Construction method and application of ship body rib plate fillet welding deformation prediction model

Abstract

The invention provides a construction method and application of a hull rib plate fillet welding deformation prediction model, and relates to the technical field of welding. The construction method comprises the following steps: acquiring plate thickness values of a plurality of fillet welding joint samples; establishing a finite element analysis model of each fillet welding 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 value of each fillet welding joint sample and the thermophysical performance parameter information of the sample material, and determining the welding deformation parameter value of each fillet welding joint sample; building a correlation model among the welding deformation parameters, the welding line energy and the plate thickness through dimensional analysis; and according to the plate thickness value, the welding process parameter value and the welding deformation parameter value of each fillet welding joint sample, a dimensionless coefficient of the correlation model is solved, and a target hull rib plate fillet welding deformation prediction model is obtained. According to the method, the ship body rib plate fillet welding deformation is quickly and accurately predicted by constructing the target ship body rib plate fillet welding deformation prediction model.

Description

Technical Field

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

[0002] During the construction of ship hull sections, in order to effectively reduce its own weight and ensure structural strength. Generally, longitudinal angle bars need to be welded along the ship length direction, and structures such as ribs and stiffeners need to be welded along the ship width direction. The welding deformation of the welded structure will seriously affect the construction accuracy of the ship hull section, and further affect the subsequent section assembly and ship 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 prediction model for fillet welding deformation of ship hull stiffeners.

[0005] In a first aspect, the present application provides a method for constructing a prediction model for fillet welding deformation of ship hull stiffeners, the method for constructing the prediction model for fillet welding deformation of ship hull stiffeners comprising: Obtaining the 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 the bottom plate thickness value and the vertical plate thickness value; Establishing a finite element model for each of the fillet weld joint samples based on the plate thickness values of each of the fillet weld joint samples; 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 material to determine the welding deformation parameter values of each of the fillet weld joint samples, wherein the welding deformation parameter values at least include the longitudinal shrinkage force value and the transverse bending moment value; Constructing a correlation model between the welding deformation parameters, the welding line energy, and the plate thickness through dimensional analysis; Solving the dimensionless coefficients of the correlation model according to the plate thickness values of each of the fillet weld joint samples, the welding process parameter values of each of the fillet weld joint samples, and the welding deformation parameter values to obtain the target prediction model for fillet welding deformation of ship hull stiffeners.

[0006] In one embodiment, the establishing a finite element model for each of the fillet weld joint samples based on the plate thickness values of each of the fillet weld joint samples includes: Establishing a three-dimensional model for each of the fillet weld joint samples according to the plate thickness values of each of the fillet weld joint samples; Perform finite element meshing on the 3D models of each of the corner weld joint samples to establish the finite element models of each of the corner weld joint samples.

[0007] In one embodiment, perform welding finite element analysis on each of the finite element models based on the welding process parameter values of each of the corner weld joint samples and the thermophysical property parameter information of the corner weld joint sample materials to determine the welding deformation parameter values of each of the corner weld joint samples, including: Perform thermo-elasto-plastic finite element analysis of welding on the finite element models of each of the corner weld joint samples after finite element meshing based on the welding process parameter values and the thermophysical property parameter information of the weld joint materials to obtain the residual plastic strain distribution information after cooling to room temperature after welding; Determine the welding deformation parameter values of each of the corner weld joint samples according to the residual plastic strain distribution information corresponding to each of the corner weld joint samples.

[0008] In one embodiment, the calculation formula for determining the longitudinal contraction force value according to the residual plastic strain distribution information corresponding to each of the corner weld joint samples is: ; where F longitudinal is the longitudinal contraction force of the corner weld joint sample, is the residual plastic strain value along the weld on different elements, is the elastic modulus of the weld joint material, is the coordinate of the centroid of different elements in the direction perpendicular to the weld, is the coordinate of the centroid of different elements in the thickness direction.

[0009] In one embodiment, the calculation formula for determining the transverse bending moment value according to the residual plastic strain distribution information corresponding to each of the corner weld joint samples is: ; where M transverse is the transverse bending moment of the corner weld joint sample, is the residual plastic strain value along the weld on different elements, is the bottom plate thickness, is the elastic modulus of the weld joint material, is the coordinate of the centroid of different elements in the direction perpendicular to the weld, is the coordinate of the centroid of different elements in the thickness direction.

[0010] In one embodiment, the correlation formula between the longitudinal contraction force and the welding line energy is: ; where F longitudinalis the longitudinal contraction force of the fillet weld joint sample, Qnet is the welding line energy, and a and b are dimensionless coefficients.

[0011] In one embodiment, the correlation formula between the transverse bending moment, the welding line energy, and the plate thickness is: ; where, M transverse is the transverse bending moment of the fillet weld joint sample, Qnet is the welding line energy, is the bottom plate thickness, and c and d are dimensionless coefficients.

[0012] In one embodiment, solving the dimensionless coefficients of the correlation model according to the plate thickness values of each fillet weld joint sample, the welding process parameter values of each fillet weld joint sample, and the welding deformation parameter values to obtain the target hull stiffener fillet weld deformation prediction model includes: Determining the welding line energy values corresponding to each fillet weld joint sample according to the welding process parameter values of each fillet weld joint sample; Fitting and determining the dimensionless coefficient values of the correlation model according to the bottom plate thickness values, welding line energy values, and welding deformation parameter values corresponding to each fillet weld joint sample; Substituting each dimensionless coefficient value into the correlation model to obtain the target hull stiffener fillet weld deformation prediction model.

[0013] In one embodiment, the method for constructing the hull stiffener fillet weld deformation prediction model further includes: Obtaining the plate thickness values and verification parameters of the verification fillet weld joint samples, where the verification parameters include the reference values of the welding deformation parameters of the verification fillet weld joint samples; Solving the target hull stiffener fillet weld deformation prediction model according to the plate thickness values and welding process parameter values of the verification fillet weld joint samples to determine the calculated values of the welding deformation parameters of the verification fillet weld joint samples; Determining the score of the target hull stiffener fillet weld deformation prediction model according to the reference values and the calculated values.

[0014] In a second aspect, the present application also provides an application of the hull stiffener fillet weld deformation prediction model, and the application of the hull stiffener fillet weld deformation prediction model includes: Obtaining the plate thickness value and the corresponding welding process parameter value of the target fillet weld joint; 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, where the target hull stiffener fillet weld deformation prediction model is constructed by the method described in the first aspect; Determine the welding deformation information of the target fillet weld joint according to the welding deformation parameter values of the target fillet weld joint.

[0015] The construction method of a fillet weld deformation prediction model for a ship hull stiffener plate of the present application has the following beneficial effects compared with the related art: 1. 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, the present application conducts welding finite element analysis on each finite element model to determine the welding deformation parameter values of each fillet weld joint sample, and then constructs a correlation model between the welding deformation parameters, the welding line energy, and the plate thickness through dimensional analysis; solve the dimensionless coefficient of the correlation model according to the plate thickness values of each fillet weld joint sample, the welding process parameter values of each fillet weld joint sample, and the welding deformation parameter values to obtain the target fillet weld deformation prediction model for the ship hull stiffener plate. During the construction process of the model, the thermophysical property parameters of the material that vary with temperature are considered, and the influence of environmental factors is fully considered, which is conducive to constructing a target fillet weld deformation prediction model for the ship hull stiffener plate with higher prediction accuracy.

[0016] 2. Compared with the traditional empirical formula modeling method based on engineering trial and error, the present application constructs a dimensionally consistent mathematical model based on the basic principle of dimensional analysis method through the Buckingham π theorem, and establishes the correlation between the welding deformation characteristic parameters and the key physical quantities such as the welding line energy and the plate thickness. This modeling method follows the physical similarity principle, ensuring the theoretical rigor and engineering applicability of the model. The constructed target fillet weld deformation prediction model for the ship hull stiffener plate not only has stronger interpretability in physical meaning, but also has a greater improvement in prediction accuracy compared with the traditional empirical model, which is conducive to accurately predicting the deformation of the fillet weld joint of the ship hull stiffener plate through the target fillet weld deformation prediction model for the ship hull stiffener plate.

[0017] 3. The target fillet weld deformation prediction model for the ship hull stiffener plate constructed in the present application is a data-driven model based on mathematical statistics and fitting analysis. Using the target fillet weld deformation prediction model for the ship hull stiffener plate can quickly obtain the deformation prediction data of the fillet weld joint, which is conducive to improving the efficiency of ship hull design and construction.

[0018] 4. Using the longitudinal contraction force and the transverse bending moment to characterize the welding deformation is more reasonable and scientific than the in-plane shrinkage, angular deformation, etc. of the traditional empirical formula in terms of physical phenomena and mechanical mechanisms, which is conducive to further improving the prediction accuracy of the target fillet weld deformation prediction model for the ship hull stiffener plate. Description of the Drawings

[0019] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0020] Figure 1 It is a schematic flowchart of a method for constructing a hull stiffener fillet weld deformation prediction model in an embodiment of the present application; Figures 2a to 2j They are cross-sectional schematic diagrams of fillet weld joints T1 to T10 in sequence; Figure 3a It is a schematic diagram of the thermal performance parameters of AH36 high-strength steel varying with temperature in an embodiment of the present application; Figure 3b It is a schematic diagram of the mechanical performance parameters of AH36 high-strength steel varying with temperature in an embodiment of the present application; Figure 4a It is a schematic diagram of the longitudinal residual plastic strain distribution after welding and cooling to room temperature state based on welding finite element calculation in an embodiment of the present application; Figure 4b It is a schematic diagram of the transverse residual plastic strain distribution after welding and cooling to room temperature state based on welding finite element calculation in an embodiment of the present application; Figure 5a It is a schematic diagram of solving the dimensionless coefficient in formula (1) by fitting in an embodiment of the present application; Figure 5b It is a schematic diagram of solving the dimensionless coefficient in formula (2) by fitting in an embodiment of the present application; Figure 6 It is a cross-sectional schematic diagram of the 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 an embodiment of the present application; Figure 7 It is a schematic flowchart of the application of the hull stiffener fillet weld deformation prediction model in an embodiment of the present application; Figure 8 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application. Detailed implementation manners

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present application in combination with the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0022] In some embodiments, such as Figure 1 shown, Figure 1 This is a method for constructing a prediction model for fillet welding deformation of a hull stiffener provided by an embodiment of the present application. The method for constructing the prediction model for fillet welding deformation of the hull stiffener includes the following steps S101 to S105.

[0023] S101: Obtain the plate thickness values and corresponding welding process parameter values of multiple fillet weld joint samples. Among them, the plate thickness values of the multiple fillet weld joint samples are different, and the plate thickness values include the bottom plate thickness value and the vertical plate thickness value. The fillet weld joint samples are fillet weld joint samples of the hull stiffener.

[0024] In application, the plate thicknesses of multiple fillet weld joint samples can be obtained in advance and stored in a database. Different sample data can be selected from the database as sample data according to requirements.

[0025] It should be noted that the number of finite element analysis models obtained can be selected according to actual needs and is not specifically limited here. Exemplarily, the plate thickness values of 10 fillet weld joint samples can be obtained to construct the target prediction model for fillet welding deformation of the hull stiffener. The bottom plate thickness and vertical plate thickness of the 10 fillet weld joint samples can be as shown in Table 1 below.

[0026] Table 1 shows the bottom plate thickness and vertical plate thickness of 10 fillet weld joint samples

[0027] S102: Establish a finite element model for each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample.

[0028] Among them, the plate thickness value can be obtained by actual measurement. Tools such as calipers can be used to directly measure the thickness of the plate in the fillet weld joint sample. Finite element analysis is a numerical calculation method. By discretizing a continuous solid structure into a finite number of elements, a mathematical model is established for each element and solved to obtain physical quantities such as the mechanical response and thermal response of the entire structure. When constructing the finite element analysis model of the fillet weld joint sample, the plate thickness value can be used to define the geometric shape and material properties of the model. For example, in the geometric modeling stage, the geometric dimensions of the fillet weld joint sample, including parameters such as the length, width, and thickness of the plate, are determined according to the plate thickness, so as to accurately construct a three-dimensional geometric model of the fillet weld joint sample. In terms of setting material properties, the thickness value will affect the setting of parameters such as the heat conduction and mechanical properties of the material, because plates of different thicknesses have different heat conduction and mechanical deformation characteristics under the same welding conditions. By reasonably using the plate thickness value to construct the finite element analysis model, the physical phenomena and mechanical behaviors of the fillet weld joint sample during the welding process can be more accurately simulated, providing a theoretical basis for the optimization of the welding process and the control of welding quality.

[0029] It is understandable that the 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. The plate thickness is an important parameter affecting many factors such as the mechanical properties, heat conduction characteristics, and welding deformation of the fillet weld joint sample. Different plate thicknesses will result in differences in the heat distribution, stress distribution, and final welding quality during the welding process. 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.

[0030] In application, a corresponding model or software can be used to establish the finite element model of each fillet weld joint sample.

[0031] Exemplarily, the cross-sectional schematic diagrams of the 10 fillet weld joint samples in Table 1 can be as Figures 2a to 2j shown Figures 2a to 2j and are, in sequence, the cross-sectional schematic diagrams of fillet weld joint samples T1 to T10.

[0032] 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 values of each fillet weld joint sample. Among them, the welding deformation parameter values at least include the longitudinal contraction force value and the transverse bending moment value.

[0033] In application, the welding process parameters can include welding current, arc voltage, and welding speed. The welding process parameters can be determined in advance. Exemplarily, the welding current can be 300A, the arc voltage can be 33V, and the welding speed can be 10mm / s. The material of the fillet weld joint sample can be determined in advance. After determining the material of the fillet weld joint sample, the thermophysical property parameter information of the fillet weld joint sample material can be determined. Exemplarily, the material of the fillet weld joint sample can be AH36 high-strength steel. The thermal performance parameters of AH36 high-strength steel varying with temperature can be referred to Figure 3a and the mechanical property parameters of AH36 high-strength steel varying with temperature can be referred to Figure 3b .

[0034] It is understandable that after determining the welding process parameter values of each fillet weld joint sample and the thermophysical property parameter information of the fillet weld joint sample material, the welding process parameter values of each fillet weld joint sample and the thermophysical property 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 a welding finite element analysis model to determine the welding deformation parameter values of each fillet weld joint sample.

[0035] S104: Construct a correlation model between the welding deformation parameters, the welding line energy, and the plate thickness through dimensional analysis.

[0036] It can be understood that there are relationships among various physical quantities, indicating that their structures must be composed of several unified basic components, and the differences in quantity and quantity are formed according to the amount of each component. Just as all things in the world are composed of only more than a hundred chemical elements. Such basic components of physical quantities are collectively called dimensions. Since physics studies the evolution and motion of matter in space-time, all quantitative problems ultimately cannot do without these three basic quantities: mass, time, and length. Therefore, it is most appropriate to select M, T, and L as the dimensions of these three basic quantities. The dimensions of all other derived quantities can be expressed as combinations of the dimensions of these three basic quantities according to definitions or objective laws. There are multiple ways to choose the basic quantities. In mechanics, mass, length, and time are usually taken as the basic quantities, and other quantities (such as velocity, force, etc.) can be derived from the basic quantities according to certain rules. Any other three types of derived quantities with independent dimensions can also be used as basic quantities. Two physical quantities with completely different natures can have the same dimension, such as work and torque. In any equation that correctly reflects the laws of physical phenomena, each term on both sides of the equation must have the same dimension.

[0037] Among them, the unit of the longitudinal contraction force is N, and the unit of the welding line energy is KJ / m, that is, ( ) / m; at the same time, the unit of the transverse bending moment is ( ), and the unit of the welding line energy × the thickness of the bottom plate is (KJ / m) m, that is, ( ). Therefore, the welding deformation parameters are dimensionally related to the welding line energy and the thickness of the plate. A correlation model between the welding deformation parameters, the welding line energy, and the thickness of the plate can be constructed based on the dimensional relationship. This modeling method follows the principle of physical similarity, ensuring the theoretical rigor and engineering applicability of the model.

[0038] In one of the embodiments, the correlation formula between the longitudinal contraction force and the welding line energy can be: (1) The correlation formula between the transverse bending moment and the welding line energy and the thickness of the plate can be: (2) Among them, F longitudinal is the longitudinal contraction force of the fillet weld joint sample, M transverse is the transverse bending moment of the fillet weld joint sample, Qnet is the welding line energy, is the thickness of the bottom plate, and a, b, c, and d are dimensionless coefficients.

[0039] S105: Solve the dimensionless coefficients of the correlation model according to the thickness values of the plates of each fillet weld joint sample, the welding process parameter values of each fillet weld joint sample, and the welding deformation parameter values to obtain the target prediction model for the fillet weld deformation of the hull stiffener.

[0040] It can be understood that there are uncertain dimensionless coefficients in the correlation model constructed in step S104. Therefore, it is necessary to solve the correlation model to determine the values of the dimensionless coefficients in the correlation model, so as to obtain the target hull stiffener fillet welding deformation prediction model. Therefore, in this embodiment, the dimensionless coefficients of the correlation model are solved by using the plate thickness values of each fillet weld joint sample, the welding process parameter values of each fillet weld joint sample, and the welding deformation parameter values, and the target hull stiffener fillet welding deformation prediction model is constructed.

[0041] The above method for constructing the hull stiffener fillet welding deformation prediction model performs welding finite element analysis on each three-dimensional model after finite element mesh division 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 values of each fillet weld joint sample, and then constructs a correlation model between the welding deformation parameters, the welding line energy, and the plate thickness through dimensional analysis; the dimensionless coefficients of the correlation model are solved according to the plate thickness values of each fillet weld joint sample, the welding process parameter values of each fillet weld joint sample, and the welding deformation parameter values to obtain the target hull stiffener fillet welding deformation prediction model, thereby establishing a correlation relationship between the welding deformation characteristic parameters and the key physical quantities such as the welding line energy and the plate thickness based on the basic principle of dimensional analysis method. The constructed target hull stiffener fillet welding deformation prediction model not only has stronger interpretability in terms of physical meaning, but also has a greater improvement in the prediction accuracy compared with the traditional empirical model, which is conducive to accurately predicting the deformation of the hull stiffener fillet weld joint sample through the target hull stiffener fillet welding deformation prediction model. In addition, the target hull stiffener fillet welding deformation prediction model constructed in this application is a data-driven model based on mathematical statistics and fitting analysis. Using the target hull stiffener fillet welding deformation prediction model can quickly obtain the deformation prediction data of the fillet weld joint sample, which is conducive to improving the efficiency of hull design and construction.

[0042] In some embodiments, in step S102, establishing the finite element model of each fillet weld joint sample based on the plate thickness value of each fillet weld joint sample includes: establishing the three-dimensional model of each fillet weld joint sample according to the plate thickness value of each fillet weld joint sample; performing finite element mesh division on the three-dimensional model of each fillet weld joint sample to establish the finite element model of each fillet weld joint sample.

[0043] In the application, the plate thickness values of each corner welded joint sample can be used as input parameters for a 3D modeling model or 3D modeling software, and a 3D model of each corner welded joint sample can be established using the 3D modeling model or 3D modeling software. After establishing the 3D model of each corner welded joint sample, finite element mesh division can be performed on the 3D model of each corner welded joint sample through finite element preprocessing software or a model to obtain the mesh information and cross-section of the 3D model of each corner welded joint sample, thereby establishing a finite element model of each corner welded joint sample.

[0044] 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 corner welded joint sample and the thermophysical property parameter information of the corner welded joint sample material to determine the welding deformation parameter values of each corner welded joint sample, including: performing thermo-elasto-plastic finite element analysis of welding on each finite element model based on the welding process parameter values and the thermophysical property parameter information of the welded joint material to obtain the residual plastic strain distribution information after cooling to room temperature; and determining the welding deformation parameter values of each corner welded joint sample according to the residual plastic strain distribution information corresponding to each corner welded joint sample.

[0045] Among them, thermo-elasto-plastic finite element analysis (Thermo-Elasto-Plastic Finite Element Analysis) is a numerical simulation method for multi-physical field coupling, aiming to reveal the non-linear behavior of materials under the combined action of thermal load and mechanical load. This method discretizes the three-dimensional continuous medium (finite element mesh) and solves the coupled control equations of the heat conduction equation and the elasto-plastic constitutive relation to simulate the thermodynamic response of the material from high-temperature loading (such as welding) to cooling and unloading throughout the process: first, a transient heat input is applied based on a heat source model (such as Gaussian distribution or double ellipsoid heat source) to calculate the spatio-temporal distribution of the temperature field; then, through a thermal-mechanical coupling algorithm, the temperature gradient is converted into thermal stress, and combined with the elasto-plastic increment theory (such as J2 flow theory), the yield behavior (beyond the elastic limit), plastic strain accumulation (irreversible deformation), and hardening effect (kinematic / isotropic hardening model) of the material in the phase change temperature range are traced; finally, through stress relaxation analysis during the cooling process, the residual stress field, plastic strain distribution, and macroscopic deformation (such as welding angular deformation, residual deflection) are obtained.

[0046] Exemplarily, based on the 10 corner welded joint samples shown in Table 1, a 3D model is established, and after finite element mesh division of each 3D model, thermo-elasto-plastic finite element analysis of welding is performed on each finite element model based on the welding process parameter values and the thermophysical property parameter information of the welded joint material. The residual plastic strain distribution and numerical values after welding finite element calculation and cooling to room temperature 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.

[0047] It can be understood that based on welding process parameters (such as current, voltage, welding speed, etc.) and thermophysical property parameters of the welding head material (including thermal conductivity, specific heat capacity, thermal expansion coefficient, etc.), a thermo-elasto-plastic finite element analysis is carried out on the finite element model to simulate the dynamic evolution of the temperature field, stress field and strain field during the welding process: First, the welding heat input is loaded through the heat source model to calculate the transient temperature distribution, driving the material to undergo thermal expansion and contraction during melting, solidification and cooling; Subsequently, the elasto-plastic constitutive relationship is coupled to track the yield behavior of the material at high temperature and the accumulation of plastic deformation until the residual plastic strain is formed after cooling to room temperature; Finally, the spatial distribution data of the residual plastic strain after welding of each finite element model is extracted, and the welding deformation parameter values are calculated through the strain-deformation conversion relationship (such as integral plastic strain gradient), realizing the quantitative mapping from microscopic plastic strain to macroscopic deformation, and obtaining the welding deformation parameter values of each fillet weld joint sample. This process integrates thermodynamics, material mechanics and numerical simulation technologies, and reveals the formation mechanism of welding residual deformation through multi-physical field coupling analysis, providing a reliable theoretical basis for welding process optimization and structural deformation prediction.

[0048] In one embodiment, the calculation formula for determining the longitudinal contraction force value according to the residual plastic strain distribution information corresponding to each fillet weld joint sample is: (3) 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: (4) where F longitudinal is the longitudinal contraction force of the fillet weld joint sample, M transverse is the transverse bending moment of the fillet weld joint sample, is the numerical value of the residual plastic strain along the weld on different elements, is the numerical value of the residual plastic strain perpendicular to the weld on different elements, is the thickness of the bottom plate, is the elastic modulus of the welding head material, is the coordinate of the centroid of different elements in the direction perpendicular to the weld, is the coordinate of the centroid of different elements in the thickness direction.

[0049] In some embodiments, in step S105, the dimensionless coefficients of the correlation model are solved according to the plate thickness values of each fillet weld joint sample, the welding process parameter values of each fillet weld joint sample, and the welding deformation parameter values, 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 values of each fillet weld joint sample; fitting and determining the dimensionless coefficient values of the correlation model according to the bottom plate thickness value, the welding line energy value, and the 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.

[0050] 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.

[0051] It can be understood that there is a correlation relationship between the welding deformation parameters, the welding line energy, and the plate thickness. The specific correlation relationship can refer to the previous formulas (1) and (2). Then, in order to calculate the dimensionless coefficients of formulas (1) and (2), the welding line energy value and the longitudinal shrinkage force value corresponding to each fillet weld joint sample can be substituted into formula (1), and the bottom plate thickness value, the welding line energy value, and the 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, so as to determine each dimensionless coefficient value 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 situation.

[0052] Exemplarily, the parameters corresponding to the 10 fillet weld joint samples in Table 1 can be as shown in Table 2 below.

[0053] Table 2 shows the welding line energy and welding deformation parameters corresponding to 10 fillet weld joint samples

[0054] Taking the parameters shown in Table 2 as an example, the dimensionless coefficients in formula (1) are solved by fitting as Figure 5a shown, and the dimensionless coefficients in formula (2) are solved by fitting as Figure 5b shown, so as to determine each dimensionless coefficient value in the correlation model, and then complete the construction of the target hull stiffener fillet weld deformation prediction model.

[0055] In some embodiments, the method for constructing the hull stiffener fillet welding deformation prediction model further includes: obtaining the plate thickness value and verification parameters of the verification fillet weld joint sample, where the verification parameters include the reference values of the welding deformation parameters of the verification fillet weld joint sample; solving the target hull stiffener fillet welding deformation prediction model according to the plate thickness value and welding process parameter value of the verification fillet weld joint sample to determine the calculated values of the welding deformation parameters of the verification fillet weld joint sample; and determining the score of the target hull stiffener fillet welding deformation prediction model based on the reference values and the calculated values.

[0056] Among them, transient thermo-elasto-plastic finite element calculation can be used for predicting the welding temperature field, strain, and deformation. Therefore, the verification parameters can be obtained through transient thermo-elasto-plastic finite element calculation.

[0057] 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 stiffener fillet welding deformation prediction model for solution to obtain the calculated values of the welding deformation parameters of the verification fillet weld joint sample (i.e., the calculated values of the longitudinal contraction force and the transverse bending moment). Then, the error parameters between the reference values and the calculated values can be calculated, and the score of the target hull stiffener fillet welding deformation prediction model can be determined based on the error parameters. For example, a relationship formula between the model score and the error parameters can be preset in advance, and after obtaining the error parameters, the score of the target hull stiffener fillet welding deformation prediction model can be determined based on the error parameters and this relationship formula. Another example is that multiple error intervals can be preset in advance, each error interval corresponds to a score, and the score of the target hull stiffener fillet welding deformation prediction model can be determined according to the interval where the error parameters are located.

[0058] Exemplarily, 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, and its finite element mesh cross-section is as Figure 6 shown; by integrating the residual plastic strain of the welding thermo-elasto-plastic finite element calculation, the longitudinal contraction force value and the transverse bending moment value can be obtained. The longitudinal contraction force value and the transverse bending moment value can also be obtained by using the target hull stiffener fillet welding deformation prediction model for calculation. Table 3 shows the evaluation results of the two methods.

[0059] Table 3 shows the comparison results between the thermo-elasto-plastic finite element prediction method and the calculation method of the target hull stiffener fillet welding deformation prediction model

[0060] In this embodiment, after determining the score of the target hull stiffener fillet weld deformation prediction model, the accuracy of the target hull stiffener fillet weld deformation prediction model can be determined according to the score of the target hull stiffener fillet weld deformation prediction model. If the score of the target hull stiffener fillet weld deformation prediction model is too low, the number of samples needs to be increased to construct a new target hull stiffener fillet weld deformation prediction model. That is, increase the number of finite element analysis models of fillet weld joint samples obtained in step S101, and based on the newly obtained finite element analysis models, use any of the above-mentioned methods for constructing a hull stiffener fillet weld deformation prediction model to construct a new target hull stiffener fillet weld deformation prediction model, so as to construct a target hull stiffener fillet weld deformation prediction model with higher accuracy and improve the accuracy of fillet weld deformation evaluation.

[0061] It should be noted that in application, the sample points can be continuously improved and increased to enhance the scale of the data-driven database, improve the accuracy of the target hull stiffener fillet weld deformation prediction model, and further improve the accuracy of fillet weld deformation evaluation.

[0062] In some embodiments, as Figure 7 shown, the present application also provides an application of a hull stiffener fillet weld deformation prediction model. The application of the hull stiffener fillet weld deformation prediction model includes the following steps S701 to S703.

[0063] S701: Obtain the plate thickness value and the corresponding welding process parameter value of the target fillet weld joint.

[0064] Among them, 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 for welding the target fillet weld joint.

[0065] S702: Determine the welding deformation parameter value of the target fillet weld joint according to the plate thickness value, welding process parameter value, and the target hull stiffener fillet weld deformation prediction model. The target hull stiffener fillet weld deformation prediction model is constructed by using any of the above-mentioned methods for constructing a hull stiffener fillet weld deformation prediction model.

[0066] 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 value of the target fillet weld joint, the welding deformation parameter value of the target fillet weld joint, that is, the longitudinal contraction force value and the transverse bending moment value of the target fillet weld joint, can be calculated based on the target hull stiffener fillet weld deformation prediction model.

[0067] 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.

[0068] It can be understood that after determining the welding deformation parameter values of the target fillet weld joint, the welding deformation information of the target fillet weld joint can be further improved based on the welding deformation parameter values of the target fillet weld joint. For example, the welding deformation information (such as the overall bending degree of the welded part and the misalignment amount of the interface) can be synthesized from the longitudinal contraction force value and the transverse bending moment value of the target fillet weld joint.

[0069] The application of the above-mentioned hull stiffener fillet weld deformation prediction model determines the welding deformation parameter values of the target fillet weld joint by inputting the plate thickness value and the corresponding welding process parameter values of the target fillet weld joint into the target hull stiffener fillet weld deformation prediction model, so that the welding deformation information of the target fillet weld joint can be determined according to the welding deformation parameter values of the target fillet weld joint. Since the target hull stiffener fillet weld deformation prediction model is a data-driven model based on mathematical statistics and fitting analysis, using the target hull stiffener fillet weld deformation prediction model can quickly obtain the deformation prediction data of the fillet weld joint samples. Compared with the transient thermo-elasto-plastic finite element calculation method, it does not require a large amount of computer resources and time. Therefore, the application of the hull stiffener fillet weld deformation prediction model in this embodiment is beneficial to improving the efficiency of hull design and construction.

[0070] In some embodiments, please refer to Figure 8 , Figure 8 which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. An electronic device 800 provided by 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 construction method of the hull stiffener fillet weld deformation prediction model described in any of the above solutions or the application of the hull stiffener fillet weld deformation prediction model described in any of the above solutions.

[0071] Specifically, the processor 810 can include, for example, a general microprocessor, an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application specific integrated circuit (ASIC)), etc. The processor 810 can also include on-board memory for caching purposes. The processor 810 can be a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiments of the present application.

[0072] The memory 820 can be, for example, any medium capable of containing, storing, transmitting, propagating, or transferring instructions. For example, the memory 820 can include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, components, or propagation media. Specific examples of the memory 820 include: magnetic storage devices, such as magnetic tapes or hard disk drives (HDDs); optical storage devices, such as compact discs (CD-ROMs); it can also be, for example, random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0073] The present application also provides a computer-readable medium, on which a computer program is stored. When the program is executed by a processor, it implements the method for constructing the fillet weld deformation prediction model of the hull stiffener as described in any of the above solutions or the application of the fillet weld deformation prediction model of the hull stiffener as described in any of the above solutions. The computer-readable medium may be included in the device / apparatus / system described in the above embodiments; or it may exist alone without being assembled into the device / apparatus / system. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed, the method of the embodiments of the present application is implemented.

[0074] According to an embodiment of the present application, the computer-readable medium may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium 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 of the above. In the present application, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device. In the present application, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code included on the computer-readable medium may be transmitted by any suitable medium, including but not limited to: wireless, wired, optical cable, radio frequency signal, etc., or any suitable combination of the above.

[0075] Those skilled in the art can understand that the features recited in the various embodiments and / or claims of the present application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly recited in the present application. In particular, without departing from the spirit and teachings of the present application, the features recited in the various embodiments and / or claims of the present application can be combined and / or combined in various ways. All such 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 embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A method for constructing a prediction model of fillet welding deformation of a ship hull stiffener, characterized in that, The method for constructing the angular welding deformation prediction model of the hull stiffener includes: Obtaining the plate thickness values and corresponding welding process parameter values of multiple fillet weld joint samples, wherein the plate thickness values of the multiple fillet weld joint samples are different, and the plate thickness values include the bottom plate thickness value and the vertical plate thickness value; Establishing finite element models for each of the fillet weld joint samples based on the plate thickness values of each of the fillet weld joint samples; 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 material to determine the welding deformation parameter values of each of the fillet weld joint samples, wherein the welding deformation parameter values at least include the longitudinal contraction force value and the transverse bending moment value; Constructing a correlation model between the welding deformation parameters, the welding line energy, and the plate thickness through dimensional analysis; Solving the dimensionless coefficients of the correlation model according to the plate thickness values of each of the fillet weld joint samples, the welding process parameter values of each of the fillet weld joint samples, and the welding deformation parameter values to obtain the target angular welding deformation prediction model of the hull stiffener.

2. The method for constructing the fillet welding deformation prediction model of the hull stiffener according to claim 1, characterized in that The establishing of the finite element models for each of the fillet weld joint samples based on the plate thickness values of each of the fillet weld joint samples includes: Establishing three-dimensional models for each of the fillet weld joint samples according to the plate thickness values of each of the fillet weld joint samples; Performing finite element mesh division on the three-dimensional models of each of the fillet weld joint samples to establish the finite element models for each of the fillet weld joint samples.

3. The method for constructing the fillet welding deformation prediction model of the hull stiffener as claimed in claim 1, wherein The performing of 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 material to determine the welding deformation parameter values of each of the fillet weld joint samples includes: Performing thermo-elasto-plastic finite element analysis of welding on each of the finite element models based on the welding process parameter values and the thermophysical property parameter information of the weld joint material to obtain the residual plastic strain distribution information after cooling to room temperature after welding; Determining the welding deformation parameter values of each of the fillet weld joint samples according to the residual plastic strain distribution information corresponding to each of the fillet weld joint samples.

4. The method for constructing the fillet welding deformation prediction model of the hull stiffener according to claim 3, characterized in that, The calculation formula for determining the longitudinal contraction force value according to the residual plastic strain distribution information corresponding to each of the fillet weld joint samples is: ； Among them, F longitudinal is the longitudinal contraction force of the fillet weld joint sample of the fillet weld joint sample, is the residual plastic strain value along the weld on different units, is the elastic modulus of the weld joint material, is the coordinate of the centroid of different units in the direction perpendicular to the weld, is the coordinate of the centroid of different units in the thickness direction.

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

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

7. The method for constructing the angular welding deformation prediction model of the hull stiffener as described in claim 1, characterized in that The correlation formula between the transverse bending moment, the welding line energy, and the plate thickness is: ； Among them, M transverse is the transverse bending moment of the fillet weld joint sample, Qnet is the welding line energy, is the thickness of the bottom plate, and c and d are dimensionless coefficients.

8. The method for constructing the fillet welding deformation prediction model of the hull stiffener according to claim 1, characterized in that, The solving of the dimensionless coefficients of the correlation model according to the plate thickness values of each of the fillet weld joint samples, the welding process parameter values of each of the fillet weld joint samples, and the welding deformation parameter values to obtain the target angular welding deformation prediction model of the hull stiffener includes: Determining the welding line energy values corresponding to each of the fillet weld joint samples according to the welding process parameter values of each of the fillet weld joint samples; Fitting and determining the dimensionless coefficient values of the correlation model according to the bottom plate thickness values, the welding line energy values, and the welding deformation parameter values corresponding to each of the fillet weld joint samples; Substitute each of the dimensionless coefficient values into the correlation model to obtain the target hull stiffener fillet weld deformation prediction model.

9. The method for constructing a hull stiffener fillet welding deformation prediction model according to any one of claims 1 to 8, characterized in that The method for constructing the hull stiffener fillet weld deformation prediction model further includes: Obtain the plate thickness value and verification parameters of the verification fillet weld joint sample, where the verification parameters include the reference values of the welding deformation parameters of the verification fillet weld joint sample; Solve 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 to determine the calculated value of the welding deformation parameters of the verification fillet weld joint sample; Determine the score of the target hull stiffener fillet weld deformation prediction model according to the reference value and the calculated value.

10. Application of a prediction model for fillet welding deformation of a ship's stiffener, characterized in that, The application of the hull stiffener fillet weld deformation prediction model includes: Obtain the plate thickness value and the corresponding welding process parameter value of the target fillet weld joint; Determine 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, and the target hull stiffener fillet weld deformation prediction model is constructed by the method according to any one of claims 1 to 9; Determine the welding deformation information of the target fillet weld joint according to the welding deformation parameter value of the target fillet weld joint.

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