Composite steel bridge deck slab welding joint structure performance prediction method based on numerical simulation

Abstract

The invention provides a numerical simulation-based composite steel bridge deck slab welding joint structure performance prediction method. The method mainly comprises the following steps of: establishing a composite steel bridge deck slab welding joint three-dimensional geometric model; carrying out regional division on the three-dimensional geometric model according to the influence amplitude of the thermal-mechanical coupling effect on the structure in the welding operation, and carrying out regional dispersion to form a three-dimensional welding finite element model; setting initial welding temperature, boundary conditions and process parameters; a welding bead track is set, a heat source load is applied, and a solving task is configured based on a thermal-mechanical coupling solving strategy of a material CCT curve; carrying out simulated welding according to preset welding process parameters; and predicting the welding node performance and the failure risk area of the welding structure according to the simulation welding result. According to the method, through a thermal-mechanical coupling numerical simulation technology, welding process parameters are accurately controlled, based on a material CCT curve strategy, accurate quantitative calculation of a post-welding microstructure is achieved, the macroscopic performance is further predicted through a microstructure evolution law, and the adaptive capacity of a welding node in a complex environment is guaranteed from the microcosmic-macroscopic multi-scale level.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of welding numerical simulation and metal composite materials, specifically involving a method for predicting the microstructure and properties of welded joints in stainless steel composite bridge decks based on numerical simulation, particularly focusing on the welding deformation coordination mechanism and performance prediction at the composite interface of composite steel bridge decks. Background Technology

[0002] In bridge construction, stainless steel composite bridge decks are widely used in cold and corrosive environments due to their advantages such as lightweight, high strength, and strong corrosion resistance. However, due to the significant differences in physical and chemical properties between the cladding stainless steel and the base carbon steel, problems such as heat conduction mismatch, interfacial stress concentration, and deterioration of microstructure and properties are encountered during the composite interface welding process, resulting in brittle and hard microstructures and large residual stress and residual deformation near the weld joint.

[0003] Performance degradation and high residual stress at the composite interface of welded joints may reduce the overall load-bearing capacity and deformation coordination performance of composite steel bridge decks. Existing technologies lack interface thermal resistance compensation algorithms, dynamic heat source energy distribution strategies, and microstructure-joint performance correlation models for composite steel bridge decks. Quantitative analysis of the performance degradation mechanism and residual stress and deformation distribution patterns at the composite interface of welded joints of composite steel bridge decks presents certain difficulties.

[0004] With the rapid development of computer and numerical simulation technology, by establishing a physical model of the welding process of composite steel bridge decks and solving the physical model using appropriate numerical methods, various state variables in the solution domain can be obtained. This allows for the accurate prediction of temperature, stress, microstructure and deformation distribution near the welding nodes during the welding process, thus making up for the shortcomings of traditional experimental methods and theoretical calculations. Summary of the Invention

[0005] This invention addresses the problems of thermal stress concentration, heat-affected zone microstructure deterioration, and weld joint performance fluctuations caused by the significant property differences between the cladding stainless steel and the base low-alloy steel materials during the welding process of stainless steel composite bridge decks. It proposes a welding process design and performance prediction method based on thermo-mechanical coupling numerical simulation. By establishing an accurate numerical model of the welding process, combined with microstructure evolution analysis and experimental verification, the method optimizes welding parameter design, predicts the comprehensive performance of the weld joint, and achieves effective control of joint quality.

[0006] To achieve the above objectives, the present invention is specifically implemented as follows:

[0007] A numerical simulation-based method for predicting the microstructure and performance of welded joints in composite steel bridge decks includes: establishing a three-dimensional geometric model of the welded joints in the composite steel bridge decks and defining the physical and temperature properties of each substructure material; dividing the three-dimensional geometric model into regions based on the influence of the thermo-mechanical coupling effect on the structure during welding, and discretizing these regions to form a three-dimensional welding finite element model; setting the initial welding temperature, boundary conditions, and process parameters; setting the weld trajectory, applying heat source loads, and configuring the solution task based on the thermo-mechanical coupling solution strategy using the material's CCT curve; performing simulated welding according to preset welding process parameters; and predicting the welded joint performance and failure risk areas of the welded structure based on the simulated welding results.

[0008] In some specific implementations, establishing the three-dimensional geometric model of the welded joints of the composite steel bridge deck includes:

[0009] The composite steel bridge deck welding nodes are subjected to three-dimensional scanning to obtain point cloud data. The point cloud data is then traversed, and data unrelated to the composite steel bridge deck welding nodes are deleted to obtain the target point cloud data.

[0010] Based on the point cloud data of the target, three-dimensional solid models of the composite steel bridge deck base layer, cladding layer and welding nodes are established using professional modeling software and integrated into the overall three-dimensional geometric model.

[0011] In some specific implementations, the physical properties-temperature characteristics of each substructure material include at least the specific values ​​of thermal conductivity, specific heat capacity, elastic modulus, Poisson's ratio, yield strength, density, and coefficient of thermal expansion at six temperature points within the range of 0 to 1500°C.

[0012] In some specific implementations, the partitioning and discretization to form a three-dimensional welding finite element model includes:

[0013] The three-dimensional geometric model was imported into professional mesh generation software, and the mesh size of different regions of the model was analyzed and confirmed according to the mesh size subdivision principle near the welding node.

[0014] Based on the mesh size, the three-dimensional geometric model is first assigned mesh attributes, and then the mesh is divided in the order of diffusion from the welding node to the surrounding area, thus discretizing the three-dimensional welding finite element model.

[0015] In some specific implementations, setting the initial welding temperature includes:

[0016] Considering whether preheating is used during the actual welding of the composite steel bridge deck, the ambient temperature is input as the initial welding temperature under the condition of no preheating, and the actual preheating temperature is input as the initial welding temperature under the condition of preheating.

[0017] In some specific implementations, the setting of boundary conditions includes:

[0018] Convection heat transfer coefficient and radiation heat transfer coefficient are defined on the exposed surface of the three-dimensional welding finite element model to simulate natural convection and thermal radiation heat dissipation during the welding process.

[0019] Based on the actual constraint state of the composite steel bridge deck, displacement constraints are set at the edge of the composite steel bridge deck base layer away from the welding node to avoid rigid displacement while retaining the degree of freedom for thermal deformation.

[0020] In some specific implementations, setting the process parameters includes:

[0021] The welding process parameters of the composite steel bridge deck welded joints in historical welding are obtained, and the performance of the welded joints under the historical welding process parameters is pre-analyzed. The process parameters are the historical welding process parameters under the optimal welded joint performance.

[0022] In some specific implementations, setting the weld bead trajectory and applying the heat source load include:

[0023] Based on the actual welding process sequence, the sequence of center coordinate points of the moving heat source is discretized according to the weld layer path in the three-dimensional welding finite element model.

[0024] The heat source energy density distribution is calculated based on welding current, voltage, and speed parameters, and then dynamically loaded by associating it with the coordinate points of the weld trajectory.

[0025] In some specific implementations, the heat source load is based on a double ellipsoidal heat source model, which is divided into two ellipsoidal parts, front and back.

[0026] The heat flux density distribution function within the ellipsoid described in the first part is:

[0027]

[0028] The heat flux density distribution function within the ellipsoid described in the latter part is:

[0029]

[0030] In the formula:

[0031] x, y, z are the local coordinate system of the double ellipsoidal heat source model;

[0032] f1 and f2 are the energy distribution coefficients of the front and rear hemispheres, respectively, and f1+f2=2;

[0033] a1, a2, b, and c are respectively determined by the front half-axis length, rear half-axis length, width, and depth of the actual molten pool;

[0034] Q w For effective heat input, , U represents welding thermal efficiency, U represents welding voltage, and I represents welding current.

[0035] In some specific implementations, the prediction of weld joint performance and failure risk areas of the welded structure based on simulated welding results includes:

[0036] Based on the welding simulation results, the temperature field, residual stress field, microstructure field and deformation field data of the welded joint of the composite steel bridge deck after welding are extracted. Combined with the microstructure evolution criteria of the welded joint area, the performance and failure risk area of ​​the welded joint are predicted.

[0037] The overall performance of the welded joint is assessed to determine whether it meets the design requirements.

[0038] If the conditions are met, the actual welding of the composite steel bridge deck shall be carried out according to the preset process parameters.

[0039] If the requirements are not met, the process parameters will be adjusted to ensure that the overall performance of the welded joint meets the design requirements.

[0040] The advantages of this invention over the prior art are:

[0041] This invention utilizes thermo-mechanical coupled numerical simulation technology, combined with material property analysis and process optimization, to provide an efficient method for predicting the microstructure and properties of welded joints in stainless steel composite bridge decks. By precisely controlling the welding heat input and process parameters, the overall performance of the welded joints is improved, while significantly enhancing the stability and reliability of the weld quality.

[0042] This invention achieves accurate calculation of the microstructure of welded joints of stainless steel composite steel bridge decks after welding by combining material CCT curves with numerical simulation. Then, the macroscopic performance of the welded joints is predicted through the microstructure, ensuring the adaptability of the welded joints of composite steel bridge decks in complex environments and ensuring that the high standard requirements of mechanical properties and corrosion resistance of the structure in practical applications are met from the perspective of microstructure.

[0043] The method of this invention can significantly shorten the development cycle of welding process parameters for composite steel bridge deck welding nodes under different environments, reduce testing costs, and is applicable to the performance evaluation of various composite steel plate welded joints.

[0044] The method of this invention is applicable to engineering fields with high requirements for welding quality, such as bridges, ships, and offshore platforms, and has significant engineering application value, especially in complex environments such as extreme cold and corrosion.

[0045] The method of this invention can be extended to the welding process design of other types of stainless steel composite materials, providing a general solution for the development of welding technology for high-performance composite plates. It has wide engineering applicability and high promotion value, and promotes the innovative development of green bridge construction technology.

[0046] It should be understood that the implementation of any embodiment of this utility model does not mean that it will simultaneously possess or achieve multiple or all of the above-mentioned beneficial effects. Attached Figure Description

[0047] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0048] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0049] Figure 1 This is a technical roadmap for the method of predicting the microstructure and properties of welded joints of stainless steel composite bridge decks based on numerical simulation, provided in an embodiment of the present invention.

[0050] Figure 2 This is a schematic diagram of the welded joint structure of the stainless steel composite steel bridge deck provided in an embodiment of the present invention;

[0051] Figure 3 The geometric model of the welding test plate and the weld distribution diagram provided in the embodiments of the present invention;

[0052] Figure 4 This is a mesh division diagram (three-dimensional, cross-section) of a welding test plate provided in an embodiment of the present invention.

[0053] Figure 5 This is a diagram of a double ellipsoidal heat source model provided in an embodiment of the present invention;

[0054] Figure 6 The heat source verification comparison diagram (actual molten pool morphology and simulated molten pool morphology) provided in the embodiments of the present invention.

[0055] Figure 7 The peak temperature distribution and molten pool morphology of the welded joint section are shown in the embodiments of the present invention.

[0056] Figure 8 This is a temperature comparison chart of the completed welding process and 500 seconds after welding, provided in an embodiment of the present invention.

[0057] Figure 9 This is a comparison diagram of the residual stress after welding completion and 500 seconds after welding, provided in an embodiment of the present invention.

[0058] Figure 10 This is a comparison chart of the deformation after welding completion and 500 seconds after welding, provided in an embodiment of the present invention.

[0059] Figure 11 The following is a diagram showing the T8 / 5 cooling rate of the welded joint cross-section at different locations after welding, provided in an embodiment of the present invention.

[0060] Figure 12A Volume fraction diagram of ferrite at different locations of the welded joint after welding, provided in an embodiment of the present invention;

[0061] Figure 12B Volume fraction diagram of bainite at different locations of the welded joint after welding, provided in an embodiment of the present invention;

[0062] Figure 12C Volume fraction diagram of microstructure (pearlite) at different locations of the welded joint after welding, provided in an embodiment of the present invention;

[0063] Figure 12D Volume fraction diagram of martensite at different locations of the welded joint after welding, provided in an embodiment of the present invention;

[0064] Figure 13 This is a diagram showing the calculated hardness of different locations of the welded joint after welding, provided in an embodiment of the present invention.

[0065] Figure 14 The diagram shows the calculation results of tensile strength at different positions after welding, as provided in the embodiments of the present invention.

[0066] The markings in the diagram are: 1-U-rib, 2-composite steel bridge deck, 21-stainless steel cladding, 22-carbon steel base layer, 3-welding node, 4-welding test plate.

[0067] The same or corresponding marks in the diagram indicate the same or corresponding parts. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments and descriptions of the present invention are used to explain the present invention, but are not intended to limit the present invention.

[0069] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0070] It should be understood that the terms "comprising / including," "consisting of," or any other variations are intended to cover non-exclusive inclusion, such that a product, apparatus, process, or method that comprises a list of elements includes not only those elements but may also include, where necessary, other elements not expressly listed, or elements inherent to such a product, apparatus, process, or method. Without further limitation, an element defined by the phrases "comprising / including," "consisting of," does not exclude the presence of additional identical elements in the product, apparatus, process, or method that includes said element.

[0071] It should also be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device, component or structure referred to must have a specific orientation, be constructed or operated in a specific orientation, and should not be construed as a limitation of the present invention.

[0072] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0073] See Figure 1As shown in the embodiment of the present invention, a method for predicting the microstructure and performance of welded nodes 3 of composite steel bridge deck 2 based on numerical simulation is provided. This method mainly includes: establishing a three-dimensional geometric model of the welded nodes 3 of the composite steel bridge deck 2; defining the physical properties and temperature attributes of each substructure material; dividing the three-dimensional geometric model into regions based on the influence of the thermo-mechanical coupling effect on the structure during welding operations, and discretizing these regions to form a three-dimensional welding finite element model; setting the initial welding temperature, boundary conditions, and process parameters; setting the weld trajectory, applying heat source load, and configuring the solution task based on the thermo-mechanical coupling solution strategy of the material CCT curve; performing simulated welding according to preset welding process parameters; and predicting the performance and failure risk areas of the welded nodes 3 of the welded structure based on the simulated welding results.

[0074] The following describes each step of the analysis method in detail with reference to preferred implementation methods and specific illustrations.

[0075] See Figure 2 The left and right sets of composite steel bridge decks 2, equipped with U-ribs 1, are butt-welded together to form a welding node 3 in the middle. The composite steel bridge deck 2 has a 3mm thick stainless steel cladding layer 21 as its cladding, and below it is a 16mm thick carbon steel base layer 22. The welding node 3 has multiple weld beads distributed in a fan shape from bottom to top (12 in the figure), and the multiple weld beads are welded in the order shown in the figure. Furthermore, the weld beads are subdivided from bottom to top according to the welding characteristics into base layer welding, transition layer welding, and cladding layer welding. The base layer welding is connected to a ceramic backing to constrain the width of the molten pool of the long straight weld, avoiding excessively wide welds or serpentine defects. Preferably, the stainless steel cladding layer 21 and the carbon steel base layer 22 are made of 316L stainless steel and Q420qENH steel, respectively, and their chemical compositions are shown in Table 1. The following description uses this welded structure as an example, but it should be understood that this welded structure is obviously not the only form, nor should it be interpreted as a limitation on the analysis method of the embodiments of the present invention.

[0076] Table 1

[0077]

[0078] S10, establish a three-dimensional geometric model of the composite steel bridge deck 2 welding node 3, and define the physical properties and temperature attributes of each substructure material.

[0079] Traditional methods of establishing 3D geometric models rely on interactive creation based on structural dimension parameters and spatial positional relationships. Various input information depends on manual operation, resulting in low efficiency and the potential for overlooking minute components. In this embodiment, a better approach is to use 3D laser scanning technology to acquire point cloud data of the welded structure. The point cloud data is then traversed, and non-structural point cloud data unrelated to the welded structure is removed to obtain the target point cloud data. Subsequently, based on the target point cloud data, 3D reverse modeling software is used to construct 3D solid models of the stainless steel cladding 21, carbon steel base 22, and welded nodes of the composite steel bridge deck 2, respectively. These models are then integrated into a welded geometric model of the overall structure. The corresponding physical performance parameters of the stainless steel cladding 21, carbon steel base 22, and welded nodes are set according to temperature changes, and the material properties are assigned to the corresponding structural parts.

[0080] like Figure 3 As shown, in this embodiment, professional 3D modeling software, such as Solidworks, is used to establish a 3D solid model, which specifically includes two butt welding test plates 4, a restraint plate (not shown in the figure) and welding nodes 3. The structural features of the welding test plates 4 are consistent with those of the composite steel bridge deck 2. The size of the restraint plate is equivalently processed according to the actual welding restraint state. The number and size of the weld beads of the welding node 3 are modeled based on the experience of multiple welding process qualification tests, and then combined and assembled into the overall geometric model shown in the figure.

[0081] Preferably, the two butt-welded test plates 4 are the same size, both being rectangular plates with a length of 400mm, a width of 250mm, and a thickness of 19mm; and their interlayer structure is the same as that of the composite steel bridge deck 2, namely, composed of a 3mm stainless steel cladding layer 21 and a 16mm carbon steel base layer 22.

[0082] Welding node 3 is divided into 11 weld passes, distributed in a fan shape. According to the welding sequence, there are 6 layers from the bottom to the top of welding node 3. Weld pass 1 is located at the bottom layer of welding node 3, weld passes 2 and 3 fill the second and third layers respectively; weld passes 4 and 5 symmetrically fill the fourth layer, weld passes 6, 7 and 8 symmetrically fill the fifth layer, and weld passes 9, 10 and 11 symmetrically fill the top layer.

[0083] It is easy to understand that the solid-thermal coupling effect is an important aspect of the welding operation. Therefore, the physical and temperature properties of the materials of each substructure are key steps in effectively simulating the microstructure and properties of the welded node 3. In this embodiment, the welding test plate 4, the restraint plate, and the welding materials of the welded node 3 are preferably endowed with physical and temperature properties, including density, thermal conductivity, specific heat capacity, elastic modulus, Poisson's ratio, and coefficient of thermal expansion.

[0084] In this embodiment, preferably, three different welding materials—T60NHQ, ER309LMo, and ER316L—are used as the welding materials for the base layer, transition layer, and cladding layer of the welding test plate 4, respectively. Since the physical properties of T60NHQ welding material are similar to those of Q420qENH steel, and the physical properties of ER309LMo and ER316L welding materials are similar to those of 316L stainless steel, the physical properties of Q420qENH steel and 316L stainless steel are used to replace the corresponding physical properties of the welding materials. The chemical compositions of the welding wires for T60NHQ, ER309LMo, and ER316L are shown in [reference needed]. The performance-temperature parameters of Q420qENH steel and 316L stainless steel are shown in [reference needed].

[0085] Table 2

[0086]

[0087] Table 3

[0088]

[0089] Table 4

[0090]

[0091] In this embodiment, after the three-dimensional welding finite element model is established, it needs to be exported in .step file format. It should be noted that the file format exported by professional mesh generation software is not limited to .step file, as long as it is compatible with the input format of subsequent professional mesh generation software.

[0092] S20. Based on the influence of the thermo-mechanical coupling effect on the structure during welding operations, the three-dimensional geometric model is divided into regions and then discretized to form a three-dimensional welding finite element model.

[0093] In this embodiment, the partitioning and discretization of the three-dimensional welding finite element model can be performed as follows:

[0094] The three-dimensional welding finite element model obtained in the previous steps is imported into professional mesh generation software. Since the thermal coupling effect gradually weakens from the welding center to the edge of the structure during the welding operation, the model can be divided into partitions according to the influence of the thermal coupling effect, and the mesh size of different regions can be determined at the same time.

[0095] In this embodiment, mesh generation software, such as HyperMesh, is used as the mesh generation medium. Since the welding residual stress is mainly concentrated near weld node 3, the thermodynamic behavior near weld node 3 should be the focus of the finite element analysis. To rationally allocate computational resources, this embodiment divides the mesh into the following sections: Figure 4The diagram shows three main regions: subdivision zone, transition zone, and coarse zone. In addition, in this embodiment, hexahedral elements are preferred for mesh generation to ensure the smooth execution of welding thermo-mechanical coupling numerical calculations.

[0096] In this embodiment, preferably, the mesh size of the welding node 3 and its surrounding area is set to 0.5 mm, the mesh size of the transition area is set to 0.5~5 mm, and the mesh size of the coarse section far from the welding node 3 is set to 5 mm.

[0097] Based on the preset mesh size for each region, an appropriate mesh generation strategy is adopted to divide the mesh into zones according to the order of diffusion from the self-welded node 3 to the surrounding area, and finally a thermal coupling calculation finite element model is obtained.

[0098] Specifically, this embodiment uses professional mesh generation software, such as the Solidmap function of the HyperMesh 3D module, to determine the mesh size for each region and perform partitioned mesh generation in the order of diffusion from welding node 3 to the surrounding areas: first, 2D mesh generation is performed on the subdivision and transition regions, and then a 3D mesh is formed by sweeping; the coarse partition mesh is freely generated by professional mesh generation software, and the mesh size can be adjusted in real time according to actual needs during the generation process; after the mesh generation of the entire model is completed, the mesh size and sweep direction need to be confirmed again to ensure that the mesh quality is qualified.

[0099] In this embodiment, after the mesh is generated, the welding finite element model needs to be exported in .bdf file format. It should be noted that the file format exported by professional mesh generation software is not limited to .bdf file, as long as it is compatible with the input format of subsequent professional welding numerical simulation software.

[0100] S30 sets the initial welding temperature, boundary conditions, and process parameters.

[0101] The initial welding temperature should be determined according to the specific operation conditions. Specifically, when the composite steel bridge deck 2 is welded without preheating, the ambient temperature should be entered as the initial welding temperature of the component; when the composite steel bridge deck 2 is welded with preheating, the actual preheating temperature should be entered as the initial welding temperature of the component.

[0102] In solid-thermal coupling analysis, boundary conditions consist of both thermal boundary conditions and structural boundary conditions. Thermal boundary conditions include the heat source model, initial temperature conditions, and heat transfer coefficients (convective and radiative heat transfer). Structural boundary conditions are the constraint conditions of the finite element model during welding. In this embodiment of the method, the software-provided fixed geometry equivalent to the actual welding constraint plate is used as the structural boundary condition. In this embodiment, since the heat exchange between the structural surface and the surrounding environment during welding is mainly convection and radiation, the convective and radiative heat transfer coefficients are preferably defined on the exposed surface of the model in the thermal boundary condition settings to simulate natural convection and thermal radiation heat dissipation during welding. Regarding structural boundary conditions, based on the actual constraint state of the composite steel bridge deck 2, displacement constraints are set at the edges of the composite steel bridge deck 2 away from the welding node 3, while avoiding rigid displacement and preserving the degree of freedom for thermal deformation.

[0103] This embodiment exemplarily provides a method for determining process parameters: obtaining the welding process parameters of the welded node 3 of the composite steel bridge deck 2 in historical welding, performing performance pre-analysis on the welded node 3 under the historical welding process parameters, determining the historical welding process parameters under the optimal performance of the welded node 3 as the target process parameters, and inputting them into the finite element calculation model.

[0104] It should be noted that the pre-performance analysis includes macroscopic mechanical property analysis and joint microstructure analysis. Macroscopic mechanical property analysis is used to obtain the mechanical parameters of historical weld node 3 in mechanical property tests. The mechanical property tests are conducted according to GB / T 16957-2012, and the macroscopic mechanical property evaluation rules are based on GB / T 229. Under the condition that the macroscopic mechanical properties meet the national standard requirements, the process parameters corresponding to historical weld node 3 with the lowest residual stress, the absence of brittle martensite in the microstructure, and the fewest defects are the target process parameters.

[0105] In this embodiment, professional welding analysis software, such as Simufact Welding, is used to perform solid-thermal coupling analysis of the welding process. In the initial analysis step, since the welding operation of the composite steel bridge deck 2 in this embodiment is without preheating, the initial temperature of the welded component is set to the ambient temperature, i.e., 20°C. When establishing the direct thermo-mechanical coupling analysis step, the thermal boundary conditions of the temperature field are set. In this embodiment, thermal radiation and convection are preferably considered together, and the loading is based on convection. The total heat transfer coefficient is set as shown in Tables 3 and 4. Regarding the structural boundary conditions, in this embodiment, the equivalent restraint plate of the fixed geometry provided by the professional welding analysis software is preferably used as the structural boundary condition. In this embodiment, the welding process parameters selected after performance pre-analysis are shown in Table 5.

[0106] Table 5

[0107]

[0108] S40 sets the weld path, applies heat source load, and configures the solution task based on the thermo-mechanical coupling solution strategy of the material CCT curve.

[0109] In professional welding analysis software, based on the actual welding process sequence, the sequence of center coordinate points of the moving heat source is set discretely according to the weld bead layer path in the welding model to simulate the weld bead trajectory. At the same time, the energy density distribution of the heat source is calculated according to the welding current, voltage, and speed parameters, and dynamically loaded and associated with the weld bead trajectory coordinate points.

[0110] Preferably, the heat source energy density distribution adopts the following method: Figure 5 The double ellipsoidal heat source model shown is divided into two ellipsoidal parts, front and back. The present invention provides, by way of example, the following heat source formula:

[0111] The heat flux density distribution function within the first half of the ellipsoid is:

[0112]

[0113] The heat flux density distribution function within the latter half of the ellipsoid is:

[0114]

[0115] In the formula: x, y, z are the local coordinates of the double ellipsoidal heat source model; f1 and f2 are the energy distribution coefficients of the front and rear hemispheres, respectively, f1+f2=2; a1, a2, b, and c are respectively the front half-axis length, rear half-axis length, molten width, and molten depth of the actual molten pool, Q w For effective heat input, , U represents welding thermal efficiency, U represents welding voltage, and I represents welding current.

[0116] This embodiment provides an exemplary preferred parameter value method: f1 = 0.6, f2 = 1.4, η = 0.7~0.85, welding voltage and current are shown in Table 5, and the values ​​of a1, a2, b, and c are verified based on actual multiple sets of welding process qualification data and actual weld pool morphology, such as... Figure 6 As shown, the simulated molten pool morphology is roughly consistent with the actual molten pool morphology, and the geometric boundaries of the two correspond well, that is, the heat source simulation effect is consistent with the actual working conditions.

[0117] It is easy to understand that welding is a process with strong thermo-mechanical-structural coupling. The thermo-mechanical coupling solution strategy based on the material CCT curve can accurately capture the essence of this process. In professional welding analysis software, the elastoplastic mechanical field solution task of the welding finite element model is set based on this strategy, and the corresponding calculation parameters are configured for solution.

[0118] S50 performs simulated welding according to preset welding process parameters.

[0119] In this embodiment, the submission medium for the solution task is preferably the thermo-mechanical coupling solver in professional welding analysis software. Numerical calculations are performed according to the task type configured in the previous steps (thermo-mechanical coupling solution strategy based on material CCT in this embodiment) and the input process parameters. The number of CPU cores for calculation is selected according to the computer's computing resources.

[0120] It should be noted that, in this embodiment, before submitting the solution task, a series of parameters need to be defined based on the preset weld trajectory in the previous steps, including: welding gun position, welding and cooling analysis step size, tracking point position, self-contact point and bonding point at the interface between the base layer and the cladding layer of the welding test plate 4.

[0121] It is easy to understand that professional welding analysis software needs to solve the temperature field based on the differential equation of heat transfer control. This embodiment provides an example of a differential equation for heat transfer control:

[0122]

[0123] In the formula: ρ, c, and α are the density, specific heat capacity, and thermal conductivity of the material, respectively; T is the temperature field distribution function; t is the heat transfer time; and Q is the thermal conductivity. sourse Q loss These are the total heat input and the heat loss due to convection and radiation, respectively.

[0124] S60, based on the simulated welding results, predicts the performance and failure risk area of ​​weld node 3 of the welded structure.

[0125] After the solution is completed, the post-processing mode is entered. The temperature field, residual stress field, microstructure field, and deformation field data of the post-weld model are extracted using the calculation results from preset tracking points. Combined with the microstructure evolution criteria of weld node 3, the performance and failure risk areas of weld node 3 are predicted. The simulation results of this embodiment are comprehensive and complete, and the calculation results are as follows:

[0126] Reference Figure 7 The morphology of the molten pool during welding and the peak temperature distribution of section 3 of the welded node after welding are shown in the figure. The temperature at the center of the heat source is 4035℃.

[0127] Reference Figure 8 The temperature field distribution after welding is shown in the figure. The temperature gradually diffuses from the arc termination point of welding node 3 to both sides of the base material.

[0128] Reference Figure 9 The figure shows a comparison of residual stress after welding and 500 seconds after welding. The residual stress after welding is mainly concentrated in welded node 3 and its heat-affected zone. The maximum stress occurs at welded node 3, with a value of 680 MPa.

[0129] Reference Figure 10 The figure shows a comparison of the deformation after welding and 500 seconds after welding. The deformation after welding is mainly concentrated in welded node 3 and its heat-affected zone. The maximum stress occurs at welded node 3, with a value of 1.74 mm.

[0130] Reference Figure 11 The cooling rates of the cross-section T8 / 5 of welded node 3 at different locations after welding are shown in the figure. The cooling rate of welded node 3 near the composite interface reaches the maximum value of 98.89℃. -1 .

[0131] Reference Figures 12A to 12D The volume fraction distribution of each microstructure at different locations of welded node 3 after welding is shown in the figure. Ferrite and bainite account for about 85% of the main microstructure at welded node 3, pearlite accounts for about 10%, and trace amounts of martensite are generated near the composite interface.

[0132] Reference Figure 13 The hardness results at different locations after welding are shown in the figure. The hardness of welded node 3 and the heat-affected zone is about 50 higher than that of the base material.

[0133] Reference Figure 14 The calculation results of tensile strength at different locations after welding are shown in the figure. The tensile strength of welded node 3 and its heat-affected zone are all greater than the design tensile strength of Q420qENH steel. Among them, the tensile strength of the bottom weld of welded node 3 is in the range of [400MPa, 500MPa], while the tensile strength of the base material of the other welds and heat-affected zone reaches 700MPa.

[0134] The results shown in the figures above demonstrate the superiority of the numerical method provided by this invention in multiple aspects. By outputting the calculation results shown in these figures, the comprehensiveness of the simulation results can be explained in detail.

[0135] Numerical simulation results show that the overall performance of welded node 3 under the preset process parameters in this embodiment meets the design requirements. In actual operation, the composite steel bridge deck 2 can be welded according to the preset welding process parameters.

[0136] It should be noted that when the tensile strength of each sub-component of the welded model fails to meet the design requirements, the welding process parameters need to be adjusted based on the performance requirements of the designed welded node 3 to ensure that the overall performance of the node meets the design requirements.

[0137] From the above description, it can be seen that the analysis method of this invention can be summarized as follows: First, a model is constructed based on the point cloud data of the welded structure obtained by three-dimensional laser scanning technology. Before use, non-structural point cloud data unrelated to the welded structure is removed, and the physical property-temperature attribute characteristics of each substructure material are defined. The physical property parameters include density, thermal conductivity, specific heat capacity, elastic modulus, Poisson's ratio, and coefficient of thermal expansion. The physical property-temperature attribute characteristics contain at least 6 temperature points, which are reasonably distributed within the range of [0, 1500]℃ or [0, 1300]℃. Second, based on the influence of the thermo-mechanical coupling effect on the structure during the welding operation, the three-dimensional geometric model is divided into subdivision zone, transition zone, and coarse zone, and the zones are discretized to form a three-dimensional welding finite element model. Third, the initial welding temperature, boundary conditions, and the optimal temperature obtained by fitting historical data are set. The process parameters corresponding to optimal welding performance include: boundary conditions based on the theory of natural convection and thermal radiation heat dissipation, and structural boundary conditions based on the actual constraint state of the composite steel bridge deck 2; fourth, setting the weld trajectory, dynamically loading heat source loads sequentially along the coordinate points of the weld trajectory, and configuring the solution task based on the thermo-mechanical coupling solution strategy of the material CCT curve; fifth, simulating welding according to the preset welding process parameters; sixth, predicting the performance and failure risk area of ​​the welded node 3 based on the simulated welding results, and determining whether the comprehensive performance of the welded node 3 meets the design requirements; if so, actually welding the composite steel bridge deck 2 according to the set welding process parameters; otherwise, adjusting the welding process parameters based on the design performance requirements of the welded node 3 to ensure that the comprehensive performance of the node meets the design requirements. In other words, this invention constructs an efficient method for predicting the microstructure and properties of welded nodes 3 of composite steel bridge deck 2 through thermo-mechanical coupling numerical simulation technology, which has the following core advantages: First, by accurately controlling the welding process parameters, the comprehensive performance of welded nodes 3 is effectively improved, while significantly enhancing the stability and reliability of welding quality; Second, based on the synergistic effect of material CCT curves and numerical simulation, accurate quantitative calculation of the microstructure after welding is achieved, and macroscopic properties are further predicted through the evolution law of microstructure, ensuring the adaptability of welded nodes 3 in complex environments from the micro-macro multi-scale level, and ensuring that its mechanical properties meet the high standard requirements of practical applications.

[0138] It will be readily understood by those skilled in the art that, without conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation, characterized in that, include: A three-dimensional geometric model of the welded joint of the composite steel bridge deck was established, and the physical and temperature properties of each substructure material were defined. Based on the influence of the thermo-mechanical coupling effect on the structure during welding operations, the three-dimensional geometric model is divided into regions, and the regions are discretized to form a three-dimensional welding finite element model; Set the initial welding temperature, boundary conditions, and process parameters; Set the weld trajectory, apply heat source load, and configure the solution task based on the thermo-mechanical coupling solution strategy based on the material CCT curve; Simulated welding was performed according to the preset welding process parameters; Based on the simulated welding results, predict the performance of welded joints and the failure risk areas of welded structures.

2. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The establishment of the three-dimensional geometric model of the welded joint of the composite steel bridge deck includes: The composite steel bridge deck welding nodes are subjected to three-dimensional scanning to obtain point cloud data. The point cloud data is then traversed, and data unrelated to the composite steel bridge deck welding nodes are deleted to obtain the target point cloud data. Based on the point cloud data of the target, three-dimensional solid models of the composite steel bridge deck base layer, cladding layer and welding nodes are established using professional modeling software and integrated into the overall three-dimensional geometric model.

3. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The physical and temperature properties of each substructure material include at least the specific values ​​of thermal conductivity, specific heat capacity, elastic modulus, Poisson's ratio, yield strength, density, and coefficient of thermal expansion at six temperature points within the range of 0 to 1500℃.

4. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The partitioning and discretization to form a three-dimensional welding finite element model includes: The three-dimensional geometric model was imported into professional mesh generation software, and the mesh size of different regions of the model was analyzed and confirmed according to the mesh size subdivision principle near the welding node. Based on the mesh size, the three-dimensional geometric model is first assigned mesh attributes, and then the mesh is divided in the order of diffusion from the welding node to the surrounding area, thus discretizing the three-dimensional welding finite element model.

5. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, Setting the initial welding temperature includes: Considering whether preheating is used during the actual welding of the composite steel bridge deck, the ambient temperature is input as the initial welding temperature under the condition of no preheating, and the actual preheating temperature is input as the initial welding temperature under the condition of preheating.

6. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The boundary conditions include: Convection heat transfer coefficient and radiation heat transfer coefficient are defined on the exposed surface of the three-dimensional welding finite element model to simulate natural convection and thermal radiation heat dissipation during the welding process. Based on the actual constraint state of the composite steel bridge deck, displacement constraints are set at the edge of the composite steel bridge deck base layer away from the welding node to avoid rigid displacement while retaining the degree of freedom for thermal deformation.

7. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The process parameters to be set include: The welding process parameters of the composite steel bridge deck welded joints in historical welding are obtained, and the performance of the welded joints under the historical welding process parameters is pre-analyzed. The process parameters are the historical welding process parameters under the optimal welded joint performance.

8. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The steps of setting the weld bead trajectory and applying the heat source load include: Based on the actual welding process sequence, the sequence of center coordinate points of the moving heat source is discretized according to the weld layer path in the three-dimensional welding finite element model. The heat source energy density distribution is calculated based on welding current, voltage, and speed parameters, and then dynamically loaded by associating it with the coordinate points of the weld trajectory.

9. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 8, characterized in that, The heat source load is applied based on a double ellipsoidal heat source model, which is divided into two ellipsoidal parts, front and rear. The heat flux density distribution function within the ellipsoid described in the first part is: ； The heat flux density distribution function within the ellipsoid described in the latter part is: ； In the formula: x, y, z are the local coordinate system of the double ellipsoidal heat source model; f1 and f2 are the energy distribution coefficients of the front and rear hemispheres, respectively, and f1+f2=2; a1, a2, b, and c are respectively determined by the front half-axis length, rear half-axis length, width, and depth of the actual molten pool; Q w For effective heat input, , U represents welding thermal efficiency, U represents welding voltage, and I represents welding current.

10. The method for predicting the microstructure and properties of welded joints in composite steel bridge decks based on numerical simulation according to claim 1, characterized in that, The prediction of weld joint performance and failure risk areas of welded structures based on simulated welding results includes: Based on the welding simulation results, the temperature field, residual stress field, microstructure field and deformation field data of the welded joint of the composite steel bridge deck after welding are extracted. Combined with the microstructure evolution criteria of the welded joint area, the performance and failure risk area of ​​the welded joint are predicted. The overall performance of the welded joint is assessed to determine whether it meets the design requirements. If the conditions are met, the actual welding of the composite steel bridge deck shall be carried out according to the preset process parameters. If the requirements are not met, the process parameters will be adjusted to ensure that the overall performance of the welded joint meets the design requirements.

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