined with the stiffness degradation and crack initiation location under repeated loading, a "calculation-test" closed-loop correction mechanism is established to narrow the gap between theoretical calculations and actual structures, ensuring that the stress concentration factor reflects the actual fatigue damage initiation state.

[0054] Based on the measured dynamic load spectrum of the target bridge (such as vehicle load history), the rainflow counting method is used to extract multi-level stress amplitudes, truly reflecting the fatigue damage accumulation process under complex loads. By converting variable-amplitude loads into equivalent stress amplitudes, this method overcomes the limitation of the traditional SN curve, which is only applicable to constant-amplitude loads. This makes fatigue damage calculations more realistic and enhances the engineering applicability of the prediction results. From modeling analysis and parameter optimization to experimental correction, load equivalence, and life prediction, this complete technical chain is formed, which can effectively guide the fatigue design and performance evaluation of corrugated steel web-concrete-filled steel tube truss composite beams. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The present invention provides a flowchart of a fatigue life prediction method for a truss-chord composite beam according to an embodiment of the present invention.

[0056] Figure 2 It is a schematic diagram of a fatigue life prediction system for a truss-chord composite beam provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a fatigue life prediction method for a truss-chord composite beam, the method comprising the following steps:

[0059] Step 1: Establish a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord, and use the corrugated steel web inclined web inclination angle, curved connection radius, plate thickness, chord diameter, steel tube wall thickness, and concrete filling state as key structural parameters;

[0060] Step 2: Analyze the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation, and determine the structural parameter combination of corrugated steel web and chord based on the structural characteristic data of existing steel tube concrete truss composite beams;

[0061] Step 3: Based on the optimized combination of structural parameters, a solid model is constructed. The actual hotspot stress distribution data is obtained through static loading. The stress concentration factor in the numerical simulation is corrected by combining the stiffness degradation characteristics and crack initiation locations under repeated loading to obtain the corrected stress concentration factor.

[0062] Step 4: Based on the corrected stress concentration factor and the measured load spectrum data, the equivalent stress amplitude of the corrugated steel web-chord connection area is calculated by load spectrum equivalent conversion;

[0063] Step 5: Determine the fatigue life prediction value of the truss-chord composite beam based on the equivalent stress amplitude.

[0064] In an embodiment of the present invention, the geometric parameters of the corrugated steel web (inclination angle, curve radius, plate thickness) and the chord parameters (tube diameter, wall thickness, concrete filling state) are incorporated into the model to fully reflect the spatial stress characteristics of the new composite beam and avoid the calculation deviation of the stress concentration factor caused by traditional simplified modeling. Shell elements and solid elements are combined to simulate the steel tube concrete interface contact, considering the effects of interface debonding and slip on hot spot stress under repeated loads, thereby improving the realism of the model's mechanical behavior. Numerical simulation is used to identify the impact of key parameters on the stress concentration factor (for example, increasing the curve radius can reduce the stress concentration factor), providing data support for parameter optimization and reducing design blindness.

[0065] Comparing the stress distribution characteristics of the new composite beam with those of traditional steel tube concrete truss composite beams ensures the engineering applicability of the optimized parameter combination and improves the reliability of model predictions. Real hotspot stress data is obtained through static load tests on physical models, and numerical simulation results are revised in stages to narrow the gap between theoretical calculations and actual structures.

[0066] By combining stiffness degradation and crack initiation locations under repeated loading, a closed-loop "calculation-test" correction mechanism is established to ensure that the stress concentration factor reflects the actual fatigue damage initiation state. Based on measured dynamic load spectra (such as vehicle load history), multi-level stress amplitudes are extracted using the rain flow counting method to truly reflect the fatigue damage accumulation process of the structure under complex loads. By converting variable amplitude loads into equivalent stress amplitudes, the traditional SN curve is no longer limited to constant amplitude loads, making fatigue damage calculations more closely aligned with actual engineering conditions.

[0067] In a preferred embodiment of the present invention, the above step 1, establishing a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord, and using the corrugated steel web inclined web inclination angle, curved connection radius, plate thickness, chord diameter, steel tube wall thickness, and concrete filling state in the tube as key structural parameters, may include:

[0068] Step 100: Using finite element analysis software, construct a three-dimensional solid model of the connection node between the corrugated steel web and the chord. The corrugated steel web and the weld area are divided using hexahedron elements, the steel tube of the concrete-filled steel tube chord is modeled using shell elements, and the concrete is modeled using solid elements. The interface contact behavior between the steel tube and the concrete is defined.

[0069] Step 101 , taking the inclined web inclination angle, curve connection radius, plate thickness of the corrugated steel web, as well as the pipe diameter of the chord, the wall thickness of the steel pipe, and the state of the concrete filled in the pipe as key construction parameters.

[0070] In this embodiment of the present invention, finite element analysis software (such as MSC.MARC) was used to create a 1:1 scale 3D solid model of the local structure of the connection between the corrugated steel web and the concrete-filled steel tube chord. The model must include the entire corrugated steel web (including at least two corrugated periods) and the chords on both sides extending 500 mm to eliminate boundary effects.

[0071] Element type and mesh division:

[0072] Hexahedral solid elements (such as Hex8 elements) are used for detailed meshing, with the mesh size controlled within 5mm. In particular, the mesh size needs to be refined to 2-3mm in the spatial curved weld area where the corrugated steel web intersects the chord to capture stress gradient variations. The steel tube is modeled using shell elements (such as Quad4 elements), with 3-5 layers of integration points through the thickness to accurately simulate the membrane and bending effects of the tube. The internal concrete is modeled using eight-node solid elements (Hex8 elements), with the mesh size matching the steel tube shell elements to ensure a one-to-one correspondence between the interface nodes. A bilinear kinematic hardening constitutive model is used for the steel (Q345), with an elastic modulus of 206GPa, a Poisson's ratio of 0.3, and a yield strength of 345MPa. An elastoplastic damage model is used for the concrete (C50), with an elastic modulus of 34.5GPa, a Poisson's ratio of 0.2, and defined compressive and tensile strengths. A “hard contact” (i.e., no penetration) is defined between the steel tube and the concrete in the normal direction, and the Coulomb friction model is used in the tangential direction, with a friction coefficient of 0.6-0.8 (referring to the steel tube concrete interface test data) to simulate the interface slip and debonding behavior.

[0073] Boundary conditions and loading settings:

[0074] A fixed constraint (UX=UY=UZ=0) is applied at one end of the model, where UX, UY, and UZ are the linear displacements of the nodes in the X, Y, and Z directions. An axial tension or bending moment (determined according to the actual load conditions) is applied at the other end. The loading step adopts a graded loading method, with each load increment being 10% of the target load until it reaches 80% of the yield stress of the steel, in order to obtain the stress distribution in the elastic stage.

[0075] Step 101: Corrugated steel web parameters include:

[0076] Inclined web angle: Measure the angle between the inclined section of the corrugated steel web and the axis of the chord. The value range is 25°-45°, and the parameter gradient is set at intervals of 5°.

[0077] Curve connection radius: The connection radius between the straight section and the arc transition section of the corrugated steel web is set to 200-500mm according to the commonly used engineering dimensions, with an increment of 50mm.

[0078] Plate thickness: The thickness of the corrugated steel web plate shall be 6-12mm with an interval of 2mm, taking into account the welding process and strength requirements.

[0079] Pipe diameter: The outer diameter of the steel tube concrete chord, referring to the existing bridge engineering data, is 300-600mm, with a gradient of 50mm.

[0080] Steel pipe wall thickness: The ratio of steel pipe wall thickness to pipe diameter is 1 / 50-1 / 30, corresponding to a wall thickness of 6-20mm, with an interval of 2mm.

[0081] Concrete filling state in the tube: Set two working conditions: "Filled" and "Not Filled". When filling with concrete, you need to define the material properties and interface contact of the concrete. When not filling, only the steel tube shell element is retained.

[0082] By simulating the corrugated steel webs and welds using hexahedral elements and combining shell and solid elements to simulate concrete-filled steel tubes (CFSTs), the model accurately depicts the three-dimensional stress distribution in the joint region (e.g., radial and hoop stresses in the arc transition section of the corrugated steel web), avoiding the underestimation of stress concentration factors often associated with traditional beam or simplified shell element models. By defining normal hard contact and tangential friction between the steel tube and concrete, the model simulates stress redistribution caused by interfacial slip under repeated loading (e.g., a decrease in the concrete's load-bearing ratio and increased stress concentration in the steel tube), ensuring a more realistic representation of the actual mechanical properties of the composite beam. By encompassing key parameters of the corrugated steel web geometry and chord construction, the model systematically analyzes the effects of different parameter combinations on hotspot stresses, avoiding the limitations of single-parameter optimization. By employing graded loading matched to actual load conditions (e.g., axial tension and bending moment), the model captures stress distribution characteristics from the elastic to elastoplastic stages, providing fundamental stress data for fatigue analysis and avoiding computational biases caused by simplified loading patterns.

[0083] In a preferred embodiment of the present invention, the above step 2, analyzing the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation, and determining the structural parameter combination of the corrugated steel web and the chord in combination with the structural characteristic data of existing concrete-filled steel tube truss composite beams, may include:

[0084] Step 200 , based on the value range of key structural parameters, the inclined web angle, curve connection radius, plate thickness, and chord diameter are used as test factors, and multiple levels are assigned to each factor to generate a test matrix containing different parameter combinations;

[0085] Step 201: Perform a finite element static loading simulation for each parameter combination, wherein the loading method is symmetrical loading at two points in the mid-span, the boundary condition is simply supported, and the vertical load is applied step by step to the target stress amplitude. The hot spot stress distribution and stress concentration factor in the connection area between the corrugated steel web and the chord are recorded.

[0086] Step 202 , based on the stress concentration coefficient, the influence of each parameter on the stress concentration coefficient is calculated to determine the degree of influence on the stress distribution, and the structural parameters whose variation exceeds a preset threshold are used as a sensitivity parameter combination;

[0087] In step 203, based on the sensitivity parameter combination, the finite element simulation results corresponding to the sensitivity parameter combination are compared with the measured data of the node stress of the existing steel tube concrete truss composite beam, and the parameter combination whose spatial distribution trend of the simulated stress concentration factor is consistent with the measured data and whose deviation is within a preset range is used as the optimized structural parameter combination.

[0088] In the embodiments of the present invention, a survey of similar bridge engineering cases and relevant literature was conducted to analyze the actual application range of the inclined web angles of corrugated steel webs. It was found that most projects were concentrated between 25° and 45°. Therefore, this interval was set as the parameter range and divided into five levels (25°, 30°, 35°, 40°, and 45°) at 5° intervals. The curve connection radius was determined based on the feasibility of the corrugated steel web processing technology. The minimum radius was limited by the bending properties of the steel plate (greater than or equal to 200mm), while the maximum radius considered the rationality of the structural dimensions (less than or equal to 500mm). The radius was divided into seven levels (200mm, 250mm, 300mm, 350mm, 400mm, 450mm, and 500mm) in 50mm increments. The plate thickness selection required a balance between structural strength and welding difficulty. The project value ranged from 6 to 12mm, divided into four levels (6mm, 8mm, 10mm, and 12mm) at 2mm intervals. The chord diameter was determined to be 300–600 mm, based on the commonly used specifications of existing concrete-filled steel tube bridges. This diameter was divided into seven levels (300 mm, 350 mm, 400 mm, 450 mm, 500 mm, 550 mm, and 600 mm) in 50 mm increments. The concrete filling state within the tube was used as an independent parameter. In the test matrix, the "filled" and "unfilled" states were used to correspond to each geometric parameter combination, forming parallel comparison conditions.

[0089] Orthogonal experimental design table L25 ( ), which is suitable for a 4-factor, 5-level experiment and contains 25 rows (one for each parameter combination) and 4 columns (one for each combination of inclination angle, radius, plate thickness, and pipe diameter). For example, the first parameter group is a 25° inclination angle, a 200mm radius, a 6mm plate thickness, and a 300mm pipe diameter; the tenth parameter group is a 35° inclination angle, a 350mm radius, a 10mm plate thickness, and a 450mm pipe diameter. Ensure that each level of each parameter appears evenly five times in the matrix to cover any interactions between the parameters.

[0090] Step 201, finite element static loading simulation:

[0091] In the finite element software, one end of the composite beam model was defined as a fixed support. Displacement at this end node was constrained in the X, Y, and Z directions (UX=UY=UZ=0), simulating the fixed pier constraints of an actual bridge. Displacement was constrained only in the Y direction (UY=0), while free movement in the X and Z directions was allowed. This prevented additional stresses due to factors such as thermal deformation and conformed to the load characteristics of a simply supported beam. A symmetrical loading method was used at two points midspan, with the load transferred to the model midspan via a distribution beam. The spacing between the two points was set at 2000mm based on the beam width to ensure a pure bending section between the two loading points. Starting from zero, the target stress amplitude was applied in increments of 10% (for example, if the target stress amplitude was 200 MPa, the increment was 20 MPa) until the target value was reached or the steel entered the plastic stage (80% of the yield stress, such as 276 MPa for Q345 steel). After each level of loading, the nodal stress data of the connection area between the corrugated steel web and the chord (especially the junction of the arc transition section and the weld) are extracted, and the stress component perpendicular to the weld direction (i.e., hot spot stress) is recorded in particular.

[0092] Based on the current load, calculate the average stress in the chord cross section using the formula "Nominal stress = load ÷ (chord steel tube cross-sectional area + concrete cross-sectional area)." Select three to five key nodes in the connection area and take the average stress perpendicular to the weld as the hotspot stress. Divide the hotspot stress by the nominal stress to obtain the stress concentration factor (SCF) for each parameter combination. For example, a hotspot stress of 300 MPa and a nominal stress of 100 MPa yields a stress concentration factor of 3.0.

[0093] In step 202, for each parameter level, the SCF values ​​for all corresponding combinations in the test matrix are counted, and the mean and standard deviation are calculated. For example, the mean SCF values ​​for the five combinations corresponding to a 25° slant web angle are 2.84, with a standard deviation of 0.12. Taking 25° and 30° as examples, if the mean SCF value for the 30° level is 3.12, then the variation is (3.12 - 2.84) ÷ 2.84 × 100%. A variation threshold of 10% is set, and parameters exceeding this threshold are identified as sensitive parameters. Parameters are sorted by variation from largest to smallest. The curve connection radius is most significantly associated with a change in SCF (e.g., a 50mm increase results in a decrease in SCF of approximately 10%-15%), followed by the slant web angle (a 5° increase results in an increase in SCF of approximately 8%-12%). Plate thickness and pipe diameter have relatively minor effects (variation less than 5%). A parameter sensitivity list is formed, such as "curve connection radius > slant web angle > plate thickness > pipe diameter," to clarify optimization priorities.

[0094] Step 203 collects measured stress data for similar steel tube concrete truss composite beams, including hotspot stress distribution contours and SCF values ​​measured using gradient strain gauges (e.g., in a measured case, the hotspot stress in the arc transition section is 280 MPa, the nominal stress is 95 MPa, and the SCF is 2.95). Outliers (such as sudden changes in data caused by equipment vibration during loading) are eliminated, and the average of multiple measurements is taken as the baseline value. The stress contours derived from finite element simulations are overlaid with the measured contours to observe whether high-stress areas (such as the weld toe and the midpoint of the arc transition section) overlap. If the high-stress areas in the simulated contours deviate from the measured locations by more than 20 mm, the distribution trends are considered inconsistent. For each sensitivity parameter combination, the relative error between the simulated SCF and the measured SCF is calculated using the formula "Error = (Simulated Value - Measured Value) ÷ Measured Value × 100%." ​​For example, if the simulated SCF is 3.2 and the measured SCF is 3.0, the error is 6.67%. If the preset error range is ±15%, the result is considered to meet the requirements.

[0095] Combinations with consistent spatial distribution trends and an error within ±15% were retained. For example, combination A (30° inclination angle, 400mm radius, 8mm plate thickness, 500mm pipe diameter) exhibited a simulated SCF of 2.85 and a measured SCF of 2.78, with an error of 2.52%, and was retained. Combination B (45° inclination angle, 250mm radius, 12mm plate thickness, 300mm pipe diameter) exhibited an error of 22% and was eliminated. The retained combinations were further analyzed for their engineering suitability, including machining difficulty (a too small radius requires specialized bending equipment) and material consumption (excessive plate thickness increases deadweight). Ultimately, two or three optimized parameter combinations were identified that balanced performance and cost-effectiveness, such as "35° inclination angle, 400mm radius, 8mm plate thickness, 500mm pipe diameter" and "30° inclination angle, 450mm radius, 10mm plate thickness, 450mm pipe diameter."

[0096] Through an orthogonal test matrix, the coupled effects of parameters such as the inclination angle and curve radius of the corrugated steel web are systematically analyzed to avoid the limitations of single-parameter optimization and comprehensively reveal the effects of various parameters on the hotspot stress distribution and stress concentration factor. Constraints and mid-span symmetrical loading are used to simulate actual bridge load conditions, making the finite element analysis results more closely aligned with the actual engineering conditions and improving the engineering applicability of the simulation data. The influence of various parameters on the stress concentration factor is quantified, and highly sensitive parameters (such as curve radius and inclination) are identified. This provides clear optimization directions for structural design (such as prioritizing the adjustment of highly sensitive parameters to reduce stress concentration), reducing blindness in the design process. The reliability of the simulation results is verified by combining existing measured data to ensure that the optimized parameter combination conforms to the actual structural performance.

[0097] In a preferred embodiment of the present invention, the above step 3, based on the optimized combination of structural parameters, constructs a solid model, obtains actual hot spot stress distribution data through static loading, and corrects the stress concentration factor in the numerical simulation in combination with the stiffness degradation characteristics and crack initiation location under repeated loading to obtain the corrected stress concentration factor, which may include:

[0098] Step 300: constructing a solid model of a composite beam with a corrugated steel web and a concrete-filled steel tube chord based on the optimized combination of construction parameters, wherein the geometry and size parameters of the welds in the connection area between the corrugated steel web and the chord correspond to those in the finite element model;

[0099] Step 301: Apply a symmetrical static load test at two points in the mid-span to the solid model, loading the model in stages to the target stress amplitude, and collect the measured value of the actual hot spot stress concentration factor using a gradient strain sensor arranged at the junction of the arc transition section of the corrugated steel web and the chord weld;

[0100] Step 302: Compare the measured value of the actual hotspot stress concentration coefficient with the stress concentration coefficient of the same parameter combination in the test matrix. When the deviation between the measured value and the stress concentration coefficient of the same parameter combination is less than a first preset threshold, maintain the original stress concentration coefficient. When the deviation exceeds the first preset threshold and is less than a second preset threshold, correct the stress concentration coefficient according to the proportional relationship between the measured value and the stress concentration coefficient of the same parameter combination to generate an intermediate correction value. When the deviation exceeds the second preset threshold, adjust the finite element model parameters and recalculate the stress concentration coefficient.

[0101] Step 303: Apply a constant-amplitude cyclic load to the solid model based on the intermediate correction value, where the load amplitude is set according to the hot spot stress amplitude corresponding to the intermediate correction value; monitor the stiffness degradation process, and when the stiffness degradation rate reaches a critical point, use phased array ultrasonic scanning to locate the coordinates of the crack initiation position;

[0102] In step 304, the coordinates of the crack initiation position are compared with the coordinates of the maximum hot spot stress area corresponding to the intermediate correction threshold. If the spatial position deviation between the crack position coordinates and the stress area coordinates is within a preset range, the intermediate correction value is output as the corrected stress concentration factor. If the deviation exceeds the preset range, the process of adjusting the finite element model parameters based on the crack position coordinates, recalculating the stress concentration factor, and verifying the spatial position deviation is iteratively performed until the deviation is within the preset range, and the final corrected stress concentration factor is output.

[0103] In this embodiment of the present invention, based on the optimized parameter combination determined in step 203 (e.g., a 35° inclined web angle, a 400mm curved connection radius, an 8mm plate thickness, and a 500mm chord diameter), a solid model was fabricated using geometric parameters identical to those in the finite element model. The corrugated steel web was machined using CNC cutting equipment to ensure dimensional accuracy (±1mm tolerance) for the inclined web angle and curved connection radius, and a 95% or greater fit between the arc transition and the chord surface. The weld geometry (e.g., leg dimensions and groove angle) was strictly defined in the finite element model, using automated welding processes (e.g., CNC welding as specified in the task specification) to minimize manual welding errors. After fabrication, key dimensions of the solid model (e.g., corrugated web thickness and chord diameter) were measured and compared with the finite element model parameters.

[0104] In step 301, a 1000 kN servo loading system is used to apply a symmetrical load at two points in the span through the distribution beam. The spacing between the loading points is consistent with the finite element simulation (e.g., 2000 mm), forming a pure bending section. Starting from zero, the load is applied in steps of 20% of the target stress amplitude (e.g., if the target stress amplitude is 200 MPa, the load is applied in steps of 40 MPa each). Loading is continued step by step until the target value is reached or the structure exhibits significant deformation (e.g., deflection exceeds 1 / 500 of the span).

[0105] After each loading stage, the load was stabilized for 5 minutes. Gradient strain sensors were deployed at the intersection of the corrugated steel web arc transition section and the chord weld to collect strain data perpendicular to the weld. Three unidirectional strain gauges (2mm apart) were placed at each measuring point to capture the stress gradient. The strain data were converted to stress values ​​using the material elastic modulus (206 GPa for steel), and the average of the three strain gauges was taken as the measured hotspot stress at that measuring point. The measured SCF = measured hotspot stress divided by nominal stress (nominal stress is calculated by dividing the applied load and the cross-sectional area of ​​the chord. For example, if the load is 100 kN and the chord cross-sectional area is 0.01 m², the nominal stress = 100 kN ÷ 0.01 m²).

[0106] Step 302 , calculate the deviation: Deviation = |Measured SCF - Simulated SCF| ÷ Simulated SCF × 100%, where Simulated SCF is the finite element calculated value with the same parameter combination as in Step 201 (e.g., if the simulated value is 3.0 and the measured value is 3.2, then the deviation = 6.67%).

[0107] Preset threshold:

[0108] The first preset threshold: 5% (within the permissible range, the simulation results are considered reliable);

[0109] The second preset threshold is 10% (if exceeded, correction is required; if between the two, proportional adjustment is required).

[0110] Corrected logic execution:

[0111] Case 1: Deviation is less than 5% (e.g., deviation is 3%), the original SCF simulation value is maintained unchanged, and the finite element model is considered accurate.

[0112] Case 2: 5% ≤ deviation < 10% (e.g., deviation is 8%), correction is made based on the ratio of measured value to simulated value, i.e., SCF intermediate = SCF simulated × (SCF measured ÷ SCF simulated) = SCF measured (e.g., simulated value 3.0, measured value 3.24, corrected to 3.24).

[0113] Case 3: Deviation ≥ 10% (e.g., deviation 15%), return to the finite element model to adjust parameters (e.g., increase the mesh density in the weld area to 2 mm, adjust the steel pipe-concrete interface friction coefficient from 0.6 to 0.7), and recalculate the SCF simulation until the deviation is < 10%.

[0114] In step 303, based on the intermediate correction value obtained in step 302 (e.g., SCF intermediate = 3.24), calculate the hot spot stress amplitude: Δσ = SCF intermediate × nominal stress amplitude (e.g., if the nominal stress amplitude is 50 MPa, Δσ = 162 MPa). Apply a constant-amplitude cyclic load with a load amplitude of Δσ × chord cross-sectional area (e.g., 162 MPa × 0.01 m²) at a loading frequency of 5 Hz. The number of cycles is increased by 10% of the estimated fatigue life (e.g., if the estimated life is 100,000 cycles, perform a shutdown inspection every 10,000 cycles). Excursion gauges are placed at the base of the chords in the L / 4, L / 2, and 3L / 4 sections of the beam. Displacements are measured before and after each loading event, and the stiffness degradation rate is calculated: Stiffness degradation rate = (initial stiffness - current stiffness) ÷ initial stiffness × 100%, where stiffness = load ÷ mid-span deflection. When the stiffness degradation rate reaches 15% (or visible cracks appear in the concrete), the loading is stopped and the weld area is scanned using phased array ultrasonic scanning to locate the three-dimensional coordinates (X, Y, Z) of the crack initiation position.

[0115] Step 304: Compare the crack initiation coordinates obtained by ultrasonic scanning (e.g., X=1000mm, Y=50mm, Z=20mm) with the coordinates of the maximum hotspot stress area corresponding to SCF_center in the finite element model (e.g., X=980mm, Y=45mm, Z=22mm), and calculate the three-dimensional distance deviation:

[0116] Deviation = .

[0117] Preset range: allowable deviation ≤ 20mm (set according to structural dimension accuracy).

[0118] Iterative correction process:

[0119] Case 1: Deviation ≤ 20 mm, the stress distribution prediction of the finite element model is considered accurate, and the middle SCF is output as the final correction value.

[0120] Case 2: Deviation > 20 mm (e.g., 25 mm). Analyze the cause of the deviation (e.g., inaccurate weld shape simulation, unreasonable interface contact parameters), adjust the finite element model parameters (e.g., increase the weld convexity from 1 mm to 1.5 mm, adjust the friction coefficient from 0.7 to 0.8), recalculate the SCF simulation and generate a new intermediate correction value. Repeat steps 303-304 until the deviation is ≤ 20 mm.

[0121] By strictly replicating the geometric parameters and process details of the finite element model, the boundary conditions of the physical model and the numerical simulation are unified. The static load measured data and fatigue crack location results are introduced in stages. Through the "calculation-test" two-way calibration, the difference between the theoretical prediction and the actual structure is gradually narrowed, avoiding the limitations of relying solely on numerical simulation. Combining the dual indicators of stiffness degradation characteristics and crack initiation location, not only the value of the stress concentration factor is corrected, but also the accuracy of its spatial distribution is verified, so that the corrected parameters more realistically reflect the initial state of structural fatigue damage. The iterative correction process fully considers practical factors such as welding technology and material nonlinearity to ensure that the final stress concentration factor can be directly used for fatigue life prediction of real bridges, thereby improving the engineering credibility of the design method.

[0122] In a preferred embodiment of the present invention, the above step 4, based on the corrected stress concentration factor and combined with the measured load spectrum data, calculates the equivalent stress amplitude of the corrugated steel web-chord connection area through load spectrum equivalent conversion, which may include:

[0123] Step 400 , obtaining measured dynamic strain time history data of the target bridge chord node, and generating a nominal stress time history curve by converting the material elastic modulus;

[0124] Step 401, extracting stress cycle events from the nominal stress time history curve to generate a nominal stress amplitude sequence;

[0125] Step 402 , fusing each stress value in the nominal stress amplitude sequence with the corrected stress concentration factor to generate an actual stress amplitude sequence of the hotspot area;

[0126] Step 403: Performing a rain flow counting method on the actual stress amplitude sequence to count the number of cycles corresponding to each stress amplitude level to construct a stress amplitude-cycle number distribution spectrum;

[0127] Step 404, based on each stress amplitude level and the number of cycles in the stress amplitude-cycle number distribution spectrum, calculates the fatigue damage degree corresponding to each stress amplitude level, and accumulates the fatigue damage degrees of all stress amplitude levels to obtain a total cumulative damage value, which specifically includes:

[0128] Step 4044, determining the corresponding number of fatigue life cycles according to the current stress amplitude level;

[0129] Step 4045 , proportionally combining the actual number of cycles corresponding to the current stress amplitude level and the number of fatigue life cycles to obtain a single-level damage degree;

[0130] Step 4046 , accumulating the single-level damage degree of each stress amplitude level to generate a total cumulative damage value;

[0131] Step 405 , taking the total cumulative damage value equal to the critical damage state as a benchmark, reversely inferring the benchmark stress amplitude that produces equivalent damage under the action of the constant amplitude load as the final equivalent stress amplitude.

[0132] In an embodiment of the present invention, dynamic strain sensors (such as the gradient strain gauges mentioned in the task book) are pasted on the chord nodes of the target bridge (such as the hot spot area where the corrugated steel web is connected to the chord), and the sensor layout needs to cover the stress gradient direction (perpendicular to the weld). The strain response of the bridge under actual traffic loads is continuously monitored by a data acquisition system (such as a dynamic signal analyzer), with a sampling frequency of not less than 500Hz and a recording time of not less than 24 hours to capture the combined effects of various vehicle loads (such as cars, trucks, and buses). The collected strain time history data (in με) is converted into a nominal stress time history curve through the elastic modulus of the material (206GPa for steel). The conversion relationship is "nominal stress (MPa) = strain value (με) × elastic modulus (GPa) × For example, a strain value of 100 με corresponds to a nominal stress of 20.6 MPa. Abnormal data points (such as sudden changes caused by sensor failure) are eliminated, and the sliding average filter method (window width 50 sampling points) is used to smooth the curve and reduce noise interference.

[0133] Step 401 traverses the nominal stress time history curve and identifies all local peaks (wave crests) and valleys (valleys). A peak is defined as a stress value that is higher than the stress values ​​of the preceding and following adjacent points, while a valley is defined as a stress value that is lower than the stress values ​​of the preceding and following adjacent points. For example, if the stress at a point on the curve is 25 MPa, and the preceding and following points are 20 MPa and 22 MPa, respectively, this is considered a peak.

[0134] Stress cycle events are extracted using the "peak-valley pairing method": starting from the first extreme point, each peak is paired with the nearest subsequent valley to form a stress cycle (stress amplitude Δσ = peak value - valley value). The midpoint stress (average stress) of this cycle is recorded. For example, if the extreme value sequence of the time history curve is 0 → 20 MPa (peak) → 5 MPa (valley value) → 15 MPa (peak) → -5 MPa (valley value), the cycle from 20 MPa to 5 MPa is first extracted (Δσ = 15 MPa, average stress 12.5 MPa), followed by the cycle from 15 MPa to -5 MPa (Δσ = 20 MPa, average stress 5 MPa). The amplitudes (Δσ) of all identified stress cycles are arranged in order of appearance to form a nominal stress amplitude sequence, such as [15 MPa, 20 MPa, 12 MPa, ...].

[0135] In step 402, take the corrected stress concentration factor (SCF) from step 304 (e.g., SCF = 3.2) and multiply each value in the nominal stress amplitude sequence by this factor to obtain the actual stress amplitude in the hotspot area. Actual stress amplitude = nominal stress amplitude × SCF. For example, a nominal stress amplitude of 15 MPa corresponds to an actual stress amplitude of 15 × 3.2 = 48 MPa, while a nominal amplitude of 20 MPa corresponds to 64 MPa. Check whether the actual stress amplitude exceeds the material yield strength (e.g., 345 MPa for Q345 steel). If a value exceeds a threshold (e.g., 300 MPa), it is marked as an abnormal cycle. Analysis is conducted to determine whether the cause is an overloaded vehicle, and the cycle is removed or adjusted if necessary.

[0136] Step 403: Input the actual stress amplitude sequence into the rainflow counting algorithm. The algorithm uses the "rainflow" simulation principle to identify all closed stress cycles from the stress-time history. The specific steps are:

[0137] Convert the stress-time curve into a "peak-valley" sequence (as obtained in step 401). Starting from the first valley, imagine a rain flow flowing downward from the valley apex, stopping when it encounters a valley lower than the current one or when all data points have been exhausted. Record the cycles formed by the peaks and valleys along the way. For example, for the sequence [48 MPa, 64 MPa, 38 MPa, 50 MPa], rain flow counting can identify cycles such as 64 MPa → 38 MPa (Δσ = 26 MPa) and 50 MPa → (subsequent valley). Finally, count the number of cycles for each amplitude. Accumulate the number of cycles for the same stress amplitude to form a discrete stress amplitude-cycle distribution spectrum. For example, a stress amplitude of 20 MPa occurs 100 times, 25 MPa occurs 50 times, 30 MPa occurs 20 times, and so on.

[0138] Step 404: For each stress amplitude level (e.g., Δσi) in the distribution spectrum, the corresponding number of fatigue life cycles (Ni) is determined using the material's SN curve. The SN curve (stress-life curve) is key data for characterizing the fatigue life of a material under alternating stress. It is obtained through standardized fatigue testing. The specific process and application logic are as follows:

[0139] The determination of the SN curve must be completed through material fatigue testing, which includes specimen preparation, graded loading, data recording and curve fitting:

[0140] Process standard specimens of the same material as the target structure (such as smooth round rod specimens of Q345 steel) with a diameter of 6-10mm. The surface needs to be polished to eliminate initial defects such as processing scratches to avoid interference with the test results. 3-5 specimens need to be prepared for each group of stress levels to statistically analyze the dispersion of fatigue life. Using an electro-hydraulic servo fatigue testing machine, cyclic loads such as sine waves and triangular waves can be applied to accurately control the stress amplitude, average stress (such as setting it to 0 to simulate a symmetrical cycle) and loading frequency (5-20Hz). Select 5-7 different stress amplitude levels (such as 150MPa, 120MPa, 100MPa, 80MPa, 60MPa) to cover the range of high stress (short life) to low stress (long life). Among them, the highest stress level requires the specimen to be at The minimum stress level to be achieved is the fracture within the cycle The specimen is subjected to a cyclic load with a fixed stress amplitude and the number of cycles (N) is recorded in real time. When the specimen breaks or reaches the upper limit of the preset number of cycles (e.g. Stop the test when:

[0141] If the specimen breaks, record the number of cycles to fracture as the fatigue life at that stress amplitude;

[0142] If it is not broken, it is recorded as “not failed” and the corresponding life is Second-rate.

[0143] For example, when the stress amplitude is 100 MPa, the fracture life of the three specimens is 1.2× times, 1.5× times, 1.3× times, the average lifespan is 1.3× times; when the stress amplitude is 50MPa, the two specimens are not broken, and the life is recorded as Second-rate.

[0144] Each stress amplitude (Δσ) and its corresponding fatigue life (Ni) are plotted as a scatter plot, with the horizontal axis representing the logarithmic number of cycles (logN) and the vertical axis representing the logarithmic stress amplitude (logΔσ). The scattered points are fitted using the least squares method to obtain an approximate straight line, whose mathematical expression is a power function (e.g., the higher the Δσ, the lower the N). For example:

[0145] When Δσ=100MPa, N= Second-rate;

[0146] When Δσ=50MPa, N= Second-rate;

[0147] After fitting, we can infer the rule that "for every halving of the stress amplitude, fatigue life increases tenfold." The SN curve for standard specimens needs to be adjusted based on the actual structural characteristics. For example, the fatigue life of large-scale components is lower than that of standard specimens, so a size correction factor (e.g., 0.8-0.9) should be multiplied. Stress concentration at welded joints reduces the material's fatigue performance, requiring a lower SN curve grade.

[0148] When obtaining the fatigue life corresponding to a certain stress amplitude through the SN curve, the following logic must be followed:

[0149] The SN curve is essentially an inverse proportional relationship of "the greater the stress amplitude, the shorter the fatigue life". For example, when Δσ=150MPa, the fatigue life of a certain steel is 2× times; when Δσ=75MPa, the fatigue life can be inferred from the curve to be 2× times (assuming the slope of the curve is 3, the life is inversely proportional to the cube of the stress amplitude). For stress amplitudes that are not directly tested (such as Δσ=80MPa), the life can be estimated by curve interpolation: that is, in the logΔσ-logN coordinate system, find the horizontal coordinate position corresponding to 80MPa, read the corresponding logN value and convert it into actual life. The fatigue performance of the structure depends not only on the material, but also on the construction details (such as weld form and stress concentration). For example: the connection weld between the corrugated steel web and the chord is a "high stress concentration detail" and requires a lower SN curve than smooth steel (that is, under the same stress amplitude, the life is shorter); fatigue details are divided into different categories (such as categories W1 and W2), and each category corresponds to SN curve parameters.

[0150] The ratio of the actual number of cycles (ni) to the fatigue life (Ni) is taken as the damage contribution of the amplitude level, that is, the damage degree Di = ni ÷ Ni. For example, Δσ = 50MPa corresponds to ni = 500 times, Ni = times, then Di=500÷ The damage degrees of all stress amplitude levels are accumulated to obtain the total cumulative damage value Dtotal=D1+D2+...+Dn, where Dn is the damage degree of the nth stress amplitude.

[0151] In step 405, it is assumed that the total damage under the constant amplitude load is equal to the total damage under the variable amplitude load (Miner linear cumulative damage theory), that is, Dtotal = neq ÷ N(Δσeq), where neq is the equivalent number of cycles (taken as 1, that is, it is assumed to be equivalent to one constant amplitude cycle), and N(Δσeq) is the fatigue life corresponding to the equivalent stress amplitude.

[0152] Inverse Logic: By extrapolating the SN curve, the stress amplitude that makes N(Δσeq) = 1 ÷ Dtotal is found, which is the equivalent stress amplitude Δσeq. Taking into account factors such as the actual structure's size effect and surface roughness, the inverse result is corrected (for example, by multiplying it by a correction factor of 0.8-1.2) to ultimately determine the equivalent stress amplitude used for fatigue life prediction.

[0153] The analysis is based on the actual load spectrum of the target bridge (such as the vehicle load history), avoiding the deviation of relying on idealized load models (such as standard fatigue vehicles), making the fatigue damage calculation closer to the actual working conditions. The complex variable amplitude load is decomposed into discrete stress amplitude-cycle number combinations through the rain flow counting method, overcoming the limitation of the traditional SN curve that is only applicable to constant amplitude loads, and realizing the quantification of fatigue damage under variable amplitude loads. Combined with the corrected stress concentration factor (reflecting the stress amplification effect of the actual node structure), the accuracy of stress calculation in hot spots is ensured, avoiding the underestimation or overestimation of fatigue life caused by direct calculation of nominal stress. The equivalent stress amplitude simplifies the variable amplitude load into a single constant amplitude parameter, which can be directly substituted into the SN curve model to calculate fatigue life, providing intuitive quantitative indicators for bridge design and maintenance, and improving the efficiency of fatigue assessment.

[0154] In a preferred embodiment of the present invention, the above step 5, determining the fatigue life prediction value of the truss-chord composite beam according to the equivalent stress amplitude, may include:

[0155] Step 500: determining a target fatigue detail category based on the final equivalent stress amplitude, and obtaining a corresponding characteristic constant and slope index according to the fatigue detail category;

[0156] Step 501: constructing a SN curve model based on the characteristic constant and slope index, inputting the final equivalent stress amplitude into the SN curve model, and obtaining the theoretical number of cycles to failure based on the relationship between the final equivalent stress amplitude and the characteristic constant;

[0157] Step 502: Using the theoretical number of cycles to failure as a fatigue life prediction value of the truss-chord composite beam.

[0158] In this embodiment of the present invention, the target detail category is determined based on the structural characteristics of the truss-chord composite beam (such as the connection method between the corrugated steel web and the chord, and the weld type) and compared with the fatigue detail classification table in the standard. For example, if the connection node is "corrugated steel web and chord connected by a full penetration weld, and the weld surface is unpolished," it may correspond to "Category W" in the standard (assuming a high stress concentration category). The corresponding characteristic constant (C) and slope exponent (m) for this category are found in the standard table. For example, Category W may specify that when the stress ratio R = -1 (symmetrical cycle), C = 1×10¹² and m = 3 (this is for reference only; actual values ​​must be determined according to the standard). If there is no exact matching detail category in the standard, parameters must be adjusted through finite element stress analysis. For example, if the measured stress concentration factor of the node is 10% higher than the standard reference value, the characteristic constant C should be reduced accordingly (for example, to 0.9×10¹²) to reflect the more stringent fatigue performance.

[0159] Step 501: The SN curve model is based on the power function relationship: "The product of the stress amplitude m-th power and the fatigue life N is a constant C", that is, (Δσeq) m ×N=C. The final equivalent stress amplitude (Δσeq) comes from the calculation results of step 405; the characteristic constant C and slope exponent m come from the fatigue detail category of step 500 (such as C=1×10¹², m=3). The formula is transformed into N=C÷(Δσeq) m , substitute into numerical calculation.

[0160] Step 502: If Δσeq is close to the yield strength of the material (e.g. 345 MPa for Q345 steel), N should be less than 10 4 times (low cycle fatigue); if Δσeq is low (such as 50MPa), N should be greater than 10 6 times (high-cycle fatigue). Combined with the crack initiation location verification results from step 304, if the finite element model deviates significantly from the measured data, multiply N by a correction factor (e.g., 0.8-1.2). The calculated theoretical number of cycles to failure (e.g., 578,703) is used as the fatigue life prediction value, expressed in "times." To convert to actual service life, further calculation can be performed based on the structure's load cycle frequency (e.g., the average daily number of load cycles).

[0161] Based on the standardized fatigue detail classification system, the fatigue life prediction of composite beams with different structural forms is ensured to be consistent and comparable, avoiding errors caused by subjective judgment. By directly associating the characteristic constant and slope index through the fatigue detail category, there is no need to repeat material fatigue tests, which reduces design costs and improves engineering application efficiency. Combining the previous equivalent stress amplitude calculation (steps 400-405) with the model correction (steps 300-304), the measured load spectrum, structural parameter optimization and material fatigue performance are organically integrated to ensure that the prediction results are close to the actual structural behavior. The output fatigue life prediction value can be directly used for fatigue verification in the bridge design stage (such as comparing the expected number of load cycles within the design reference period) or residual life assessment in the maintenance stage, providing a clear quantitative basis for engineering decision-making.

[0162] like Figure 2 As shown, an embodiment of the present invention further provides a fatigue life prediction system for a truss-chord composite beam, comprising:

[0163] The finite element modeling module is used to establish a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord. The key structural parameters are the inclined web angle of the corrugated steel web, the curve connection radius, the plate thickness, the chord diameter, the steel tube wall thickness, and the concrete filling state inside the tube.

[0164] The parameter analysis module is used to analyze the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation. It is also used to determine the structural parameter combination of corrugated steel web and chord based on the structural characteristic data of existing concrete-filled steel tube truss composite beams.

[0165] The model correction module is used to construct a solid model based on the optimized combination of structural parameters, obtain the actual hot spot stress distribution data through static loading, and correct the stress concentration factor in the numerical simulation by combining the stiffness degradation characteristics and crack initiation location under repeated loading to obtain the corrected stress concentration factor;

[0166] The stress calculation module is used to calculate the equivalent stress amplitude of the corrugated steel web-chord connection area through load spectrum equivalent conversion based on the corrected stress concentration factor and the measured load spectrum data;

[0167] The life prediction module is used to determine the fatigue life prediction value of the truss-chord composite beam according to the equivalent stress amplitude.

[0168] It should be noted that this system is a system corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0169] An embodiment of the present invention further provides a computing device comprising: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the above-described method. All implementations in the above-described method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0170] The embodiment of the present invention further provides a computer-readable storage medium storing instructions, which, when executed on a computer, causes the computer to execute the above-described method. All implementations in the above-described method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0171] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A fatigue life prediction method for a truss-chord composite beam, characterized in that: The method comprises: Step 1: Establish a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord, and use the corrugated steel web inclined web inclination angle, curved connection radius, plate thickness, chord diameter, steel tube wall thickness, and concrete filling state as key structural parameters; Step 2: Analyze the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation, and determine the optimal structural parameter combination of corrugated steel web and chord based on the structural characteristic data of existing concrete-filled steel tube truss composite beams; Step 3, based on the optimized combination of structural parameters, constructing a solid model, obtaining actual hot spot stress distribution data through static loading, and correcting the stress concentration factor in the numerical simulation in combination with the stiffness degradation characteristics and crack initiation location under repeated loading to obtain a corrected stress concentration factor, including: constructing a solid model of a corrugated steel web-concrete-filled steel tube chord composite beam based on the optimized combination of structural parameters, wherein the weld geometry and dimensional parameters of the connection area between the corrugated steel web and the chord correspond to those of the finite element model; A two-point symmetrical static load test is applied to the solid model at the mid-span, and the load is applied in stages to the target stress amplitude. The measured value of the actual hot spot stress concentration coefficient is collected by a gradient strain sensor arranged at the junction of the arc transition section of the corrugated steel web and the chord weld. The measured value of the actual hot spot stress concentration coefficient is compared with the stress concentration coefficient of the same parameter combination in the test matrix. When the deviation between the measured value and the stress concentration coefficient of the same parameter combination is less than the first preset threshold, the original stress concentration coefficient is maintained. When the deviation exceeds the first preset threshold and is less than the second preset threshold, the stress concentration coefficient is corrected according to the proportional relationship between the measured value and the stress concentration coefficient of the same parameter combination to generate an intermediate correction value. When the deviation exceeds the second preset threshold, the finite element model parameters are adjusted and the stress concentration coefficient is recalculated. intermediate coefficient; based on the intermediate correction value, applying a constant amplitude cyclic load to the solid model, wherein the load amplitude is set according to the hot spot stress amplitude corresponding to the intermediate correction value; monitoring the stiffness degradation process, when the stiffness degradation rate reaches the critical point, using phased array ultrasonic scanning to locate the coordinates of the crack initiation position; comparing the crack initiation position coordinates with the coordinates of the maximum hot spot stress area corresponding to the intermediate correction value, if the spatial position deviation between the crack position coordinates and the stress area coordinates is within a preset range, outputting the intermediate correction value as the corrected stress concentration coefficient; if the deviation exceeds the preset range, iteratively executing the process of adjusting the finite element model parameters based on the crack position coordinates, recalculating the stress concentration coefficient and verifying the spatial position deviation until the deviation is within the preset range, and outputting the final corrected stress concentration coefficient; Step 4: Based on the corrected stress concentration factor and the measured load spectrum data, the equivalent stress amplitude of the corrugated steel web-chord connection area is calculated by load spectrum equivalent conversion; Step 5: Determine the fatigue life prediction value of the truss-chord composite beam based on the equivalent stress amplitude.

2. The fatigue life prediction method of the truss-chord composite beam according to claim 1, characterized in that: A finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord was established, and the inclination angle of the corrugated steel web, the curved connection radius, the plate thickness, the chord diameter, the steel tube wall thickness, and the concrete filling state in the tube were used as key structural parameters, including: Finite element analysis software was used to construct a three-dimensional solid model of the connection between the corrugated steel web and the chord. The corrugated steel web and weld area were divided using hexahedral elements. The steel tube of the concrete-filled steel tube chord was modeled using shell elements, and the concrete was modeled using solid elements. The interface contact behavior between the steel tube and concrete was also defined. The key structural parameters are the inclined web inclination angle, curve connection radius, plate thickness of the corrugated steel web, as well as the tube diameter of the chord, the wall thickness of the steel tube, and the state of the concrete filled in the tube.

3. The fatigue life prediction method of the truss-chord composite beam according to claim 2, characterized in that: Through numerical simulation analysis of the influence of key structural parameters on hot spot stress distribution and stress concentration factor, combined with the structural characteristic data of existing steel tube concrete truss composite beams, the optimal structural parameter combination of corrugated steel web and chord was determined, including: Based on the value range of key structural parameters, the inclined web angle, curved connection radius, plate thickness and chord tube diameter are used as experimental factors, and multiple levels are assigned to each factor to generate an experimental matrix containing different parameter combinations. Finite element static loading simulation was performed for each parameter combination. The loading method was symmetrical loading at two points in the mid-span, the boundary condition was simply supported, and the vertical load was applied step by step to the target stress amplitude. The hot spot stress distribution and stress concentration factor in the connection area between the corrugated steel web and the chord were recorded. According to the stress concentration factor, the influence of each parameter on the stress concentration factor is calculated to determine the degree of influence on the stress distribution, and the structural parameters whose change exceeds the preset threshold are regarded as the sensitivity parameter combination; Based on the sensitivity parameter combination, the finite element simulation results corresponding to the sensitivity parameter combination are compared with the measured data of the node stress of the existing steel tube concrete truss composite beam. The parameter combination whose spatial distribution trend of the simulated stress concentration factor is consistent with the measured data and whose deviation is within the preset range is taken as the optimized construction parameter combination.

4. The fatigue life prediction method of the truss-chord composite beam according to claim 3, characterized in that: Based on the corrected stress concentration factor and the measured load spectrum data, the equivalent stress amplitude of the corrugated steel web-chord connection area is calculated through load spectrum equivalent conversion, including: Obtain the measured dynamic strain time history data of the target bridge chord node and generate the nominal stress time history curve through material elastic modulus conversion; Extract stress cycle events from the nominal stress time history curve to generate a nominal stress amplitude sequence; Each stress value in the nominal stress amplitude sequence is fused with the corrected stress concentration factor to generate the actual stress amplitude sequence of the hotspot area; The actual stress amplitude series is processed by rain flow counting method, and the number of cycles corresponding to each stress amplitude level is counted to construct the stress amplitude-cycle number distribution spectrum; Based on each stress amplitude level and number of cycles in the stress amplitude-cycle number distribution spectrum, the fatigue damage degree corresponding to each stress amplitude level is calculated, and the fatigue damage degrees of all stress amplitude levels are accumulated to obtain the total cumulative damage value; Taking the total cumulative damage value equal to the critical damage state as the benchmark, the benchmark stress amplitude that produces equivalent damage under the action of constant amplitude load is reversed as the final equivalent stress amplitude.

5. The fatigue life prediction method of the truss-chord composite beam according to claim 4, characterized in that: Based on each stress amplitude level and number of cycles in the stress amplitude-cycle number distribution spectrum, the fatigue damage degree corresponding to each stress amplitude level is calculated, and the fatigue damage degrees of all stress amplitude levels are accumulated to obtain the total cumulative damage value, including: Determine the corresponding number of fatigue life cycles based on the current stress amplitude level; The actual number of cycles corresponding to the current stress amplitude level and the number of fatigue life cycles are proportionally combined to obtain the single-level damage degree; The single-level damage degree of each stress amplitude level is accumulated to generate the total cumulative damage value.

6. The fatigue life prediction method of the truss-chord composite beam according to claim 5, characterized in that: Based on the equivalent stress amplitude, the fatigue life prediction value of the truss-chord composite beam is determined, including: Based on the final equivalent stress amplitude, the target fatigue detail category is determined, and the corresponding characteristic constant and slope index are obtained according to the fatigue detail category; Based on the characteristic constant and slope index, the SN curve model is constructed, and the final equivalent stress amplitude is input into the SN curve model. According to the relationship between the final equivalent stress amplitude and the characteristic constant, the theoretical number of failure cycles is obtained; The theoretical failure cycles are used as the fatigue life prediction value of the truss-chord composite beam.

7. A fatigue life prediction system for a truss-chord composite beam, the system implementing the method according to any one of claims 1 to 6, characterized in that: include: The finite element modeling module is used to establish a finite element model of the connection node between the corrugated steel web and the concrete-filled steel tube chord. The key structural parameters are the inclined web angle of the corrugated steel web, the curve connection radius, the plate thickness, the chord diameter, the steel tube wall thickness, and the concrete filling state inside the tube. The parameter analysis module is used to analyze the influence of key structural parameters on hot spot stress distribution and stress concentration factor through numerical simulation. It is also used to determine the optimal structural parameter combination of corrugated steel web and chord based on the structural characteristic data of existing concrete-filled steel tube truss composite beams. a model correction module for constructing a solid model based on the optimized structural parameter combination, obtaining actual hot spot stress distribution data through static loading, and correcting the stress concentration factor in the numerical simulation based on the stiffness degradation characteristics and crack initiation location under repeated loading to obtain a corrected stress concentration factor; The stress calculation module is used to calculate the equivalent stress amplitude of the corrugated steel web-chord connection area through load spectrum equivalent conversion based on the corrected stress concentration factor and the measured load spectrum data; The life prediction module is used to determine the fatigue life prediction value of the truss-chord composite beam according to the equivalent stress amplitude.

8. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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