Aircraft fuel gear pump sliding bearing oil pollution simulation method based on mixed two-phase flow
By simulating oil contamination in the sliding bearing of an aviation fuel gear pump using a mixed two-phase flow model, the problem of deviation in lubrication performance prediction in existing technologies is solved, enabling more accurate prediction of lubrication characteristics and improved adaptability to complex operating conditions, thus supporting reliable design.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-25
- Publication Date
- 2026-03-27
AI Technical Summary
Existing technologies cannot accurately describe the interphase interactions of solid-liquid two-phase flow and the interaction mechanism between contaminants and bearing material surfaces, leading to discrepancies between lubrication performance predictions and actual operating conditions.
A simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow is adopted. By establishing the control equations for the fluid and solid particle phases and performing numerical iterative solutions, the oil film pressure and particle volume fraction distribution are simulated to predict lubrication characteristics.
It improves the accuracy of lubrication performance prediction and simulation, enhances the adaptability of aviation fuel gear pumps under complex operating conditions, saves testing resources, accurately identifies lubrication failure risks, and supports the reliability design of complex lubrication systems.
Smart Images
Figure CN121744693A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of aero-engine gear pump performance modeling simulation, in particular to a simulation method for oil pollution of a sliding bearing of an aero-engine fuel gear pump based on mixed two-phase flow. BACKGROUND
[0002] The sliding bearing reliability of an aero-engine fuel gear pump directly determines the working efficiency and service life of the pump, as the pump is a core power component of the aero-engine fuel system. Under complex working conditions, solid particles and water vapor, etc. are mixed into the fuel medium due to external environmental invasion, mechanical wear or thermal decomposition reaction, etc., forming a solid-liquid two-phase mixed flow state. The presence of such pollutants not only changes the physical properties of the lubricating fluid such as viscosity and density, but also may cause problems such as surface wear, cavitation and local high temperature of the sliding bearing, leading to lubrication failure and even bearing jam.
[0003] However, the simulation research on the lubrication performance of the sliding bearing is mostly based on the setting of single-phase clean fluid, which cannot fully reflect the coupling effect of two-phase pollutants on the oil film bearing characteristics. For example, the method proposed by Liu Wei et al. in the article "Liquid-solid two-phase fluid lubrication research considering particle behavior" to directly simulate the influence of particles on the flow field, although it has the advantages of intuitive particle distribution state and clear influence on the flow field, cannot characterize the interphase action of solid-liquid two-phase flow, and is not suitable for engineering practice due to long calculation time and large calculation amount.
[0004] In summary, the main limitations of current research are as follows: first, the existing models mostly use homogeneous single-phase flow setting, which cannot accurately describe the interphase action of solid-liquid two-phase flow (such as micro-jet impact caused by bubble collapse) and the discrete motion behavior of solid particles; second, the interaction mechanism between pollutants and the surface of bearing material (such as particle deposition and local vaporization of liquid film) lacks multi-physical field coupling analysis, resulting in deviation between wear prediction and real working conditions. SUMMARY
[0005] In order to overcome the above technical problems, the present application aims to provide a simulation method for oil pollution of a sliding bearing of an aero-engine fuel gear pump based on mixed two-phase flow, which builds a lubrication characteristic prediction system under the synergistic action of solid-liquid two-phase flow by coupling computational fluid dynamics. This method aims to reveal the oil film pressure distribution and pollutant volume fraction distribution, and to provide support for pollution tolerance design and fault warning of high-reliability fuel pumps.
[0006] The technical scheme adopted by the present application is as follows: A simulation method for oil pollution of a sliding bearing of an aero-engine fuel gear pump based on mixed two-phase flow, comprising the following steps: Step 1: setting the oil pollution particles of the sliding bearing of the aero-engine fuel gear pump; Step two: according to the settings made in step one and the existing derivation, the control equation of the fluid and solid particle phase is established; Step three: for the control equation established in step two, the calculation formula of the fluid and solid particle phase is differentiated for the convenience of calculation and simulation; Step four: for the differentiated formula in step three s and f , numerical iteration is performed, the structure parameters, working condition parameters and physical property parameters are input, and the oil film thickness, pressure and particle volume fraction distribution are initialized, and the oil film pressure distribution is pre-calculated; Step five: according to the oil film pressure distribution pre-calculated in step four, the particle volume fraction distribution is calculated, if the volume fraction converges, step six is calculated; if the volume fraction does not converge, the particle volume fraction distribution is repeatedly iterated until convergence; Step six: according to the final calculated particle volume fraction distribution in step five, the calculation of the oil film pressure distribution is updated, if the updated pressure distribution converges, the oil film pressure distribution and the particle volume fraction distribution are output, and the calculation is completed; if the updated pressure distribution does not converge, step five is repeated to iteratively calculate.
[0007] The step one is specifically: Settings: 1. The particles are small enough (according to experimental experience, the particle diameter should be less than 25 microns) to show statistical characteristics on the fluid element of a single grid; 2. The particles are light enough (according to experimental experience, the particle mass should be less than 5×10 -4 mg) to move completely with the fluid; 3. The fluid and particles have no slip on the solid ground.
[0008] The step two is specifically: The control equation of the fluid and solid particle phase is established: Wherein, is the equivalent viscosity of the particle ( ); is the oil film thickness distribution; is the volume fraction of particles in the fluid, which requires ; ; ; ; is the velocity ratio coefficient; f is the fluid phase calculation formula, s is the solid particle phase calculation formula.
[0009] The step three is specifically: (1) for the fluid phase: f: but: in: , , (2) For the solid phase: s : but: in: ;in, U The linear velocity of the bearing rotation; These are the dimensions of the circumferential and axial grids, respectively. Particle equivalent viscosity ( ); Oil film thickness distribution; Given the volume percentage of particulate matter in a fluid, the requirement is... ; ; ; ; This is the speed ratio coefficient; f This is the formula for calculating fluid phases. s This is the formula for calculating the solid particulate phase.
[0010] Step four specifically involves: For the difference obtained in step three s and f The formula is used for numerical iteration, and the oil film pressure distribution is calculated using the successive over-relaxation (SOR) method. The relative error of the newly calculated pressure distribution is then determined. The calculation method is as follows: in, The three steps are respectively the first step. k Second and third k- The pressure field obtained from one iteration, if the relative error If the value is less than the threshold given by the user, the result is considered converged and the pressure distribution is saved as the pre-calculated result before proceeding to the next step.
[0011] Step five specifically involves: Based on the oil film pressure distribution pre-calculated in step four, calculate the particle volume fraction distribution. If the volume fraction converges, proceed to step six; if the volume fraction does not converge, repeat the iterative calculation of the particle volume fraction distribution until convergence. The method for determining volume fraction convergence is as follows: in, The three steps are respectively the first step. k Second and third k- The volume fraction field obtained from one iteration, if the relative error If the value is less than the threshold given by the user, it is considered to have converged and proceeds to the next step.
[0012] Step six specifically involves: Based on the particle volume fraction distribution calculated in step five, substitute it into... f The oil film pressure distribution is updated. If the relative error between the updated pressure distribution and the pre-calculated pressure distribution in step four is within the allowable range, the oil film pressure distribution and particle volume fraction distribution are output to complete the calculation. If the updated pressure distribution does not meet the relative error, step five iterative calculation is repeated.
[0013] The beneficial effects of this invention are: Compared with traditional methods that only use a single-phase flow model, the mixed two-phase flow method used in this invention has significant advantages.
[0014] On the one hand, this method can simulate more realistic physical processes of contamination and improve the accuracy of lubrication performance prediction; on the other hand, by iteratively calculating the fluid and solid fields in steps four and five, this method improves the adaptability of aviation fuel gear pumps to complex operating conditions and provides a more scientific and efficient approach to contamination calculation of sliding bearings.
[0015] Furthermore, this method replaces part of the full-life test with computational simulation, saving test resources and accurately identifying the risk of lubrication failure caused by oil contamination. It significantly improves the simulation accuracy and engineering applicability of sliding bearings of aerospace gear pumps under oil contamination conditions, providing more comprehensive technical support for the reliability design of complex lubrication systems. It has great practical value and broad application prospects. Attached Figure Description
[0016] Figure 1 Flowchart of the oil film lubrication simulation method that takes into account oil contamination.
[0017] Figure 2 This is a schematic diagram of oil film pressure and particle volume fraction distribution. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] like Figure 1 As shown, the main technology employed in this invention is an oil film lubrication simulation method that takes into account oil contamination. Its basic principle is summarized below: To achieve the above objectives, the present invention provides the following technical approach: Step 1: Set parameters for oil contamination particles in the sliding bearing of the aviation fuel gear pump; The first step is as follows: set up: 1. The particles are small enough that their influence on the fluid micro-elements of a single grid exhibits statistical characteristics.
[0020] 2. The particles are light enough to move entirely with the fluid.
[0021] 3. Neither the fluid nor the particles slip on the solid ground.
[0022] Step 2: Establish the governing equations for the fluid and solid particle phases based on existing derivations; The second step is specifically as follows: The governing equations for both fluid and solid particle phases are established: in, Particle equivalent viscosity ( ); Oil film thickness distribution; Given the volume percentage of particulate matter in a fluid, the requirement is... ; ; ; ; This is the speed ratio coefficient; f This is the formula for calculating fluid phases. s This is the formula for calculating the solid particulate phase.
[0023] Step 3: To facilitate calculation and simulation, the calculation formulas for fluid and solid particle phases are finite. Step three specifically refers to: (3) For the fluid phase: f : but: in: , , (4) For the solid phase: s : but: in: .
[0024] Step Four: For s and f The formula is solved numerically through iteration. Structural parameters, operating parameters, and physical property parameters are input, and oil film thickness, pressure, and particle volume fraction distribution are initialized. The oil film pressure distribution is pre-calculated.
[0025] Step 5: Calculate the particle volume fraction distribution based on the oil film pressure distribution. If the volume fraction converges, proceed to Step 6. If the volume fraction does not converge, repeat the iterative calculation of the particle volume fraction distribution until convergence.
[0026] Step 6: Update the calculation of oil film pressure distribution based on particle volume fraction distribution. If the updated pressure distribution converges, output the oil film pressure distribution and particle volume fraction distribution to complete the calculation. If the updated pressure distribution does not converge, repeat step 5 iterative calculation.
[0027] Experimental Example: The advantages of this invention can be further illustrated by the following simulation experiments: 1. Simulation parameters To demonstrate the accuracy and reliability of this simulation prediction method, a set of key parameters of a fuel gear pump under a specific load spectrum were selected for simulation. The basic parameters of a certain type of bearing targeted in this study are shown in Table 1. The working medium is RP-3 aviation fuel, and the surface coating is molybdenum disulfide.
[0028] Table 1 Main parameters of sliding bearings
[0029] 2. Simulation Results The simulation results obtained by iterative calculation based on the parameters in Table 1 are as follows: Figure 2 As shown.
[0030] 3. Results Analysis Conclusion 1: Through Figure 2 Comparing the simulated pressure distribution results in the left figure with the actual experimental results, it was found that the relative error between the simulated pressure values and the experimental values at each sample point was about 5%, which is within the range of the experimental results. The accuracy of the pressure field simulation model of the oil film lubrication simulation model under oil contamination conditions was verified. Conclusion 2: Through Figure 2 Comparing the simulation results of particle volume fraction distribution in the right figure with the theoretical analysis results, it was found that the contaminant particles in the oil film are mainly concentrated in the low-speed region, that is, the region with low pressure change in the left figure. The simulation results meet the theoretical requirements, and the accuracy of particle field simulation of oil film lubrication simulation model under oil contamination conditions has been verified. Conclusion 3: By simulating the sliding bearing of an aviation fuel gear pump under actual operating conditions, the location of severe bearing wear can be predicted based on particle distribution, and further, the expected life of the sliding bearing can be predicted. This means that the method of this patent has applications in predicting the life of aviation fuel gear pump sliding bearings and guiding condition-based maintenance, thus verifying the effectiveness and practicality of the method proposed in this patent.
Claims
1. A simulation method for oil contamination in sliding bearings of aviation fuel gear pumps based on mixed two-phase flow, characterized in that, Includes the following steps; Step 1: Set parameters for oil contamination particles in the sliding bearing of the aviation fuel gear pump; Step 2: Based on the settings made in Step 1 and the existing derivations, the governing equations for the fluid and solid particle phases are established. Step 3: For the governing equations established in Step 2, perform finite difference calculations on the fluid and solid particle phases; Step 4: For the difference obtained in Step 3 s and f The formula is used to perform numerical iteration and solve the problem. The structural parameters, operating parameters and physical property parameters are input and the oil film thickness, pressure and particle volume fraction distribution are initialized. The oil film pressure distribution is pre-calculated. Step 5: Based on the oil film pressure distribution pre-calculated in Step 4, calculate the particle volume fraction distribution. If the volume fraction converges, proceed to Step 6; if the volume fraction does not converge, repeat the iterative calculation of the particle volume fraction distribution until convergence. Step 6: Based on the particle volume fraction distribution finally calculated in Step 5, update the calculated oil film pressure distribution. If the updated pressure distribution converges, output the oil film pressure distribution and particle volume fraction distribution to complete the calculation; if the updated pressure distribution does not converge, repeat Step 5 iterative calculation.
2. The simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow as described in claim 1, characterized in that, The first step is as follows: set up: (1) The particle diameter should be less than 25 micrometers so that its influence on the fluid micro-elements of a single grid exhibits statistical characteristics; (2) The particle mass should be less than 5×10 -4 Milligrams, allowing them to move entirely with the fluid; (3) Neither the fluid nor the particles slipped on the solid ground.
3. The simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow as described in claim 1, characterized in that, The second step is specifically as follows: The governing equations for both fluid and solid particle phases are established: in, Particle equivalent viscosity ( ); Oil film thickness distribution; Given the volume percentage of particulate matter in a fluid, the requirement is... ; ; ; ; This is the speed ratio coefficient; f This is the formula for calculating fluid phases. s This is the formula for calculating the solid particulate phase.
4. The simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow as described in claim 1, characterized in that, The third step is specifically as follows: (1) For the fluid phase: f : but: in: , , (2) For the solid phase: s : but: in: ;in, U The linear velocity of the bearing rotation; These are the dimensions of the circumferential and axial grids, respectively. Particle equivalent viscosity ( ); Oil film thickness distribution; Given the volume percentage of particulate matter in a fluid, the requirement is... ; ; ; ; This is the speed ratio coefficient; f This is the formula for calculating fluid phases. s This is the formula for calculating the solid particulate phase.
5. The simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow as described in claim 1, characterized in that, Step four specifically involves: For the difference obtained in step three s and f The formula is used for numerical iteration, and the oil film pressure distribution is calculated using the successive over-relaxation method. The relative error of the newly calculated pressure distribution is then determined. The calculation method is as follows: in, The three steps are respectively the first step. k Second and third k- The pressure field obtained from one iteration, if the relative error If the value is less than the threshold given by the user, the result is considered converged and the pressure distribution is saved as the pre-calculated result before proceeding to the next step.
6. The simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow as described in claim 1, characterized in that, Step five specifically involves: Based on the oil film pressure distribution pre-calculated in step four, calculate the particle volume fraction distribution. If the volume fraction converges, proceed to step six; if the volume fraction does not converge, repeat the iterative calculation of the particle volume fraction distribution until convergence. The method for determining volume fraction convergence is as follows: in, The three steps are respectively the first step. k Second and third k- The volume fraction field obtained from one iteration, if the relative error If the value is less than the threshold given by the user, it is considered to have converged and proceeds to the next step.
7. The simulation method for oil contamination in the sliding bearing of an aviation fuel gear pump based on mixed two-phase flow as described in claim 1, characterized in that, Step six specifically involves: Based on the particle volume fraction distribution calculated in step five, substitute it into... f The oil film pressure distribution is updated. If the relative error between the updated pressure distribution and the pre-calculated pressure distribution in step four is within the allowable range, the oil film pressure distribution and particle volume fraction distribution are output to complete the calculation. If the updated pressure distribution does not meet the relative error, step five iterative calculation is repeated.