A simulation method for the oil collection process of under-ring lubrication

Abstract

The present invention discloses a simulation method for the oil collection process of under-ring lubrication, comprising the following steps: establishing geometric models required for under-ring lubrication; performing patch mesh division on each geometric model based on the snappyHexMesh mesh generation tool in Openfoam to obtain the three-dimensional flow domain mesh of each geometric model; establishing a computational fluid dynamics model; setting the boundary conditions and fluid properties of the boundaries of the three-dimensional flow domain mesh of each geometric model; performing two-phase fluid numerical calculations on the three-dimensional flow domain mesh of each geometric model to obtain the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain mesh of each geometric model; using the paraView visualization tool to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil in the oil collection process of under-ring lubrication. The present invention solves the problem that the traditional experimental method cannot obtain the specific proportion of the velocity, pressure, lubricating oil and air respectively occupied by the flow field volume at any point in the flow field.

Description

Technical Field

[0001] The invention relates to the technical field of computer numerical simulation, in particular to a simulation method for an under-ring lubrication oil collection process. Background Art

[0002] Aircraft gas turbine engines (abbreviated as aero engines) are the main power units of aircraft and helicopters. They are known as the "crown jewel of modern industry" because of their complex structure, high reliability requirements, and integration of many cutting-edge technologies. With the rapid development of science and technology in my country and the continuous improvement of the process level of the aviation industry, the performance and output power of aero engines have been continuously improved, and the spindle speed has increased significantly, reaching the ultra-high speed level. The high-speed and stable operation of the spindle depends on the reliable operation of the spindle fulcrum rolling bearing (spindle bearing), which places extremely high requirements on the lubrication and cooling of the spindle bearing. If the lubrication and cooling of the spindle bearing are poor, it may cause a reduction in bearing life, increase engine vibration, and even cause catastrophic damage such as shaft seizure, which seriously threatens flight safety. There are two main ways to lubricate the main shaft bearings of aircraft engines: jet lubrication and under-ring lubrication: the jet lubrication method refers to the lubrication of the bearing directly through the lubricating oil sprayed by the nozzle. For the spindle bearing, the lubricating oil generally enters the bearing through the gap between the retainer and the guide surface of the inner ring of the bearing. The under-ring lubrication method refers to the lubricating oil passing through the axial oil delivery groove and radial oil throwing hole set on the inner ring of the bearing in turn, and then enters the bearing for lubrication and cooling. Studies have shown that jet lubrication is suitable for bearings with lower DN values, while under-the-ring lubrication is more suitable for bearings with higher DN values. At the same time, the amount of lubricating oil required by bearings using under-the-ring lubrication is also less than that of bearings using conventional jet lubrication.

[0003] During the process of lubrication and oil collection under the ring, the internal flow field is quite complex, involving complex flow states such as oil and gas two phases, liquid impacting solid wall, rotating turbulence, etc. The distribution of lubricating oil can be obtained through traditional experimental methods. The traditional experimental method is to first build a test bench and then use a high-speed camera to shoot the distribution of lubricating oil. However, the traditional experimental method can only capture the macroscopic distribution of lubricating oil in space, and cannot obtain the specific process of lubricating oil being impacted and then broken, nor can it obtain the specific proportion of the velocity, pressure, and flow field volume occupied by lubricating oil and air at any point in the flow field. Summary of the invention

[0004] In view of the above-mentioned defects, the present invention proposes a simulation method for the under-ring lubrication oil collection process, which aims to solve the problem that the traditional experimental method can only capture the macroscopic distribution of the lubricating oil in space, but cannot obtain the specific process of the lubricating oil being impacted and then broken, nor can it obtain the velocity, pressure, and specific proportions of the flow field volume occupied by the lubricating oil and air at any point in the flow field.

[0005] To achieve this object, the present invention adopts the following technical solutions:

[0006] A simulation method for an under-ring lubrication oil collection process comprises the following steps:

[0007] Step S1: establishing a geometric model of an axial oil collecting ring, a radial oil collecting ring, at least three nozzles and a rotating space required for under-ring lubrication;

[0008] Step S2: performing patch mesh division on each of the geometric models based on the snappyHexMesh mesh generation tool in Openfoam to obtain a three-dimensional watershed mesh of each of the geometric models;

[0009] Step S3: establishing a computational fluid dynamics model, wherein the computational fluid dynamics model includes a Navier-Stokes equation model, a continuity equation model and a turbulence equation model;

[0010] Step S4: setting boundary conditions and fluid properties of the boundaries of the three-dimensional flow domain grids of each of the geometric models, and setting process parameters for controlling the simulation process and the input and output formats of the calculations;

[0011] Step S5: Based on the computational fluid dynamics model, the boundary conditions, the fluid properties, the process parameters and the input and output formats, numerical calculation of the two-phase fluid is performed in the three-dimensional flow domain grid of each of the geometric models to obtain the mass of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each of the geometric models;

[0012] Step S6: Based on the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, the paraView visualization tool is used to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil during the under-ring lubrication oil collection process.

[0013] Preferably, in step S2, the following sub-steps are specifically included:

[0014] Step S21: pre-setting the blockMesh mesh generation tool;

[0015] Step S22: using the blockMesh mesh generation tool to generate a background mesh;

[0016] Step S23: pre-setting snappyHexMesh mesh generation tool;

[0017] Step S24: Generate a patch mesh using the snappyHexMesh mesh generation tool.

[0018] Preferably, in step S21, the pre-setting blockMesh mesh generation tool specifically includes the following sub-steps:

[0019] Step S211: setting blockMeshDict dictionary file and blocks dictionary file;

[0020] Step S212: setting 8 vertices in the blockMeshDict dictionary file;

[0021] Step S213: using eight vertices to form a block in the blocks dictionary file;

[0022] Step S214: using the blocks to determine boundary surfaces at the boundaries of the three-dimensional watershed grids of each of the geometric models.

[0023] Preferably, in step S23, presetting the snappyHexMesh mesh generation tool specifically includes the following sub-steps:

[0024] Step S231: Setting snappyHexMeshDict dictionary file and geometry dictionary file;

[0025] Step S232: calling out the characterization mesh and the patch mesh in the snappyHexMeshDict dictionary file;

[0026] Step S233: inputting the files of each geometric model into the geometry dictionary file;

[0027] Step S234: adjusting the maximum global grid number, the minimum grid encryption level and the number of transition grids between grids of different levels, and dividing and encrypting the overall grid and the rotation area grid respectively.

[0028] Preferably, in step S3, the computational fluid dynamics model is a VOF model, and the specific model equation is as follows:

[0029]

[0030]

[0031]

[0032] Among them, α is the phase function; τ is the time; ρ is the density; U is the velocity; p rgh is the relative pressure; g is the acceleration due to gravity; is the surface tension term; v is the viscosity; h is the position vector of the center of the grid unit.

[0033] Preferably, in step S5, two-phase fluid numerical calculation is performed on the three-dimensional flow domain grid of each geometric model to obtain the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, which specifically includes the following sub-steps:

[0034] Step S51: obtaining the change of boundary mass flow rate of the three-dimensional watershed grid of each geometric model over time;

[0035] Step S52: multiplying the boundary mass flow rate of the three-dimensional flow domain grid of each geometric model by the phase function of one of the two-phase fluids to obtain the mass flow rate of each corresponding phase fluid;

[0036] Step S53: Obtain a record file of the mass flow rate of each corresponding phase fluid.

[0037] Preferably, in step S6, the following sub-steps are also included:

[0038] According to the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, the oil recovery efficiency of the entire oil recovery process is obtained. The specific calculation formula is as follows:

[0039]

[0040] Among them, Efficiency is the oil recovery efficiency; M inner_outlet1 is the mass of lubricating oil passing through the inner_outlet1 boundary; M inner_outlet2 is the mass of lubricating oil passing through the inner_outlet2 boundary; M inner_outlet3 is the mass of lubricating oil passing through the inner_outlet3 boundary; M Inlet is the mass of lubricating oil passing through the Inlet boundary.

[0041] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0042] This scheme first establishes a geometric model, then obtains a three-dimensional grid based on the geometric model, then establishes a computational fluid dynamics model, and then sets the parameters and boundary conditions required for calculations such as fluid properties. Finally, based on the established computational fluid dynamics model and the set relevant parameters, numerical calculations of the two-phase fluid are performed on the three-dimensional flow domain grid to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil in the under-annular lubrication oil collection process, and accurately obtains the velocity, pressure, and specific proportions of the flow field volume occupied by the lubricating oil and air at any point in the flow field, thereby solving the problems of difficulty and low accuracy in capturing the oil-gas two-phase interface in the complex flow field in the under-annular lubrication oil collection process in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1The invention is a flow chart of steps of a simulation method for the under-ring lubrication oil collection process. DETAILED DESCRIPTION

[0044] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0045] A simulation method for an under-ring lubrication oil collection process comprises the following steps:

[0046] Step S1: establishing a geometric model of an axial oil collecting ring, a radial oil collecting ring, at least three nozzles and a rotating space required for under-ring lubrication;

[0047] Step S2: performing patch mesh division on each of the geometric models based on the snappyHexMesh mesh generation tool in Openfoam to obtain a three-dimensional watershed mesh of each of the geometric models;

[0048] Step S3: establishing a computational fluid dynamics model, wherein the computational fluid dynamics model includes a Navier-Stokes equation model, a continuity equation model and a turbulence equation model;

[0049] Step S4: setting boundary conditions and fluid properties of the boundaries of the three-dimensional flow domain grids of each of the geometric models, and setting process parameters for controlling the simulation process and the input and output formats of the calculations;

[0050] Step S5: Based on the computational fluid dynamics model, the boundary conditions, the fluid properties, the process parameters and the input and output formats, numerical calculation of the two-phase fluid is performed in the three-dimensional flow domain grid of each of the geometric models to obtain the mass of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each of the geometric models;

[0051] Step S6: Based on the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, the paraView visualization tool is used to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil during the under-ring lubrication oil collection process.

[0052] A simulation method for the oil collection process of under-ring lubrication in this scheme is as follows: Figure 1As shown, the first step is to establish the geometric model of the axial oil collecting ring, radial oil collecting ring, at least three nozzles and rotating space required for under-ring lubrication. In this embodiment, there are three nozzles, the geometric model of the axial oil collecting ring is named Inlet.stl, the geometric model of the radial oil collecting ring is named outer_outlet.stl, the geometric models of the three nozzles are named inner_outlet1.stl, inner_outlet2.stl, inner_outlet3.stl, and the geometric model of the rotating space is named ring_Wall.stl. The establishment of the geometric model of the axial oil collecting ring, radial oil collecting ring, nozzle and rotating space is conducive to the subsequent calculation of the distribution of lubricating oil in the under-ring lubrication oil collecting process. The second step is to perform patch meshing on each of the geometric models based on the snappyHexMesh mesh generation tool in Openfoam to obtain the three-dimensional flow domain mesh of each of the geometric models. Specifically, Openfoam is an object-oriented computational fluid dynamics library. Openfoam supports polyhedral meshes, so it can handle complex geometric shapes. The snappyHexMesh mesh generation tool that comes with Openfoam can quickly and efficiently divide hexahedron + polyhedron meshes with high mesh quality. The third step is to establish a computational fluid dynamics model, which includes a reduced Navier-Stokes equation model, a continuity equation model, and a turbulence equation model. Specifically, the reduced Navier-Stokes equation model, the continuity equation model, and the turbulence equation model all have existing fluid dynamics models, and the computational fluid dynamics model can be used as a basis for subsequent simulation calculations. The fourth step is to set the boundary conditions and fluid properties of the boundaries of the three-dimensional flow basin grids of each of the geometric models, and set the process parameters that control the simulation process and the input and output formats of the calculations. Specifically, the boundaries of the three-dimensional flow basin grids of each of the geometric models are Inlet, outer_outlet, inner_outlet1, inner_outlet2, inner_outlet3, and ring_Wall, respectively. Setting boundary conditions includes setting boundary conditions on the Inlet boundary, outer_outlet boundary, inner_outlet1 boundary, inner_outlet2 boundary, inner_outlet3 boundary and ring_Wall boundary respectively. Among them, the Inlet boundary needs to set the velocity boundary condition, and set the phase function to 1, which means that the inlet is all lubricating oil; the outer_outlet boundary, inner_outlet1 boundary, inner_outlet2 boundary and inner_outlet3 boundary all use pressure outlet boundary conditions; the ring_Wall boundary uses a no-slip wall condition, and no-slip means setting the velocity of the boundary surface to 0.For the setting of fluid properties, it is necessary to set the kinematic viscosity, density and surface tension of the two-phase fluid. Set the process parameters of the control simulation process and the input and output formats of the calculation, including the start time, end time, calculation step, maximum Courant number, input format and output format. The fifth step is to perform numerical calculations of the two-phase fluid in the three-dimensional flow domain grid of each geometric model based on the computational fluid dynamics model, the boundary conditions, the fluid properties, the process parameters and the input and output formats, and obtain the quality of one of the two-phase fluids passing through the boundary of the three-dimensional flow domain grid of each geometric model. In this embodiment, the quality of one of the two-phase fluids passing through the inner_outlet1 boundary, the inner_outlet2 boundary and the inner_outlet3 boundary is obtained through post-processing, so that the oil collection efficiency of the entire oil collection process of the under-ring lubrication can be further obtained. The sixth step is to use the paraView visualization tool to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil in the under-ring lubrication oil collection process based on the quality of one of the two-phase fluids passing through the boundary of the three-dimensional flow domain grid of each geometric model. Specifically, the paraView visualization tool is an existing application program that can intuitively display the two-phase fluid distribution and velocity distribution of the lubricating oil during the under-the-ring lubrication oil collection process.

[0053] This scheme first establishes a geometric model, then obtains a three-dimensional grid based on the geometric model, then establishes a computational fluid dynamics model, and then sets the parameters and boundary conditions required for calculations such as fluid properties. Finally, based on the established computational fluid dynamics model and the set relevant parameters, numerical calculations of the two-phase fluid are performed on the three-dimensional flow domain grid to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil in the under-annular lubrication oil collection process, and accurately obtains the velocity, pressure, and specific proportions of the flow field volume occupied by the lubricating oil and air at any point in the flow field, thereby solving the problems of difficulty and low accuracy in capturing the oil-gas two-phase interface in the complex flow field in the under-annular lubrication oil collection process in the prior art.

[0054] Preferably, in step S2, the following sub-steps are specifically included:

[0055] Step S21: pre-setting the blockMesh mesh generation tool;

[0056] Step S22: using the blockMesh mesh generation tool to generate a background mesh;

[0057] Step S23: pre-setting snappyHexMesh mesh generation tool;

[0058] Step S24: Generate a patch mesh using the snappyHexMesh mesh generation tool.

[0059] In this embodiment, the blockMesh mesh generation tool and the snappyHexMesh mesh generation tool are both tools provided by Openfoam. The background mesh generated by the blockMesh mesh generation tool can provide a reference for the generation of the patch mesh.

[0060] To further explain, meshes are divided for the parts other than the oil collecting ring according to the mesh encryption level of 0, and meshes are divided for the rotating area of ​​the oil collecting ring according to the mesh encryption levels of 1, 2 and 3. Because the mesh of the oil collecting ring area is rotating and is a dynamic mesh, the snappyHexMesh mesh generation tool is needed to divide the AMI area (the AMI area is the rotating mesh area), where the mesh rotation speeds are 10000RPM, 20000RPM and 40000RPM respectively, and the mesh of the AMI area must rotate at the same speed.

[0061] Preferably, in step S21, the pre-setting blockMesh mesh generation tool specifically includes the following sub-steps:

[0062] Step S211: setting blockMeshDict dictionary file and blocks dictionary file;

[0063] Step S212: setting 8 vertices in the blockMeshDict dictionary file;

[0064] Step S213: using eight vertices to form a block in the blocks dictionary file;

[0065] Step S214: using the blocks to determine boundary surfaces at the boundaries of the three-dimensional watershed grids of each of the geometric models.

[0066] In this embodiment, the blockMesh mesh generation tool includes a blockMeshDict dictionary file and a blocks dictionary file. Before using the blockMesh mesh generation tool, the blockMesh mesh generation tool needs to be pre-set. The use of the 8 vertices vertices in the pre-setting can quickly find the boundary points of the three-dimensional watershed mesh of the geometric model, and connect the boundary points to form a boundary surface, which is conducive to the subsequent setting of boundary conditions for each boundary surface.

[0067] Preferably, in step S23, the pre-setting snappyHexMesh mesh generation tool specifically includes the following sub-steps:

[0068] Step S231: Setting snappyHexMeshDict dictionary file and geometry dictionary file;

[0069] Step S232: calling out the characterization mesh and the patch mesh in the snappyHexMeshDict dictionary file;

[0070] Step S233: inputting the files of each geometric model into the geometry dictionary file;

[0071] Step S234: adjusting the maximum global grid number, the minimum grid encryption level and the number of transition grids between grids of different levels, and dividing and encrypting the overall grid and the rotation area grid respectively.

[0072] In this embodiment, the snappyHexMesh mesh generation tool includes a snappyHexMeshDict dictionary file and a geometry dictionary file. Before using the snappyHexMesh mesh generation tool, the snappyHexMesh mesh generation tool needs to be pre-set, which is convenient for subsequent use to mesh the geometric model.

[0073] Further explanation: In the presetting, the overall grid and the rotating area grid are divided and encrypted respectively. Since it is necessary to analyze the fine lubricating oil particles after the collision between the lubricating oil in the rotating area and the oil collecting ring, it is necessary to encrypt the grid in the rotating area. The encryption levels are set to 1, 2 and 3, where the minimum grid spacing is 0.25mm, and the minimum grid spacing outside the rotating area is 0.5mm. The rotating area is realized by sliding grid. The relative position between the grids in this area remains unchanged, and the overall grids maintain the same rotation speed.

[0074] Preferably, in step S3, the computational fluid dynamics model is a VOF model, and the specific model equation is as follows:

[0075]

[0076]

[0077]

[0078] Among them, α is the phase function; τ is the time; ρ is the density; U is the velocity; p rgh is the relative pressure; g is the acceleration due to gravity; is the surface tension term; v is the viscosity; h is the position vector of the center of the grid unit.

[0079] In this embodiment, since the computational fluid dynamics model is a VOF model, the VOF model is suitable for calculating the flow of fluids that cannot be mixed with each other, such as gas and liquid. Specifically, when the phase function α in the model equation is 1, it means that the three-dimensional flow grid is full of liquid; when the phase function α in the model equation is 0, it means that the three-dimensional flow grid is full of gas; when the phase function α in the model equation is 0-1, it represents the interface between oil and gas phases.

[0080] Preferably, in step S5, numerical calculation of two-phase fluid is performed on the three-dimensional flow domain grid of each geometric model to obtain the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, which specifically includes the following sub-steps:

[0081] Step S51: obtaining the change of boundary mass flow rate of the three-dimensional watershed grid of each geometric model over time;

[0082] Step S52: multiplying the boundary mass flow rate of the three-dimensional flow domain grid of each geometric model by the phase function of one of the two-phase fluids to obtain the mass flow rate of each corresponding phase fluid;

[0083] Step S53: Obtain a record file of the mass flow rate of each corresponding phase fluid.

[0084] In this embodiment, the mass flow rate refers to the mass of one of the two-phase fluids of oil and gas passing through the boundary of the three-dimensional flow grid of the geometric model per unit time. According to the definition of the phase function in the two-phase flow, the mass flow rate of a phase can be obtained by multiplying the mass flow rate by the phase function of a phase. Therefore, in this solution, the boundary mass flow rate of the three-dimensional flow grid of each geometric model is multiplied by the phase function of one of the two-phase fluids to obtain the mass flow rate of each corresponding phase fluid.

[0085] To further illustrate, after obtaining the record files of the comprehensive mass flow of each corresponding phase fluid, each record file needs to be processed, which specifically includes the following steps: the first step is to delete the non-data rows in each record file; the second step is to read all the data rows in each record file to obtain the relationship graph between each mass flow and time; the third step is to integrate each mass flow with respect to the corresponding time according to the relationship graph between each mass flow and time.

[0086] Preferably, in step S6, the following sub-steps are also included:

[0087] According to the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, the oil recovery efficiency of the entire oil recovery process is obtained. The specific calculation formula is as follows:

[0088]

[0089] Among them, Efficiency is the oil recovery efficiency; M inner_outlet1 is the mass of lubricating oil passing through the inner_outlet1 boundary; M inner_outlet2 is the mass of lubricating oil passing through the inner_outlet2 boundary; M inner_outlet3 is the mass of lubricating oil passing through the inner_outlet3 boundary; M Inlet is the mass of lubricating oil passing through the Inlet boundary.

[0090] In this embodiment, by obtaining key parameters that affect the oil collection efficiency of the under-ring lubrication, technical support is provided for the subsequent structural design of the oil collection ring.

[0091] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0092] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A simulation method for the oil collection process of under-ring lubrication, characterized in that: The following steps are involved: Step S1: establishing a geometric model of an axial oil collecting ring, a radial oil collecting ring, at least three nozzles and a rotating space required for under-ring lubrication; Step S2: performing patch mesh division on each of the geometric models based on the snappyHexMesh mesh generation tool in Openfoam to obtain a three-dimensional watershed mesh of each of the geometric models; Step S3: establishing a computational fluid dynamics model, wherein the computational fluid dynamics model includes a Navier-Stokes equation model, a continuity equation model and a turbulence equation model; Step S4: setting boundary conditions and fluid properties of the boundaries of the three-dimensional flow domain grids of each of the geometric models, and setting process parameters for controlling the simulation process and the input and output formats of the calculations; Step S5: Based on the computational fluid dynamics model, the boundary conditions, the fluid properties, the process parameters and the input and output formats, numerical calculation of the two-phase fluid is performed in the three-dimensional flow domain grid of each of the geometric models to obtain the mass of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each of the geometric models; Step S6: according to the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, using the paraView visualization tool to obtain the two-phase fluid distribution and velocity distribution of the lubricating oil in the under-ring lubrication oil collection process; In step S5, two-phase fluid numerical calculation is performed on the three-dimensional flow domain grid of each geometric model to obtain the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, which specifically includes the following sub-steps: Step S51: obtaining the change of boundary mass flow rate of the three-dimensional watershed grid of each geometric model over time; Step S52: multiplying the boundary mass flow rate of the three-dimensional flow domain grid of each geometric model by the phase function of one of the two-phase fluids to obtain the mass flow rate of each corresponding phase fluid; Step S53: Obtain the record files of the mass flow rate of each corresponding phase fluid, and process each record file, specifically including the following steps: the first step is to delete the non-data lines in each record file; the second step is to read all the data lines in each record file to obtain the relationship diagram between each mass flow rate and time; the third step is to integrate each mass flow rate with respect to the corresponding time according to the relationship diagram between each mass flow rate and time; In step S2, the following sub-steps are specifically included: Step S21: pre-setting the blockMesh mesh generation tool; Step S22: using the blockMesh mesh generation tool to generate a background mesh; Step S23: pre-setting snappyHexMesh mesh generation tool; Step S24: using the snappyHexMesh mesh generation tool to generate a patch mesh; In step S23, the pre-setting snappyHexMesh mesh generation tool specifically includes the following sub-steps: Step S231: setting snappyHexMeshDict dictionary file and geometry dictionary file; Step S232: calling out the characterization mesh and the patch mesh in the snappyHexMeshDict dictionary file; Step S233: inputting the files of each geometric model into the geometry dictionary file; Step S234: adjusting the maximum global grid number, the minimum grid encryption level and the number of transition grids between grids of different levels, and dividing and encrypting the overall grid and the rotation area grid respectively.

2. The simulation method for the under-ring lubrication oil collection process according to claim 1 is characterized in that: In step S21, the pre-setting blockMesh mesh generation tool specifically includes the following sub-steps: Step S211: setting blockMeshDict dictionary file and blocks dictionary file; Step S212: setting 8 vertices in the blockMeshDict dictionary file; Step S213: using eight vertices to form a block in the blocks dictionary file; Step S214: using the blocks to determine boundary surfaces at the boundaries of the three-dimensional watershed grids of each of the geometric models.

3. The simulation method for the under-ring lubrication oil collection process according to claim 1 is characterized in that: In step S3, the computational fluid dynamics model is a VOF model, and the specific model equation is as follows: Among them, α is the phase function; τ is the time; ρ is the density; U is the velocity; p rgh is the relative pressure; g is the acceleration due to gravity; is the surface tension term; v is the viscosity; h is the position vector of the center of the grid unit.

4. The simulation method for the under-ring lubrication oil collection process according to claim 1 is characterized in that: In step S6, the following sub-steps are also included: According to the quality of one phase of the two-phase fluid passing through the boundary of the three-dimensional flow domain grid of each geometric model, the oil recovery efficiency of the entire oil recovery process is obtained. The specific calculation formula is as follows: Among them, Efficiency is the oil recovery efficiency; M inner_outlet1 is the mass of lubricating oil passing through the inner_outlet1 boundary; M inner_outket2 is the mass of lubricating oil passing through the inner_outlet2 boundary; M inner_outlet3 is the mass of lubricating oil passing through the inner_outlet3 boundary; M Inlet is the mass of lubricating oil passing through the Inlet boundary.

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