A numerical simulation method for predicting easy cavitation region of axial flow pump blade

Abstract

The application discloses a numerical simulation method for predicting an easy cavitation region of an axial flow pump blade, and comprises the following steps: adopting a three-dimensional modeling software to perform geometric and water body modeling on the axial flow pump; adopting a grid division software to perform spatial grid discretization on the water body of the axial flow pump; performing numerical calculation on a cavitation flow field of the axial flow pump while importing a cavitation numerical model constructed based on an energy transmission method; and analyzing cavitation energy distribution on the impeller blade to obtain an easy cavitation-affected region in the blade. The method displays cavitation energy from the entire flow field on the blade by considering that the cavitation energy in the flow field is radiated to the blade surface, realizes accurate prediction of the cavitation region in the axial flow pump, is helpful for targeted protection of the easy cavitation-affected region in the design stage of the axial flow pump, and thus improves the service life and working stability of the axial flow pump. Meanwhile, the cavitation prediction method can also be extended to hydraulic machines such as centrifugal pumps, water turbines and propellers which are easy to be affected by cavitation.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology for cavitation erosion in fluid machinery, and particularly to a numerical simulation method for predicting the cavitation erosion-prone region of axial flow pump blades. Background Technology

[0002] Axial flow pumps are characterized by large flow rates, low head, and high efficiency, and are widely used in national defense equipment fields such as large-scale water diversion projects, nuclear power projects, ship waterjet propulsion, and submarine launch systems. The internal structure of an axial flow pump contains complex vortex cavitation, including tip leakage vortices, backflow vortices, hub vortices, and impeller vortices. These cavitation types interfere with each other, creating an extremely complex cavitation environment within the pump. Therefore, axial flow pumps have long been plagued by cavitation disturbances during operation.

[0003] Among the many adverse effects of cavitation, cavitation erosion damage to materials is the most difficult problem to solve: cavitation bubbles near the material wall in a fluid, driven by high pressure, collapse instantaneously in localized areas, generating highly impactful microjets and pulsed pressure waves. These waves exert localized surface stresses on the material surface, reaching tens of atmospheres. When this stress exceeds the material's plasticity limit, it damages the material surface, forming... Figure 5 The image on the right shows cavitation pitting. In hydraulic machinery, when a large number of cavitation bubbles or cavitation clusters repeatedly act on the material surface, it leads to material peeling, mass loss, fatigue failure, and even fracture, causing further deterioration of the hydraulic machinery's performance, a significant increase in vibration and noise, and consequently, increased maintenance costs and frequency. Cavitation is unavoidable and has always been a direct factor affecting the efficient operation of hydraulic machinery under multiple working conditions, causing vibration, noise, and cavitation damage.

[0004] Therefore, how to predict the cavitation-prone areas of hydraulic machinery in the design stage using numerical methods, and thus effectively carry out cavitation-resistant design of hydraulic machinery, has become a key technical problem that urgently needs to be solved in my country. Summary of the Invention

[0005] To address the blade cavitation erosion phenomenon caused by the complex cavitation environment inside axial flow pumps, the purpose of this invention is to comprehensively consider the cavitation energy generated when cavitation bubbles collapse in the entire flow field of the pump, and to predict the energy erosion of the axial flow pump blades by the cavitation energy in the entire flow field by considering energy radiation and energy attenuation, thereby accurately predicting the distribution of cavitation erosion areas on the axial flow pump blades.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] Step 1: Using 3D geometric modeling software, geometric model the impeller and guide vanes of the axial flow pump and divide the water body according to the design drawings of the axial flow pump. At the same time, the inlet section of the axial flow pump impeller is extended according to the outer diameter D1 of the impeller, and the length of the inlet section satisfies L1>5D1. Similarly, the outlet section of the guide vane is extended according to the outer diameter D2 of the guide vane, and the extension distance satisfies L2>5D2.

[0008] Step 2: Import the water body diagrams of each component of the axial flow pump drawn by the 3D software into the mesh generation software. Since high-precision solution of cavitation flow of axial flow pump is required, high-quality structural mesh generation is adopted, and the mesh is refined in the blade tip region of the impeller computation domain.

[0009] Step 3: Import the generated mesh into the calculation software and perform numerical settings for the entire computational domain, including defining material properties, selecting multiphase flow and turbulence models, setting boundary conditions, setting the interface between the moving and stationary rotors, and controlling the discrete solution format, etc.

[0010] Step 4: Conduct numerical calculations of cavitation flow in the axial flow pump. In the numerical calculations, to numerically simulate cavitation, a gas-liquid two-phase mass transfer phenomenon, the gas-phase transport equations are solved, and the source terms of the transport equations are defined using a cavitation model. The transport equations are as follows:

[0011]

[0012] Where the subscript v represents the gas phase, α v Gas phase volume fraction; ρ v This represents the gas phase density, and u is the velocity vector. The source term, defined by the cavitation model, is the gas-liquid mass transfer rate.

[0013] Based on the numerical settings in step three, the following numerical model calculation algorithm for cavitation erosion is inserted:

[0014] The energy density of the cavitation bubble in each grid cell of the flow field can be calculated using the following formula:

[0015]

[0016] in, The reciprocal of the gas phase volume fraction for particles can be derived from Formula 1 and calculated as follows:

[0017]

[0018] Furthermore, by combining Equations 2 and 3, the cavitation energy density in the flow field can be obtained:

[0019]

[0020] According to Formula 4, the cavitation energy at each grid point in the flow field can be obtained. This energy will then radiate in the form of a spherical wave, and the energy attenuation during radiation is inversely proportional to the radiation distance. Based on the above theory, an energy radiation and attenuation model is constructed. Assume that in the flow field grid x... i The energy in it is Then the energy of this grid is radiated to the wall grid x. j At that time, the wall x j The stress borne by grid x i The energy is:

[0021]

[0022] According to Formula 5, the wall mesh x j The cumulative energy borne by all flow field grids is:

[0023]

[0024] Formula 6 can be used to calculate the cavitation energy borne by each grid on the wall from the entire flow field region, thus showing the cavitation energy distribution in the wall region.

[0025] Step 5: Analyze the numerical results calculated in Step 4, obtain the cavitation energy distribution cloud map on the axial flow pump blades, and then determine the areas containing high cavitation energy, marking them as the cavitation-prone areas of the axial flow pump under this operating condition.

[0026] This invention offers the following advantages: By considering cavitation phenomena across the entire flow field of the impeller and converting the energy from cavitation bubble collapse into cavitation erosion energy through a model, while also considering the energy attenuation process as this energy radiates to the blade surface, the cavitation erosion energy in the entire flow field is mapped onto the blade wall. This allows for accurate prediction of the cavitation erosion energy distribution on the blade, reflecting the areas of the impeller blade most susceptible to cavitation erosion. Based on this prediction method, targeted protection can be implemented for cavitation-prone areas of axial flow pumps during the impeller blade design phase, ensuring more stable and reliable operation of the axial flow pump. Furthermore, this prediction method can also be applied to centrifugal pumps, water turbines, propellers, and other fluid machinery, providing numerical prediction models for the cavitation-resistant optimization design of various fluid machinery. Attached Figure Description

[0027] Figure 1 A flowchart of a numerical simulation method for predicting the cavitation-prone region of axial flow pump blades, provided in an embodiment of the present invention;

[0028] Figure 2 A schematic diagram of a model considering the attenuation of cavitation energy radiation from the entire flow field to the material surface, provided for an embodiment of the present invention;

[0029] Figure 3 This is a three-dimensional structural diagram of an axial flow pump provided in an embodiment of the present invention;

[0030] Figure 4 A grid division diagram of the water body in the axial flow pump impeller provided in an embodiment of the present invention;

[0031] Figure 5 The predicted cavitation intensity distribution diagram and test results of the axial flow pump blades are provided for embodiments of the present invention. Detailed Implementation

[0032] The technical solutions in the embodiments of the present invention will now be clearly and completely described in conjunction with the accompanying drawings.

[0033] Example:

[0034] Please see Figure 1 A numerical simulation method for predicting the cavitation erosion zone of axial flow pump blades mainly includes the following steps:

[0035] Step 1: Please refer to Figure 3 The axial flow pump was geometrically modeled and the water body was divided using three-dimensional geometric modeling software (UG, Solidworks, Creo, etc.), and the impeller inlet and guide vane outlet were extended.

[0036] Step Two: Please refer to Figure 4 The three-dimensional geometry is imported into mesh generation software (ICEM, Turborid, Meshing, etc.). High-quality hexahedral meshes are generated for each component of the axial flow pump by using a block-based method. Appropriate mesh refinement should be done in the material wall area, and many layers of mesh must be arranged in the blade tip area to capture the cavitation structure.

[0037] Step 3: Conduct preprocessing settings for numerical calculation of cavitation flow in axial flow pumps. Import the divided mesh into the calculation software and perform numerical settings for the entire computational domain, including defining material properties, selecting multiphase flow models and turbulence models, setting boundary conditions, setting the interface between the dynamic and static rotors, and controlling the discrete solution format, etc.

[0038] Step 4: Conduct numerical calculations of cavitation flow in the axial flow pump. The selection of the calculation model for the cavitation two-phase flow is particularly important in this calculation. In this embodiment, a homogeneous flow model is chosen for numerical calculation. This model is used to numerically simulate the gas-liquid two-phase mass transfer phenomenon of cavitation. Generally, it employs the method of solving the gas-phase transport equation and defining the source terms of the transport equation through the cavitation model. The typical transport equation is as follows:

[0039]

[0040] Where the subscript v represents the gas phase, α v Gas phase volume fraction; ρv This represents the gas phase density, and u is the velocity vector. The source term, defined by the cavitation model, is the gas-liquid mass transfer rate.

[0041] Based on the numerical settings in step three, the following numerical model calculation algorithm for cavitation erosion is inserted:

[0042] The energy density of the cavitation bubble in each grid cell of the flow field can be calculated using the following formula:

[0043]

[0044] in, The reciprocal of the gas phase volume fraction for particles can be derived from Formula 1 and calculated as follows:

[0045]

[0046] Furthermore, combining Equations 2 and 3, the cavitation energy density in the flow field can be obtained:

[0047]

[0048] The cavitation energy at each grid point in the flow field can be obtained from the above formula. This energy will then radiate in the form of a spherical wave, and the energy attenuation during radiation is inversely proportional to the radiation distance. Based on the above theory, please refer to... Figure 2 An energy radiation and attenuation model was constructed. It is assumed that in the flow field mesh x... i The energy in it is Then the energy of this grid is radiated to the wall grid x. j At that time, the wall x j The stress borne by grid x i The energy is:

[0049]

[0050] According to Formula 5, the cumulative energy borne by the wall mesh xj from all flow field meshes is:

[0051]

[0052] According to formulas five and six, the cavitation energy borne by each grid on the wall from the entire flow field region can be obtained, thus showing the cavitation energy distribution in the wall region.

[0053] Step 5: Analyze the numerical results calculated in Step 4 to obtain the cavitation energy distribution cloud map on the axial flow pump blades. Please refer to [link / reference needed]. Figure 5 This further identified regions containing high cavitation energy, marking them as cavitation-prone areas for the axial flow pump under this operating condition. Furthermore, Figure 5The middle right figure shows the cavitation test results of an axial flow pump. The test results show that the current cavitation model can accurately predict the cavitation-prone areas in the axial flow pump, namely the hub area and the area near the blade tip.

[0054] The technical solution of the present invention has been described in detail with reference to the above steps and accompanying drawings. However, the embodiments described above are only some embodiments of the present invention, and not all embodiments. Their purpose is to enable those skilled in the art to understand the content of the present invention and to implement it without creative effort. Therefore, equivalent variations made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A numerical simulation method for predicting the cavitation-prone region of axial flow pump blades, characterized in that: Includes the following steps: Three-dimensional geometric modeling of axial flow pumps; The three-dimensional geometric shapes of each component of the axial flow pump are divided into structural meshes, and the mesh is refined in the area near the blade wall and blade tip. Import the divided mesh into the calculation software, and select the model and set the calculation settings; After completing the model selection and calculation settings, cavitation calculations for the axial flow pump were performed. In the numerical calculations, to numerically simulate the gas-liquid two-phase mass transfer phenomenon of cavitation, the gas-phase transport equations were solved, and the source terms of the transport equations were defined using the cavitation model. The transport equations are as follows: Formula 1 Wherein, the subscript v indicates the gas phase. Gas phase volume fraction; This represents the density of the gas phase. It is a velocity vector. The source term, defined by the cavitation model, is the gas-liquid mass transport rate. Subsequently, a cavitation erosion calculation model was implemented, and the following cavitation erosion numerical model calculation algorithm was inserted. The energy density of the cavitation bubble in each grid cell of the flow field can be calculated using the following formula: Formula 2 Among them, P pot V is the energy of cavitation. cell The volume of the grid containing the gas phase. The particle derivative of the gas phase volume fraction can be derived from Formula 1 and calculated as follows: Formula 3 Combining equations (2) and (3), the cavitation energy density in the flow field can be obtained: Formula 4 The cavitation energy density at each grid point in the flow field is obtained from formula four. This energy will be radiated in the form of a spherical wave, and the energy attenuation during radiation is inversely proportional to the radiation distance; based on the above theory, an energy radiation and attenuation model is constructed; assuming that in the flow field grid x i The energy in it is The energy of this grid radiates to the wall grid x j At that time, the wall x j The stress borne by grid x i The energy is: Formula 5 According to Formula 5, the wall mesh x j The cumulative energy borne by all flow field grids is: Formula Six Formula 6 is used to calculate the cavitation energy borne by each grid on the wall from the entire flow field region, thus showing the cavitation energy distribution in the wall region. The calculation results were analyzed to obtain the cavitation intensity distribution and cavitation area marking of the axial flow pump blades.

2. The numerical simulation method for predicting the cavitation-prone region of axial flow pump blades according to claim 1, characterized in that, The three-dimensional geometric modeling of the axial flow pump includes: performing three-dimensional geometric modeling and water body division based on the design drawings of the axial flow pump impeller and guide vane, and extending the pump impeller inlet and guide vane outlet.

3. The numerical simulation method for predicting the cavitation-prone region of axial flow pump blades according to claim 1, characterized in that, Importing the mesh into the computational software and selecting the model and setting up the computation includes: importing the mesh into the computational software and setting up the numerical settings for the entire computational domain; the numerical settings include defining material properties, selecting multiphase flow models and turbulence models, setting boundary conditions, setting the dynamic-static-rotor interface, and controlling the discrete solution format.

4. The numerical simulation method for predicting the cavitation-prone region of axial flow pump blades according to claim 1, characterized in that, The cavitation calculation algorithm for axial flow pumps is a homogeneous flow algorithm. The cavitation calculation uses a transport model to consider the mass transfer rate between the gas and liquid phases.

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