A numerical evaluation method for aeration efficiency of a water-lifting aerator based on multi-field coupling

Abstract

This invention discloses a numerical evaluation method for the aeration efficiency of a pumping aerator based on multi-field coupling, belonging to the field of in-situ water quality remediation technology for water sources and reservoirs. The method includes: establishing a three-dimensional computational model of the pumping aerator and completing network partitioning and regional densification; using an iterative coupling calculation with a gas-liquid two-phase flow model, an interphase mass transfer model, and an oxygen component transport model to obtain the target cross-sectional velocity and the dissolved oxygen concentration distribution throughout the water area; performing area-weighted averaging on the target cross-sectional velocity to obtain its average velocity; calculating the corresponding flow rate based on the target cross-sectional area and average velocity, and combining this with the increase in oxygen concentration to complete the numerical evaluation of aeration efficiency. This invention, through multi-field coupling calculation, simulates the entire process of oxygen dissolution and diffusion, obtaining a dissolved oxygen distribution consistent with on-site measurements. It solves the problem of difficult measurement of dissolved oxygen at the bottom of deep-water reservoirs, enabling accurate quantitative evaluation of aeration efficiency without extensive underwater monitoring, and significantly reducing evaluation costs.

Description

Technical Field

[0001] This invention belongs to the field of in-situ water quality remediation technology for water sources and reservoirs, specifically involving a numerical evaluation method for the aeration efficiency of a pumping aerator based on multi-field coupling. Background Technology

[0002] The water-lifting aerator is a water quality improvement device that combines oxygenation and water lifting functions, and it has been widely used in water quality remediation projects in lakes, reservoirs, and other water sources. Powered by compressed air, the device releases air bubbles to oxygenate the water and uses the resulting air bubbles to propel the water flow, achieving circulation and mixing between upper and lower water layers. This inhibits algae growth, increases dissolved oxygen in the water, and suppresses the release of pollutants from bottom sediments. Currently, this technology has been applied in water quality improvement projects at several water sources, including the Heihe Reservoir, Lijiahe Reservoir, and Fenhe Reservoir.

[0003] Current methods for assessing the aeration efficiency of pumping aerators mainly rely on on-site dissolved oxygen monitoring, which has significant limitations in deep-water reservoir conditions: on-site measurement of dissolved oxygen at the bottom of deep water areas is difficult, costly, and suffers from poor long-term monitoring stability, making it difficult to obtain high-precision oxygen concentration distribution data across the entire water area; existing computational fluid dynamics (CFD) simulations can only calculate flow field and velocity distribution, lacking the ability to simulate the dissolution, diffusion, and concentration distribution of oxygen in water, thus failing to achieve accurate assessment of aeration efficiency during the design phase; conventional assessment methods rely on extensive on-site testing, which is time-consuming, lacks versatility, and cannot meet the needs of refined and high-efficiency engineering.

[0004] In view of this, the present invention is hereby proposed. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a numerical evaluation method for the aeration efficiency of pumping aerators based on multi-field coupling, so as to solve the problems of difficult actual measurement, lack of methods and long evaluation cycle in the evaluation of the bottom aeration efficiency of deep water reservoirs.

[0006] To achieve the above objectives, the present invention provides the following technical solution: This evaluation method uses a multi-field coupled model of gas-liquid two-phase flow model, oxygen component transport model and interphase mass transfer model to perform numerical simulation, complete the simulation of the entire process of oxygen dissolution and diffusion, obtain dissolved oxygen distribution consistent with field measurements, and realize numerical evaluation of bottom aeration efficiency in deep water reservoirs.

[0007] Specifically, the following steps are included: Step 1: Establish a three-dimensional calculation model of the water pumping aerator and divide it into grids, and refine the grid in key flow field regions.

[0008] Step 2: Iterative coupling calculations are performed using a gas-liquid two-phase flow model, an interphase mass transfer model, and an oxygen component transport model to obtain the velocity distribution of the target section and the dissolved oxygen concentration distribution of the entire water area.

[0009] Step 3: Perform area-weighted averaging on the velocity distribution of the target cross section mentioned in Step 2 to obtain the average velocity of the target cross section.

[0010] Step 4: Calculate the flow rate of the target cross-section based on the target cross-sectional area and the average flow velocity of the target cross-section in Step 3, and combine it with the increase in oxygen concentration to complete the numerical evaluation of aeration efficiency.

[0011] Furthermore, the water-lifting aerator includes a rising cylinder, an air chamber, and a guide disc structure, and the outlet cross-section of the guide disc is defined as the target cross-section.

[0012] Furthermore, step 2 includes the following specific steps: Step 2.1, Gas-liquid two-phase flow simulation: The VOF (Volume of Fluid) model is used to capture the gas-liquid two-phase interface, and the velocity field, pressure field and phase volume fraction distribution are obtained by solving the continuity equation and momentum equation.

[0013] The continuity equation is: , in, For the first Phase volume fraction This is the velocity vector.

[0014] The momentum equation is: , in, and These are the volume average density and dynamic viscosity, respectively. For pressure, It is the acceleration due to gravity. This is the surface tension source term.

[0015] Step 2.2, Simulation of interphase mass transfer process: Based on the velocity field, pressure field, and phase volume fraction distribution obtained in Step 2.1, the mass transfer rate of oxygen from the gas phase to the liquid phase is calculated using an interphase mass transfer model to obtain the oxygen mass transfer source term. The formula for calculating the oxygen mass transfer rate from the gas phase to the liquid phase is: , in, This refers to the oxygen mass transfer rate per unit volume. The volumetric mass transfer coefficient is . This represents the saturated dissolved oxygen concentration. This represents the local dissolved oxygen concentration in the liquid phase. Volumetric mass transfer coefficient. Based on the flow field characteristics (such as turbulent kinetic energy k and turbulent dissipation rate ε), empirical correlation dynamic calculations are used, such as the Higbie infiltration model or the eddy diffusion model.

[0016] Step 2.3, Dissolved Oxygen Component Transport Simulation: Substitute the oxygen mass transfer source term from Step 2.2 into the liquid-phase dissolved oxygen component transport equation and solve to obtain the dissolved oxygen concentration distribution across the entire water area. The liquid-phase dissolved oxygen component transport equation is as follows: , in, It is the liquid volume fraction. The effective diffusion coefficient.

[0017] Step 2.4, Coupled Solution Strategy: The three physical processes described above—gas-liquid two-phase flow, interphase mass transfer, and oxygen component transport—are solved jointly through an iterative coupling method: Within each time step, the VOF two-phase flow equations are first solved to update the velocity field, pressure field, and phase volume fraction. Calculate the local volumetric mass transfer coefficient based on the updated flow field parameters. With saturation concentration Oxygen mass transfer source item obtained ; Will Substituting the source term into the dissolved oxygen component transport equation, the dissolved oxygen concentration field of the entire water body at the current moment can be obtained by solving the equation. Repeat the above process until the computational residuals of each equation converge to 10. -3 Once the preset physical time is reached, the output will show the velocity vector and velocity scalar data on each grid node of the guide disc outlet section (target section), as well as the liquid phase dissolved oxygen concentration distribution data in the entire computational domain.

[0018] Furthermore, in step 2, the calculation process is performed using Fluent (a mainstream international commercial computational fluid dynamics software under ANSYS) based on the finite volume method. The specific numerical format is as follows: the turbulence model adopts the standard k-ε turbulence model, the pressure-velocity coupling adopts the PISO algorithm, the spatial discretization adopts the momentum equation and the turbulence equation adopts the second-order upwind scheme, the volume fraction equation adopts the Geo-Reconstruct interface reconstruction format, the pressure interpolation adopts the PRESTO! format, and the time discretization adopts the first-order implicit scheme.

[0019] Furthermore, in step 3, the flow velocity of all grid points on the target cross section is processed by area-weighted averaging using Tecplot 360 software (a professional engineering data analysis and visualization software developed by Tecplot Corporation of the United States).

[0020] Furthermore, step 4 includes the following specific steps: Step 4.1: Calculate the flow rate at the target cross-section using the flow rate calculation formula. The formula for calculating the flow rate is: , in, For the target cross-sectional area, The average flow velocity of the target cross section obtained in step 3; Step 4.2: Extract the dissolved oxygen concentration at the lower point of the water pumping aerator at the initial moment of the simulation and after a specified simulation period, and calculate the difference to obtain the oxygen concentration increase. Step 4.3, Numerical Evaluation of Aeration Efficiency: Based on the target cross-sectional flow rate described in Step 4.1 and the calculation results of the oxygen concentration increase in Step 4.2, the aeration efficiency is evaluated using the target cross-sectional flow rate per unit time. and the corresponding increase in dissolved oxygen The aeration efficiency of the water pumping aerator is evaluated using two indicators.

[0021] Specifically, the target interface traffic per unit time. Under certain conditions, the increase in dissolved oxygen The larger the aeration volume, the higher the aeration efficiency.

[0022] Furthermore, in step 1, ICEM CFD (The Integrated Computer Engineering and Manufacturing code for Computational Fluid Dynamics, a professional CAE preprocessing software integrated into the ANSYS Workbench platform, and the standard mesh generation software for Fluent and CFX) is used to generate a structured mesh. Mesh refinement is applied to key flow regions such as the interior of the gas chamber, the outlet of the guide vane, and the inner wall of the riser to ensure the accuracy of the gas-liquid interface and flow field calculations. The total number of meshes should ideally be controlled between 5 million and 8 million, and the Y+ value of the boundary layer mesh should be controlled to around 1.

[0023] Furthermore, the method of the present invention is particularly applicable to the numerical evaluation of the aeration efficiency of pumping aerators in deep-water reservoirs with a water depth of 30m to 60m.

[0024] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects: 1. This invention uses an iterative coupling calculation of a gas-liquid two-phase flow model, an interphase mass transfer model, and an oxygen component transport model to completely simulate the entire process of oxygen dissolution, diffusion, and transport from air into water. It obtains a dissolved oxygen distribution that is highly consistent with the actual field measurement, and the prediction error can be controlled within 5%. This solves the industry pain point that it is difficult to measure dissolved oxygen at the bottom of deep water reservoirs.

[0025] 2. The method of the present invention can complete the aeration efficiency assessment through numerical simulation during the design stage, without the need to deploy a large number of underwater sensors for long-term on-site monitoring, which significantly reduces the assessment cost and shortens the research and development cycle.

[0026] 3. This invention uses two indicators, namely the target cross-sectional flow rate and the increase in oxygen concentration, to determine efficiency. This is more scientific and closer to engineering practice than traditional single indicators (such as considering only flow rate or only concentration), and can more comprehensively reflect the overall performance of the pumping aerator.

[0027] 4. Based on the detailed flow field and concentration field data obtained by this invention, the influence of aerator structural parameters (such as guide disc diameter and air chamber volume) and operating parameters (such as aeration rate) on aeration efficiency can be further analyzed, providing a scientific basis for equipment structure optimization and energy consumption reduction.

[0028] 5. This invention is applicable to deep-water reservoirs of 30m to 60m, demonstrating strong specificity, a clear scope of application, and high engineering practicality. Furthermore, the framework of this invention exhibits good compatibility and scalability with different gas-liquid two-phase flow models (such as the Eulerian-Eulerian model), turbulence models (such as large eddy simulation), and mass transfer models. Attached Figure Description

[0029] The accompanying drawings are incorporated in and form part of this specification, and together with the description serve to explain the principles of the invention.

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 A flowchart of a method for numerically evaluating the aeration efficiency of a water pumping aerator based on multi-field coupling, provided by the present invention; Figure 2 This is a structural diagram of the water-lifting aerator used in Embodiment 1 of the present invention; Figure 3 A streamline diagram of the fluid movement process inside the water pumping aerator; Figure 4 This is a graph showing the change in outlet velocity of the water-lifting aerator within one air-bomb cycle.

[0032] Among them, the ascending cylinder is 1, the air chamber is 2, and the guide disc is 3. Detailed Implementation

[0033] Exemplary embodiments will now be described in detail. The embodiments described below are not representative of all embodiments consistent with this invention. Rather, they are merely examples consistent with some aspects of the invention as detailed in the appended claims.

[0034] See Figure 1 As shown, this invention provides a numerical evaluation method for the aeration efficiency of a pumping aerator based on multi-field coupling. The evaluation method includes: Step 1, establishing a computational model of the pumping aerator and completing mesh generation and key area refinement. Step 2, performing numerical simulation using a multi-field coupling model combining a gas-liquid two-phase flow model, an oxygen component transport model, and an interphase mass transfer model to obtain the target cross-section velocity and the oxygen concentration distribution throughout the water area. Step 3, performing area-weighted averaging on the target cross-section velocity from Step 2 to obtain the target cross-section average velocity. Step 4, calculating the target cross-section flow rate based on the target cross-section area and the target cross-section average velocity from Step 3, and combining this with the oxygen concentration increase to complete the numerical evaluation of the aeration efficiency.

[0035] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0036] Example 1 This embodiment provides a numerical evaluation method for the aeration efficiency of a pumping aerator based on multi-field coupling, targeting a typical deep-water reservoir with a water depth of 45 meters. For example... Figures 2-4 As shown, the water-lifting aerator includes a riser cylinder 1, an air chamber 2, and a guide disc 3. The cross-sectional diameter of the outlet of the guide disc 3 is 1.2m, and the cross-sectional area is... The aeration rate is 0.1 m³ / s; the volume of air chamber 2 is 0.797 m³; and the width of air chamber 2 is 0.9 m.

[0037] Specifically, the following steps are included: Step 1: Establish the computational model and mesh generation. A full-size 3D computational model containing the riser 1, air chamber 2, and guide vane 3 is constructed in Fluent. The simulation area covers the aerator body and a cylindrical reservoir with a radius of 5m and a depth of 45m. The bottom of the aerator air chamber 2 is designated as the velocity inlet with an air intake velocity of 0.1m / s; the sides and bottom of the reservoir are designated as non-slip walls; and the top of the reservoir is designated as the pressure outlet with a gauge pressure of 0Pa. A structured hexahedral mesh is generated using ICEM CFD, with a total mesh size of approximately 5.2 million. Mesh refinement is applied to key flow regions inside air chamber 2, at the outlet of guide vane 3, and on the inner wall of riser 1. The first mesh layer near the wall has a height of 0.5mm to ensure a Y+ value of approximately 1, accurately capturing boundary layer flow and gas-liquid interface evolution.

[0038] Step 2: Perform multi-field coupling calculations using Fluent. Enable the VOF multiphase flow model, setting the primary phase as water and the secondary phase as air, with a surface tension coefficient of 0.072 N / m. Enable the component transport model, setting the dissolved oxygen component in the liquid phase. Load the interphase mass transfer model using a user-defined function (UDF), and calculate the oxygen mass transfer source term according to the formula for the oxygen transfer rate from the gas phase to the liquid phase. Select the standard k-ε turbulence model with standard wall functions. Pressure-velocity coupling uses the PISO algorithm; pressure interpolation uses the PRESTO! format; spatial discretization of the momentum equation, turbulent kinetic energy, and turbulent dissipation rate equations uses a second-order upwind scheme; the volume fraction equation uses the Geo-Reconstruct interface reconstruction format; time discretization uses a first-order implicit scheme with a time step of 0.001 s.

[0039] Within each time step, the VOF equations are solved first to update the flow field, then the mass transfer source terms are calculated, and finally the oxygen component transport equations are solved to update the concentration field. This calculation continues until both the flow field and concentration field reach statistical steady state (the residuals of each equation are all less than 1). The total simulation physics time is 228s.

[0040] After the simulation is completed, the output will show the velocity vector and velocity scalar data of each grid node at the outlet section (target section) of the flow guide disk 3, as well as the liquid phase dissolved oxygen concentration distribution data in the entire computational domain.

[0041] Step 3: Area-weighted averaging of velocity. Import the velocity data at the outlet section of guide vane 3 obtained in Step 2 into Tecplot 360 software. Using the area-weighted averaging function of this software, calculate the area-weighted average of the velocity scalars at all grid points of the section, obtaining the average velocity of the section, v = 1.85 m / s. This processing method effectively eliminates single-point estimation errors caused by uneven velocity distribution across the section.

[0042] Step 4: Flow rate calculation and quantitative evaluation of aeration efficiency.

[0043] Step 4.1, Calculation of the target cross-section flow rate: Q = A × v = 1.1304 m² × 1.85 m / s ≈ 2.09 m³ / s. That is, under this operating condition, the circulating flow rate at the outlet of the guide disc 3 of the pumping aerator is approximately 2.09 cubic meters per second.

[0044] Step 4.2, Calculation of Oxygen Concentration Increase: First, extract data from the monitoring point located 1m below the bottom of the pumping aerator in the overall dissolved oxygen concentration distribution of the entire water area. Simulate the initial dissolved oxygen concentration at this point (t=0) as 4.2 mg / L. With the outlet flow rate of guide disc 3 maintained at 2.09 m³ / s, after 72 hours (physical time), the dissolved oxygen concentration at this point increased to 7.8 mg / L. Therefore, the oxygen concentration increase ΔC = 3.6 mg / L.

[0045] Step 4.3, Numerical Evaluation of Aeration Efficiency: Using the flow rate Q = 2.09 m³ / s per unit time and the dissolved oxygen increase ΔC = 3.6 mg / L as dual indicators, the flow rate at the target interface per unit time is... Under certain conditions, the increase in dissolved oxygen The larger the aerator, the higher the aeration efficiency. Furthermore, the industry standard for successful reservoir bottom aeration is that the oxygen content on the sediment surface is consistently above 2 mg / L, and the oxygen content at a depth of 0.5 meters above the sediment surface reaches above 3 mg / L. Therefore, it is determined that the pumping aerator can achieve stable and efficient water aeration under this condition, and the aeration efficiency meets the engineering requirements.

[0046] To verify the accuracy and advancement of the method of the present invention, the simulation results of this embodiment are compared with the field measurement data, and a horizontal comparison is made with traditional evaluation methods.

[0047] As shown in Table 1, the results indicate that: 1. The dissolved oxygen concentration distribution predicted by the method of this invention is in high agreement with the actual measured values ​​on site, with an average prediction error of less than 5%.

[0048] 2. Compared with the prior art, this embodiment shows significant advantages in terms of functional integrity, evaluation accuracy and engineering applicability.

[0049] Therefore, the method of the present invention can complete the accurate quantitative assessment of aeration efficiency without the need for extensive underwater monitoring, which significantly reduces the assessment cost and provides reliable technical support for the optimized design and efficient operation of pumping aerators.

[0050] Example 2 Building upon Example 1, this example provides a numerical evaluation method for the aeration efficiency of a pumping aerator based on multi-field coupling. The difference from Example 1 lies in that, in the gas-liquid two-phase flow simulation of step 2, an Eulerian-Eulerian two-fluid model is used instead of the VOF model to describe the gas-liquid two-phase interaction. Correspondingly, the governing equations are replaced with the momentum equations and continuity equations for each phase, and an SN interphase drag model is introduced to calculate interphase momentum exchange.

[0051] This embodiment employs the Euler-Euler model, which is better suited to conditions with a wide distribution of bubble size and strong interphase mixing. This demonstrates that the method framework of this invention has good compatibility with different gas-liquid two-phase flow models, allowing users to flexibly select the appropriate model based on specific operating conditions.

[0052] Example 3 Based on Example 1, this example provides a numerical evaluation method for the aeration efficiency of a pumping aerator based on multi-field coupling. The difference from Example 1 is that the turbulence model in step 2 uses Large Eddy Simulation (LES) instead of the standard model. The model aims to capture the transient turbulent structure during aeroelastic motion and its impact on oxygen mass transfer rate with greater precision. Accordingly, the grid resolution needs to be further improved (total grid count approximately 12 million), and the time step reduced to [missing value]. To meet the CFL conditions.

[0053] This embodiment employs Large Eddy Simulation (LES), demonstrating the good compatibility of the present invention's methodological framework with high-precision turbulence models. This framework can be applied to scientific research or critical engineering design scenarios requiring higher computational accuracy.

[0054] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention.

[0055] It should be understood that the present invention is not limited to the content already described above, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. A numerical evaluation method for the aeration efficiency of a water pumping aerator based on multi-field coupling, characterized in that, Includes the following steps: Step 1: Establish a three-dimensional calculation model of the water pumping aerator and divide it into grids, and refine the grid in key flow field regions; Step 2: Iterative coupling calculations are performed using a gas-liquid two-phase flow model, an interphase mass transfer model, and an oxygen component transport model to obtain the velocity distribution at the target cross section and the dissolved oxygen concentration distribution throughout the water area. Step 3: Perform area-weighted averaging on the velocity distribution of the target cross section mentioned in Step 2 to obtain the average velocity of the target cross section; Step 4: Calculate the flow rate Q of the target cross-section based on the target cross-sectional area and the average flow velocity of the target cross-section in Step 3, and combine this with the increase in dissolved oxygen concentration. Complete the numerical evaluation of aeration efficiency.

2. The method according to claim 1, wherein The water pumping aerator includes a riser cylinder (1) and an air chamber (2) located on the outer side of the lower section of the riser cylinder (1), and a flow guide disc (3) located below the air chamber (2). The outlet cross section of the flow guide disc (3) is defined as the target cross section.

3. The method according to claim 2, wherein, Step 2 includes the following specific steps: Step 2.1: Use the VOF model to capture the gas-liquid two-phase interface, and obtain the velocity field, pressure field and phase volume fraction distribution by solving the continuity equation and momentum equation; Step 2.2: Based on the velocity field, pressure field and phase volume fraction distribution obtained in Step 2.1, calculate the mass transfer rate of oxygen from the gas phase to the liquid phase using the interphase mass transfer model to obtain the oxygen mass transfer source term. Step 2.3: Substitute the oxygen mass transfer source term described in Step 2.2 into the liquid phase dissolved oxygen component transport equation and solve it to obtain the dissolved oxygen concentration distribution of the entire water area; Step 2.4: Iteratively execute steps 2.1 to 2.3 within each time step until the computational residuals of each equation converge to 10. -3 The following may be reached within the preset physical time.

4. The method according to claim 3, wherein, The continuity equation in step 2.1 is: ， in, For the first Phase volume fraction It is a velocity vector; The momentum equation is: ， in, and These are the volume average density and dynamic viscosity, respectively. For pressure, It is the acceleration due to gravity. This is the surface tension source term.

5. The method according to claim 3, wherein The formula for calculating the oxygen mass transfer rate from the gas phase to the liquid phase in step 2.2 is as follows: ， in, This refers to the oxygen mass transfer rate per unit volume. The volumetric mass transfer coefficient is . This represents the saturated dissolved oxygen concentration. This refers to the local dissolved oxygen concentration in the liquid phase.

6. The method according to claim 3, wherein The transport equation for the dissolved oxygen component in the liquid phase in step 2.3 is as follows: ， wherein, is the liquid volume fraction, is the effective diffusion coefficient.

7. The method according to claim 2, wherein Step 4 includes the following specific steps: Step 4.1: Calculate the flow rate at the target cross-section using the flow rate calculation formula. The formula for calculating the flow rate is: ， in, For the target cross-sectional area, The average flow velocity of the target cross section obtained in step 3; Step 4.2: Extract the dissolved oxygen concentration at the lower point of the water pumping aerator at the initial moment of the simulation and after a specified simulation period, and calculate the difference to obtain the oxygen concentration increase. Step 4.3, Aeration efficiency numerical evaluation: based on the target cross-sectional flow rate per unit time. and the corresponding increase in dissolved oxygen The aeration efficiency of the water pumping aerator is evaluated using two indicators.

8. The numerical evaluation method for aeration efficiency of a water pumping aerator based on multi-field coupling according to claim 2, characterized in that, In step 2, the calculation process is performed using Fluent. The specific numerical format is as follows: the turbulence model adopts the standard k-ε turbulence model, the pressure-velocity coupling adopts the PISO algorithm, the spatial discretization adopts the momentum equation and the turbulence equation adopts the second-order upwind scheme, the volume fraction equation adopts the Geo-Reconstruct interface reconstruction scheme, the pressure interpolation adopts the PRESTO! scheme, and the time discretization adopts the first-order implicit scheme.

9. The numerical evaluation method for aeration efficiency of a water pumping aerator based on multi-field coupling according to claim 2, characterized in that, In step 1, Fluent is used to construct a full-size three-dimensional calculation model including the riser (1), air chamber (2), and guide disc (3), and the simulation area covers the aerator body and the surrounding reservoir water area; ICEM CFD is used to divide the structured mesh, and the mesh is refined in the key flow field areas, including the air chamber, the guide disc outlet, and the inner wall area of ​​the riser.

10. A numerical evaluation method for the aeration efficiency of a water pumping aerator based on multi-field coupling according to any one of claims 1-9, characterized in that, The evaluation method described herein is applicable to the numerical evaluation of the aeration efficiency of pumping aerators in deep-water reservoirs with a water depth of 30m to 60m.

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