Construction method and application of deformation prediction model for hull stiffener fillet weld

Abstract

The present application proposes a method for constructing and applying a hull stiffener corner weld deformation prediction model, which relates to the field of welding technology. The construction method includes: obtaining the plate thickness values ​​of multiple corner weld joint samples; establishing a finite element analysis model of each corner weld joint sample based on each plate thickness value; performing welding finite element analysis on each finite element analysis model based on the welding process parameter values ​​of each corner weld joint sample and the thermophysical performance parameter information of the sample material, and determining the welding deformation parameter value of each corner weld joint sample; constructing a correlation model between welding deformation parameters and welding line energy and plate thickness through dimensional analysis; solving the dimensionless coefficient of the correlation model according to the plate thickness values, welding process parameter values ​​and welding deformation parameter values ​​of each corner weld joint sample, and obtaining a target hull stiffener corner weld deformation prediction model. The present application quickly and accurately predicts the hull stiffener corner weld deformation by constructing a target hull stiffener corner weld deformation prediction model.

Description

Technical Field

[0001] The present application relates to the field of welding technology, and in particular to a method for constructing and applying a deformation prediction model for hull stiffener fillet welds. Background Art

[0002] During the hull block construction process, in order to effectively reduce its own weight and ensure structural strength, it is generally necessary to weld longitudinal angle steel along the ship's length and weld ribs, stiffeners and other structures along the ship's width. Welding deformation of the welded structure will seriously affect the construction accuracy of the hull block, and thus affect the subsequent block assembly and the ship's hydrodynamic performance.

[0003] In view of this, how to quickly and accurately predict the deformation of welded joints is an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the present application proposes a method for constructing and applying a deformation prediction model for hull stiffener fillet welds.

[0005] In a first aspect, the present application provides a method for constructing a hull stiffener fillet weld deformation prediction model, the method comprising:

[0006] Obtaining plate thickness values ​​and corresponding welding process parameter values ​​of a plurality of fillet weld joint samples, wherein the plate thickness values ​​of the plurality of fillet weld joint samples are different, and the plate thickness values ​​include a bottom plate thickness value and a vertical plate thickness value;

[0007] Establishing a finite element model of each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample;

[0008] performing welding finite element analysis on each of the finite element models based on the welding process parameter values ​​of each of the fillet weld joint samples and the thermophysical property parameter information of the fillet weld joint sample materials to determine welding deformation parameter values ​​of each of the fillet weld joint samples, wherein the welding deformation parameter values ​​include at least a longitudinal shrinkage force value and a transverse bending moment value;

[0009] The correlation model between welding deformation parameters, welding line energy and plate thickness is constructed through dimensional analysis;

[0010] The dimensionless coefficient of the correlation model is solved according to the plate thickness value, welding process parameter value and welding deformation parameter value of each fillet weld joint sample to obtain the target hull stiffener fillet weld deformation prediction model.

[0011] In one embodiment, establishing a finite element model of each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample includes:

[0012] Establishing a three-dimensional model of each fillet weld joint sample according to the plate thickness value of each fillet weld joint sample;

[0013] Finite element meshing is performed on the three-dimensional model of each fillet weld joint sample to establish a finite element model of each fillet weld joint sample.

[0014] In one embodiment, performing welding finite element analysis on each finite element model based on the welding process parameter values ​​of each fillet weld joint sample and the thermophysical property parameter information of the fillet weld joint sample material to determine the welding deformation parameter value of each fillet weld joint sample includes:

[0015] performing a thermal-elastic-plastic finite element analysis of the welding on the finite element model of each fillet weld joint sample after finite element meshing based on the welding process parameter values ​​and the thermophysical property parameter information of the weld joint material, and obtaining the residual plastic strain distribution information after cooling to room temperature after welding;

[0016] The welding deformation parameter value of each fillet weld joint sample is determined according to the residual plastic strain distribution information corresponding to each fillet weld joint sample.

[0017] In one embodiment, the calculation formula for determining the longitudinal shrinkage force value according to the residual plastic strain distribution information corresponding to each fillet weld joint sample is:

[0018] ;

[0019] Among them, F longitudinal is the longitudinal shrinkage force of the fillet weld joint sample, is the residual plastic strain value along the weld on different elements, is the elastic modulus of the welding head material, are the coordinates of the centroids of different units in the direction perpendicular to the weld, are the coordinates of the centroids of different elements in the thickness direction.

[0020] In one embodiment, the calculation formula for determining the transverse bending moment value according to the residual plastic strain distribution information corresponding to each fillet weld joint sample is:

[0021] ;

[0022] Among them, M transverse is the transverse bending moment of the fillet weld joint specimen, is the residual plastic strain value along the weld on different elements, is the bottom plate thickness, is the elastic modulus of the welding head material, are the coordinates of the centroids of different units in the direction perpendicular to the weld, are the coordinates of the centroids of different elements in the thickness direction.

[0023] In one embodiment, the correlation formula between the longitudinal contraction force and the welding line energy is:

[0024] ;

[0025] Among them, F longitudinal is the longitudinal contraction force of the fillet weld specimen, Qnet is the weld line energy, and a and b are dimensionless coefficients.

[0026] In one embodiment, the correlation formula between the transverse bending moment, the welding line energy and the plate thickness is:

[0027] ;

[0028] Among them, M transverse is the transverse bending moment of the fillet weld joint specimen, Qnet is the welding line energy, is the base plate thickness, c and d are dimensionless coefficients.

[0029] In one embodiment, solving the dimensionless coefficient of the correlation model based on the plate thickness value, welding process parameter value, and welding deformation parameter value of each fillet weld joint sample to obtain the target hull stiffener fillet weld deformation prediction model includes:

[0030] Determining the welding energy input value corresponding to each fillet weld joint sample according to the welding process parameter value of each fillet weld joint sample;

[0031] Determining the dimensionless coefficient values ​​of the correlation model by fitting the bottom plate thickness value, welding line energy value and welding deformation parameter value corresponding to each fillet weld joint sample;

[0032] Substituting each dimensionless coefficient value into the correlation model, the target hull stiffener fillet weld deformation prediction model is obtained.

[0033] In one embodiment, the method for constructing the hull stiffener fillet weld deformation prediction model further includes:

[0034] Obtaining a plate thickness value and verification parameters of a verification fillet weld joint sample, wherein the verification parameters include a reference value of a welding deformation parameter of the verification fillet weld joint sample;

[0035] Solving the target hull stiffener fillet weld deformation prediction model according to the plate thickness value and welding process parameter values ​​of the verification fillet weld joint sample, and determining the solution value of the welding deformation parameter of the verification fillet weld joint sample;

[0036] A score of the target hull stiffener fillet weld deformation prediction model is determined according to the reference value and the solution value.

[0037] In a second aspect, the present application further provides an application of a hull stiffener fillet weld deformation prediction model, wherein the application of the hull stiffener fillet weld deformation prediction model includes:

[0038] Obtain the plate thickness value and corresponding welding process parameter values ​​of the target fillet weld joint;

[0039] Determining the welding deformation parameter value of the target fillet weld joint according to the plate thickness value, the welding process parameter value and the target hull stiffener fillet weld deformation prediction model, wherein the target hull stiffener fillet weld deformation prediction model is constructed using the method described in the first aspect;

[0040] The welding deformation information of the target fillet weld joint is determined according to the welding deformation parameter value of the target fillet weld joint.

[0041] The method for constructing a hull stiffener fillet weld deformation prediction model in this application has the following beneficial effects compared to related technologies:

[0042] 1. This application performs welding finite element analysis on each finite element model based on the welding process parameter values ​​of each fillet weld joint sample and the thermal physical performance parameter information of the fillet weld joint sample material, determines the welding deformation parameter value of each fillet weld joint sample, and then constructs a correlation model between the welding deformation parameter and the welding line energy and the plate thickness through dimensional analysis; the dimensionless coefficient of the correlation model is solved according to the plate thickness value of each fillet weld joint sample, the welding process parameter value and the welding deformation parameter value of each fillet weld joint sample, and the target hull stiffener fillet weld deformation prediction model is obtained. In the process of constructing the model, the material thermal physical performance parameters that change with temperature are taken into account, and the influence of environmental factors is fully considered, which is conducive to constructing a target hull stiffener fillet weld deformation prediction model with higher prediction accuracy.

[0043] 2. Compared with the traditional empirical formula modeling method based on engineering trial and error, this application is based on the basic principles of dimensional analysis. It constructs a mathematical model with dimensional consistency through the Buckingham π theorem and establishes the correlation between the characteristic parameters of welding deformation and key physical quantities such as welding line energy and plate thickness. This modeling method follows the principle of physical similarity, ensuring the theoretical rigor and engineering applicability of the model. The constructed target hull stiffener corner weld deformation prediction model is not only more interpretable in a physical sense, but its prediction results are also much more accurate than those of traditional empirical models, which is conducive to the accurate prediction of the deformation of hull stiffener corner weld joints through the target hull stiffener corner weld deformation prediction model.

[0044] 3. The target hull stiffener fillet weld deformation prediction model constructed in this application is a data-driven model based on mathematical statistics and fitting analysis. The target hull stiffener fillet weld deformation prediction model can quickly obtain deformation prediction data of fillet weld joints, which is conducive to improving the efficiency of hull design and construction.

[0045] 4. The longitudinal shrinkage force and transverse bending moment are used to characterize welding deformation. From the perspective of physical phenomena and mechanical mechanisms, this is more reasonable and scientific than the traditional empirical formulas for in-plane shrinkage, angular deformation and other welding deformations, which is conducive to further improving the prediction accuracy of the target hull stiffener corner weld deformation prediction model. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 Schematic diagram of a flow chart of a method for constructing a hull stiffener fillet weld deformation prediction model in one embodiment of the present application;

[0048] Figures 2a to 2j Schematic diagrams of cross sections of fillet welded joint samples T1 to T10 are shown in order;

[0049] Figure 3a Schematic diagram of thermal performance parameters of AH36 high-strength steel varying with temperature in one embodiment of the present application;

[0050] Figure 3b Schematic diagram of mechanical property parameters of AH36 high-strength steel varying with temperature in one embodiment of the present application;

[0051] Figure 4a Schematic diagram of longitudinal residual plastic strain distribution after cooling to room temperature after welding based on welding finite element calculation in one embodiment of the present application;

[0052] Figure 4b Schematic diagram of transverse residual plastic strain distribution after cooling to room temperature after welding based on welding finite element calculation in one embodiment of the present application;

[0053] Figure 5a This is a schematic diagram of solving the dimensionless coefficients in formula (1) by fitting in an embodiment of the present application;

[0054] Figure 5b This is a schematic diagram of solving the dimensionless coefficients in formula (2) by fitting in an embodiment of the present application;

[0055] Figure 6 This is a schematic cross-sectional view of a finite element mesh of a fillet weld joint sample with a vertical plate thickness of 28 mm and a bottom plate thickness of 32 mm in one embodiment of the present application;

[0056] Figure 7 This is a flow chart of the application of a hull stiffener fillet weld deformation prediction model in one embodiment of the present application;

[0057] Figure 8 Schematic diagram of the structure of an electronic device in one embodiment of the present application. DETAILED DESCRIPTION

[0058] The following will be combined with the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0059] In some embodiments, as Figure 1 As shown, Figure 1 An embodiment of the present application provides a method for constructing a hull stiffener fillet weld deformation prediction model, and the method for constructing a hull stiffener fillet weld deformation prediction model includes the following steps S101 to S105.

[0060] S101: Obtain plate thickness values ​​and corresponding welding process parameter values ​​for multiple fillet weld joint samples. The fillet weld joint samples have different plate thickness values, including base plate thickness values ​​and vertical plate thickness values. The fillet weld joint samples are hull stiffener fillet weld joint samples.

[0061] In the application, the plate thickness of multiple fillet weld samples can be obtained in advance and stored in the database. Different sample data can be selected from the database as sample data according to needs.

[0062] It should be noted that the number of finite element analysis models to be obtained can be selected based on actual needs and is not specifically limited here. For example, the plate thickness values ​​of 10 fillet weld joint samples can be obtained to construct a target hull stiffener fillet weld deformation prediction model. The bottom plate thickness and vertical plate thickness of the 10 fillet weld joint samples can be as shown in Table 1 below.

[0063] Table 1 shows the bottom plate thickness and vertical plate thickness of 10 fillet weld joint samples

[0064]

[0065] S102: Establishing a finite element model of each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample.

[0066] The plate thickness can be obtained by directly measuring the thickness of the fillet weld sample using a measuring tool such as a caliper. Finite element analysis (FEA) is a numerical calculation method that discretizes a continuous solid structure into a finite number of elements, establishes a mathematical model for each element, and solves the equation to obtain physical quantities such as the mechanical and thermal responses of the entire structure. When constructing a FEA model for a fillet weld sample, the plate thickness can be used to define the model's geometry and material properties. For example, during the geometric modeling phase, the plate thickness is used to determine the geometric dimensions of the fillet weld sample, including parameters such as the length, width, and thickness, thereby accurately constructing a three-dimensional geometric model of the fillet weld sample. Regarding material property settings, the thickness value influences the setting of parameters such as thermal conductivity and mechanical properties, as plates of different thicknesses exhibit different thermal conductivity and mechanical deformation characteristics under the same welding conditions. By rationally utilizing the plate thickness value to construct a FEA model, the physical phenomena and mechanical behavior of the fillet weld sample during the welding process can be more accurately simulated, providing a theoretical basis for optimizing the welding process and controlling welding quality.

[0067] It is understood that a finite element analysis model can also be constructed based on the plate thickness of each fillet weld joint sample during the construction of the hull stiffener fillet weld deformation prediction model. Plate thickness is a key parameter that affects many factors, including the mechanical properties, thermal conductivity characteristics, and welding deformation of the fillet weld joint sample. Different plate thicknesses will lead to differences in heat distribution, stress distribution, and ultimate weld quality during welding. Therefore, a finite element analysis model of the corresponding fillet weld joint sample can be constructed based on the plate thickness of the fillet weld joint sample, thereby providing sample support for the subsequent construction of the target hull stiffener fillet weld deformation prediction model.

[0068] In application, corresponding models or software can be used to establish finite element models of each fillet weld joint sample.

[0069] For example, the cross-sectional schematic diagrams of the 10 fillet weld joint samples in Table 1 can be as follows: Figures 2a to 2j As shown, Figures 2a to 2j Schematic diagrams of cross sections of fillet weld joint samples T1 to T10 are shown in order.

[0070] S103: Perform welding finite element analysis on each finite element model based on the welding process parameter values ​​of each fillet weld joint sample and the thermophysical property parameter information of the fillet weld joint sample material to determine the welding deformation parameter value of each fillet weld joint sample. The welding deformation parameter value includes at least the longitudinal shrinkage force value and the transverse bending moment value.

[0071] In the application, welding process parameters may include welding current, arc voltage, and welding speed. The welding process parameters may be predetermined. For example, the welding current may be 300A, the arc voltage may be 33V, and the welding speed may be 10mm / s. The material of the fillet weld joint sample may be predetermined. After determining the material of the fillet weld joint sample, the thermal physical performance parameter information of the fillet weld joint sample material may be determined. For example, the material of the fillet weld joint sample may be AH36 high-strength steel. The thermal performance parameters of AH36 high-strength steel that vary with temperature can be found in [1]. Figure 3a The mechanical properties of AH36 high strength steel as a function of temperature can be found in Figure 3b .

[0072] It can be understood that after determining the welding process parameter values ​​of each fillet weld joint sample and the thermal physical performance parameter information of the fillet weld joint sample material, the welding process parameter values ​​of each fillet weld joint sample and the thermal physical performance parameter information of the fillet weld joint sample material can be used as input parameters, and welding finite element analysis can be performed through welding finite element analysis software or welding finite element analysis model to determine the welding deformation parameter value of each fillet weld joint sample.

[0073] S104: Construct a correlation model between welding deformation parameters, welding line energy and plate thickness through dimensional analysis.

[0074] It's understandable that relationships exist between various physical quantities, indicating that their structure must be composed of a number of unified basic components, with the abundance of each component leading to vast variations in quantity, just as all things in the world are composed of just over a hundred chemical elements. These basic building blocks of physical quantities are collectively known as dimensions. Since physics studies the evolution and motion of matter in space and time, all quantitative problems ultimately hinge on the three fundamental quantities of mass, time, and length. Therefore, M, T, and L are the most appropriate dimensions for these three fundamental quantities. The dimensions of all other derived quantities can be expressed as combinations of the dimensions of these three fundamental quantities, based on definitions or objective laws. There are many ways to define fundamental quantities. In mechanics, mass, length, and time are typically considered fundamental quantities, and other quantities (such as velocity and force) can be derived from them according to certain rules. Any other derived quantity with three independent dimensions can also serve as a fundamental quantity. Two physical quantities with completely different properties can have the same dimensions, such as work and torque. Any equation that accurately reflects the laws governing physical phenomena must have the same dimensions for both terms.

[0075] Among them, the unit of longitudinal shrinkage force is N, and the unit of welding line energy is KJ / m, that is ( ) / m; At the same time, the unit of the transverse bending moment is ( ), the unit of welding line energy × bottom plate thickness is (KJ / m) m, that is ( ), therefore, welding deformation parameters have a dimensionally related relationship with the weld energy input and plate thickness. Based on this dimensional relationship, a correlation model between welding deformation parameters, weld energy input, and plate thickness can be constructed. This modeling approach adheres to the principle of physical similarity, ensuring the theoretical rigor and engineering applicability of the model.

[0076] In one embodiment, the correlation formula between the longitudinal shrinkage force and the welding line energy can be:

[0077] (1)

[0078] The correlation formula between the transverse bending moment, welding line energy and plate thickness can be expressed as follows:

[0079] (2)

[0080] Among them, F longitudinal is the longitudinal shrinkage force of the fillet weld specimen, M transverse is the transverse bending moment of the fillet weld joint specimen, Qnet is the welding line energy, is the base plate thickness, a, b, c and d are dimensionless coefficients.

[0081] S105: Solve the dimensionless coefficient of the correlation model according to the plate thickness value, welding process parameter value and welding deformation parameter value of each fillet weld joint sample to obtain the target hull stiffener fillet weld deformation prediction model.

[0082] It is understood that the correlation model constructed in step S104 contains uncertain dimensionless coefficients. Therefore, it is necessary to solve the correlation model to determine the dimensionless coefficients in the correlation model in order to obtain the target hull stiffener fillet weld deformation prediction model. Therefore, in this embodiment, the dimensionless coefficients of the correlation model are solved using the plate thickness values, welding process parameter values, and welding deformation parameter values ​​of each fillet weld joint sample to construct the target hull stiffener fillet weld deformation prediction model.

[0083] The method for constructing the above-mentioned hull stiffener fillet weld deformation prediction model performs welding finite element analysis on each three-dimensional model after finite element meshing based on the welding process parameter values ​​and thermophysical property parameter information of the fillet weld sample materials, determines the welding deformation parameter values ​​of each fillet weld sample, and then constructs a correlation model between the welding deformation parameters, welding input energy, and plate thickness through dimensional analysis. The dimensionless coefficients of the correlation model are solved based on the plate thickness values, welding process parameter values, and welding deformation parameter values ​​of each fillet weld sample to obtain the target hull stiffener fillet weld deformation prediction model. Based on the basic principles of dimensional analysis, the correlation relationship between the welding deformation characteristic parameters and key physical quantities such as welding input energy and plate thickness is established. The constructed target hull stiffener fillet weld deformation prediction model not only has stronger interpretability in a physical sense, but also has significantly improved prediction accuracy compared to traditional empirical models, thereby facilitating the accurate prediction of hull stiffener fillet weld sample deformation using the target hull stiffener fillet weld deformation prediction model. In addition, the target hull stiffener fillet weld deformation prediction model constructed in this application is a data-driven model based on mathematical statistics and fitting analysis. The use of the target hull stiffener fillet weld deformation prediction model can quickly obtain deformation prediction data of fillet weld joint samples, which is conducive to improving the efficiency of hull design and construction.

[0084] In some embodiments, in step S102, a finite element model of each fillet weld joint sample is established based on the plate thickness value of each fillet weld joint sample, including: establishing a three-dimensional model of each fillet weld joint sample according to the plate thickness value of each fillet weld joint sample; performing finite element meshing on the three-dimensional model of each fillet weld joint sample to establish a finite element model of each fillet weld joint sample.

[0085] In the application, the plate thickness value of each fillet weld joint sample can be used as an input parameter of a three-dimensional modeling model or three-dimensional modeling software, and a three-dimensional model of each fillet weld joint sample can be established using the three-dimensional modeling model or three-dimensional modeling software. After the three-dimensional model of each fillet weld joint sample is established, the three-dimensional model of each fillet weld joint sample can be finite element meshed using finite element pre-processing software or model to obtain mesh information and cross-sections of the three-dimensional model of each fillet weld joint sample, thereby establishing a finite element model of each fillet weld joint sample.

[0086] In some embodiments, in step S103, welding finite element analysis is performed on each finite element model based on the welding process parameter values ​​of each fillet weld joint sample and the thermal physical property parameter information of the fillet weld joint sample material to determine the welding deformation parameter value of each fillet weld joint sample, including: performing thermal-elastic-plastic finite element analysis of welding on each finite element model based on the welding process parameter values ​​and the thermal physical property parameter information of the weld joint material to obtain residual plastic strain distribution information after cooling to room temperature after welding; and determining the welding deformation parameter value of each fillet weld joint sample according to the residual plastic strain distribution information corresponding to each fillet weld joint sample.

[0087] Among them, Thermo-Elasto-Plastic Finite Element Analysis (TEFA) is a multi-physics coupled numerical simulation method designed to reveal the nonlinear behavior of materials under the combined effects of thermal and mechanical loads. This method discretizes a three-dimensional continuum (finite element mesh) and solves the coupled governing equations of the heat conduction equation and the elasto-plastic constitutive relation. It simulates the thermodynamic response of a material from high-temperature loading (such as welding) to cooling and unloading. First, a transient heat input is applied based on a heat source model (such as a Gaussian distribution or a double ellipsoid heat source) to calculate the spatiotemporal distribution of the temperature field. Then, a thermo-mechanical coupling algorithm is used to convert the temperature gradient into thermal stress. In combination with elasto-plastic incremental theory (such as the J2 flow theory), the yield behavior (elastic limit exceeded), plastic strain accumulation (irreversible deformation), and hardening effects (kinematic / isotropic hardening models) of the material in the phase transition temperature range are tracked. Finally, stress relaxation analysis during the cooling process is used to obtain the residual stress field, plastic strain distribution, and macroscopic deformation (such as weld angle distortion and residual deflection).

[0088] For example, a three-dimensional model was established based on the 10 fillet weld samples shown in Table 1. After the finite element mesh was divided for each three-dimensional model, the thermo-elastic-plastic finite element analysis of the welding was performed on each finite element model based on the welding process parameter values ​​and the thermophysical property parameter information of the weld material. The residual plastic strain distribution and value calculated by the welding finite element after cooling to room temperature after welding can be referred to Figure 4a and Figure 4b , Figure 4a is the longitudinal residual plastic strain distribution after welding, Figure 4b is the transverse residual plastic strain distribution after welding.

[0089] As can be understood, a thermo-elastic-plastic finite element analysis (TEA) is performed on the finite element model based on welding process parameters (such as current, voltage, and welding speed) and the thermophysical properties of the weld material (including thermal conductivity, specific heat capacity, and thermal expansion coefficient). This method simulates the dynamic evolution of the temperature, stress, and strain fields during welding. First, the heat input is applied to the heat source model to calculate the transient temperature distribution, driving the material through thermal expansion and contraction during melting, solidification, and cooling. Elastoplastic constitutive relations are then coupled to track the yield behavior and accumulated plastic deformation of the material at high temperatures until residual plastic strain forms upon cooling to room temperature. Finally, the spatial distribution of residual plastic strain after welding is extracted from each FE model. The weld deformation parameter values ​​are calculated using strain-deformation conversion relationships (such as the integrated plastic strain gradient), achieving a quantitative mapping from microscopic plastic strain to macroscopic deformation, and obtaining the weld deformation parameter values ​​for each fillet weld sample. This process integrates thermodynamics, material mechanics, and numerical simulation techniques. Through multi-physics field coupling analysis, the formation mechanism of weld residual deformation is revealed, providing a reliable theoretical basis for welding process optimization and structural deformation prediction.

[0090] In one embodiment, the calculation formula for determining the longitudinal shrinkage force value based on the residual plastic strain distribution information corresponding to each fillet weld joint sample is:

[0091] (3)

[0092] The calculation formula for determining the transverse bending moment value based on the residual plastic strain distribution information corresponding to each fillet weld joint sample is:

[0093] (4)

[0094] Among them, F longitudinal is the longitudinal shrinkage force of the fillet weld specimen, M transverse is the transverse bending moment of the fillet weld joint specimen, is the residual plastic strain value along the weld on different elements, is the residual plastic strain value of the vertical weld on different units, is the bottom plate thickness, is the elastic modulus of the welding head material, are the coordinates of the centroids of different units in the direction perpendicular to the weld, are the coordinates of the centroids of different elements in the thickness direction.

[0095] In some embodiments, in step S105, the dimensionless coefficient of the correlation model is solved according to the plate thickness value, welding process parameter value and welding deformation parameter value of each fillet weld joint sample to obtain the target hull stiffener fillet weld deformation prediction model, including: determining the welding line energy value corresponding to each fillet weld joint sample according to the welding process parameter value of each fillet weld joint sample; fitting and determining the dimensionless coefficient values ​​of the correlation model according to the bottom plate thickness value, welding line energy value and welding deformation parameter value corresponding to each fillet weld joint sample; and substituting the dimensionless coefficient values ​​into the correlation model to obtain the target hull stiffener fillet weld deformation prediction model.

[0096] Among them, the welding line energy reflects the amount of energy input to the weld during the welding process. The welding line energy is related to the welding current, arc voltage and welding speed respectively. When the welding current, arc voltage and welding speed are determined, the welding line energy value can be calculated based on the determined welding current, arc voltage and welding speed.

[0097] It can be understood that there is a correlation between welding deformation parameters and welding line energy and plate thickness. The specific correlation can be referred to the previous formulas (1) and (2). In order to calculate the dimensionless coefficients of formulas (1) and (2), the welding line energy value and longitudinal shrinkage force value corresponding to each fillet weld joint sample can be substituted into formula (1), and the bottom plate thickness value, welding line energy value and welding deformation parameter value corresponding to each fillet weld joint sample can be substituted into formula (2). The dimensionless coefficients in formulas (1) and (2) are solved by fitting, thereby determining the dimensionless coefficient values ​​in the correlation model. Finally, the obtained dimensionless coefficient values ​​are substituted into the correlation model to obtain the construction of the target hull stiffener fillet weld deformation prediction model. In this way, when the welding process parameters are known and the welding line energy is obtained, this prediction model can be used to predict the welding deformation.

[0098] For example, the parameters corresponding to the 10 fillet weld joint samples in Table 1 may be shown in Table 2 below.

[0099] Table 2 shows the welding energy input and welding deformation parameters corresponding to the 10 fillet weld joint samples

[0100]

[0101] Taking the parameters shown in Table 2 as an example, the fitting method is used to solve formula (1) as follows: Figure 5a As shown, the dimensionless coefficients in formula (2) are solved by fitting as follows: Figure 5b As shown in the figure, the dimensionless coefficient values ​​in the associated model are determined, and the target hull stiffener fillet weld deformation prediction model is constructed.

[0102] In some embodiments, the method for constructing the hull stiffener fillet weld deformation prediction model also includes: obtaining the plate thickness value and verification parameters of the verification fillet weld joint sample, the verification parameters including the reference value of the welding deformation parameters of the verification fillet weld joint sample; solving the target hull stiffener fillet weld deformation prediction model according to the plate thickness value and welding process parameter value of the verification fillet weld joint sample, and determining the solution value of the welding deformation parameter of the verification fillet weld joint sample; and determining the score of the target hull stiffener fillet weld deformation prediction model according to the reference value and the solution value.

[0103] Among them, transient thermal-elastic-plastic finite element calculation can be used to predict welding temperature field, strain and deformation. Therefore, verification parameters can be obtained through transient thermal-elastic-plastic finite element calculation.

[0104] It can be understood that after obtaining the plate thickness value and welding process parameter value of the verification fillet weld joint sample, the plate thickness value and welding process parameter value of the verification fillet weld joint sample can be directly input into the target hull rib fillet weld deformation prediction model for solution to obtain the solution value of the welding deformation parameter of the verification fillet weld joint sample (i.e., the solution value of the longitudinal shrinkage force and the transverse bending moment). Then, the error parameter between the reference value and the solution value can be calculated, and the score of the target hull rib fillet weld deformation prediction model can be determined based on the error parameter. For example, a relationship formula between the model score and the error parameter can be pre-set. After obtaining the error parameter, the score of the target hull rib fillet weld deformation prediction model is determined based on the error parameter and the relationship formula. For another example, multiple error intervals can be pre-set, each error interval corresponds to a score, and the score of the target hull rib fillet weld deformation prediction model is determined based on the interval in which the error parameter is located.

[0105] For example, a fillet weld joint sample with a vertical plate thickness of 28 mm and a bottom plate thickness of 32 mm is used for application verification. The cross section of the finite element mesh is as follows: Figure 6 As shown in Figure 3, by integrating the residual plastic strain from the weld thermo-elastic-plastic finite element calculation, the longitudinal shrinkage force and transverse bending moment values ​​can be obtained. The longitudinal shrinkage force and transverse bending moment values ​​can also be obtained using the target hull stiffener fillet weld deformation prediction model. Table 3 shows the evaluation results of these two methods.

[0106] Table 3 shows the comparison results between the thermo-elastic-plastic finite element prediction method and the target hull stiffener fillet weld deformation prediction model calculation method.

[0107]

[0108] In this embodiment, after determining the score of the target hull rib fillet weld deformation prediction model, the accuracy of the target hull rib fillet weld deformation prediction model can be determined based on the score of the target hull rib fillet weld deformation prediction model. If the score of the target hull rib fillet weld deformation prediction model is too low, it is necessary to increase the number of samples and construct a new target hull rib fillet weld deformation prediction model. Specifically, the number of finite element analysis models of the fillet weld joint samples acquired in step S101 is increased. Based on the newly acquired finite element analysis models, a new target hull rib fillet weld deformation prediction model is constructed using the method for constructing any of the above hull rib fillet weld deformation prediction models. This results in a more accurate target hull rib fillet weld deformation prediction model, thereby improving the accuracy of the fillet weld deformation assessment.

[0109] It should be noted that in the application, the sample points can be continuously improved and increased to increase the scale of the data-driven database, improve the accuracy of the target hull stiffener fillet weld deformation prediction model, and thus improve the accuracy of the fillet weld deformation assessment.

[0110] In some embodiments, as Figure 7 As shown, the present application also provides an application of a hull stiffener fillet weld deformation prediction model, and the application of the hull stiffener fillet weld deformation prediction model includes the following steps S701 to S703.

[0111] S701: Obtain the plate thickness value and corresponding welding process parameter values ​​of the target fillet weld joint.

[0112] The target fillet weld joint is the fillet weld joint to be evaluated. The plate thickness value of the target fillet weld joint may include the vertical plate thickness value and the bottom plate thickness value of the target fillet weld joint. The welding process parameters corresponding to the target fillet weld joint include the welding current, arc voltage, and welding speed used to weld the target fillet weld joint.

[0113] S702: Determine welding deformation parameter values ​​of a target fillet weld joint based on the plate thickness, welding process parameter values, and a target hull stiffener fillet weld deformation prediction model. The target hull stiffener fillet weld deformation prediction model is constructed using the method for constructing a hull stiffener fillet weld deformation prediction model in any of the above schemes.

[0114] It can be understood that the variables in the target hull stiffener fillet weld deformation prediction model are the plate thickness, welding process parameters, and welding deformation parameters. Therefore, after determining the plate thickness value and the corresponding welding process parameter values ​​of the target fillet weld joint, the welding deformation parameter values ​​of the target fillet weld joint, that is, the longitudinal shrinkage force value and transverse bending moment value of the target fillet weld joint, can be calculated based on the target hull stiffener fillet weld deformation prediction model.

[0115] S703: Determine the welding deformation information of the target fillet weld joint according to the welding deformation parameter value of the target fillet weld joint.

[0116] It will be appreciated that after determining the welding deformation parameter values ​​for the target fillet weld, the welding deformation information for the target fillet weld can be further refined based on the welding deformation parameter values ​​for the target fillet weld. For example, the longitudinal shrinkage force value and the transverse bending moment value of the target fillet weld can be used to synthesize welding deformation information (such as the overall curvature of the weldment and the amount of misalignment at the interface).

[0117] The application of the above-mentioned hull stiffener fillet weld deformation prediction model is to input the plate thickness value and corresponding welding process parameter values ​​of the target fillet weld joint into the target hull stiffener fillet weld deformation prediction model, and then determine the welding deformation parameter value of the target fillet weld joint based on the target hull stiffener fillet weld deformation prediction model, thereby determining the welding deformation information of the target fillet weld joint based on the welding deformation parameter value of the target fillet weld joint. Because the target hull stiffener fillet weld deformation prediction model is a data-driven model based on mathematical statistics and fitting analysis, the target hull stiffener fillet weld deformation prediction model can quickly obtain deformation prediction data for fillet weld joint samples. Compared with the transient thermal-elastic-plastic finite element calculation method, it does not consume a large amount of computer resources and time. Therefore, the application of the hull stiffener fillet weld deformation prediction model of this embodiment is conducive to improving the efficiency of hull design and construction.

[0118] In some embodiments, see Figure 8 , Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. An electronic device 800 provided in an embodiment of the present application includes a processor 810 and a memory 820; the memory 820 stores a computer program, wherein the computer program, when executed by the processor, implements the method for constructing a hull stiffener fillet weld deformation prediction model as described in any of the above solutions or the application of the hull stiffener fillet weld deformation prediction model as described in any of the above solutions.

[0119] Specifically, the processor 810 may include, for example, a general-purpose microprocessor, an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 810 may also include onboard memory for caching purposes. The processor 810 may be a single processing unit or multiple processing units for executing different actions of the method flow according to the embodiments of the present application.

[0120] Memory 820 can be, for example, any medium capable of containing, storing, conveying, disseminating, or transmitting instructions. For example, memory 820 can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, components, or communication media. Specific examples of memory 820 include: magnetic storage devices, such as magnetic tape or hard disk drives (HDDs); optical storage devices, such as compact discs (CD-ROMs); random access memory (RAM) or flash memory; and / or wired or wireless communication links.

[0121] This application also provides a computer-readable medium having a computer program stored thereon. When executed by a processor, this program implements the method for constructing a hull stiffener fillet weld deformation prediction model as described in any of the above solutions, or the application of the hull stiffener fillet weld deformation prediction model as described in any of the above solutions. This computer-readable medium may be included in the device / apparatus / system described in the above embodiments, or it may exist independently and not be incorporated into the device / apparatus / system. The computer-readable medium carries one or more programs, and when executed, implements the method described in the embodiments of this application.

[0122] According to an embodiment of the present application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, radio frequency signals, or any suitable combination thereof.

[0123] Those skilled in the art will understand that the features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present application. In particular, without departing from the spirit and teachings of the present application, the features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present application. Therefore, the scope of the present application should not be limited to the above-mentioned embodiments, but should be determined not only by the attached claims, but also by the equivalents of the attached claims. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for constructing a deformation prediction model for hull rib fillet welds, characterized in that: The method for constructing the hull stiffener fillet weld deformation prediction model includes: Obtaining plate thickness values ​​and corresponding welding process parameter values ​​of a plurality of fillet weld joint samples, wherein the plate thickness values ​​of the plurality of fillet weld joint samples are different, and the plate thickness values ​​include a bottom plate thickness value and a vertical plate thickness value; Establishing a finite element model of each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample; performing welding finite element analysis on each of the finite element models based on the welding process parameter values ​​of each of the fillet weld joint samples and the thermophysical property parameter information of the fillet weld joint sample materials to determine welding deformation parameter values ​​of each of the fillet weld joint samples, wherein the welding deformation parameter values ​​include at least a longitudinal shrinkage force value and a transverse bending moment value; The correlation model between welding deformation parameters, welding line energy and plate thickness is constructed through dimensional analysis; The dimensionless coefficient of the correlation model is solved according to the plate thickness value, welding process parameter value and welding deformation parameter value of each fillet weld joint sample to obtain the target hull stiffener fillet weld deformation prediction model.

2. The method for constructing a hull rib fillet weld deformation prediction model according to claim 1, wherein: The step of establishing a finite element model of each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample comprises: Establishing a three-dimensional model of each fillet weld joint sample according to the plate thickness value of each fillet weld joint sample; Finite element meshing is performed on the three-dimensional model of each fillet weld joint sample to establish a finite element model of each fillet weld joint sample.

3. The method for constructing a hull stiffener fillet weld deformation prediction model according to claim 1, wherein: The step of performing welding finite element analysis on each finite element model based on the welding process parameter values ​​of each fillet weld joint sample and the thermophysical performance parameter information of the fillet weld joint sample material to determine the welding deformation parameter value of each fillet weld joint sample includes: Performing a thermal-elastic-plastic finite element analysis of the welding on each of the finite element models based on the welding process parameter values ​​and the thermophysical property parameter information of the welding joint material, and obtaining the residual plastic strain distribution information after cooling to room temperature after welding; The welding deformation parameter value of each fillet weld joint sample is determined according to the residual plastic strain distribution information corresponding to each fillet weld joint sample.

4. The method for constructing a hull rib fillet weld deformation prediction model according to claim 3, wherein: The calculation formula for determining the longitudinal shrinkage force value according to the residual plastic strain distribution information corresponding to each fillet weld joint sample is: ； Among them, F longitudinal is the longitudinal shrinkage force of the fillet weld joint sample, is the residual plastic strain value along the weld on different elements, is the elastic modulus of the welding head material, are the coordinates of the centroids of different units in the direction perpendicular to the weld, are the coordinates of the centroids of different elements in the thickness direction.

5. The method for constructing a hull stiffener fillet weld deformation prediction model according to claim 3, wherein: The calculation formula for determining the transverse bending moment value according to the residual plastic strain distribution information corresponding to each fillet weld joint sample is: ； Among them, M transverse is the transverse bending moment of the fillet weld joint specimen, is the residual plastic strain value along the weld on different elements, is the bottom plate thickness, is the elastic modulus of the welding head material, are the coordinates of the centroids of different units in the direction perpendicular to the weld, are the coordinates of the centroids of different elements in the thickness direction.

6. The method for constructing a hull stiffener fillet weld deformation prediction model according to claim 1, wherein: The correlation formula between the longitudinal shrinkage force and the welding line energy is: ； Among them, F longitudinal is the longitudinal contraction force of the fillet weld specimen, Qnet is the weld line energy, and a and b are dimensionless coefficients.

7. The method for constructing a hull stiffener fillet weld deformation prediction model according to claim 1, wherein: The correlation formula between the transverse bending moment, welding line energy and plate thickness is: ； Among them, M transverse is the transverse bending moment of the fillet weld joint specimen, Qnet is the welding line energy, is the base plate thickness, c and d are dimensionless coefficients.

8. The method for constructing a hull stiffener fillet weld deformation prediction model according to claim 1, wherein: Solving the dimensionless coefficient of the correlation model based on the plate thickness value, welding process parameter value and welding deformation parameter value of each fillet weld joint sample to obtain the target hull stiffener fillet weld deformation prediction model includes: Determining the welding energy input value corresponding to each fillet weld joint sample according to the welding process parameter value of each fillet weld joint sample; Determining the dimensionless coefficient values ​​of the correlation model by fitting the bottom plate thickness value, welding line energy value and welding deformation parameter value corresponding to each fillet weld joint sample; Substituting each dimensionless coefficient value into the correlation model, the target hull stiffener fillet weld deformation prediction model is obtained.

9. The method for constructing a hull stiffener fillet weld deformation prediction model according to any one of claims 1 to 8, wherein: The method for constructing the hull stiffener fillet weld deformation prediction model further includes: Obtaining a plate thickness value and verification parameters of a verification fillet weld joint sample, wherein the verification parameters include a reference value of a welding deformation parameter of the verification fillet weld joint sample; Solving the target hull stiffener fillet weld deformation prediction model according to the plate thickness value and welding process parameter values ​​of the verification fillet weld joint sample, and determining the solution value of the welding deformation parameter of the verification fillet weld joint sample; A score of the target hull stiffener fillet weld deformation prediction model is determined according to the reference value and the solution value.

10. An application of a hull stiffener fillet weld deformation prediction model, characterized in that: Applications of the hull stiffener fillet weld deformation prediction model include: Obtain the plate thickness value and corresponding welding process parameter values ​​of the target fillet weld joint; determining a welding deformation parameter value of the target fillet weld joint according to the plate thickness value, the welding process parameter value, and a target hull stiffener fillet weld deformation prediction model, wherein the target hull stiffener fillet weld deformation prediction model is constructed using the method according to any one of claims 1 to 9; The welding deformation information of the target fillet weld joint is determined according to the welding deformation parameter value of the target fillet weld joint.

Images