A method for optimizing parameters of combined heat sources in deep-sea riser welding
By combining planar Gaussian heat source and conical Gaussian heat source models, and combining orthogonal experiments and range analysis, the combined heat source parameters of the circumferential weld of thick-walled circular pipe in deep-sea risers are optimized, solving the problems of high computational cost and insufficient prediction accuracy in existing technologies, and realizing efficient and accurate prediction of molten pool morphology.
Patent Information
- Application Number
- CN202611066410.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-17
- Publication Date
- 2026-11-06
AI Technical Summary
Existing technologies struggle to efficiently and cost-effectively optimize combined heat source parameters in the circumferential weld of thick-walled circular pipes in deep-sea risers, and the accuracy of molten pool morphology prediction is insufficient. In particular, a quantitative mapping relationship between combined heat source parameters and molten pool morphology for specific working conditions of thick-walled circular pipe circumferential welds in deep-sea risers has not been established.
A combined model of planar Gaussian heat source and conical Gaussian heat source was adopted. By combining L9 orthogonal experimental design and minimum objective function method, the combined heat source parameters were optimized through orthogonal experimental screening and range analysis. A quantitative mapping relationship between heat source parameters and molten pool morphology was established for specific working conditions of thick-walled circular pipe circumferential weld.
It significantly reduces computational costs, achieves global optimal parameter optimization, controls the weld depth prediction error within ±5%, and the weld width prediction error within ±8%, providing reliable support for the optimization of deep-sea riser welding process.
Smart Images
Figure CN123049983A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of welding processing technology, and in particular to a method for optimizing combined heat source parameters in deep-sea riser welding. Background Technology
[0002] As global offshore oil and gas resource development gradually advances into the deep sea, deep-sea risers, as a key structure connecting subsea oil and gas fields to offshore platforms, endure complex marine environmental loads over long periods. The reliability of their welded joints directly determines the safety of the entire transportation system. Deep-sea riser walls are typically 20-30mm thick, and traditional welding process testing suffers from limitations such as high cost, long cycle time, and large parameter space. Numerical simulation technology provides an efficient alternative for welding process optimization. The selection of the heat source model directly affects the prediction accuracy of the temperature field and molten pool morphology, and is a core element determining the reliability of the simulation.
[0003] For welding medium and thick plates, single-surface or volume heat source models are insufficient to simultaneously characterize the heat transfer differences in the surface extension and depth directions of the molten pool. Although double ellipsoidal heat sources are widely used in butt welding of flat plates, their front and rear hemisphere parameters mainly control the asymmetry of the molten pool, limiting their ability to independently control the weld width and depth. Especially in circumferential welds of thick-walled circular pipes, the curved surface geometric constraints and heat dissipation boundary conditions are more complex, further amplifying the prediction bias of the double ellipsoidal model.
[0004] The combined model of a planar Gaussian heat source and a conical Gaussian heat source can separately control the surface weld width and deep weld depth, theoretically making it more suitable for thick-walled deep-penetration welding conditions. Regarding the determination of the characteristic parameters of the combined heat source, existing research has attempted to use orthogonal experiments, response surface methodology, or intelligent optimization algorithms for parameter calibration, which to some extent consider the coupling effect between multiple parameters. However, these methods still have the following shortcomings: First, some methods (such as response surface methodology and genetic algorithms) usually require a large number of simulation samples, resulting in high computational costs; second, existing research is mostly focused on flat or thin-walled tube structures, and a quantitative mapping relationship between the planar-conical combined heat source parameters and the weld pool morphology for the specific working conditions of circumferential welds in thick-walled circular tubes (20-30mm) in deep-sea risers has not yet been established. Therefore, a combined heat source parameter optimization framework that balances computational efficiency and global optimization capability is urgently needed for deep-sea thick-walled circular tubes to solve the technical problem that existing parameter calibration methods cannot simultaneously meet the requirements of low computational cost and high prediction accuracy. Summary of the Invention
[0005] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a method for optimizing combined heat source parameters in deep-sea riser welding, comprising the following steps: Obtain the geometric dimensions, material thermophysical parameters, bevel shape, welding path, and welding process boundary conditions of the deep-sea riser to be welded, and establish a welding finite element geometric model; In the welding finite element geometric model, a combined moving heat source is constructed using a planar Gaussian heat source and a conical Gaussian body heat source. A reference weld test section with the same material, wall thickness, bevel shape and welding process boundary conditions as the deep-sea riser to be welded is obtained to obtain the reference weld width and reference weld depth. The initial parameters of the combined moving heat source are then substituted into the welding finite element geometric model to obtain the verification simulation weld width and verification simulation weld depth. When the simulated weld width and simulated weld depth meet the preset verification conditions, the radius of the planar heat source, the top radius of the conical heat source, the bottom radius of the conical heat source, and the depth of the cone are used as orthogonal experimental factors. Welding numerical simulation is performed according to the preset orthogonal parameter group to obtain the simulated weld width and simulated weld depth corresponding to each orthogonal parameter group. Based on the simulated melt width, simulated melt depth, target melt width, and target melt depth, the morphology deviation score of each orthogonal parameter group is calculated, and the range analysis of the morphology deviation score is performed to obtain the candidate parameter group; Substitute the candidate parameter set into the welding finite element geometric model to perform a confirmation simulation. When the simulated weld width and weld depth both meet the preset allowable deviation of morphology, output the candidate parameter set. If the simulation does not meet the allowable deviation of the morphology, adjust the level range of the corresponding experimental factor and re-execute the orthogonal experiment.
[0006] Furthermore, the planar Gaussian heat source is used to adjust the heat flow coverage range on the weld surface, and the conical Gaussian heat source is used to adjust the heat flow coverage range along the thickness direction.
[0007] Furthermore, the preset verification conditions include at least: verifying the comparison between the simulated weld width and the reference weld width at the same cross-sectional position, and verifying the comparison between the simulated weld depth and the reference weld depth at the same cross-sectional position; if the preset verification conditions are not met, the orthogonal test step is not entered.
[0008] Furthermore, the heat input distribution ratio of the planar Gaussian heat source and the conical Gaussian heat source satisfies: In the formula, This represents the percentage of heat input from a planar Gaussian heat source. This represents the percentage of heat input from the conical Gaussian heat source.
[0009] Furthermore, the candidate levels of the orthogonal experimental factors are determined based on the bevel width, riser wall thickness, target melt depth, and verified heat source coverage; each orthogonal parameter group performs numerical simulations under the same material parameters, boundary conditions, and heat input distribution ratio.
[0010] Furthermore, the method for calculating the morphological deviation score is as follows: In the formula, For the weighted comprehensive scoring function, and As the scoring weight, and The depth and width of the weld were measured in the experiment. and The target is the depth of penetration and the width of weld. The weights for the depth of penetration deviation and the width of weld deviation are determined based on the root penetration requirements, the groove filling requirements, or the weld formation requirements.
[0011] Furthermore, the allowable deviation in morphology is determined based on the design requirements, process evaluation requirements, or test plan of the welded joint; the confirmation simulation of the candidate parameter group does not participate in the original scoring sample of the range analysis.
[0012] This invention provides an orthogonal optimization method for combined heat source characteristic parameters of thick-walled circular pipes in deep-sea risers. It integrates a combined model of a planar Gaussian heat source and a conical Gaussian heat source, orthogonal experimental design, and the minimum objective function method to form a systematic parameter optimization process that achieves multi-parameter decoupling and global optimization with fewer simulation samples. Furthermore, it establishes a quantitative mapping relationship between heat source parameters and molten pool morphology for specific working conditions of the circumferential weld of thick-walled circular pipes. Compared with existing technologies, the method of this invention has the following advantages and technical effects: 1. Efficiently achieves global optimal parameter search, significantly reducing computational costs. Given the characteristics of the combined planar heat source and the conical Gaussian heat source, which involve four shape parameters and strong coupling among multiple parameters, existing single-factor rotation methods require adjusting each parameter individually. For a 27mm thick plate, a single simulation can take thousands of hours, resulting in an unacceptable total computational load. While existing intelligent optimization algorithms can achieve automatic optimization, they typically require hundreds or even thousands of simulation samples, leading to high computational costs and a tendency to get trapped in local optima. This invention uses an L9 orthogonal array, requiring only 9 simulations to systematically decouple the four-parameter coupling effect. Combining a weighted objective function and range analysis, it achieves global optimization with the fewest samples, avoiding the computational burden of numerous simulations and the risk of getting trapped in local optima. The computational cost is significantly reduced compared to existing methods.
[0013] 2. This invention fills the gap in the calibration of combined heat source parameters for specific working conditions of thick-walled circular pipe circumferential welds. Existing research on combined heat sources mostly focuses on flat or thin-walled pipe structures. A quantitative mapping relationship between planar-conical combined heat source parameters and molten pool morphology for the specific working condition of circumferential welds in thick-walled circular pipes (20-30mm) in deep-sea risers has not yet been established. This invention, specifically for the circumferential weld of a 27mm thick X80 pipeline steel deep-sea riser, establishes a four-parameter system calibration method for a planar Gaussian and conical Gaussian combined heat source and obtains the optimal parameter combination suitable for this working condition, filling the gap in combined heat source parameter calibration for this specific application scenario.
[0014] 3. High accuracy in predicting molten pool morphology. Numerical simulations using the optimal parameter combination obtained in this invention show that the prediction error for weld depth is controlled within ±5%, and the prediction error for weld width is controlled within ±8%, verifying the effectiveness and practicality of this method and providing reliable support for optimizing the welding process of deep-sea risers.
[0015] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0017] Figure 1 This is a model mesh partitioning diagram according to an embodiment of the present invention.
[0018] Figure 2 This is a schematic diagram of a planar Gaussian heat source according to an embodiment of the present invention.
[0019] Figure 3 This is a schematic diagram of a cone-shaped Gaussian heat source according to an embodiment of the present invention.
[0020] Figure 4 This is a comparison diagram of the simulated molten pool cross section and the experimental molten pool cross section in an embodiment of the present invention. Detailed Implementation
[0021] To make the objectives, technical solutions, and key points of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.
[0022] This implementation example Figures 1 to 4 As shown, taking the thick-walled circular pipe of the X80 pipeline steel deep-sea riser as the object, the specific implementation process and effect of the orthogonal optimization method of the combined heat source parameters of the thick-walled circular pipe are described in detail.
[0023] (1) Establish a finite element geometric model for welding.
[0024] Two hollow cylindrical risers were constructed as the workpieces to be welded, each segment being 500 mm long, 162 mm in radius, and 27 mm thick. V-grooves with a bevel angle of 52° were machined on the mating surfaces of both workpieces to facilitate weld filling and formation. A circular weld was generated using an approximate fan-shaped rotation method, with an appropriate root gap left at the bottom to ensure complete penetration at the weld root. After assembling all components, binding constraints were applied to the contact surfaces.
[0025] To improve computational accuracy, linear hexahedral elements (C3D8RT) were selected for mesh generation. Considering both computational accuracy and resource constraints, finer elements were used in the weld region; a gradient mesh was used in the base metal region, with denser elements near the weld and gradually increasing in size further away to form a transition mesh. To facilitate the application of a moving heat source at the weld center to obtain symmetrical loads, the weld surface was set to 8 elements (an even number). The final model has a total of 66,914 nodes and 48,280 elements. Figure 1 As shown.
[0026] The thermophysical properties of the base material, X80 pipeline steel (including thermal conductivity, specific heat capacity, density, elastic modulus, and yield strength), all change with temperature. The welding wire parameters are replaced with a material similar to JQ.TG55-Ni1. During welding, the material follows a thermo-elastic-plastic constitutive relationship, and the thermal softening effect of the material is considered.
[0027] (2) Construct a mobile heat source model.
[0028] A planar Gaussian heat source is suitable for simulating the heat flow distribution on the welding surface, used to control the weld pool width; a conical Gaussian heat source is used to simulate the heat flow distribution attenuating along the depth direction in three-dimensional space, used to control the weld pool depth. Superimposing the two forms a combined moving heat source model. This combination allows for independent control of weld width and depth, making it more suitable for thick-walled, deep-penetration welding conditions.
[0029] like Figure 2 As shown, construct a planar Gaussian heat source: In the formula, The heat flux density is a two-dimensional Gaussian distribution. Characterizing the total input power of the heat source, This represents the radius of the arc of the heat source.
[0030] like Figure 3 As shown, a conical Gaussian heat source is constructed: In the formula, The heat flux density is a conical Gaussian distribution. Characterizing the total input power of the heat source, Indicates the radius of the top of the heat source. Indicates the radius of the bottom of the heat source. Indicates the depth of the heat source. and These are the z-coordinate positions of the heat sources acting on the upper and lower surfaces, respectively.
[0031] The combined heat source allocation ratio satisfies: In the formula, This represents the percentage of heat input from a planar Gaussian heat source. This represents the percentage of heat input from the conical Gaussian heat source.
[0032] (3) Perform preliminary numerical simulation of the welding process and compare the molten pool morphology obtained from the simulation with the actual welding test results.
[0033] A preheating temperature of 120℃ was set in the predefined field to slow down the weld cooling rate and prevent cold cracking. Two temperature-displacement coupled analysis steps were set to capture the interaction between the temperature and displacement fields during welding. Fixed-end boundary conditions were applied at both ends of the model to simulate the actual constraint state. Surface heat exchange conditions and surface radiation conditions were applied to the model surface: ambient temperature 20℃, film heat dissipation coefficient 0.01 mW / (mm²). 2 ·K), emissivity 0.85, Stefan-Boltzmann constant 5.67×10 -11 mW / (mm 2 ·K 4 ).
[0034] Based on the above boundary conditions, a preliminary simulation was conducted using a set of trial parameters. The simulated molten pool profile was then compared with the weld test section under the same conditions. Figure 4 As shown; this step is used to verify whether the finite element model and heat source model can enter the subsequent orthogonal screening, and will not extrapolate this comparison to the performance conclusion under other working conditions.
[0035] (4) Design an orthogonal experimental scheme.
[0036] Under the verified heat input distribution ratio, the radius of the planar heat source, the top radius and bottom radius of the conical heat source, and the depth of the cone are used as factors, with three levels for each factor, forming a factor level table. Nine sets of parameter combinations are generated using an L9 orthogonal array; Tables 1 and 2 record the parameter levels and combinations of the original scheme.
[0037] Table 1 Factor Level Settings
[0038] Table 2. Heat source shape parameter settings
[0039] (5) Substitute the parameter combinations of each group of the orthogonal experimental design into the heat source model in sequence, perform numerical simulation of the welding process, and obtain the molten pool morphology data corresponding to each group of parameters.
[0040] Under the same boundary conditions after verification, the nine sets of heat source parameter combinations from the L9 orthogonal array were sequentially substituted into the combined moving heat source model to perform thermo-elastic-plastic numerical simulation. After each simulation, the melt depth and melt width were extracted at the same position as the reference section; Table 3 shows the simulation records of the original scheme.
[0041] Table 3. Orthogonal Experiment Data Recording Table
[0042] (6) Construct the minimum objective function, calculate the objective function value for each group of orthogonal experimental results, and perform range analysis to obtain the optimal heat source shape parameter combination that minimizes the objective function value.
[0043] The test indicators consider both weld width error and weld depth error. The target weld depth, target weld width, and corresponding weights are determined by the current joint's root penetration requirements, groove filling requirements, weld formation requirements, design requirements, or process qualification requirements; the scoring calculation follows the weighted comprehensive scoring formula in the original instruction manual immediately following this section.
[0044] In the formula, For the weighted comprehensive scoring function, and As the scoring weight, and The depth and width of the weld were measured in the experiment. and To determine the target melting depth and width.
[0045] The F-values were calculated for the results of the nine orthogonal experiments. The lower the score, the closer the simulation results are to the target.
[0046] Table 4 Objective Function Scoring
[0047] Range analysis was performed on each group of scores to obtain the influence ranking and candidate level of each factor under the current target morphology. The range analysis outputs candidate parameter groups, not the final parameter groups that can be directly used for production; Table 5 shows the range records of the original scheme.
[0048] Table 5. Range values of orthogonal experiments
[0049] The candidate parameter set obtained from the range analysis is resubmitted into the same finite element model for verification simulation, and the deviations of the verified simulated weld width and depth relative to the target weld width and depth are calculated. The candidate parameter set is output only if both deviations meet the current design requirements, process evaluation requirements, or the allowable deviations in morphology determined by the test plan; otherwise, the verification simulation results are added to the analysis record, the corresponding factor level ranges are adjusted, and the orthogonal test is reorganized.
[0050] This invention is based on the planar Gaussian heat source, conical Gaussian heat source, heat input distribution ratio, and weighted comprehensive scoring formula in the original specification. It sequentially connects the benchmark weld section verification, orthogonal screening, and candidate parameter group confirmation simulation. If the combined heat source has not completed verification, it will not enter the orthogonal screening; if the candidate parameter group fails the confirmation simulation, it will not be output as production parameters.
[0051] This method determines the combined heat source version for orthogonal experiments through benchmark section verification and organizes parameter groups within a preset level range using an orthogonal array. The effect of this technique is limited to ensuring a continuous process relationship between heat source verification, parameter selection, and simulation confirmation; it does not extrapolate the computation time or sample size in the original scheme to a general performance commitment.
[0052] The candidate parameter set output by this method is saved together with its reference weld section, material, wall thickness, groove, heat input distribution ratio, and welding boundary conditions. Under different material, wall thickness, groove, or welding boundary conditions, the parameters should be re-verified before performing orthogonal screening.
[0053] The values in Tables 3 to 5 are numerical simulation records of the original scheme under specific X80 thick-walled circular tube conditions, used to illustrate the organization of orthogonal experiments, scoring, and range analysis; this specification does not regard them as general accuracy or production yield conclusions that are not supported by confirmed experiments.
[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for optimizing combined heat source parameters in deep-sea riser welding, characterized in that, Includes the following steps: Obtain the geometric dimensions, material thermophysical parameters, bevel shape, welding path, and welding process boundary conditions of the deep-sea riser to be welded, and establish a welding finite element geometric model; In the welding finite element geometric model, a combined moving heat source is constructed using a planar Gaussian heat source and a conical Gaussian body heat source. A reference weld test section with the same material, wall thickness, bevel shape and welding process boundary conditions as the deep-sea riser to be welded is obtained to obtain the reference weld width and reference weld depth. The initial parameters of the combined moving heat source are then substituted into the welding finite element geometric model to obtain the verification simulation weld width and verification simulation weld depth. When the simulated weld width and simulated weld depth meet the preset verification conditions, the radius of the planar heat source, the top radius of the conical heat source, the bottom radius of the conical heat source, and the depth of the cone are used as orthogonal experimental factors. Welding numerical simulation is performed according to the preset orthogonal parameter group to obtain the simulated weld width and simulated weld depth corresponding to each orthogonal parameter group. Based on the simulated melt width, simulated melt depth, target melt width, and target melt depth, the morphology deviation score of each orthogonal parameter group is calculated, and the range analysis of the morphology deviation score is performed to obtain the candidate parameter group; Substitute the candidate parameter set into the welding finite element geometric model to perform a confirmation simulation. When the simulated weld width and weld depth both meet the preset allowable deviation of morphology, output the candidate parameter set. If the simulation does not meet the allowable deviation of the morphology, adjust the level range of the corresponding experimental factor and re-execute the orthogonal experiment.
2. The method according to claim 1, characterized in that, The planar Gaussian heat source is used to adjust the heat flow coverage range on the weld surface, and the conical Gaussian heat source is used to adjust the heat flow coverage range along the thickness direction.
3. The method according to claim 1, characterized in that, The preset verification conditions include at least: verifying the comparison between the simulated weld width and the reference weld width at the same cross-sectional position, and verifying the comparison between the simulated weld depth and the reference weld depth at the same cross-sectional position; if the preset verification conditions are not met, the orthogonal test step is not entered.
4. The method according to claim 1, characterized in that, The heat input distribution ratio of the planar Gaussian heat source and the conical Gaussian heat source satisfies: In the formula, This represents the percentage of heat input from a planar Gaussian heat source. This represents the percentage of heat input from the conical Gaussian heat source.
5. The method according to claim 1, characterized in that, The candidate levels of the orthogonal experimental factors are determined based on the bevel width, riser wall thickness, target melt depth, and verified heat source coverage. Each orthogonal parameter group performs numerical simulations under the same material parameters, boundary conditions, and heat input distribution ratio.
6. The method according to claim 1, characterized in that, The method for calculating the morphological deviation score is as follows: In the formula, For the weighted comprehensive scoring function, and As the scoring weight, and The depth and width of the weld were measured in the experiment. and The target is the depth of penetration and the width of weld. The weights for the depth of penetration deviation and the width of weld deviation are determined based on the root penetration requirements, the groove filling requirements, or the weld formation requirements.
7. The method according to claim 1, characterized in that, The allowable deviation in morphology is determined based on the design requirements, process evaluation requirements, or test plan of the welded joint; the confirmation simulation of the candidate parameter group does not participate in the original scoring sample of the range analysis.