A method and system for predicting leakage of a metal seal structure

Abstract

The application discloses a metal sealing structure leakage prediction method and system, first, a macroscopic service finite element model is constructed according to the structure and service parameters of the sealing structure, the service deformation behavior is simulated, the model is based on the rotation symmetry characteristic of the sealing structure, the axisymmetric shell model is adopted in the finite element software, the cross section is simplified, the grid is divided and the flange movement is set. Then, a microscopic crystal plastic model with a rough surface is constructed based on the surface roughness, the model construction and grid processing are carried out by considering the material microstructure and characteristics. The deformation amount of the contact position is extracted from the macroscopic model as the boundary condition of the microscopic model to simulate the microscopic deformation. Finally, the distance between the rough surface mean line and the flange surface distance is determined from the microscopic model as the gap height, and the internal and external pressure difference in the service of the sealing structure is combined to calculate the leakage amount of the sealing structure. In this way, the simulation result is more close to the actual situation by combining the macroscopic and microscopic models, and the leakage prediction precision and efficiency of the sealing structure are improved.

Description

Technical Field

[0001] This application relates to the field of mechanical seal technology, and in particular to a leakage prediction method and system for metal sealing structures. Background Technology

[0002] In modern industry, metal sealing structures, as key components ensuring system sealing, are widely used in various fields such as machinery, aviation, aerospace, and energy. For example, common metal sealing structures such as metal sealing rings and wave springs play an important sealing role in different equipment.

[0003] The sealing performance of metal seals directly affects the operating efficiency, energy consumption, safety, and service life of the corresponding equipment. Whether it's equipment operating under extreme conditions such as high temperature, high pressure, and strong corrosion, or precision instruments with extremely high sealing requirements, metal seals play an indispensable role. Therefore, accurate prediction and prevention of leaks in metal seals are of paramount importance.

[0004] Traditional leak prediction methods primarily rely on empirical formulas or experimental tests. While these methods can reflect the leakage situation of metal sealing structures to some extent, they often suffer from low accuracy and limited applicability. This is particularly true when dealing with leaks under complex operating conditions, where traditional methods exhibit poor prediction accuracy. Furthermore, although finite element simulation methods exist, the study of sealing structures under service conditions remains limited to the macroscopic or microscopic level, and microscopic models typically do not consider the influence of material microstructure and crystal orientation. In addition, experimental testing methods are time-consuming and resource-intensive, hindering rapid response and cost control. Summary of the Invention

[0005] This application provides a leakage prediction method and system for metal sealing structures, which solves the problems of poor accuracy and low efficiency in leakage prediction of metal sealing structures in the prior art.

[0006] To achieve the above objectives, the technical solution of this invention is as follows:

[0007] In a first aspect, embodiments of the present invention provide a leakage prediction method for a metal sealing structure, comprising: constructing a macroscopic service finite element model based on the structural parameters and service parameters of the sealing structure to simulate the deformation behavior of the sealing structure during service; establishing a microcrystalline plastic model with a rough surface based on the surface roughness of the sealing structure; extracting the deformation amount at the contact position between the sealing structure and the flanges on both sides from the finite element model as boundary conditions, and applying the boundary conditions to the microcrystalline plastic model to simulate the microscopic deformation behavior of the sealing structure at the contact position; determining the distance value between the mean line of the lower rough surface of the sealing structure and the flange surface from the microcrystalline plastic model, and substituting the distance value as the gap height into a preset leakage calculation formula, and calculating the leakage amount of the sealing structure by combining the pressure difference on both sides of the sealing structure and the total contact area between the sealing structure and the flange.

[0008] In some possible implementations, a macroscopic service finite element model is constructed based on the structural and service parameters of the sealing structure to simulate the deformation behavior of the sealing structure during service. This includes: in finite element software, using an axisymmetric shell model to simulate the structure of the sealing structure and flange based on the structural parameters, and using its cross-section to simplify the calculation; where the structural parameters include, but are not limited to, the wall thickness, outer diameter, inner diameter, crest radius, trough radius, transition arc radius, contact arc radius, wave height, and ring height of the sealing structure; meshing the finite element model, and refining the mesh in the contact area between the sealing structure and the flange to accurately capture the deformation behavior in the contact area; and controlling the displacement of the flange based on the service parameters to simulate the deformation behavior of the sealing structure during service; where the service parameters include service parameters for the pre-tightening stage and service parameters for the fatigue stage.

[0009] In some possible implementations, a microcrystalline plastic model with a rough surface is established based on the surface roughness of the sealing structure. This includes: obtaining the surface roughness of the sealing structure through roughness measurement, and establishing the contact conditions between the flange and the sealing structure based on the surface roughness; wherein the contact conditions include: setting the flange as rigid and the surface as ideally smooth, setting the sealing structure as plastic and the initial surface roughness being consistent with the measured value; performing EBSD characterization on the contact position between the sealing structure and the flanges on both sides, and selecting a region of a preset size from the obtained EBSD map to construct a microcrystalline plastic model with a preset thickness.

[0010] In some possible implementations, in the microcrystalline plasticity model, the surface area of ​​the contact position is meshed by a preset number of elements to avoid errors caused by mesh distortion during simulation.

[0011] In some possible implementations, the leakage of the sealing structure is expressed as:

[0012] ;

[0013] in, To determine the leakage rate of the sealing ring, The inner radius of the sealing ring, The outer radius of the sealing ring, The length of the microcrystalline plastic model, The thickness is the thickness of the microcrystalline plastic model.

[0014] Secondly, embodiments of the present invention provide a leakage prediction system for metal sealing structures, including: a macroscopic model construction module, used to construct a macroscopic service finite element model based on the structural parameters and service parameters of the sealing structure, and to simulate the deformation behavior of the sealing structure during service;

[0015] The micro-model building module is used to build a micro-crystal plasticity model with a rough surface based on the surface roughness of the sealed structure.

[0016] The boundary condition extraction module is used to extract the deformation at the contact position between the sealing structure and the flanges on both sides from the finite element model as boundary conditions, and apply the boundary conditions to the microcrystalline plastic model to simulate the micro deformation behavior of the sealing structure at the contact position.

[0017] The leakage calculation module is used to determine the distance between the mean line of the rough surface of the sealing structure and the flange surface from the microcrystalline plastic model, and substitute the distance value as the gap height into the preset leakage calculation formula. Combined with the pressure difference on both sides of the sealing structure and the contact area between the sealing structure and the flange, the leakage of the sealing structure is calculated.

[0018] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0019] In this embodiment of the invention, a comprehensive and accurate simulation is achieved by integrating macroscopic and microscopic models. The macroscopic service finite element model is constructed based on the structure and service parameters of the metal sealing structure, effectively simulating its overall deformation behavior under actual working conditions, laying a solid foundation for subsequent analysis. The microscopic crystal plasticity model is constructed based on surface roughness, fully considering factors at the microscopic level, complementing the macroscopic model, and greatly improving the accuracy of performance analysis of the metal sealing structure.

[0020] By accurately extracting the deformation at the contact point as a boundary condition and applying it to the microscopic model, an organic combination of macroscopic and microscopic deformation behavior is achieved. This makes the simulation results more closely resemble reality and effectively avoids errors caused by traditional methods that neglect microscopic deformation or weak macroscopic-microscopic connections when dealing with such problems. In the leakage calculation process, the gap height obtained from the microscopic model, combined with key factors such as the pressure difference between the two sides and the contact area, is substituted into a scientifically sound preset formula to accurately quantify the leakage situation of the metal sealing structure. Compared with previous empirical or simple model calculation methods, this method has higher reliability and accuracy, providing strong technical support for the design optimization, quality control, and safe operation of metal sealing structures, effectively reducing the risk of equipment failure and maintenance costs caused by leakage problems. Attached Figure Description

[0021] To more clearly illustrate the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention 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.

[0022] Figure 1 A schematic flowchart illustrating an embodiment of a leakage prediction method for a metal sealing structure provided for the implementation of this invention;

[0023] Figure 2 This is a schematic diagram of the structure of the macroscopic service finite element model in an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the cross-section of a sealing ring according to an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of a displacement load applied to a flange during service in an embodiment of the present invention;

[0026] Figure 5a The EBSD diagram and pole figure of the cross-section of the W-type metal sealing ring are shown.

[0027] Figure 5b A schematic diagram of the mesh generation for a microcrystalline plasticity model;

[0028] Figure 5c A schematic diagram of applying boundary conditions to a microcrystalline plasticity model;

[0029] Figure 6 This is a schematic diagram of a leakage prediction system for a metal sealing structure according to an embodiment of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0031] In the relevant descriptions of this embodiment, the terms "including," "containing," and "possessing" are all open terms and are generally understood to include but not be limited to; the term "at least one" is generally understood to mean one or more, where "multiple" refers to two or more; the term "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items, for example, "at least one of a, b, or c", or "at least one of a, b, and c", which can all mean: a, b, c, ab (i.e., a and b), ac, bc, or abc, where a, b, and c can be single or multiple; the symbol "A / B" is used to describe the selection relationship of associated objects, generally indicating an "or" relationship.

[0032] In the following description of the embodiments, the terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms "a" and "the" as used in the embodiments of this application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0033] Those skilled in the art should understand that, in the following description of the embodiments of this application, the sequence of numbers does not imply the order of execution. Some or all steps may be executed in parallel or sequentially. 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.

[0034] Those skilled in the art will understand that the numerical ranges in the embodiments of this application should be understood to specifically disclose each intermediate value between the upper and lower limits of the range. Any stated value or intermediate value within a stated range, as well as any other stated value or each smaller range between intermediate values ​​within a range, are also included within this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0035] Unless otherwise stated, the technical / scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. While this application describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this application. All references to this specification are incorporated by way of citation to disclose and describe the methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0036] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0037] In modern industry, metal sealing structures, as key components ensuring system sealing, are widely used in various fields such as machinery, aviation, aerospace, and energy. For example, common metal sealing structures such as metal sealing rings and wave springs play an important sealing role in different equipment.

[0038] The sealing performance of metal seals directly affects the operating efficiency, energy consumption, safety, and service life of the corresponding equipment. Whether it's equipment operating under extreme conditions such as high temperature, high pressure, and strong corrosion, or precision instruments with extremely high sealing requirements, metal seals play an indispensable role. Therefore, accurate prediction and prevention of leaks in metal seals are of paramount importance.

[0039] Traditional leak prediction methods primarily rely on empirical formulas or experimental tests. While these methods can reflect the leakage situation of metal sealing structures to some extent, they often suffer from low accuracy and limited applicability. This is particularly true when dealing with leaks under complex operating conditions, where traditional methods exhibit poor prediction accuracy. Furthermore, although finite element simulation methods exist, the study of sealing structures under service conditions remains limited to the macroscopic or microscopic level, and microscopic models typically do not consider the influence of material microstructure and crystal orientation. In addition, experimental testing methods are time-consuming and resource-intensive, hindering rapid response and cost control.

[0040] Based on this, embodiments of the present invention provide a leakage prediction method for metal sealing structures, which solves the problems of poor leakage prediction accuracy and low efficiency of metal sealing structures in the prior art.

[0041] Figure 1 A schematic flowchart illustrating an embodiment of a leakage prediction method for a metal sealing structure provided for implementation of the present invention is shown below. Figure 1 As shown, the leakage prediction method for the above-mentioned metal sealing structure may include:

[0042] S101. Based on the structural and service parameters of the metal sealing structure, a macroscopic service finite element model is constructed to simulate the deformation behavior of the metal sealing structure during service.

[0043] Among them, the structural parameters of a metal sealing structure are physical quantities used to describe its geometric shape, size, interrelationships between parts, and material properties. These parameters play a decisive role in accurately understanding and analyzing the performance, mechanical behavior, and sealing effect of the metal sealing structure.

[0044] In this embodiment of the invention, taking a metal sealing structure as a sealing ring as an example, the above structural parameters include, but are not limited to, the wall thickness, outer diameter, inner diameter, crest radius, trough radius, transition arc radius, contact arc radius, wave height, and ring height of the sealing ring;

[0045] It should be noted that the embodiments of the present invention only use the sealing ring as an example for illustrative purposes. Other types of metal sealing structures (such as wave springs) are based on the same principle when calculating leakage, and will not be repeated here.

[0046] For example, taking a W-shaped sealing ring as an example, Figure 2 This is a schematic diagram of the structure of a macroscopic service finite element model according to an embodiment of the present invention. Figure 2 In Figure 'a', the structure of the macroscopic service finite element model is shown in the diagram, and in Figure 'b', the magnified view of a portion of the macroscopic service finite element model during its service period is shown in the diagram.

[0047] It should be noted that sealing rings of different shapes have similar sealing principles, such as C-type and U-type, and the leakage amount can be calculated using the method in the embodiments of this invention. This embodiment only uses the W-type as an example for illustration.

[0048] Understandably, in finite element software (such as Abaqus), given the rotational structural characteristics of the flanges on both sides of the sealing ring and the negligible circumferential differences, and considering that the sealing ring and flanges are typically perfect annular and planar structures (e.g., Figure 2 (The W-shaped sealing ring and flange structure shown). Therefore, the entire sealing ring structure can be reasonably simplified into a rotationally symmetric structure. Based on this, in this embodiment of the invention, an axisymmetric shell model can be used to simulate the structure of the sealing ring and flange, and the calculation process can be further simplified by utilizing the cross-section. This ensures calculation accuracy and significantly improves calculation efficiency by reducing the number of meshes.

[0049] During mesh generation, since subsequent studies require the contact width and pressure within the contact area, a finer mesh can be applied to the contact area between the sealing ring and the flange to accurately capture the deformation behavior within this critical region.

[0050] See also Figure 2 As shown, in this embodiment of the invention, 19245 CAX4R type elements can be used for basic mesh generation, and fine-tuning is applied to the contact positions. For example, in... Figure 2 In option b, the mesh size of the flange can be set to 0.5mm, the mesh size of the sealing ring at the contact position can be set to 0.01mm, and the mesh size of the remaining positions can be set to 0.02mm, so as to ensure that deformation information can be accurately captured in critical areas.

[0051] Understandably, from a geometric perspective, although the sealing ring itself is a three-dimensional structure, its rotational symmetry means that its cross-section can largely represent the overall structural characteristics. In this embodiment of the invention, its cross-section is used to simplify calculations, transforming a complex three-dimensional spatial problem into a relatively simple two-dimensional planar problem.

[0052] For example, Figure 3 This is a schematic diagram of the cross-section of a sealing ring according to an embodiment of the present invention. Figure 3 The specific values ​​of each structural parameter are shown in Table 1 below.

[0053] Table 1:

[0054] .

[0055] See Figure 3 As shown in Table 1, key geometric parameters such as the wall thickness, crest and trough shapes of the sealing ring are clearly presented on the cross-section. These parameters directly affect the mechanical properties and deformation behavior of the sealing ring in the model calculation. By simplifying it into a two-dimensional cross-sectional model, the amount of data to be processed during the calculation can be greatly reduced, avoiding large-scale meshing and complex calculations in the entire three-dimensional space, thus effectively reducing the complexity of the calculation.

[0056] After constructing a macroscopic service finite element model of the sealing ring using finite element software and performing mesh generation, the flange displacement can be controlled using service parameters to simulate the deformation behavior of the sealing ring during service.

[0057] Specifically, the movement settings of the upper and lower flanges can be controlled by displacement based on service parameters. These service parameters include those for the pre-tightening stage and those for the fatigue stage.

[0058] For example, Figure 4 This is a schematic diagram of a displacement load applied to a flange during service in an embodiment of the present invention. Figure 4 The horizontal axis represents time in seconds (s), and the vertical axis represents displacement in millimeters (mm). See also... Figure 4As shown, during the pre-tightening stage, the displacement increases linearly from the point of contact with the sealing ring, precisely reaching the target pre-tightening force displacement value u within 5 seconds. Subsequently, during the fatigue stage, an amplitude of 0.3 mm is applied to the flange according to a given frequency f. Figure 4 The fatigue load in A) is used to simulate the complex mechanical environment experienced by the sealing ring during actual service, thereby accurately simulating the deformation behavior of the sealing ring throughout its service life, and providing a reliable macroscopic deformation data basis for subsequent leakage prediction analysis.

[0059] S102, Based on the surface roughness of the sealed structure, a microcrystalline plasticity model with a rough surface is constructed;

[0060] Specifically, taking the aforementioned sealing ring as an example of a metal sealing structure, the first step is to accurately measure the surface roughness of the sealing ring. This can be done using surface roughness measuring instruments, such as a 3D profilometer, to obtain detailed roughness information about the sealing ring surface. The obtained roughness information may include, but is not limited to, key parameters such as the average roughness (Ra), root mean square roughness (Rq), and maximum peak-to-valley depth (Rz). This measurement data can serve as the basic input for constructing a microcrystalline plasticity model to characterize the microscopic properties of the sealing ring surface.

[0061] Then, at the microscale, appropriate constitutive relations can be selected for the microcrystalline plasticity model based on the material properties of the sealing ring (such as the crystal structure, crystal orientation, dislocation density, etc.). Different metallic materials exhibit different crystal plasticity behaviors, so the constitutive equations can be determined by combining the corresponding material properties to accurately reflect the deformation behavior of the sealing ring material at the microscale.

[0062] When constructing the model, the sealing ring and flange can be treated differently based on their surface roughness. Since the primary focus at the microscopic level is on the deformation behavior of the sealing ring, it is considered the main deformable component. For example, the flange is set as rigid with an ideally smooth surface. The sealing ring, however, is set as an elastoplastic component, and the measured surface roughness values ​​are used as its initial surface roughness parameters. Based on the information obtained from the macroscopic service finite element model and the actual measured surface roughness, appropriate algorithms or techniques can be used to generate realistic rough surfaces. For example, the rough surface of the sealing ring can be achieved using methods such as the Monte Carlo method.

[0063] Furthermore, by performing electron backscattered diffraction (EBSD) characterization on the contact position between the sealing ring and the flanges on both sides, a microcrystalline plastic model with a preset thickness can be constructed in the contact area based on the microstructure of the component material and a suitable size range can be selected.

[0064] It should be noted that the microcrystalline plasticity model must consider not only the size and shape of the crystals but also the influence of grain boundaries. To better simulate microscopic deformation behavior, the model size must be large enough to contain a sufficient number of crystals, but not so large as to result in excessive computation. Therefore, a balance needs to be found between accuracy and computational cost. A region of a preset size is selected from the obtained EBSD map to construct a microcrystalline plasticity model with a preset thickness. The specific preset size can be an empirical value or determined based on the needs of practical applications; this embodiment of the invention does not impose specific limitations on this.

[0065] For the meshing of the contact area, the maximum time step can be determined based on the contact stress conditions to ensure the stability and accuracy of the calculation. Simultaneously, to more accurately simulate micro-deformation, the contact surface area needs finer mesh subdivision using denser mesh elements, such as smaller mesh elements than those used in the macroscopic model, like C3D20R elements. The number of elements can be determined based on the model size and required computational accuracy.

[0066] S103, the deformation at the contact point between the sealing structure and the flanges on both sides is extracted from the finite element model as a boundary condition, and the boundary condition is applied to the microcrystalline plastic model to simulate the micro deformation behavior of the sealing structure at the contact point.

[0067] Specifically, after the finite element model calculation is completed, professional finite element analysis software tools can be used to accurately locate the contact area between the sealing structure and the flanges on both sides. Using the software's post-processing function, the displacement information of each node in this area can be extracted in detail. This displacement information can cover deformation data in different directions (such as axial and radial directions), which together constitute the deformation at the contact position.

[0068] When these extracted deformation quantities are applied as boundary conditions to the microcrystalline plasticity model, rigorous data conversion and adaptation can be performed. Since the macroscopic finite element model and the microcrystalline plasticity model differ in scale, element type, and calculation methods, the deformation quantities of the macroscopic model can be reasonably allocated to the corresponding boundary nodes of the microscopic model based on the node distribution and calculation rules of the microscopic model.

[0069] In the microcrystalline plasticity model, the initial state and loading method of the model are precisely adjusted based on these boundary conditions. For example, the nodal displacement constraints at the contact points are set to be consistent with the extracted deformation, simulating the initial stress state of the microstructure under the influence of macroscopic deformation. Simultaneously, in subsequent simulations, other external loads and internal stresses are gradually applied based on this, to accurately simulate the microscopic deformation behavior of the sealed structure at the contact points.

[0070] During the simulation, interactions between crystals and dislocation movement can be considered, introducing relevant crystal plasticity theories, such as the generation and slip of dislocations at the microscopic level. This allows the microscopic crystal plasticity model to more realistically simulate the deformation and failure process of the sealing structure at the microscopic level. This helps to deepen the understanding of how leakage phenomena in sealing structures gradually arise and develop at the microscopic level during macroscopic service, providing a more detailed microscopic basis for subsequent accurate prediction of leakage behavior in sealing structures.

[0071] For example, the sealing structure is as described above. Figure 2 Taking the sealing ring as an example, the surface roughness of the sealing ring is measured to be 0.4 μm. The material of the W-type sealing ring can be GH4169 high-temperature alloy. Since GH4169 high-temperature alloy has a relatively simple microstructure, mainly composed of equiaxed crystals, the influence of subsurface particles on mechanical behavior can be ignored if sufficient particles are included in the calibration model. The contact length L between the flange and the sealing ring is 50 μm in the macroscopic model. Therefore, a 50*50 μm region can be selected in the EBSD diagram of the metal ring contact position to construct a three-dimensional microcrystalline plastic model with a thickness t of 2.5 μm. For example... Figures 5a to 5c This is a schematic diagram of a microcrystalline plasticity model based on a real microstructure in an embodiment of the present invention. Figure 5a The EBSD diagram and pole diagram of the cross-section of the W-type metal sealing ring are shown. Figure 5b This is a schematic diagram of the mesh generation for a microcrystalline plasticity model. Figure 5c This is a schematic diagram illustrating the application of boundary conditions to a microcrystalline plasticity model. Leakage mainly occurs in areas such as... Figure 5c The gap between the upper flange surface and the rough surface of the lower sealing ring is shown.

[0072] See Figures 5a to 5c As shown, due to the large variation in contact stress, the microcrystalline plasticity model can accurately analyze the loading process using a maximum time step of 0.01 s. This model consists of 36 particles, and the rough surface generated by the Monte Carlo method exhibits many peaks. To avoid analysis failure due to mesh distortion during simulation and to more accurately characterize the deformation of the rough surface, the surface area at the contact location can be meshed using a preset number of elements to avoid errors caused by mesh distortion during simulation. For example... Figure 5b The diagram shows that a total of 8728 C3D20R elements were used for mesh generation.

[0073] In some embodiments, in addition to making the model more accurate, the microcrystalline plasticity model can be calibrated and verified based on experimental data or actual service data to ensure that the model can accurately reflect the actual microscopic deformation behavior of the sealing ring. By continuously adjusting the model's parameters, such as grain boundary strength and dislocation mobility, the model's performance and predictive ability can be optimized.

[0074] S104. Determine the distance between the mean line of the rough surface of the sealing structure and the flange surface from the microcrystalline plastic model, and substitute the distance value as the gap height into the preset leakage calculation formula. Combined with the pressure difference on both sides of the sealing structure, calculate the leakage of the sealing structure.

[0075] Specifically, after the simulation of the microcrystalline plasticity model is completed, advanced image processing and data analysis techniques can be used to accurately identify and analyze the rough surface under the sealed structure in the model. By statistically processing the microscopic morphology data of the rough surface, the position coordinates of its mean line can be calculated.

[0076] Taking the sealing structure as an example, for instance... Figure 5c As shown, there is a certain gap between the upper flange surface and the rough surface of the lower sealing ring. A precise spatial measurement algorithm can be used to obtain the distance between the mean line of the lower rough surface and the flange surface in the vertical direction.

[0077] Understandably, the leakage of fluid in the sealing gap between the flange and the sealing ring mainly depends on factors such as the pressure difference between the two sides, the gap height, and the contact area. Therefore, it can be approximated as leakage between two upper and lower plates. Based on the parallel circular plate model, the distance in the vertical direction between the mean line of the lower rough surface and the upper surface is defined as the gap height, that is, the gap height is related to the roughness.

[0078] For example, the leakage rate of fluid flowing through the leakage channel can be expressed as:

[0079] ;

[0080] in, The leakage rate is the amount of fluid flowing through the leakage channel, and h is the gap height. t is the dynamic viscosity of the fluid, L is the length of the microcrystalline plastic model, t is the thickness of the microcrystalline plastic model, and P1-P2 is the pressure difference.

[0081] Based on the parallel circular plate model, the reference flow coefficient The effect of surface roughness of the sealing gap on leakage can be described by the following expression:

[0082] ;

[0083] in, For flow factor, For roughness;

[0084] The leakage rate of a sealing gap in contact with a rough surface can be expressed as:

[0085] ;

[0086] in, The leakage rate of the sealing gap in contact with a rough surface. The density of the leaked gas.

[0087] Therefore, the overall leakage rate It can be represented as:

[0088] ;

[0089] This is equivalent to dividing the total contact area by the area of ​​the microcrystalline plastic model and then multiplying by Q. Where A is the contact area between the component and the mold.

[0090] Substituting the parameters in this invention, the leakage of the sealing ring described above can be expressed as:

[0091] ;

[0092] in, To determine the leakage rate of the sealing ring, The inner radius of the sealing ring, The outer radius of the sealing ring, The length of the microcrystalline plastic model, The thickness is the thickness of the microcrystalline plastic model.

[0093] In this embodiment of the invention, a comprehensive and accurate simulation is achieved by integrating macroscopic and microscopic models. The macroscopic service finite element model is constructed based on the structure and service parameters of the metal sealing structure, effectively simulating its overall deformation behavior under actual working conditions, laying a solid foundation for subsequent analysis. The microscopic crystal plasticity model is constructed based on surface roughness, fully considering factors at the microscopic level, complementing the macroscopic model, and greatly improving the accuracy of performance analysis of the metal sealing structure.

[0094] By accurately extracting the deformation at the contact point as a boundary condition and applying it to the microscopic model, an organic combination of macroscopic and microscopic deformation behavior is achieved. This makes the simulation results more closely resemble reality and effectively avoids errors caused by traditional methods that neglect microscopic deformation or weak macroscopic-microscopic connections when dealing with such problems. In the leakage calculation process, the gap height obtained from the microscopic model, combined with key factors such as the pressure difference between the two sides and the contact area, is substituted into a scientifically sound preset formula to accurately quantify the leakage situation of the metal sealing structure. Compared with previous empirical or simple model calculation methods, this method has higher reliability and accuracy, providing strong technical support for the design optimization, quality control, and safe operation of metal sealing structures, effectively reducing the risk of equipment failure and maintenance costs caused by leakage problems.

[0095] Based on the same inventive concept, embodiments of this application also provide a leakage prediction system for metal sealing structures. Figure 6 This is a schematic diagram of a leakage prediction system for a metal sealing structure according to an embodiment of the present invention. See also... Figure 6 As shown, the leakage prediction system 600 for the metal sealing structure may include:

[0096] The macroscopic model construction module 601 is used to construct a macroscopic service finite element model based on the structural parameters and service parameters of the sealing structure, and to simulate the deformation behavior of the sealing structure during service.

[0097] The micro-model building module 602 is used to build a micro-crystal plasticity model with a rough surface based on the surface roughness of the sealed structure.

[0098] The boundary condition extraction module 603 is used to extract the deformation of the sealing structure at the contact position with the flanges on both sides from the finite element model as boundary conditions, and apply the boundary conditions to the microcrystalline plastic model to simulate the micro deformation behavior of the sealing structure at the contact position.

[0099] The leakage calculation module 604 is used to determine the distance between the mean line of the lower rough surface of the sealing structure and the flange surface from the microcrystalline plastic model, and substitute the distance value as the gap height into the preset leakage calculation formula. Combined with the pressure difference on both sides of the sealing structure and the contact area between the sealing structure and the flange, the leakage of the sealing structure is calculated.

[0100] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, please refer to each other. Each embodiment focuses on describing the differences from other embodiments.

[0101] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application 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 or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. A method for predicting leakage in a metal sealing structure, characterized in that, include: Based on the structural and service parameters of the metal sealing structure, a macroscopic service finite element model is constructed to simulate the deformation behavior of the sealing structure during service. Based on the surface roughness of the sealing structure, a microcrystalline plasticity model with a rough surface is constructed. The deformation at the contact point between the sealing structure and the flanges on both sides is extracted from the finite element model as a boundary condition, and the boundary condition is applied to the microcrystalline plastic model to simulate the microscopic deformation behavior of the sealing structure at the contact point. The distance between the mean line of the rough surface of the sealing structure and the flange surface is determined from the microcrystalline plastic model, and the distance is used as the gap height and substituted into the preset leakage calculation formula. Combined with the pressure difference on both sides of the sealing structure, the leakage of the sealing structure is calculated. The process of constructing a macroscopic service finite element model based on the structural and service parameters of the metal sealing structure to simulate the deformation behavior of the sealing structure during service includes: In finite element software, based on the structural parameters, an axisymmetric shell model is used to simulate the structure of the sealing structure and the flange, and its cross-section is used to simplify the calculation; wherein, the structural parameters include, but are not limited to, the wall thickness, outer diameter, inner diameter, crest radius, trough radius, transition arc radius, contact arc radius, wave height, and ring height of the sealing structure; The finite element model is meshed, and the mesh is refined in the contact area between the sealing structure and the flange to accurately capture the deformation behavior in the contact area. The flange displacement is controlled according to the service parameters to simulate the deformation behavior of the sealing structure during service; wherein, the service parameters include service parameters for the pre-tightening stage and service parameters for the fatigue stage; Based on the surface roughness of the sealing structure, a microcrystalline plasticity model with a rough surface is established, including: The surface roughness of the sealing structure is obtained by roughness measurement, and the contact conditions between the flange and the sealing structure are established based on the surface roughness; wherein, the contact conditions include: setting the flange as rigid and the surface as ideally smooth, and setting the sealing structure as elastic-plastic and the initial surface roughness is consistent with the measured value; The contact position between the sealing structure and the flanges on both sides is characterized by EBSD, and a region of a preset size is selected from the obtained EBSD image to construct a microcrystalline plastic model with a preset thickness. The leakage rate of the sealing structure is expressed as: ； in, To determine the leakage rate of the sealing ring, The inner radius of the sealing ring, The outer radius of the sealing ring, The length of the microcrystalline plastic model, The thickness is the thickness of the microcrystalline plastic model.

2. The method according to claim 1, characterized in that, In the microcrystalline plasticity model, the surface at the contact position is meshed using a preset number of elements to avoid errors caused by mesh distortion during the simulation process.

3. A leakage prediction system for a metal sealing structure, The method according to claim 1 is characterized in that, include: The macroscopic model construction module is used to construct a macroscopic service finite element model based on the structural parameters and service parameters of the metal sealing structure, and to simulate the deformation behavior of the sealing structure during service. The microscopic model building module is used to establish a microscopic crystal plasticity model with a rough surface based on the surface roughness of the sealing structure. The boundary condition extraction module is used to extract the deformation of the sealing structure at the contact position with the flanges on both sides from the finite element model as the boundary condition, and apply the boundary condition to the microcrystalline plastic model to simulate the microscopic deformation behavior of the sealing structure at the contact position. The leakage calculation module is used to determine the distance between the mean line of the rough surface of the sealing structure and the flange surface from the microcrystalline plastic model, and substitute the distance value as the gap height into the preset leakage calculation formula. Combined with the pressure difference on both sides of the sealing structure and the contact area between the sealing structure and the flange, the leakage of the sealing structure is calculated.

Images