A method for predicting solid-liquid two-phase flow erosion life of submersible electric pump under wide flow condition

Abstract

The present application relates to a kind of solid-liquid two-phase flow erosion life prediction method of submersible electric pump wide flow condition, it includes: constructing the full parameterization fluid domain grid model of submersible electric pump impeller guide vane;Set wide flow discrete working condition sequence, obtain the unsteady flow field data under the multiple discrete flow working condition section covered to;By constructing the two-way coupling discrete phase-turbulent two-phase flow model coupled Saffman lift correction, extract the transient parameter when particle impact impeller guide vane wall;Flow correlation dynamic hardness index function is built;Determine the instantaneous erosion rate of each working condition section in combination with Saffman lift correction factor;Obtain the total erosion damage degree of each node on impeller guide vane wall after experiencing total flow working condition section;The erosion life of impeller guide vane and each sub-region is predicted.The present application introduces flow correlation dynamic hardness index and dynamic velocity index, and reduces the simulation prediction error of erosion rate under variable condition to 12% or less from more than 30% of traditional method.

Description

Technical Field

[0001] This invention relates to the field of marine oil and gas equipment technology, specifically a method for predicting the erosion life of key components of submersible electric pumps used in deep-sea oil production platforms under wide flow variation conditions and solid-liquid two-phase flow conditions. Background Technology

[0002] Submersible electric pumps (ESPs) are the core artificial lift equipment for deep-sea oil and gas extraction, often referred to as the "heart" of offshore oil fields. Their key flow components, such as impellers, endure long-term high sand content (0.05%~2%, particle size ≤0.1mm), severe corrosion, and drastic production fluctuations (flow rate fluctuations can reach the design flow rate) during service. Under harsh working conditions (such as 0.4 to 1.4 times the normal operating temperature), erosion and wear are the main causes of failure. This application was supported by the Zhejiang Provincial Marine Industry Science and Technology Project (NO.2026HYC03007).

[0003] Currently, the prediction of erosion life of submersible electric pumps mainly faces the following technical bottlenecks: (1) Poor adaptability to operating conditions: Existing prediction methods are mostly based on fixed operating conditions (such as design flow rate). Empirical formulas or simplified numerical simulations based on existing methods cannot accurately assess the nonlinear impact of wide flow rate fluctuations caused by natural well production decline or operational measures on erosion rates. When the flow rate deviates from the design point, the flow field shear rate, particle trajectory, and collision angle all change significantly, and the prediction error of conventional methods typically exceeds 30%.

[0004] (2) Insufficient consideration of material properties: Existing erosion models (such as Finnie model, Oka model, E / CRC model) lack consideration of material-related parameters (such as velocity index). Hardness index The constant is usually considered to be a constant. However, for materials with significant strain hardening characteristics, such as low-nickel high-nitrogen duplex stainless steel (nickel content <6%, hardness >220HB) developed in the project, their erosion resistance exhibits complex nonlinear characteristics as the flow rate changes, and the constantization process leads to a significant decrease in prediction accuracy.

[0005] (3) Lack of multi-scale coupling mechanism: Traditional prediction methods have failed to effectively link micro-particle collision dynamics with macro-erosion damage evolution. In particular, under wide flow conditions, the triple interaction of particles-vortex-boundary layer in the near-wall region leads to an abnormal increase in local erosion rate, and existing single-phase flow or simplified Euler-Euler multiphase flow models cannot capture this cross-scale effect.

[0006] (4) Disconnect between calculation and verification: Fully coupled Navier-Stokes equation-DEM simulation consumes huge computational resources and is difficult to be directly applied to engineering iterative design; while pure empirical formulas lack specificity for specific materials and working conditions.

[0007] Therefore, there is an urgent need to develop a method for predicting erosion life that can accurately reflect the characteristics of wide flow conditions, finely consider the dynamic mechanical response of low-nickel and high-nitrogen duplex stainless steel, and take into account both computational efficiency and engineering practicality. Summary of the Invention: The purpose of this invention is to provide a method for predicting the erosion life of a submersible electric pump under wide flow conditions in a solid-liquid two-phase flow. This method addresses the problems of low prediction accuracy and inability to accurately quantify the erosion suppression effect of dynamic material hardening under varying operating conditions in traditional methods. It provides technical support for the reliability assessment and erosion-resistant optimization design of high-efficiency, wide-flow submersible electric pumps used in deep-sea oil production platforms.

[0008] The technical solution adopted by this invention to solve its technical problem is as follows: This method for predicting the erosion life of a submersible electric pump under wide flow conditions in solid-liquid two-phase flow includes the following steps: Step 1: Construct a fully parameterized fluid domain mesh model of the submersible electric pump impeller; Step 2: Set up a wide-flow discrete operating condition sequence to obtain the data covering... to Unsteady flow field data under multiple discrete flow conditions, including Design traffic; Step 3: By constructing a two-way coupled discrete phase-turbulent two-phase flow model with Saffman lift correction, the transient parameters of particles impacting the impeller wall are extracted, including collision velocity, impact angle, local shear rate near the wall, and particle mass concentration. Step 4: Construct a dynamic hardness index function for flow correlation. ; Step 5: Determine the instantaneous erosion rate for each operating condition by combining the Saffman lift correction factor. ; Step Six: Based on Miner's linear accumulation rule, calculate the cumulative erosion damage of the impeller over a wide flow range, and obtain the cumulative erosion damage of each node on the impeller wall after experiencing all [the following conditions]. Total erosion damage after each flow rate operating period L ; Step 7: Predict the erosion life of the blade guide vane and its sub-regions, and assign differentiated safety factor weights to different sub-regions of the blade guide vane: the safety factor threshold is... S f, Leading edge area of ​​the blade =1.0, leaf back edge =1.1~1.3, hub transition zone =1.2~1.5, when L x S f When ≥1, the region is determined to have reached the end of its lifespan; when damaged... L x S f When the value is less than 1, it indicates that the area is in a safe service period. The predicted total lifespan is: current cumulative operating days / total damage level.

[0009] Step one of the above scheme is specifically as follows: A three-dimensional parametric model of the blade guide wheel is constructed based on NURBS surface. The blade wrap angle, inlet and outlet placement angle and flow channel contraction rate are used as geometric design variables to generate high-quality structured or hybrid meshes. Boundary layer meshes are refined for the near-wall region.

[0010] Step two in the above scheme is specifically as follows: Based on historical or predicted production profile data of the target oil well, extract the flow rate fluctuation range. Discretize the range into Characteristic flow condition segment And determine the duration of each working condition segment. Meanwhile, solid phase parameters are set, including sand content of 0.05% to 2%, particle size distribution, and density.

[0011] Step three in the above scheme is: The bidirectional coupled solver of the coupled discrete phase-turbulence model is invoked to calculate the motion parameters of the particle phase based on the unsteady flow field data, and the transient collision velocities of the particles in the near-wall region of the impeller are extracted. and the angle of impact The particle-fluid interaction force in the bidirectional coupled solver includes a Saffman lift correction term associated with the shear rate variation under wide flow conditions. The Saffman lift correction term introduces a particle lateral migration correction force associated with the wall shear rate, resulting in a bidirectional coupled discrete phase-turbulent two-phase flow model with Saffman lift correction.

[0012] The above scheme utilizes a bidirectional coupled solver that invokes the coupled discrete phase-turbulence model, including: The continuous phase is described using Euler, and the Navier-Stokes equations are solved in combination with... Turbulence model; The discrete phase is described using Lagrange, and the particle motion trajectory is tracked through the discrete phase model. The particle-fluid interaction forces include drag, virtual mass force, and pressure gradient force. Additionally, a Saffman lift term is introduced based on the velocity gradient field under the wide flow rate conditions, and the coefficient of the Saffman lift term varies with the flow rate conditions. Dynamic adjustment.

[0013] Furthermore, step three in the above plan specifically involves: An Eulerian-Lagrange framework is adopted, with the continuous phase (liquid phase) solved using the Navier-Stokes equations and turbulence model in Eulerian coordinates; the discrete phase (solid particles) is tracked using a discrete phase model in Lagrange coordinates. To achieve bidirectional coupling, within each time step: (1) The CFD solver transmits local flow field velocity, vorticity and shear strain rate to the discrete phase model; (2) The discrete model calculates the drag force, pressure gradient force and virtual mass force on the particles, and introduces the Saffman lift correction term associated with the velocity gradient field under wide flow conditions to accurately simulate the lateral migration and aggregation behavior of particles in the strong shear near-wall region. (3) The discrete phase model feeds back the momentum source term of the particles to the Navier-Stokes equation solver to correct the turbulent structure of the flow field; Through the above coupled solution, transient parameters of the particle impacting the impeller wall are extracted, including the collision velocity. Impact angle Near-wall local shear rate and particle mass concentration .

[0014] Step four in the above scheme is specifically as follows: To address the strain hardening characteristics of low-nickel, high-nitrogen duplex stainless steel, a hardness index was established. Operating conditions with flow rate The dynamic functional relationship is expressed as follows: ; in: The reference hardness index, calibrated by erosion tests at the design flow rate, is taken as 0.6~0.8. To be related to the material strain hardening index The adjustment coefficient, which is positively correlated, determines the sensitivity of the material to strain hardening, and its value ranges from 0.15 to 0.35. Characterizing the physical mechanism by which changes in flow field shear force drive the evolution of the hardened layer on the material surface when the flow rate deviates from the design flow rate, thereby affecting the hardness erosion suppression efficiency, i.e., the sensitivity of material hardness to the dynamic response of flow rate changes.

[0015] Step five in the above scheme is specifically as follows: Based on the collision parameters extracted in step three and the dynamic hardness index constructed in step four, the instantaneous erosion rate is calculated. : ; In the formula: The correction factor is the reference material. It is a dynamic velocity exponential function; The measured hardness of low-nickel, high-nitrogen duplex stainless steel. For reference hardness; This is the Saffman lift correction factor; For the first i Near-wall shear rate under various working conditions; To introduce material yield strength Corrected impact angle function; In the above scheme satisfy: ; in: The baseline velocity index under design flow conditions This represents the amplitude of the velocity exponent change, ranging from 0.3 to 0.5. This is the exponential decay coefficient, with a value ranging from 0.8 to 1.2; The piecewise function form is used, fitted based on the erosion experimental data of the low-nickel, high-nitrogen duplex stainless steel, and the impact angle corresponding to the peak erosion rate is given. Located within interval c; ; ; In the formula: All constant coefficients are obtained by fitting the erosion test data of the low-nickel high-nitrogen duplex stainless steel. The yield strength of the low-nickel, high-nitrogen duplex stainless steel is 460–500 MPa. For reference yield strength; satisfy: ; in: For the first i Near-wall shear rate under various working conditions; For reference shear rate; The lift effect coefficient ranges from 0.05 to 0.15. The shear rate exponent has a value range of 0.5 to 0.8.

[0016] Step six in the above scheme is specifically as follows: Using Miner's linear accumulation rule, the calculation of each node on the impeller wall after experiencing all [the following conditions] is performed. Total erosion damage after each flow rate operating period : ; in, For instantaneous erosion rate Under the action, the time required for the wall surface to reach the critical erosion depth. The critical erosion depth is determined based on the design wall thickness margin of the blade guide vane. 30% to 50% of the minimum cross-sectional wall thickness of the blade is taken as the judgment threshold, or the specific value is determined based on the structural strength safety margin of the blade and engineering experience. For the first The actual running time of each flow condition segment. Beneficial effects

[0017] 1. This invention significantly improves prediction accuracy: by introducing a dynamic hardness index related to flow rate. and dynamic speed index Through comparison and verification with bench erosion test data, the simulation prediction error of erosion rate under variable working conditions has been reduced from more than 30% in the traditional method to less than 12%.

[0018] 2. The physical mechanism of this invention is profoundly revealed: For the first time, the Saffman lift correction factor is explicitly introduced into the erosion prediction model. It accurately captures the modulation effect of shear rate variation on particle near-wall aggregation and collision frequency under wide flow conditions.

[0019] 3. The material of this invention is highly targeted: it is specifically designed for low-nickel, high-nitrogen duplex stainless steel, and its yield strength is [highly targeted / targeted]. The data were coupled to the impact angle function, and the logarithmic variation law of the hardness index with the flow rate was established, filling the technical gap of this new material system in the field of wide flow rate erosion assessment.

[0020] 4. The invention has good engineering practicality: By constructing a discrete working condition sequence and the Miner cumulative rule, the huge computational overhead of full-cycle transient simulation is avoided, and it can be directly used for life assessment and pump inspection cycle optimization in oilfields.

[0021] 5. To address the issues of large prediction errors in traditional erosion prediction methods under wide flow range fluctuations (0.4 to 1.4 times the design flow rate) and the failure to consider the dynamic hardening effect of low-nickel, high-nitrogen duplex stainless steel, this invention constructs a two-way coupled discrete-turbulent two-phase flow model with Saffman lift correction. This model extracts the collision velocity, impact angle, and near-wall shear rate of particles in the near-wall region of the impeller guide vane. It establishes a hardness exponential function and a velocity exponential function that dynamically change with flow rate conditions, and calculates the instantaneous erosion rate for each operating condition using the Saffman lift correction factor. Based on the Miner linear accumulation rule, it obtains the total erosion damage and predicted erosion life of the impeller guide vane over a wide flow range. This invention can be used for life assessment and erosion-resistant optimization design of key components of submersible electric pumps on deep-sea oil production platforms. Attached image description: Figure 1 This is the overall flowchart of the present invention. Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings: This method for predicting the erosion life of a submersible electric pump under wide flow conditions in solid-liquid two-phase flow: Construct a fluid domain mesh model of the submersible electric pump impeller and obtain the fluid domain mesh model covering the impeller. to Unsteady flow field data under multiple discrete flow conditions, including Design traffic; The bidirectional coupled solver of the coupled discrete phase-turbulence model is invoked to calculate the motion parameters of the particle phase based on the unsteady flow field data, and the transient collision velocities of the particles in the near-wall region of the impeller are extracted. and the angle of impact The particle-fluid interaction force in the bidirectional coupled solver includes a Saffman lift correction term associated with shear rate variation under wide flow conditions, which introduces a particle lateral migration correction force related to the wall shear rate. Based on the yield strength of low-nickel high-nitrogen duplex stainless steel Compared with the measured hardness Build and traffic conditions Associated dynamic hardness index function and dynamic velocity exponential function And based on the dynamic hardness exponent function The dynamic velocity exponential function The transient collision velocity The impact angle and near-wall shear rate Associated Saffman lift correction factor Determine the instantaneous erosion rate for each of the aforementioned flow conditions. The instantaneous erosion rate and Proportional and with Proportional; Instantaneous erosion rate corresponding to the multiple flow rate segments The total erosion damage at the blade guide vane wall node is obtained by performing a weighted summation of cumulative damage. and in the total erosion damage When the value is greater than or equal to the preset threshold of 1, the predicted erosion life of the output blade guide wheel is calculated.

[0023] This method for predicting the erosion life of a submersible electric pump under wide flow conditions in solid-liquid two-phase flow includes the following steps: Step 1: Construct a fully parameterized fluid domain mesh model of the submersible electric pump impeller; A three-dimensional parametric model of the guide vane is constructed based on NURBS surface. The blade wrap angle, inlet and outlet placement angle, and flow channel contraction rate are used as geometric design variables to generate a high-quality structured or hybrid mesh. Boundary layer mesh is refined for the near-wall region to meet the wall resolution requirements of the turbulence model.

[0024] Step 2: Set up a wide-flow discrete operating condition sequence; Based on historical or predicted production profile data of the target oil well, extract the flow rate fluctuation range. ( To design the flow rate), discretize the range into Characteristic flow condition segment And determine the duration of each working condition segment. Simultaneously, solid phase parameters were set, including sand content of 0.05%~2%, particle size distribution, and density.

[0025] Step 3: Perform bidirectional coupled calculations of the discrete phase-turbulence model based on Saffman lift correction.

[0026] The continuous phase is described using Euler, and the Navier-Stokes equations are solved in combination with... Turbulence model; The discrete phase is described using Lagrange, and the particle motion trajectory is tracked through the discrete phase model. In addition to drag, virtual mass force, and pressure gradient force, the particle-fluid interaction force also incorporates a Saffman lift term based on the velocity gradient field under the wide flow rate conditions. The coefficient of the Saffman lift term varies with the flow rate conditions. Dynamic adjustment.

[0027] Using an Eulerian-Lagrange framework, the continuous phase (liquid phase) is solved using the Navier-Stokes equations and turbulence model in Eulerian coordinates; the discrete phase (solid particles) is tracked using a discrete phase model in Lagrange coordinates. To achieve bidirectional coupling, within each time step: (1) The CFD solver transmits local flow field velocity, vorticity and shear strain rate to the discrete phase model; (2) The discrete model calculates the drag force, pressure gradient force and virtual mass force on the particles, and introduces the Saffman lift correction term associated with the velocity gradient field under wide flow conditions to accurately simulate the lateral migration and aggregation behavior of particles in the strong shear near-wall region. (3) The discrete phase model feeds back the momentum source term of the particles to the Navier-Stokes equation solver to correct the turbulent structure of the flow field.

[0028] Through the above coupled solution, transient parameters of the particle impacting the impeller wall are extracted, including the collision velocity. Impact angle Near-wall local shear rate and particle mass concentration .

[0029] Step 4: Construct a dynamic hardness index function for traffic correlation ; To address the strain hardening characteristics of low-nickel, high-nitrogen duplex stainless steel, a hardness index was established. Operating conditions with flow rate The dynamic function relationship. The specific expression is: ; in: The reference hardness index (usually 0.6~0.8) is determined by erosion test under the design flow rate. To be related to the material strain hardening index The adjustment coefficient, which shows a positive correlation, determines the material's sensitivity to strain hardening, and its value ranges from 0.15 to 0.35. This represents the current traffic.

[0030] This function This study characterizes the physical mechanism by which changes in flow field shear force drive the evolution of the hardened layer on the material surface when the flow rate deviates from the design flow rate, thereby affecting the hardness erosion suppression efficiency; that is, the sensitivity of material hardness to the dynamic response of flow rate changes.

[0031] Step 5: Determine the instantaneous erosion rate for each flow rate section. ; Based on the collision parameters extracted in step three and the dynamic hardness index constructed in step four, the instantaneous erosion rate is calculated. The aforementioned The following relationships must be satisfied: ; In the formula: —Instantaneous erosion rate, mm / year; — is the correction factor for the reference material; — represents the particle mass concentration; —For reference hardness, the hardness value calibrated at the design flow rate is usually taken; —Measured hardness of low-nickel, high-nitrogen duplex stainless steel; The instantaneous erosion rate Collision speed with particles The velocity is proportional to the exponential power of the velocity, and is related to the impact angle function. Proportional to, and relative to hardness of It is inversely proportional to the power and also related to the Saffman lift correction factor. Proportional; wherein, the speed index is the flow rate under operating conditions. function The impact angle function Yield strength of the low-nickel, high-nitrogen duplex stainless steel Correction items; This is the Saffman lift correction factor, used to correct the effect of particles on the erosion rate when subjected to fluid shear in the near-wall region; — is the dynamic velocity exponential function, expressed as .in, To design the baseline velocity index under flow conditions, This represents the amplitude of the velocity exponent change, ranging from 0.3 to 0.5. This is the exponential decay coefficient, with a value ranging from 0.8 to 1.2; — is the Saffman lift correction factor, expressed as .in, λ is the lift influence coefficient, ranging from 0.05 to 0.15, which controls the overall contribution intensity of Saffman lift to the erosion rate. The larger λ is, the more obvious the enhancing effect of shearing on erosion. It is usually determined by back-calculation through erosion test data or by referring to empirical values ​​of similar working conditions. The shear rate exponent is 0.5 to 0.8, which controls the degree of nonlinear growth of the correction factor as the shear rate increases. — is a "shear amplification factor" that makes the predicted erosion rate higher than that of conventional models when the flow velocity near the wall changes drastically, in order to reflect the actual physical process by which Saffman lift "pushes" particles toward the wall or changes the impact angle. —The ratio within the parentheses is a pure number, serving as a reference shear rate; —for the first i Near-wall shear rate under various working conditions; —To introduce material yield strength The corrected impact angle function adopts a piecewise function form fitted based on the erosion experimental data of the low-nickel high-nitrogen duplex stainless steel. The impact angle corresponding to its peak value is located in the range of 25°~40°. The calculation formula of the impact angle function is as follows: ; ; in, These are the constant coefficients obtained by fitting the erosion test data of the low-nickel, high-nitrogen duplex stainless steel. The actual strength of the material is as described above, specifically referring to the yield strength of the low-nickel, high-nitrogen duplex stainless steel, which ranges from 460 to 500 MPa. The reference yield strength (a benchmark value for dimensionless measurement) is usually taken as the typical yield strength of the material in the standard state (such as annealed state, room temperature, quasi-static tension); or the yield strength of the material under experimental calibration at the design flow rate.

[0032] Step Six: Calculation of cumulative erosion damage over a wide flow range; Using Miner's linear accumulation rule, the calculation of each node on the impeller wall after experiencing all [the following conditions] is performed. Total erosion damage after each flow rate operating period : ; in, For instantaneous erosion rate The time required for the wall surface to reach the critical erosion depth under the influence of the action. The critical erosion depth is usually determined based on the design wall thickness margin of the blade guide vane. Generally, 30% to 50% of the minimum cross-sectional wall thickness of the blade is taken as the judgment threshold, but it can also be specifically set based on the results of structural integrity analysis.

[0033] To improve engineering practicality, differentiated safety factor weights are set for different sub-regions of the blade guide vane: safety factor threshold for the leading edge region of the blade. =1.0, leaf back edge =1.1~1.3, hub transition zone =1.2~1.5. When the corrected damage degree When that time comes, the region is determined to have reached the end of its lifespan.

[0034] Step 7: Output Predicted Lifetime and Engineering Applications Predicted erosion life of the entire guide vane and its sub-regions (when hour).

[0035] This method can be directly applied to life assessment and pump inspection cycle optimization in oilfields. As an extended application, the prediction results can be further used to guide erosion-resistant optimization design (e.g., using genetic algorithms or particle swarm optimization to optimize impeller geometry parameters with the goal of minimizing the weighted average erosion rate over a wide flow range). Example

[0036] Erosion life prediction of the impeller guide of a submersible electric pump in a deep-sea oilfield (1) Basic parameter settings Impeller design flow rate .

[0037] Material: Low-nickel, high-nitrogen duplex stainless steel, containing 5.0% nickel, 23.5% chromium, 3.0% molybdenum, and 0.25% nitrogen by weight, with the balance being iron. Actual hardness measured. =235 Yield strength =480 .

[0038] Solid phase parameters: sand content 0.8%, median particle size =0.075 .

[0039] The critical erosion depth is set at 2.0. .

[0040] (2) Division of operating condition sequence Based on oilfield production data, the flow fluctuations within the forecast period are divided into four typical operating conditions:

[0041] (3) Determination of dynamic exponential function Based on the erosion test calibration of low-nickel, high-nitrogen duplex stainless steel, the reference hardness index is taken. =0.72, adjustment coefficient =0.22, then the dynamic hardness exponent function is: ; Calculations for each working condition They are respectively: 0.597 (0.4) ),0.678(0.7 ),0.72(1.0 ), 0.769 (1.4 ).

[0042] Baseline speed index =2.2, =0.4, =1.0, speed index for each operating condition The corresponding calculations.

[0043] (4) Navier-Stokes-DEM Coupled Simulation and Parameter Extraction Call the Navier-Stokes-DEM coupling platform and set the Saffman lift correction term as described in step three. =0.1, =0.6). The simulation results extract the average parameters of the leading edge region (the most severely worn area) of the impeller: average collision velocity. From 8.2 (0.4) (increased to 15.8) (1.4) ).

[0044] Main impact angle It is distributed between 28° and 35°.

[0045] Near-wall mean shear rate It increases approximately fourfold with the increase in traffic.

[0046] (5) Calculation of instantaneous erosion rate and cumulative damage Calculate the instantaneous erosion rate for each working condition using the formula in step five. : ; Each working condition section The time required to independently reach the critical erosion level is not the actual operating time.

[0047] Calculate the total damage (Taking the leading edge region safety factor) =1.0): ; The component has been in operation for 210 days, and the total damage level is far less than 1, indicating that it is within its safe service life. Based on linear extrapolation of the current erosion rate, the predicted total lifespan is approximately: Days (approximately 34 years); The above prediction results are based on the assumption that the operating condition sequence repeats periodically within the prediction period. In practical applications, the production profile data should be updated regularly to correct the prediction values, and the prediction error should be within ±15%.

[0048] This invention's method can be integrated into marine oil and gas equipment design software platforms or oilfield digital operation and maintenance systems for the selection, design, life assessment, and predictive maintenance of submersible electric pumps. The required computing resources can be met by a conventional engineering workstation, demonstrating significant value for industrial application.

Claims

1. A method for predicting the erosion life of a submersible electric pump under wide flow conditions in solid-liquid two-phase flow, characterized in that... Includes the following steps: Step 1: Construct a fully parameterized fluid domain mesh model of the submersible electric pump impeller; Step 2: Set up a wide-flow discrete operating condition sequence to obtain the data covering... to Unsteady flow field data under multiple discrete flow conditions, including Design traffic; Step 3: By constructing a two-way coupled discrete phase-turbulent two-phase flow model with Saffman lift correction, the transient parameters of particles impacting the impeller wall are extracted, including collision velocity, impact angle, local shear rate near the wall, and particle mass concentration. Step 4: Construct a dynamic hardness index function for flow correlation. ; Step 5: Determine the instantaneous erosion rate for each operating condition by combining the Saffman lift correction factor. ; Step Six: Based on Miner's linear accumulation rule, calculate the cumulative erosion damage of the impeller over a wide flow range, and obtain the cumulative erosion damage of each node on the impeller wall after experiencing all [the following conditions]. Total erosion damage after each flow rate operating period L ; Step 7: Predict the erosion life of the blade guide vane and its sub-regions, and assign differentiated safety factor weights to different sub-regions of the blade guide vane: the safety factor threshold is... S f, Leading edge area of ​​the blade =1.0, leaf back edge =1.1~1.3, hub transition zone =1.2~1.5, when L x S f When ≥1, the region is determined to have reached the end of its lifespan; when damaged... L x S f When the value is less than 1, it indicates that the area is in a safe service period; the predicted total lifespan is: current cumulative operating days / total damage level.

2. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 1, characterized in that: Step one specifically involves: A three-dimensional parametric model of the blade guide wheel is constructed based on NURBS surface. The blade wrap angle, inlet and outlet placement angle and flow channel contraction rate are used as geometric design variables to generate high-quality structured or hybrid meshes. Boundary layer meshes are refined for the near-wall region.

3. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 2, characterized in that: Step two specifically involves: Based on historical or predicted production profile data of the target oil well, extract the flow rate fluctuation range. Discretize the range into Characteristic flow condition segment And determine the duration of each working condition segment. Meanwhile, solid phase parameters are set, including sand content of 0.05% to 2%, particle size distribution, and density.

4. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 3, characterized in that: Step three is as follows: The bidirectional coupled solver of the coupled discrete phase-turbulence model is invoked to calculate the motion parameters of the particle phase based on the unsteady flow field data, and the transient collision velocities of the particles in the near-wall region of the impeller are extracted. and the angle of impact The particle-fluid interaction force in the bidirectional coupled solver includes a Saffman lift correction term associated with the shear rate variation under wide flow conditions. The Saffman lift correction term introduces a particle lateral migration correction force associated with the wall shear rate, resulting in a bidirectional coupled discrete phase-turbulent two-phase flow model with Saffman lift correction.

5. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 4, characterized in that: The bidirectional coupled solver that invokes the coupled discrete phase-turbulence model includes: The continuous phase is described using Euler, and the Navier-Stokes equations are solved in combination with... Turbulence model; The discrete phase is described using Lagrange, and the particle motion trajectory is tracked through the discrete phase model. The particle-fluid interaction forces include drag, virtual mass force, and pressure gradient force. Additionally, a Saffman lift term is introduced based on the velocity gradient field under the wide flow rate conditions, and the coefficient of the Saffman lift term varies with the flow rate conditions. Dynamic adjustment.

6. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 5, characterized in that: Step three specifically involves: An Eulerian-Lagrange framework is adopted, with the continuous phase (liquid phase) solved using the Navier-Stokes equations and turbulence model in Eulerian coordinates; the discrete phase (solid particles) is tracked using a discrete phase model in Lagrange coordinates. To achieve bidirectional coupling, within each time step: (1) The CFD solver transmits local flow field velocity, vorticity and shear strain rate to the discrete phase model; (2) The discrete model calculates the drag force, pressure gradient force and virtual mass force on the particles, and introduces the Saffman lift correction term associated with the velocity gradient field under wide flow conditions to accurately simulate the lateral migration and aggregation behavior of particles in the strong shear near-wall region. (3) The discrete phase model feeds back the momentum source term of the particles to the Navier-Stokes equation solver to correct the turbulent structure of the flow field; Through the above coupled solution, transient parameters of the particle impacting the impeller wall are extracted, including the collision velocity. Impact angle Near-wall local shear rate and particle mass concentration .

7. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 6, characterized in that: Step four specifically involves: To address the strain hardening characteristics of low-nickel, high-nitrogen duplex stainless steel, a hardness index was established. Operating conditions with flow rate The dynamic functional relationship is expressed as follows: ； in: The reference hardness index, calibrated by erosion tests at the design flow rate, is taken as 0.6~0.

8. To be related to the material strain hardening index The adjustment coefficient, which is positively correlated, determines the sensitivity of the material to strain hardening, and its value ranges from 0.15 to 0.

35. Characterizing the physical mechanism by which changes in flow field shear force drive the evolution of the hardened layer on the material surface when the flow rate deviates from the design flow rate, thereby affecting the hardness erosion suppression efficiency, i.e., the sensitivity of material hardness to the dynamic response of flow rate changes.

8. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 7, characterized in that: Step five specifically involves: Based on the collision parameters extracted in step three and the dynamic hardness index constructed in step four, the instantaneous erosion rate is calculated. : ； In the formula: The correction factor is the reference material. It is a dynamic velocity exponential function; The measured hardness of low-nickel, high-nitrogen duplex stainless steel. For reference hardness; This is the Saffman lift correction factor; For the first i Near-wall shear rate under various working conditions; To introduce material yield strength The corrected impact angle function.

9. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 8, characterized in that: The satisfy: ； in: To design the baseline velocity index under flow conditions, This represents the amplitude of the velocity exponent change, ranging from 0.3 to 0.

5. This is the exponential decay coefficient, with a value ranging from 0.8 to 1.2; The piecewise function form is used, fitted based on the erosion experimental data of the low-nickel, high-nitrogen duplex stainless steel, and the impact angle corresponding to the peak erosion rate is given. Located within interval c; ； ； In the formula: All constant coefficients are obtained by fitting the erosion test data of the low-nickel high-nitrogen duplex stainless steel. The yield strength of the low-nickel, high-nitrogen duplex stainless steel is 460–500 MPa. For reference yield strength; satisfy: ； in: For the first i Near-wall shear rate under various working conditions; Reference shear rate; The lift effect coefficient ranges from 0.05 to 0.

15. The shear rate exponent has a value range of 0.5 to 0.

8.

10. The method for predicting the erosion life of a submersible electric pump under wide flow conditions according to claim 9, characterized in that: Step six specifically involves: Using Miner's linear accumulation rule, the calculation of each node on the impeller wall after experiencing all [the following conditions] is performed. Total erosion damage after each flow rate operating period : ； in, For instantaneous erosion rate Under the action, the time required for the wall surface to reach the critical erosion depth. The critical erosion depth is determined based on the design wall thickness margin of the blade guide vane. 30% to 50% of the minimum cross-sectional wall thickness of the blade is taken as the judgment threshold, or the specific value is determined based on the structural strength safety margin of the blade and engineering experience. For the first The actual running time of each flow condition segment.

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