Ship stern bearing interference press-fitting quality prediction method considering complex meteorological conditions

Abstract

The invention discloses a ship stern bearing interference press-fitting quality prediction method considering complex meteorological conditions. The method comprises the following steps: constructing a full-size multi-physical field simulation model; establishing a fluid calculation environment considering solar radiation; loading temperature field data for structural calculation; simulating a nonlinear contact interference press-fitting process; the press fitting curve, the press fitting contact area, the energy consumption in the press fitting process and the cylindricity error of the stern bearing after press fitting are used as evaluation indexes, and the press fitting failure risk is subjected to multi-dimensional quantitative evaluation. According to the method, the variable characteristics of the real environment temperature and the wind speed serve as the time-varying boundary conditions to be dynamically applied to the model, and quantitative evaluation of the dynamic change of the wind speed on the press-fitting quality is achieved; a solar radiation model and a DO radiation model are set in fluid calculation to realize accurate loading of non-uniform radiation heat flow, so that temperature field distribution of the stern shaft tube is accurately predicted; by constructing a multi-dimensional quantitative evaluation system, various failure risks in the press-fitting process are comprehensively identified.

Description

Technical Field

[0001] This invention relates to the field of shipbuilding technology, and in particular to a method for predicting the failure risk of stern bearing press-fitting under open-air conditions, taking into account the coupling of multiple physical fields such as ambient temperature, wind speed and solar radiation. Background Technology

[0002] Press-fitting stern bearings is a core and critical process in shafting installation, and the quality of the interference fit directly determines the long-term operational stability of the shafting system. Currently, press-fitting of stern bearings on large ships is typically carried out on open slipways or in dry docks. Existing press-fitting process guidelines and risk assessment methods have the following limitations: 1. The model is severely simplified and deviates from actual working conditions: Existing methods are mostly based on the assumption of constant convection heat transfer coefficient or steady-state temperature field, completely ignoring the structural non-uniformity and transient thermal deformation caused by solar radiation, transient wind speed and diurnal temperature difference in open environment.

[0003] 2. Lack of key physical field coupling mechanism: The precise coupling model between "meteorological environment (radiation, convection) - structural thermal response - press-fit mechanical behavior" was not established. In particular, the shading effect of complex structures such as the fairing on the stern tube was ignored (resulting in a significant temperature difference between the illuminated and shaded areas), which led to serious distortion in the prediction of "out-of-roundness" deformation of the key reference surface of the stern tube before press-fitting.

[0004] 3. Single evaluation dimension and incomplete risk identification: Traditional assessment mainly relies on the macroscopic pressing force curve, lacking a comprehensive quantitative evaluation of the effective contact area of ​​the mating surface after pressing, the energy consumption of the pressing process, and the final cylindricity error of the stern bearing. It is difficult to identify hidden risks such as local jamming, fretting wear, or excessive form and position tolerances after assembly.

[0005] Therefore, these limitations prevent existing technologies from accurately predicting the pressing quality under complex meteorological conditions, leading to reliance on experience in process window selection and a high risk of pressing failure or quality issues. Thus, there is a need in this field for a pressing quality prediction method that can accurately simulate the coupling effects of real meteorological environments and perform multi-dimensional quantitative risk assessment. Summary of the Invention

[0006] The main objective of this invention is to provide a method for predicting the quality of interference fit for ship stern bearings under complex meteorological conditions. This method introduces a multi-physics coupling model for stern bearing interference fit that considers ambient temperature, solar radiation, and wind speed, enabling it to accurately capture the actual deformation of exposed structures and solving the problem that traditional models cannot predict nozzle ellipticization. A four-dimensional evaluation system is established, including pressing force, contact area, energy consumption, and stern bearing cylindricity error, which can identify hidden risks that cannot be detected by relying solely on pressing force.

[0007] The technical solution adopted in this invention is: A method for predicting the quality of interference fit in ship stern bearings considering complex weather conditions includes the following steps: S1. Construct a full-size multiphysics simulation model: Establish a full-size three-dimensional geometric model including the stern bearing, stern tube, and fairing assembly, and perform mesh generation; S2. Establish a fluid computational environment that considers solar radiation, including: S2.1 Construct an air computational domain that fully surrounds the press-fit structure and introduce a turbulence model to simulate the flow separation and complex turbulent heat transfer effects around the fairing; S2.2 Calculate solar radiation and shading; S2.3, Load dynamic meteorological boundaries; S3. Load temperature field data for structural calculations, including: S3.1. Based on the computing environment built by S2, unsteady flow and heat transfer calculations are carried out. The transient and non-uniform temperature field of the structure surface in the fluid domain obtained therefrom is mapped to the nodes of the solid structure mesh in real time through the fluid-structure interaction interface as a thermal load. S3.2 Apply a fixed constraint to the rear end of the stern tube and solve for the transient thermal strain of the structure under non-uniform heating. S4. Simulate the nonlinear contact interference fitting process, including: S4.1 Define the frictional contact pair between the outer surface of the stern bearing and the inner surface of the stern tube; S4.2 Apply axial displacement load to simulate the pressing process, plot the pressing curve by calculating the support reaction force in the displacement direction, and obtain the contact area and pressing energy consumption by solving the contact state. S5. Using the press-fit curve, press-fit contact area, press-fit process energy consumption, and stern bearing cylindricity error after press-fit as evaluation indicators, a multi-dimensional quantitative assessment of press-fit failure risk is conducted.

[0008] In the above scheme, in S1, a hybrid meshing strategy is adopted. To capture the details of airflow and heat transfer, a structured mesh is used in the airflow domain surrounding the structure, and a boundary layer mesh is generated at the fluid-structure interaction interface. In the solid structure domain, the local mesh is refined in the interference contact area between the stern bearing and the stern tube to ensure the accuracy of the calculation of contact stress and deformation.

[0009] In the above scheme, S2.1, considering the significant unsteady characteristics of airflow in open-air environments, the Reynolds-averaged Navier-Stokes equations are used as the governing equations to describe the macroscopic airflow behavior. To address the strong adverse pressure gradient, large streamline curvature, and flow separation phenomena around the stern tube and fairing surfaces, Realizable is introduced. The turbulence model is solved in a closed loop.

[0010] In the above scheme, in S2.2, the method for calculating solar radiation and shading is as follows: using the solar calculator algorithm, the solar altitude angle and azimuth angle are automatically calculated based on the latitude and longitude of the work location and the planned work date and time to determine the solar incident vector; a discrete coordinate radiation model is adopted, and through its ray detection function, the shadow determination factor is automatically calculated to accurately distinguish the illuminated area and shadow area formed by the fairing on the stern tube surface, thereby achieving accurate loading of non-uniform radiative heat flow.

[0011] In the above scheme, in S2.3, the method for loading dynamic meteorological boundaries is as follows: the curves of the measured or forecasted ambient temperature over time and the wind speed-time curve of the work day are compiled by a user-defined function and dynamically applied to the model as time-varying boundary conditions.

[0012] In the above scheme, S4.1 uses the augmented Lagrange algorithm to handle the normal constraints of the contact interface in order to improve convergence.

[0013] In the above scheme, in S5, the evaluation method of the pressing curve is as follows: draw the simulated pressing force-displacement curve. If the curve exceeds the upper limit or shows an abnormally steep slope, it is determined that there is a risk of "over-pressing" or "jamming".

[0014] In the above scheme, the evaluation method for the press-fit contact area in S5 is as follows: based on the finite element post-processing results, extract the node contact state of the contact pair surface, and calculate the sum of the effective coverage areas of all nodes in the contact state; if the area shows abnormal fluctuations or is too small locally, it indicates poor alignment or local gaps.

[0015] In the above scheme, in S5, the energy consumption assessment method for the pressing process is as follows: integrate the pressing force-displacement curve to calculate the mechanical energy consumed in the entire pressing process. If the energy consumption is too high, it indicates that the micro-protrusions on the contact surface have undergone excessive plastic shearing, which poses a potential risk of wear.

[0016] In the above scheme, in S5, the evaluation method for the cylindricity error of the stern bearing after press-fitting is as follows: extract the node coordinates of the inner surface of the stern bearing after press-fitting, calculate its cylindricity error based on the least squares circle method, and if the error exceeds the design allowable threshold, it is determined that the form and position tolerances after assembly do not meet the requirements and are high-risk items.

[0017] The beneficial effects of this invention are: 1. This invention dynamically applies the variable characteristics of real ambient temperature and wind speed as time-varying boundary conditions to the model, enabling a quantitative assessment of the impact of dynamic wind speed changes on press-fit quality. This solves the problem of existing models neglecting the variable characteristics of real ambient temperature and wind speed and their impact on structural temperature field heat transfer. 2. This invention achieves precise loading of non-uniform radiative heat flow by setting up solar radiation and DO radiation models in fluid calculations. This allows for accurate calculation of non-uniform heat flow input caused by structures such as the shroud, thereby accurately predicting the stern tube temperature field distribution and solving the problem of traditional thermal analysis lacking a solar radiation model. 3. This invention constructs a multi-dimensional quantitative evaluation system integrating press-fit curves, press-fit contact area, press-fit process energy consumption, and post-press-fit stern bearing cylindricity error to comprehensively identify various failure risks during the press-fit process, solving the problem of existing evaluation systems having only one dimension.

[0018] 2. Experimental verification shows that the fluid-thermal-structure coupled model constructed in this invention provides reliable simulation results for temperature field, deformation, and press-fit curves. Therefore, using the method of this invention, shipyards can conduct simulations based on weather forecast data before press-fitting operations, scientifically select the optimal operation date, and thus avoid the risk of irreversible press-fitting failure. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the method for predicting the quality of interference fit of ship stern bearings under complex meteorological conditions, as described in this invention. Figure 2 This is a schematic diagram of the air fluid domain boundary conditions in an embodiment of the present invention; Figure 3 This is a schematic diagram of the arrangement of surface temperature sensors on the actual ship structure during temperature field verification in an embodiment of the present invention; Figure 4 These are the definitions of each section of the actual ship structure during deformation verification in this embodiment of the invention; Figure 5 This is a comparison chart of the press-fit curve verification experiment and simulation in the embodiments of the present invention; Figure 6 These are the temperature and wind speed curves for four examples in the embodiments of this invention; Figure 7 This is a schematic diagram of the pressure loading curve evaluation in an embodiment of the present invention; Figure 8This is a schematic diagram of the contact area state response during the interference fit stroke in an embodiment of the present invention; Figure 9 This is a schematic diagram of the energy consumption curve of the pressing process in an embodiment of the present invention; Figure 10 This is a schematic diagram of the cylindricity error of the stern bearing after assembly in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0022] It should be noted that the illustrations provided in the embodiments of the present invention are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0023] In this invention, it should also be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first" and "second" are used only for descriptive and distinguishing purposes and should not be construed as indicating or implying relative importance.

[0024] Furthermore, it should be noted that the features of the various embodiments of the present invention can be combined or integrated in whole or in part, and as those skilled in the art will understand, they can interact and operate in different ways. Each embodiment can be implemented independently of each other or in association with one another.

[0025] like Figure 1 As shown, a method for predicting the interference fit quality of ship stern bearings considering complex weather conditions includes the following steps: S1. Construct a full-size multiphysics simulation model.

[0026] S1.1 Geometric Modeling: Based on the target ship's design drawings, establish a full-size 3D geometric model including the stern bearing, stern tube, and fairing assembly. Simplify and repair microscopic features such as the lubrication grooves on the stern bearing surface to improve computational efficiency while preserving key geometric characteristics.

[0027] S1.2 Mesh Generation: A hybrid meshing strategy was adopted. To capture the details of airflow and heat transfer, a structured mesh was used in the airflow domain surrounding the structure, and a boundary layer mesh was generated at the fluid-structure interaction interface. In the solid structural domain, the interference contact area between the stern bearing and the stern tube was locally meshed to ensure the accuracy of the calculated contact stress and deformation.

[0028] S2. Establish a fluid computing environment that takes into account solar radiation.

[0029] S2.1 Fluid Domain and Turbulence Model Setup: Construct an air computational domain that fully encloses the press-fit structure. The Reynolds-averaged Navier-Stokes (RANS) equations are used to describe the airflow, and Realizable is introduced. A turbulence model is used to accurately simulate the flow separation and complex turbulent heat transfer effects around the fairing.

[0030] S2.2 Solar Radiation and Shading Calculation: Utilizing a solar calculator algorithm, the solar altitude and azimuth angles are automatically calculated based on the latitude and longitude of the work location and the planned work date and time to determine the solar incident vector. A discrete coordinate (DO) radiation model is employed, and its ray detection function automatically calculates the shadow determination factor to accurately distinguish between the illuminated and shadowed areas formed by the fairing on the stern tube surface, achieving precise loading of non-uniform radiative heat flow. Specifically, these conditions are loaded by activating the "DO radiation model" and "solar ray tracing" functions in the simulation software and inputting geographical location and time parameters. Based on these parameters and the three-dimensional geometric model, the software automatically calculates the shadow distribution on the structural surface at each moment using a ray tracing algorithm, directly mapping the radiative heat flow as wall boundary conditions, eliminating the need for manual division of illuminated or shadowed areas.

[0031] S2.3 Dynamic meteorological boundary loading: The curves of ambient temperature change over time and wind speed-time curves measured or predicted for the workday are compiled using user-defined functions (UDFs) and dynamically applied to the model as time-varying boundary conditions.

[0032] S3. Load temperature field data for structural calculation.

[0033] S3.1 Fluid Domain Calculation: Based on the computing environment built by S2, unsteady flow and heat transfer calculations are carried out. The transient and non-uniform temperature field of the structural surface in the fluid domain is extracted and mapped to the nodes of the solid structure mesh in real time through the fluid-structure interaction interface as a thermal load. S3.2 Thermal Deformation Calculation: Apply a fixed constraint to the rear end of the stern tube and solve for the transient thermal strain of the structure under non-uniform heating.

[0034] S4. Simulate the nonlinear contact interference fit process.

[0035] S4.1 Contact Definition: Define the frictional contact pair between the outer surface of the stern bearing and the inner surface of the stern tube. An augmented Lagrangian algorithm is used to handle the normal constraints of the contact interface to improve convergence. The friction coefficient is set according to the material and lubrication conditions.

[0036] S4.2 Pressing Simulation: Apply axial displacement load to simulate the pressing process, calculate the pressing curve by solving the support reaction force in the displacement direction, and obtain the contact area and pressing energy consumption by solving the contact state.

[0037] S5. Multi-dimensional quantitative assessment of press-fitting failure risk.

[0038] Based on the simulation results from step S4, the following four evaluation metrics are calculated in parallel to conduct a comprehensive risk assessment: (1) Pressing curve: Plot the simulated pressing force-displacement curve. If the curve exceeds the upper limit or shows an abnormally steep slope, it is determined that there is a risk of "over-pressing" or "jamming".

[0039] (2) Press-fit contact area: Based on the finite element post-processing results, extract the node contact state of the contact pair surface and calculate the sum of the effective coverage areas of all nodes in the contact state; if the area shows abnormal fluctuations or is too small locally, it indicates poor alignment or local gaps.

[0040] (3) Energy consumption during press fitting: Integrate the press fitting force-displacement curve to calculate the mechanical energy consumed during the entire press fitting process. If the energy consumption is too high, it indicates that the micro-protrusions on the contact surface are subjected to excessive plastic shearing, which poses a potential risk of wear.

[0041] (4) Cylindricity error of stern bearing after press fitting: Extract the node coordinates of the inner surface of the stern bearing after press fitting, and calculate its cylindricity error based on the least squares circle method. If the error exceeds the design allowable threshold, it is determined that the form and position tolerance after assembly does not meet the requirements and is a high-risk item.

[0042] The following example, using a ship under construction at a shipyard, will be used to further illustrate the method of this invention in detail.

[0043] S1. Construct a full-size multiphysics simulation model.

[0044] Based on the design drawings of a certain ship, a full-size geometric model and material parameters were created in the finite element preprocessing software, as shown in Table 1.

[0045] Table 1: Material Performance Parameters

[0046] Hybrid mesh generation is performed: the fluid domain is meshed using a structured mesh, and the local boundary layer mesh is refined; in the press-fitting calculation, the solid domain structured mesh is meshed into tetrahedral meshes, and mesh independence is verified.

[0047] S2. Establish a fluid computing environment that takes into account solar radiation.

[0048] An air computational domain fully enclosing the press-fit structure is constructed. Considering the significant unsteady characteristics of airflow in open-air environments, the Reynolds-averaged Navier-Stokes (RANS) equations are used as the governing equations to describe the macroscopic airflow behavior, ensuring both computational accuracy and solution efficiency. To address the strong adverse pressure gradient, large streamline curvature, and flow separation phenomena around the stern tube and fairing surfaces, a Realizable... The turbulence model is solved in a closed loop. Compared to the standard... The model improves the turbulent viscosity formula and dissipation rate. The transport equations can more accurately capture the details of vortex shedding and complex turbulent heat transfer effects on the leeward side of the fairing, thereby ensuring the accuracy of the calculation of the convective heat transfer coefficient of the structural surface.

[0049] In the fluid calculation, set up the DO radiation model and the solar radiation model, input the local latitude and longitude, and the software will automatically calculate the solar incidence angle.

[0050] The measured temperature and wind speed variation curves for a typical day in this region were loaded using a UDF. The flow field diagram and boundary condition settings are shown in [link to UDF]. Figure 2 It should be noted that, Figure 2 In the figure, l, d, and h represent the length, width, and height of the stern bearing press-fit structure, respectively. A suitable fluid computation domain is established based on these geometric dimensions.

[0051] S3. Load temperature field data for structural calculation.

[0052] S3.1 Fluid Domain Calculation: A computational model is constructed in the fluid simulation software. The governing equations are activated, and a turbulence model combined with wall functions is used for solving. Simultaneously, the DO radiation model and solar ray tracing function are enabled, and the latitude and longitude of the work site are input to automatically update the solar vector. A UDF is written to compile the time-varying ambient temperature and wind speed curves measured during the work day into dynamic boundary conditions. Then, data transfer is performed in ANSYS Workbench, mapping the structural temperature field calculated from the fluid to the solid structure mesh nodes as thermal loads.

[0053] S3.2 Thermal Deformation Calculation: A fixed constraint is applied to the rear end of the stern tube to solve for the transient thermal strain of the structure under non-uniform heating. The coordinates of the mesh nodes with the actual thermal deformation are derived to generate the deformed geometric model as the geometric model for subsequent press-fitting simulation.

[0054] To verify the accuracy of the above coupling model, temperature sensors were placed at the same locations on the actual ship, and the diameter of the key cross-section was measured.

[0055] (1) Temperature field verification: The temperature change trend of each measuring point on the structure surface obtained by simulation is highly consistent with the measured data, with a maximum relative error of 5.85%, which proves the accuracy of the model in capturing non-uniform temperature rise. The temperature sensor measuring points are arranged as follows: Figure 3 As shown.

[0056] (2) Deformation verification: Before press fitting, the simulated and measured values ​​of diameter deformation of the stern tube and stern bearing at different sections were in good agreement, and the deviation was within the allowable range for engineering. The section selection was as follows: Figure 4 As shown, the diameters in the vertical and horizontal directions are measured for the selected cross-section. It should be noted that... Figure 4 The left image shows a schematic diagram of the selection of the cross-section of the outer surface of the stern bearing, and the right image shows a schematic diagram of the selection of the cross-section of the inner surface of the stern tube.

[0057] (3) Pressing Curve Verification: The simulated pressing force-displacement curve and the measured curve on site showed consistency in both trend and magnitude, verifying the reliability of the overall mechanical model. The pressing curve and pressing force error were as follows: Figure 5 As shown.

[0058] S4. Simulate the nonlinear contact interference fit process.

[0059] Input the pressing weather conditions and execute the pressing prediction process. Using a validated model, input the ambient temperature curve, wind speed, and latitude and longitude of the planned operation day. Apply displacement only in the stern bearing axial direction to simulate the pressing action. Calculate the pressing force by the support reaction force in the pressing direction using the solver, and extract the total area of ​​the closed contact nodes in real time based on the state variables of the contact elements. This yields the effective contact area and pressing energy consumption data that vary with the stroke, providing multi-dimensional quantitative prediction data for pressing quality.

[0060] This embodiment conducts predictive analysis on four typical weather combinations for the shipyard in winter and summer. The experimental design table for extreme conditions is shown in Table 2, and the ambient temperature and wind speed curves for the four conditions are shown below. Figure 6 As shown.

[0061] Table 2: Extreme Condition Experiment Design Table

[0062] S5. Multi-dimensional quantitative assessment of press-fitting failure risk.

[0063] (1) Evaluation of the pressing curve. Figure 7 Comparing the press-fit curves of the four operating conditions with the ideal condition, it can be seen that the curves of operating conditions 3 and 4 completely exceed the upper limit of allowable pressure, indicating that there is an extremely high risk of interference failure under high-temperature conditions in summer, with operating condition 3 exhibiting the strongest interference characteristics. The press-fit curve of operating condition 2 is closest to the ideal reference curve under no temperature difference conditions.

[0064] (2) Evaluation of press-fit contact area.

[0065] like Figure 8 As shown, the contact area in condition 3 is the largest, even exceeding the theoretical value under ideal conditions. This indicates that significant material penetration may have occurred under this condition, which could easily lead to severe frictional damage between the stern bearing and the inner wall of the stern tube. In contrast, conditions 1 and 2 show a decreasing trend in contact area at the end of the press-fitting process. This may be because deformation and bending occur under these two conditions, causing the surfaces around the deflection deformation protrusion area to not fully adhere.

[0066] (3) Energy consumption assessment of the pressing process.

[0067] Further integration Figure 9 The energy consumption curves shown in the press-fitting process reveal that the larger the contact area or the steeper the slope of the press-fitting curve, the higher the energy consumption required. This indicates a significant increase in the risk of severe plastic shear and adhesive wear on the micro-protrusions at the contact interface. However, the energy consumption curve for condition 2 largely coincides with the reference curve. This may be because the reduced contact area at the end of the press-fitting process in condition 2, combined with the deformation differences between the structures before press-fitting, interferes with each other, partially offsetting the additional energy consumption caused by geometric errors, thus making the overall energy consumption performance close to the ideal state. It should be noted that the criterion for high or low energy consumption is based on... Figure 9 The comparison working condition curve is used to determine this.

[0068] (4) Evaluation of the cylindricity error of the stern bearing after press fitting.

[0069] Figure 10 The results demonstrate the cylindricity error of the stern bearing after press-fitting under four different operating conditions. Condition 3 exhibits the largest cylindricity error, while Condition 4 achieves a final cylindricity error of only 0.022 mm, significantly better than Condition 3's 1.412 mm. Appropriate weather conditions can improve assembly accuracy by nearly two orders of magnitude. Comparing Conditions 1, 2, and 4 reveals that a smaller press-fitting curve deviation does not necessarily equate to superior press-fitting quality. Although Condition 4 shows a significantly larger press-fitting curve deviation, it also exhibits the smallest final cylindricity error. This phenomenon indicates that the final cylindricity error is not solely determined by the press-fitting process but is primarily controlled by the asymmetric compression effect on the bearing caused by the "out-of-roundness" deformation of the stern tube under a non-uniform temperature field.

[0070] Using the method of this invention, shipyards can conduct simulations based on weather forecast data before press-fitting operations, scientifically select the best operation date, and thus avoid the risk of irreversible press-fitting failure.

[0071] This invention introduces for the first time a multi-physics coupling model for stern bearing press fitting, considering ambient temperature, solar radiation, and wind speed. This model can accurately capture the actual deformation of open-air structures and solves the problem that traditional models cannot predict pipe ellipticization. A four-dimensional evaluation system is established, including press fitting force, contact area, energy consumption, and stern bearing cylindricity error. This system can identify hidden risks that cannot be detected by press fitting force alone (such as cases where the press fitting force is qualified but the cylindricity exceeds the standard).

[0072] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0073] The order of the steps in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0074] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for predicting the quality of interference fit in ship stern bearings considering complex weather conditions, characterized in that, Includes the following steps: S1. Construct a full-size multiphysics simulation model: Establish a full-size three-dimensional geometric model including the stern bearing, stern tube, and fairing assembly, and perform mesh generation; S2. Establish a fluid computational environment that considers solar radiation, including: S2.1 Construct an air computational domain that fully surrounds the press-fit structure and introduce a turbulence model to simulate the flow separation and complex turbulent heat transfer effects around the fairing; S2.2 Calculate solar radiation and shading; S2.3, Load dynamic meteorological boundaries; S3. Load temperature field data for structural calculations, including: S3.

1. Based on the computing environment built by S2, unsteady flow and heat transfer calculations are carried out. The transient and non-uniform temperature field of the structure surface in the fluid domain obtained therefrom is mapped to the nodes of the solid structure mesh in real time through the fluid-structure interaction interface as a thermal load. S3.2 Apply a fixed constraint to the rear end of the stern tube and solve for the transient thermal strain of the structure under non-uniform heating. S4. Simulate the nonlinear contact interference fitting process, including: S4.1 Define the frictional contact pair between the outer surface of the stern bearing and the inner surface of the stern tube; S4.2 Apply axial displacement load to simulate the pressing process, plot the pressing curve by calculating the support reaction force in the displacement direction, and obtain the contact area and pressing energy consumption by solving the contact state. S5. Using the press-fit curve, press-fit contact area, press-fit process energy consumption, and press-fit stern bearing cylindricity error as evaluation indicators, a multi-dimensional quantitative assessment of press-fit failure risk is conducted.

2. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S1, a hybrid meshing strategy is adopted. To capture the details of airflow and heat transfer, a structured mesh is used in the airflow domain surrounding the structure, and a boundary layer mesh is generated at the fluid-structure interaction interface. In the solid structure domain, the interference contact area between the stern bearing and the stern tube is locally meshed to ensure the accuracy of the calculation of contact stress and deformation.

3. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S2.1, considering the significant unsteady characteristics of airflow in open-air environments, the Reynolds-averaged Navier-Stokes equations are used as the governing equations to describe the macroscopic airflow behavior. To address the strong adverse pressure gradient, large streamline curvature, and flow separation phenomena around the stern tube and fairing surfaces, Realizable is introduced. The turbulence model is solved in a closed loop.

4. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S2.2, the method for calculating solar radiation and shading is as follows: using the solar calculator algorithm, the solar altitude angle and azimuth angle are automatically calculated based on the latitude and longitude of the work location and the planned work date and time to determine the solar incident vector; a discrete coordinate radiation model is adopted, and through its ray detection function, the shadow determination factor is automatically calculated to accurately distinguish the illuminated area and shadow area formed by the fairing on the stern tube surface, thereby achieving accurate loading of non-uniform radiative heat flow.

5. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S2.3, the method for loading dynamic meteorological boundaries is as follows: the curves of ambient temperature change over time as measured or predicted on the workday and the wind speed-time curve are compiled by a user-defined function and dynamically applied to the model as time-varying boundary conditions.

6. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S4.1, the augmented Lagrange algorithm is used to handle the normal constraints of the contact interface in order to improve convergence.

7. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S5, the evaluation method for the pressing curve is as follows: plot the simulated pressing force-displacement curve. If the curve exceeds the upper limit or shows an abnormally steep slope, it is determined that there is a risk of "over-pressing" or "jamming".

8. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S5, the evaluation method for press-fit contact area is as follows: based on the finite element post-processing results, extract the node contact state of the contact pair surface, and calculate the sum of the effective coverage areas of all nodes in the contact state; if the area shows abnormal fluctuations or is too small locally, it indicates poor alignment or local gaps.

9. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S5, the energy consumption assessment method for the pressing process is as follows: integrate the pressing force-displacement curve to calculate the mechanical energy consumed in the entire pressing process. If the energy consumption is too high, it indicates that the micro-protrusions on the contact surface are subjected to excessive plastic shearing, which poses a potential risk of wear.

10. The method for predicting the quality of interference fit in ship stern bearings considering complex meteorological conditions according to claim 1, characterized in that, In S5, the evaluation method for the cylindricity error of the stern bearing after press-fitting is as follows: extract the node coordinates of the inner surface of the stern bearing after press-fitting, calculate its cylindricity error based on the least squares circle method. If the error exceeds the design allowable threshold, it is determined that the form and position tolerances after assembly do not meet the requirements and are considered a high-risk item.

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