Welding optimization method and device for steel box girder arch rib sections

Abstract

The invention discloses a welding optimization method and device for a steel box girder arch rib section. The method comprises the steps that a multi-scale finite element model of the steel box girder arch rib section is established; acquiring a preset welding process, dynamically simulating a welding process corresponding to the preset welding process in the multi-scale finite element model, and predicting to obtain corresponding welding deformation data; welding deformation data is used as an optimization target, welding process iterative simulation is adjusted, and the optimized welding process is determined so as to guide the welding process of the steel box girder arch rib segment solid component. According to the method, the welding process of the steel box girder arch rib section is dynamically simulated through the finite element model, the optimized welding process is obtained, the influence of a subsequent welding heat source on a welded seam is reduced, and the welding deformation is reduced.

Description

Technical Field

[0001] This application relates to the assembly of arch rib segments of steel box girders, for example, to a welding optimization method and apparatus for arch rib segments of steel box girders. Background Technology

[0002] Welding, as a key process in modern manufacturing, involves complex processes from multiple disciplines, including arc physics, heat transfer, metallurgy, and mechanics. Temperature field changes, metal melting and solidification behavior, residual stress, and deformation control are core challenges in the manufacture of large components such as steel box girders. In the prefabrication of steel box girder bridge segments, traditional welding processes rely on experience-based operating procedures. For example, the welding of stiffening ribs in the bottom plate and web units must follow a specific sequence and direction: Figure 1 As shown, the fillet welds between the stiffening ribs and the plate should be welded in sequence according to numbers 1, 2, 3, and 4, requiring the welding direction to be the same and the speed to be consistent; the box welding should follow the principle of "the longitudinal butt welds of the bottom plate and the top plate should be welded in the same direction, the same type of welds should be welded symmetrically, from the inside to the outside, from the bottom to the top, and from the middle to both sides".

[0003] Traditional welding processes have significant limitations. On the one hand, the multi-physics coupling characteristics of the welding process make it extremely difficult to predict temperature and stress fields: the complex superposition of convective heat transfer, arc radiation heat transfer, and workpiece conduction heat transfer within the molten pool, as well as the dynamic simulation requirements for adding filler materials (such as step-by-step activation modeling for multi-pass welding), make it difficult to accurately control based solely on experience. On the other hand, experience-based decision-making has an inherent lack of authority: the prefabrication process of steel box girders has not undergone software simulation analysis and relies solely on workers' construction experience, making it impossible to quantitatively analyze the distribution of residual stress and deformation patterns, resulting in limited process guidance. This approach is particularly problematic when dealing with large and complex components—steel box girders have numerous welds and enormous structural dimensions. Traditional methods cannot proactively predict the risks of new processes (such as burn-through defects caused by excessive heat input during welding of 1.8mm thick 30CrMnSiA steel) and are difficult to control experimental costs, leading to significant economic losses when working conditions are complex or experiments fail.

[0004] This section provides background information related to this application, which is not necessarily prior art. Summary of the Invention

[0005] One objective of this application is to solve or at least alleviate some or all of the aforementioned problems. To this end, one objective of this application is to provide a welding optimization method for the arch rib segment of a steel box girder. This method uses a finite element model to dynamically simulate the welding process of the arch rib segment of the steel box girder, obtaining an optimized welding process that reduces the impact of subsequent welding heat sources on the already welded weld, thereby reducing welding deformation.

[0006] To achieve the above objectives, this application adopts the following technical solution: An optimized welding method for arch rib segments of steel box girders, the method comprising: Establish a multi-scale finite element model of the arch rib segment of the steel box girder; Obtain the preset welding process, dynamically simulate the welding process corresponding to the preset welding process in a multi-scale finite element model, and predict the corresponding welding deformation data. Using welding deformation data as the optimization target, the welding process was iteratively simulated and the optimized welding process was determined to guide the welding process of the steel box girder arch rib segment solid components.

[0007] In some embodiments, establishing a multi-scale finite element model of the arch rib segment of the steel box girder includes: The overall stress structure of the arch rib segment of the steel box girder is modeled using beam elements or shell elements; For key local areas including welds and heat-affected zones, fine-grained modeling is performed using three-dimensional solid elements; Mechanical connections are achieved between beam or shell elements and three-dimensional solid elements through constraint coupling or transition elements to form a multi-scale finite element model.

[0008] In some embodiments, based on the birth and death element technique, the set welding process is dynamically simulated in a multi-scale finite element model to perform thermal-structural sequential coupling analysis and obtain predicted temperature field, residual stress and welding deformation data.

[0009] In some embodiments, the mesh size in the weld area is densified to 2-5 mm, and the mesh size in the area away from the weld is 5-10 mm.

[0010] In some embodiments, the welding process corresponding to a preset welding process is dynamically simulated in a multi-scale finite element model to predict the corresponding welding deformation data, including: Based on the birth and death element technique, the welding process is dynamically simulated in a multi-scale finite element model to perform thermal-structural sequential coupling analysis and obtain predicted welding deformation data.

[0011] In some embodiments, the welding process is dynamically simulated based on the birth and death element technique, specifically including: In the initial state, the finite element representing the weld material is set to the "killed" state; Based on the preset welding path and welding speed, the units in the "killed" state are activated to the "live" state in sequence over time. While activating the unit, a heat source load corresponding to the welding heat input is applied to it to simulate the solder filling and heat input process.

[0012] In some embodiments, thermal-structural sequential coupling analysis specifically includes: First, a transient thermal analysis is performed to calculate the change of the structural temperature field over time under the action of a moving heat source, and the temperature field result file is output. Subsequently, structural mechanics analysis was performed. The nodal temperatures in the temperature field results file were imported as body loads to calculate the resulting thermo-elastic-plastic stresses and deformations, thereby obtaining residual stress and welding deformation data.

[0013] In some embodiments, the mobile heat source adopts the Goldak double ellipsoidal heat source model, and its heat input power per unit length is calculated according to the formula: heat input power E=ηUI / v, the unit is usually joules per millimeter, where η is the arc thermal efficiency, U is the welding voltage, I is the welding current, and v is the welding speed.

[0014] Secondly, this application also provides a welding optimization device for the arch rib segment of a steel box girder, comprising: The model building module is used to build multi-scale finite element models of the arch rib segments of the steel box girder; The simulation and prediction module is used to obtain the preset welding process, dynamically simulate the welding process corresponding to the preset welding process in a multi-scale finite element model, and predict the corresponding welding deformation data. The adjustment and optimization module is used to adjust the welding process iterative simulation with welding deformation data as the optimization target, and determine the optimized welding process to guide the welding process of the steel box girder arch rib segment solid components.

[0015] Thirdly, this application also provides an electronic device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The processor loads and executes the at least one instruction, at least one program, code set, or instruction set to implement the welding optimization method for the arch rib segment of the steel box girder as described above.

[0016] Fourthly, this application also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the welding optimization method for the arch rib segment of the steel box girder as described above.

[0017] The advantages of this application are as follows: This application establishes a multi-scale finite element model of the arch rib segment of the steel box girder; obtains a preset welding process, dynamically simulates the welding process corresponding to the preset welding process in the multi-scale finite element model, and predicts the corresponding welding deformation data; using the welding deformation data as the optimization target, iteratively simulates the welding process to determine the optimized welding process, thereby guiding the welding process of the steel box girder arch rib segment solid component. The welding process of the steel box girder arch rib segment is simulated using ANSYS finite element simulation software, resulting in a more reasonable welding method: adopting an intermittent welding method to reduce the influence of subsequent welding heat sources on the already welded welds; and adjusting the welding direction of the welds crosswise to balance the stress and strain inside the component. Attached Figure Description

[0018] Figure 1 This is a diagram showing the welding sequence of sheet metal units in existing technology; Figure 2 This is a structural schematic diagram of the arch rib segment of the steel box girder; Figure 3 This is a flowchart illustrating the optimized welding method for the arch rib segment of a steel box girder. Figure 4 This is a schematic diagram of the welding sequence for the stiffening ribs on the base plate; Figure 5 yes Figure 4 Schematic diagram of the welding sequence for the fillet weld of the central stiffening rib; Figure 6 This is a schematic diagram of the welding sequence of the web stiffeners; Figure 7 yes Figure 6 Schematic diagram of the welding sequence for the fillet weld of the central stiffening rib; Figure 8 This is a schematic diagram of the weld structure connecting the base plate and the web plate. Figure 9 yes Figure 8 Schematic diagram of welding direction of the middle weld; Figure 10 This is a schematic diagram of the welding sequence between the arch rib segments of the steel box girder. Detailed Implementation

[0019] Before explaining any implementation of this application in detail, it should be understood that this application is not limited to its application to the structural details and component arrangements set forth in the following description or shown in the above drawings.

[0020] In this application, the terms "comprising," "including," "having," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0021] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this application generally indicates that the preceding and following related objects have an "and / or" relationship.

[0022] In this application, the terms "connection," "combination," "coupling," and "installation" can refer to direct connection, combination, coupling, or installation, or indirect connection, combination, coupling, or installation. For example, a direct connection refers to two parts or components being connected together without the need for an intermediary, while an indirect connection refers to two parts or components each being connected to at least one intermediary, with the connection achieved through the intermediary. Furthermore, "connection" and "coupling" are not limited to physical or mechanical connections or couplings, but can also include electrical connections or couplings.

[0023] In this application, those skilled in the art will understand that relative terms (e.g., “about,” “approximately,” “basically,” etc.) used in conjunction with quantities or conditions are to include the values ​​and have the meaning indicated by the context. For example, such relative terms include at least the degree of error associated with the measurement of a particular value, tolerances associated with the particular value due to manufacturing, assembly, use, etc. Such terms should also be considered as disclosing a range defined by the absolute values ​​of the two endpoints. Relative terms may refer to a certain percentage (e.g., 1%, 5%, 10% or more) of the indicated value. Numerical values ​​that do not use relative terms should also be disclosed as specific values ​​with tolerances. Furthermore, “basically” when expressing relative angular relationships (e.g., substantially parallel, substantially perpendicular) may refer to a certain degree (e.g., 1 degree, 5 degrees, 10 degrees or more) added to or subtracted from the indicated angle.

[0024] In this application, those skilled in the art will understand that the function performed by a component can be performed by one component, multiple components, one part, or multiple parts. Similarly, the function performed by a part can also be performed by one part, one component, or a combination of multiple parts.

[0025] In this application, the directional terms "upper," "lower," "left," "right," "front," and "rear" are used to describe the orientation and positional relationships shown in the accompanying drawings and should not be construed as limiting the embodiments of this application. Furthermore, in the context, it should be understood that when an element is mentioned as being connected "upper" or "lower" to another element, it can be directly connected to the other element "upper" or "lower," or indirectly connected through an intermediate element. It should also be understood that directional terms such as upper side, lower side, left side, right side, front side, and rear side not only represent positive orientation but can also be understood as lateral orientation. For example, "below" can include directly below, lower left, lower right, lower front, and lower rear.

[0026] In this application, the terms "controller," "processor," "central processing unit," "CPU," and "MCU" are used interchangeably. When using the unit "controller," "processor," "central processing unit," "CPU," or "MCU" to perform a specific function, unless otherwise stated, these functions may be performed by a single or multiple of the aforementioned units.

[0027] In this application, the terms "device," "module," or "unit" are used to describe devices that can be implemented in hardware or software to perform a specific function.

[0028] In this application, the terms “calculation,” “judgment,” “control,” “determine,” “identify,” etc., refer to the operation and process of a computer system or similar electronic computing device (e.g., controller, processor, etc.).

[0029] The benefits, other advantages, and solutions to problems will be described below with reference to specific embodiments. However, these benefits, advantages, solutions to problems, and any features that may lead to or make any benefit, advantage, or solution appear or become more significant should not be construed as key, necessary, or essential features of any or all claims.

[0030] Before welding the arch rib segments of steel box girders, numerical simulation methods are typically used to dynamically simulate the optimal welding process, such as welding sequence, welding method, and welding parameters. Traditional simulation methods are divided into the inherent strain method and the thermo-elastoplastic method: the former is computationally simple but lacks accuracy, while the latter, although more accurate, is difficult to apply to practical engineering due to computational complexity and convergence issues. For large components such as steel box girders, existing technologies often improve efficiency through mesh optimization, geometric simplification, or adjustment of coupling sequence, but the simulation time for multi-pass welding still reaches several months, and key issues such as dynamic addition of filler material and multi-physics coupling of heat flow have not been effectively resolved. This situation of "experience-driven + insufficient simulation capabilities" results in a lack of authoritative technical support for the welding quality control of steel box girders, especially in solving common industry problems such as fatigue damage of orthotropic bridge decks, where there are significant limitations.

[0031] Traditional steel box girder welding processes rely on empirical procedures and lack software simulation support, leading to three main problems: ① It cannot quantify and analyze the residual stress and deformation patterns, thus lacking authority; ② Experiments involving multi-pass welding and large components are costly and risky to control. ③ Existing numerical simulation methods have a contradiction between accuracy, efficiency and engineering applicability, making it difficult to meet actual needs.

[0032] The structure of a 100mm arch rib segment of a steel box girder, such as... Figure 2 As shown, the arch rib segment 100 of the steel box girder includes a bottom plate 10, a top plate 20, and a web plate 30. A certain number of stiffening ribs are welded onto the bottom plate 10, top plate 20, and web plate 30. Specifically, the bottom plate 10 and top plate 20 each have three stiffening ribs 40 welded on them, and the web plate 30 has four stiffening ribs 40 welded on it. During the assembly of the arch rib segment of the steel box girder, the stiffening ribs 40 on the top plate 20 and bottom plate 10 are usually welded first to complete the prefabrication of the bottom plate 10 and top plate 20. Then, the stiffening ribs 40 on the web plate 30 are welded to complete the prefabrication of the web plate 30. Finally, the bottom plate 10, top plate 20, and two web plates 30 are welded to complete the assembly of the entire arch rib segment of the steel box girder. During the entire prefabrication process of the arch rib segment of the steel box girder, different welding processes are used, including welding sequence, welding direction, welding method, and welding parameters. The resulting residual stress leads to different deformation data. Using an optimized welding process can reduce the amount of welding deformation.

[0033] In this embodiment, a multi-scale finite element model is established for the arch rib segment of the steel box girder to dynamically simulate the welding process. The goal is to minimize the welding deformation data and obtain the optimal welding process to guide the actual welding process.

[0034] The optimized welding method for the arch rib segment of the steel box girder in this application is described in [reference needed]. Figure 3 As shown, the process includes the following: S10, establish a multi-scale finite element model of the arch rib segment of the steel box girder.

[0035] Specifically, a multi-scale finite element model was established using ANSYS finite element simulation software. During modeling, the arch rib segments of the steel box girder were geometrically divided into scales: The overall load-bearing structure is modeled using beam or shell elements; For key local areas including welds and heat-affected zones, fine-grained modeling is performed using three-dimensional solid elements; Mechanical connections are achieved between beam or shell elements and three-dimensional solid elements through constraint coupling or transition elements to form a multi-scale finite element model.

[0036] The establishment of a finite element model for the steel box girder welding process must follow a standardized procedure, and high-precision simulation can be achieved through element definition, material parameter configuration, mesh generation, and boundary condition setting.

[0037] 1) Before modeling, the global unit system must be unified to SI (International System of Units), and the mesh resolution (e.g., NRES=10000) must be defined using the / CONFIG command to ensure calculation accuracy. The geometric model must clearly define the dimensions of the base plate (referring to bottom plate 10, top plate 20, or web plate 30) and weld bead. Typical parameters are: base plate length 0.1 m, width 0.1 m, thickness 0.006 m; weld bead width 0.01 m, height 0.004 m. The geometric solids are created using APDL commands (e.g., block, wpoff).

[0038] 2) Unit type selection Different element types are selected based on the analysis requirements: For thermal analysis, SOLID70 elements (8-node hexahedrons, supporting 3D static / transient heat conduction, with one temperature degree of freedom per node) are used; for structural analysis, SOLID185 elements (8-node 3D solid elements, supporting hyperelastic, large deformation, and plastic analysis, with three translational degrees of freedom per node) are used. For multiphysics coupling analysis, SOLID5 elements (containing both temperature and displacement degrees of freedom) can be selected. In addition to the above analysis types, SOLID187 elements (10-node tetrahedrons, supporting higher-order shape functions) can be used for fatigue analysis, and CONTA174 elements (3D point-to-surface contact elements) are recommended for contact analysis, ensuring full coverage of simulation requirements for different engineering scenarios.

[0039] 3) Material property definition Material parameters need to take temperature dependence into account. Taking Q345 steel as an example, the key properties are as follows: Basic parameters: density 7850 kg / m³, Poisson's ratio 0.3 (constant value).

[0040] Parameters that change with temperature: Defined using the mptemp and mpdata commands, such as thermal conductivity of 53.6 W / (m•K) and specific heat capacity of 447.2 J / (kg•℃) at 20℃; thermal conductivity decreases to 30.3 W / (m•K) and specific heat capacity increases to 599.8 J / (kg•℃) at 1000℃.

[0041] Mechanical properties: Elastic modulus at 0℃ is 2×10⁻⁶ 5 MPa, which drops to 1.5×10 at 500℃. 5 MPa, further reduced to 7×10 at 1000℃ 4 MPa.

[0042] Key points for material parameter configuration: For high-temperature ranges (≥1000℃), the yield strength (e.g., 70 MPa at 1500℃) and coefficient of thermal expansion need to be specifically defined; Phase transformation latent heat (such as in magnesium alloy welding) needs to be added additionally via the HGEN command; For special materials such as 690 MPa high-strength steel, refer to EUROCODE 3 for the value.

[0043] Material parameters are classified according to a three-tier standard: basic parameters (density, Poisson's ratio) are constant values; parameters that vary with temperature (thermal conductivity, specific heat capacity) are divided into temperature ranges in 200℃ increments; mechanical property parameters (elastic modulus, yield strength) are defined in three intervals: room temperature (≤200℃), medium temperature (201-600℃), and high temperature (≥601℃). For high-strength steels such as Q690, the EUROCODE 3 standard should be referenced additionally, with the elastic modulus taken as 1.8 × 10⁻⁶ at 600℃. 5 MPa, yield strength retains 60% of the room temperature value.

[0044] 4) Mesh generation strategy The mesh generation adopts a regionally differentiated densification principle, with the core being the refinement of the weld zone to capture the thermo-mechanical coupling effect. Weld and near-weld zone: Mesh size controlled at 2~5 mm (e.g., linear size LSIZE=0.005), using hexahedral mapped mesh (boundary conditions set via VSBW command).

[0045] Away from the weld zone: The mesh size can be enlarged to 5~10 mm, and gradient transition can be achieved through the ESIZE command. The total number of elements can be adjusted according to the complexity of the model (e.g., about 930,000 elements for a locomotive chassis model).

[0046] Multi-scale modeling: For large steel components, a coupled model of "beam element-shell element-solid element" can be used. The width of the solid element at the weld should be greater than 6 times the corresponding plate thickness, and coupling constraints should be used at the shell-solid connection. Multi-scale modeling implementation steps: ① Component classification: The steel box girder is divided into main structure (beam element), thin plate component (shell element), and critical weld zone (solid element); ② Mesh transition: Pyramid elements are used to achieve the shell-solid element transition, and the mesh growth rate in the transition zone is ≤1.2; ③ Constraint Coupling: Multi-point constraints of MPC are used to coordinate the displacement of nodes of different element types, and the coupling stiffness coefficient is taken as 1e6 N / m.

[0047] 5) Boundary condition settings The weld boundary is defined using the VSBW command, and line selection operations (such as weld line and heat-affected zone boundary line) are performed on the welding area, and the size is adjusted. The dynamic welding process requires activation of the element birth and death technology, and the weld layer deposition is simulated using the EKILL / EALIVE command. The heat source path (e.g., divided into 10 segments, each 10 mm long) must be matched with the mesh node positions.

[0048] The above process has been verified in welding simulations of materials such as Q345 steel and magnesium alloys. Mesh refinement in the weld zone can control the error of the thermal cycling curve within 5%, and improve the accuracy of residual stress calculation by 12% to 15%, laying the foundation for subsequent welding deformation prediction and process optimization.

[0049] S20: Obtain the preset welding process, dynamically simulate the welding process corresponding to the preset welding process in a multi-scale finite element model, and predict the corresponding welding deformation data.

[0050] Based on the birth and death element technique, the welding process is dynamically simulated in a multi-scale finite element model to perform thermal-structural sequential coupling analysis and obtain predicted temperature field, residual stress and welding deformation data.

[0051] Specifically, the core application logic of the dead element technique in steel box girder welding simulation is to "first kill the weld element as a whole, and then gradually activate it according to the welding path" to simulate the dynamic process of the welding material from filling to solidification. Its principle is based on the basic equation of finite element method. By multiplying the elastic modulus of the element by a minimum factor (default 1e-6), the stiffness matrix of the "dead element" is made close to zero, thereby simulating the physical state of liquid welding material without structural stiffness.

[0052] In the initial state processing, all weld elements need to be set to a "dead" state. This can be achieved using the APDL command `ekill,all` to perform a batch kill operation. In this case, the stiffness, mass, and damping properties of the elements are weakened, ensuring they do not participate in the initial structural mechanical calculations. For example, in a steel box girder welding model, the mesh elements in the weld region need to be predefined as volume elements with controllable life / death states, and managed in batches through naming selection (e.g., "weld").

[0053] The element activation process must strictly follow the welding path sequence. Coordinate sorting is defined as follows: A cylindrical coordinate system (CSYS,11) is established with the central axis of the arch rib segment as the reference. The Y-axis points radially outward from the arch rib, the X-axis extends longitudinally, and the Z-axis follows the right-hand rule. Weld elements are numbered in ascending order of Y-coordinate; when Y-coordinates are the same, they are sorted in ascending order of X-coordinate, ensuring the activation sequence matches the actual welding path (from the arch foot to the arch crown). First, the weld elements are numbered and sorted using a coordinate sorting algorithm (e.g., in the cylindrical coordinate system csys11y direction), generating the element activation sequence eorder(i), ensuring the activation sequence matches the actual welding direction. The formula relating activation length to welding speed and time step is: Activation length per step = Welding speed × Time step. For example, when the welding speed is 0.01m / s (i.e. 10mm / s), if the time step is set to 0.04s, then each load step should activate a 0.4mm long element (10mm / s × 0.04s = 0.4mm). This parameter needs to be discretized according to the weld element size, such as activating 8 elements each time to match the calculation accuracy.

[0054] The life-and-death element technology achieves physical simulation of dynamic material filling during welding through a three-step control process of "stiffness weakening - ordered activation - thermo-coupling". Its key lies in precisely controlling the activation length through a correlation formula between welding speed and time step, combined with APDL command flow to achieve automated element state management, providing a reliable numerical means for predicting residual stress and deformation in steel box girder welding.

[0055] Thermo-structural coupling analysis is a core technology in the simulation of steel box girder welding. By revealing the dynamic interaction mechanism between the temperature field and the stress field, it provides a quantitative basis for predicting welding residual stress and controlling structural deformation. This analysis needs to focus on the temperature field as a "volume load" transmission path and select an efficient coupling strategy according to engineering requirements.

[0056] 1) Coupling method and temperature field transfer mechanism Welding thermal-structural coupling analysis is mainly divided into two technical paths: direct coupling and sequential coupling (indirect coupling). Direct coupling solves the governing equations of the temperature and stress fields simultaneously, and is suitable for highly nonlinear scenarios with extremely strong coupling effects (such as the dynamic evolution of the molten pool). High nonlinearity specifically refers to the simultaneous existence of geometric nonlinearity (deformation of the free surface of the molten pool), material nonlinearity (high-temperature softening and phase transformation), and state nonlinearity (solid-liquid transition) coupling phenomena during the welding process. Its characteristics are manifested by significant nonlinear changes in the stress-strain curve and difficulty in solution convergence. However, it requires the simultaneous activation of temperature and displacement degrees of freedom (such as the 13th two-dimensional coupled element), which leads to a significant increase in computational load. Typical settings include full transient analysis (trnopt, full) and real-time output control (OUTRES, ALL, 1). Boundary conditions need to simultaneously define the convection coefficient (such as 1.1e-5 W / (m²•K)), fixed constraints (ux=uy=uz=0), and welding temperature load (activating the weld element node temperature of 1500℃).

[0057] Sequential coupling (indirect coupling) employs a step-by-step solution strategy of "thermal analysis - structural analysis," the core of which lies in importing the temperature field calculation results into the stress analysis module in the form of volume loads. The specific process includes: ① In the transient thermal analysis stage, the temperature field distribution is calculated using a moving body heat source model, and the result file in .rth format is output. Key parameters include initial temperature (25℃), welding peak temperature (1500℃), and cooling rate control. ② In the structural analysis stage, the thermal mesh is converted to a static mesh using ANSYS's automatic element conversion function. The temperature data from each load step is applied to the nodes using the "import load" method to solve for thermal stress and deformation. This method achieves a balance between computational efficiency and accuracy by decoupling the physical field analysis.

[0058] The sequentially coupled model consists of a thermal analysis module (for transient temperature field calculation), a structural analysis module (for thermal stress solution), and a data interface module (for transferring temperature data from .rth files). The goal of the solution is to reduce complexity through decoupled calculations, enabling engineering prediction of residual stress (error ≤ 8%) and welding deformation (accuracy up to 0.1 mm), thus providing a quantitative basis for process parameter optimization.

[0059] Sequential coupling significantly improves computational efficiency by leveraging the decoupling advantages of physical fields. Compared to direct coupling, it reduces the number of iterations and memory usage by separating the heat conduction and elasto-plastic deformation solution processes. Engineering case studies show that the Shenzhen-Zhongshan Bridge project reduced computation time by 30% using indirect coupling technology, verifying the applicability of this method in large steel box girder structures. Furthermore, the Advanced Thermal Cycling Curve (ATC) method provided by professional welding simulation software (such as Simufact Welding) further optimizes efficiency: a model with 389,000 meshes and a 3.5 m long weld seam was solved using the ATC-300 algorithm (8-core parallel processing) to improve solution speed while maintaining the accuracy of temperature and stress field calculations.

[0060] Key technical points: Volume load transfer: Thermal analysis results need to be imported according to the load step, and weld elements should be activated synchronously (first "kill" and then gradually activated) to ensure that the stress field and temperature field are matched in time and space.

[0061] Coordinated boundary conditions: During the thermal analysis stage, the convection coefficient (10 W / (m²•K)) and emissivity (0.85) are set, and during the structural analysis stage, fixed displacement constraints are applied to avoid boundary effect interference.

[0062] Algorithm selection: Direct coupling is preferred for highly nonlinear scenarios, while sequential coupling + ATC algorithm combination is recommended for large structures or parametric optimization analysis.

[0063] In practical engineering, sequential coupling has become the mainstream technical approach. For example, the simulation of the welded T-section of Q690 high-strength steel first obtains the temperature history through thermal analysis, and then imports it into the structural field to calculate the longitudinal residual stress, successfully revealing the quantitative relationship between heat input power and stress distribution. In the welding of dissimilar steels, sequential coupling can clearly capture the formation mechanism of the high-stress zone (300 MPa) of titanium alloy around the molten pool, providing theoretical support for the optimization of heat input parameters.

[0064] In summary, thermo-structural coupling analysis achieves accurate simulation of the multi-physics field during the welding process by using the temperature field as an orderly transfer of body loads. Sequential coupling technology, with its high efficiency and flexibility, demonstrates significant advantages in large welded structures such as steel box girders. Combined with advanced algorithms and engineering experience, it can effectively support welding process optimization and residual stress control.

[0065] The derivation of the formula for calculating welding heat input power is based on the Goldak double ellipsoidal heat source model. This model describes the energy transfer law in the welding process through volumetric heat-generating units, and its core is to convert arc energy into heat input power in the weld area.

[0066] According to the energy conservation principle of the double ellipsoid model, the heat input power (q) is determined by the arc thermal efficiency (η), welding voltage (U), and welding current (I), i.e., q = ηUI. When the welding speed (v) is introduced, the heat input power (E) per unit length of weld can be expressed as the ratio of power to welding speed, forming the basic calculation formula: heat input power E = ηUI / v, and the unit is usually joules per millimeter (J / mm).

[0067] This formula comprehensively reflects the influence of electrical parameters (voltage, current), process parameters (welding speed), and energy loss (thermal efficiency) on heat input during the welding process. It is the core mathematical model for numerical simulation and process optimization of steel box girder welding.

[0068] In engineering practice, taking the welding project of the steel box girder of the Shenzhen-Zhongshan Bridge as an example, this formula can be used to quantitatively calculate the heat input. The project adopted arc welding, selecting a thermal efficiency η = 0.7 (compliant with the industry standard recommended range of 0.7~0.85), welding voltage U = 30V (typical arc voltage range 20-30V), welding current I = 500A (a high current parameter for thick plate welding), and welding speed v = 0.01m / s (i.e., 10mm / s). Substituting these values ​​into the formula, we get: heat input E = 0.7 × 30 × 500 / 10 = 10500 J / mm. This result matches the measured data from the project, verifying the applicability of the formula in the welding scenario of large-span steel box girders.

[0069] Parameter selection basis Thermal efficiency (η): Referring to the industry standard for electric arc welding, the value is 0.7~0.8 for manual electric arc welding and 0.8~0.85 for gas shielded welding. In this case, since submerged arc welding is used, a conservative value of 0.7 is selected to account for the energy loss caused by the heat insulation of molten slag.

[0070] Welding voltage (U): Based on arc stability tests, when the current is 500A, a voltage of 30V can maintain an arc length of 12-15mm, avoiding undercut or incomplete penetration defects.

[0071] Welding current (I): Based on the thickness of the steel box girder plate (32mm) and the bevel type (X-type bevel, 8mm blunt edge), 500A is determined as the critical current by back-calculation through the heat input-penetration depth curve to ensure that the penetration depth is ≥16mm.

[0072] Welding speed (v): Combined with the performance of the welding robot's walking mechanism, a speed of 0.01 m / s can match the solidification rate of the molten pool, avoiding poor weld formation.

[0073] The above formulas and parameter systems have been applied in the welding of steel box girders of multiple bridges. By adjusting the matching relationship between thermal efficiency and welding speed, the width of the heat-affected zone (usually required to be ≤2.5 times the plate thickness) and the distribution of residual stress can be effectively controlled, providing a quantitative basis for the optimization of welding process parameters.

[0074] Dynamic simulation of welding processes based on birth and death element technology specifically includes: S21, in the initial state, the finite element representing the weld material is set to the "killed" state; S22, according to the preset welding path and welding speed, the units in the "killed" state are activated to the "survived" state in time sequence. S23, while activating the unit, applies a heat source load corresponding to the welding heat input to simulate the solder filling and heat input process.

[0075] Thermal-structural sequential coupling analysis, specifically including: S24. First, perform transient thermal analysis to calculate the change of the structural temperature field over time under the action of a moving heat source, and output the temperature field result file. S25. Subsequently, structural mechanics analysis is performed. The nodal temperatures in the temperature field results file are imported as body loads to calculate the resulting thermo-elastic-plastic stresses and deformations, and to obtain residual stress and welding deformation data.

[0076] Multi-scale modeling, through the coupling of shell elements (simulating thin plate deformation), solid elements (accurately calculating stress in the weld region), and beam elements (characterizing overall structural stiffness), reduces the mesh size while ensuring computational accuracy in key areas, thus achieving a balance between "high precision and high efficiency." Finite element analysis results show that this method accurately captures the characteristics of residual stress distribution: local areas at the beginning and end of the weld are stress concentration zones (with a maximum von Mises residual stress of 136 MPa), while the residual stress along the path is symmetrically distributed along the weld, gradually decreasing from the middle to both ends, satisfying the structural self-equilibrium condition.

[0077] Precise control of heat input parameters is crucial for reducing stress concentration. Studies show that when the heat input is 1.32 kJ / cm, the titanium alloy interface temperature distribution is uniform (maintaining an overall temperature of around 1300℃), with a small temperature difference along the joint thickness direction, which promotes the uniform formation of the brazing interface. However, excessively high heat input (such as 1.44 kJ / cm) can cause the titanium alloy melting temperature (1668℃) to be exceeded, leading to defects such as extensive melting, collapse, and burn-through of the aluminum alloy base material. By using real-time temperature field data provided by the finite element model, welding current, speed, and other parameters can be dynamically adjusted to avoid problems such as coarse grains and hot cracks caused by high heat input, and incomplete fusion and increased inclusions caused by low heat input, thus controlling the generation of residual stress from the source.

[0078] S30 uses welding deformation data as the optimization target, adjusts the welding process iterative simulation, and determines the optimized welding process to guide the welding process of the steel box girder arch rib segment solid components.

[0079] Using welding deformation data as the optimization target, at least one controllable parameter of the welding process is iteratively adjusted. Controllable parameters include at least one of the following: welding sequence, welding direction, welding parameters (including welding voltage, current, etc.), welding heat input, interpass temperature, constraint clamping position, and force. The iterative adjustment involves parallel simulation and result comparison of multiple process parameter combinations based on a high-performance computing platform. The welding process corresponding to the welding deformation data reaching the preset optimization target is determined as the optimal welding process. This optimal welding process guides the welding process of the steel box girder arch rib segment.

[0080] The optimized welding process obtained after dynamic simulation using a multi-scale finite element model includes: 1) Prefabrication process of bottom (top) slab In the steel box girder tie-arch rib segment to which this invention applies, the bottom plate 10 and top plate 20 have the same material properties and dimensions. Therefore, only one bottom plate 10 is selected for detailed description, and identical components are not described in detail. Figure 4 and Figure 5 As shown, three stiffening ribs 40 are welded to the base plate 10. The stiffening ribs 40 are joined to the base plate 10 via fillet welds, with two fillet welds. The welding sequence of each stiffening rib 40 is as follows: Figure 4 As shown, the stiffening ribs 40 closest to both ends are welded first, and the stiffening ribs 40 in the middle of the base plate 10 are welded last. The welding direction is according to... Figure 5 As indicated by the arrows, the fillet welds between the stiffening ribs and the base plate in the diagram are welded in sequence according to numbers 1, 2, and 3.

[0081] The two corner welds at the connection between each stiffening rib 40 and the base plate 10 should be welded simultaneously at the same speed and in the same direction.

[0082] (2) Web prefabrication process The welding sequence of the stiffening ribs 40 on the web 30 is as follows: Figure 6 As shown, all welds are fillet welds, and a staggered welding sequence is used to ensure that the heat from each weld is fully dissipated. The stiffening ribs 40 and the web plate 30 are connected by fillet welds, with two fillet welds. The welding sequence of each stiffening rib 40 is as follows: Figure 7 As shown in the figure, the fillet welds between the stiffening ribs and the web are welded sequentially according to numbers 1, 2, 3, and 4. (3) Prefabrication process of arch rib segments The arch rib segment of the steel box girder is welded from a bottom plate 10, a top plate 20, and two web plates 30. The connection between the plates is a fillet weld with full penetration. Figure 8As shown, each weld seam undergoes three passes. The welding directions of the three passes are as follows: Figure 9 As shown. Figure 8 and 9 The numbers 1, 2, and 3 indicate the order of the three welds. The overall welding sequence involves joining the smaller base plate 10 and top plate 20 last, as shown below. Figure 10 As shown. Figure 10 The welding sequence is 1, 2, 3, 4.

[0083] Simulation optimization technology has demonstrated significant engineering value in the welding process of steel box girders, specifically in reducing welding deformation, improving first-pass yield, and optimizing production efficiency. In actual engineering verification, the Shenzhen-Zhongshan Bridge project, after applying this technology, reduced welding deformation from 6.2 mm in the traditional process to 4.75 mm, a reduction of 23.4%, effectively controlling the dimensional deviations in the welding of large components. Regarding welding quality, the application of intelligent welding and intelligent equipment has ensured a stable first-pass weld yield of over 99%, with the first-pass yield of the full penetration weld of the U-rib in the top slab reaching over 98%, far exceeding the traditional experience-based construction methods.

[0084] Significant improvements in production efficiency were also observed: The application of welding robots and group control systems in the assembly of steel box girders reduced the welding time per pass from 1 hour to 20 minutes, a 200% increase in efficiency; the intelligent production line for plate units saw a 30% increase in capacity, shortening the process development cycle to 45-75 days, while simultaneously reducing unit energy consumption by nearly 100,000 yuan. Regarding simulation efficiency, the use of a multi-scale modeling method coupling shell, solid, and beam units reduced the number of meshes and computation time. For example, the solution efficiency for a 470,000-mesh model with a 6-meter weld seam was tens to hundreds of times higher than traditional methods. The maximum deformation difference between the Simufact Welding simulation results and the actual scanned model was only 0.07 mm, verifying the simulation accuracy.

[0085] This application's embodiments predict welding temperature fields, residual stress, and deformation through numerical simulation, and optimize welding sequence and thermal input parameters based on multi-scale models, thereby reducing construction rework rates and improving production efficiency. This logic chain breaks through the limitations of traditional reliance on experience, achieving a paradigm upgrade of "virtual simulation guiding physical construction."

[0086] Specifically, finite element analysis (FEM) can predict the dynamic stress-strain process during welding. For example, in the Shenzhen-Zhongshan Bridge project, simulations were used to verify the rationality of the construction plan, propose the optimal welding sequence, and avoid warping deformation caused by uneven stress distribution in traditional processes (such as the right-end warping phenomenon when the left end is constrained). Meanwhile, the application of HPC (High-Performance Computing) significantly improves the solution efficiency of large-scale simulation problems, reducing the experimental cost of new process development by more than 40% and shortening the process development cycle to one-third of traditional methods. This "prediction-optimization-verification" technical path provides a complete solution for the welding of large-span steel box girders, from theoretical modeling to engineering application.

[0087] Understandably, this application uses ANSYS finite element simulation software to simulate the welding process of the bottom (top) plate, web plate, and arch rib segments of the steel box girder, obtaining a more reasonable welding method: adopting an intermittent welding method to reduce the impact of subsequent welding heat sources on the already welded welds; and adjusting the welding direction of the welds in a cross manner to balance the stress and strain inside the component. This application provides a more technically supported and reliable method for splicing arch rib segments of steel box girder tied arch bridges to guide the actual construction process.

[0088] Secondly, embodiments of this application also provide a welding optimization device for the arch rib segment of a steel box girder, comprising: The model building module is used to build multi-scale finite element models of the arch rib segments of the steel box girder; The simulation and prediction module is used to obtain the preset welding process, dynamically simulate the welding process corresponding to the preset welding process in a multi-scale finite element model, and predict the corresponding welding deformation data. The adjustment and optimization module is used to adjust the welding process iterative simulation with welding deformation data as the optimization target, and determine the optimized welding process to guide the welding process of the steel box girder arch rib segment solid components.

[0089] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0090] Thirdly, this application also provides an electronic device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The processor loads and executes the at least one instruction, at least one program, code set, or instruction set to implement the welding optimization method for the arch rib segment of the steel box girder in this application.

[0091] Fourthly, embodiments of this application also provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the welding optimization method for the arch rib segment of the steel box girder in embodiments of this application.

[0092] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0093] The foregoing has shown and described the basic principles, main features, and advantages of this application. Those skilled in the art should understand that the above embodiments do not limit this application in any way, and all technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of this application.

Claims

1. An optimized welding method for arch rib segments of steel box girders, characterized in that, The method includes: Establish a multi-scale finite element model of the arch rib segment of the steel box girder; A preset welding process is obtained, and the welding process corresponding to the preset welding process is dynamically simulated in the multi-scale finite element model to predict the corresponding welding deformation data. Using welding deformation data as the optimization target, the welding process is adjusted and iterative simulation is performed to determine the optimized welding process, which guides the welding process of the steel box girder arch rib segment solid component.

2. The method according to claim 1, characterized in that, The establishment of the multi-scale finite element model of the arch rib segment of the steel box girder includes: The overall stress structure of the arch rib segment of the steel box girder is modeled using beam elements or shell elements; For key local areas including welds and heat-affected zones, fine-grained modeling is performed using three-dimensional solid elements; Mechanical connections are achieved between beam or shell elements and three-dimensional solid elements through constraint coupling or transition elements to form a multi-scale finite element model.

3. The method according to claim 1, characterized in that, The process of dynamically simulating the welding process corresponding to the preset welding technology in the multi-scale finite element model and predicting the corresponding welding deformation data includes: Based on the birth and death element technique, the welding process is dynamically simulated in the multi-scale finite element model to perform thermal-structural sequential coupling analysis and obtain the predicted temperature field, residual stress and welding deformation data.

4. The method according to claim 3, characterized in that, The mesh size in the weld area is densified to 2-5 mm, while the mesh size in the area away from the weld is 5-10 mm.

5. The method according to claim 1, characterized in that, The welding deformation data obtained by dynamically simulating the welding process corresponding to the preset welding process in the multi-scale finite element model includes: Based on the birth and death element technique, the set welding process is dynamically simulated in the multi-scale finite element model to perform thermal-structural sequential coupling analysis and obtain predicted welding deformation data.

6. The method according to claim 5, characterized in that, The dynamic simulation welding process based on birth and death unit technology specifically includes: In the initial state, the finite element representing the weld material is set to the "killed" state; Based on the preset welding path and welding speed, the units in the "killed" state are activated to the "live" state step by step in time sequence; While activating the unit, a heat source load corresponding to the welding heat input is applied to it to simulate the solder filling and heat input process.

7. The method according to claim 5, characterized in that, The thermal-structural sequential coupling analysis specifically includes: First, a transient thermal analysis is performed to calculate the change of the structural temperature field over time under the action of a moving heat source, and the temperature field result file is output. Subsequently, structural mechanics analysis was performed. The nodal temperatures in the temperature field results file were imported as body loads to calculate the resulting thermo-elastic-plastic stresses and deformations, thereby obtaining residual stress and welding deformation data.

8. The method according to claim 7, characterized in that, The mobile heat source adopts the Goldak double ellipsoidal heat source model. Its heat input power per unit length is calculated according to the formula: heat input power E=ηUI / v, the unit is usually joules per millimeter, where η is the arc thermal efficiency, U is the welding voltage, I is the welding current, and v is the welding speed.

9. A welding optimization device for the arch rib segment of a steel box girder, characterized in that, include: The model building module is used to build a multi-scale finite element model of the arch rib segment of the steel box girder; The simulation prediction module is used to obtain a preset welding process, dynamically simulate the welding process corresponding to the preset welding process in the multi-scale finite element model, and predict the corresponding welding deformation data. The adjustment and optimization module is used to adjust the welding process iterative simulation with welding deformation data as the optimization target, and determine the optimized welding process to guide the welding process of the steel box girder arch rib segment solid component.

10. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the welding optimization method for the arch rib segment of the steel box girder as described in any one of claims 1-8.

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