Hydropower station cavitation simulation prediction method, system, equipment and medium

Abstract

The invention discloses a hydropower station cavitation simulation prediction method, system, equipment and medium, and belongs to the technical field of program simulation, and the method comprises the steps: building a geometric model calculation domain according to the whole flow channel structure parameters of a water turbine in a hydropower station; processing the geometric model computational domain to obtain a geometric file; importing the geometric file into preset grid division software for processing to obtain a grid file; constructing a code according to the working condition of the water turbine, inputting the code into simulation software to complete compiling, and obtaining a simulation program; importing the grid file into simulation software, and associating the grid file with a simulation program to obtain a solution model; and processing the solving model by utilizing simulation software, and outputting the processing result after the processing result meets a convergence condition. The problems that in the prior art, simulation accuracy is not high, and cavitation cannot be predicted are solved.

Description

Technical Field

[0001] This invention relates to the field of program simulation technology, specifically to a method, system, equipment, and medium for cavitation simulation and prediction of hydropower stations. Background Technology

[0002] As a highly efficient energy conversion device, the hydro turbine plays a crucial role in the energy sector. However, due to variations in operating head, hydro turbines often operate under off-design conditions, making them highly susceptible to cavitation, which in turn affects their stable operation. Therefore, accurate cavitation prediction is essential.

[0003] To address this issue, numerical simulation technology has become an important tool for studying cavitation in hydraulic turbines under various operating conditions. Through three-dimensional numerical simulation, a comprehensive analysis and evaluation of the internal flow field, impeller performance, and cavitation characteristics of a hydraulic turbine can be achieved. Furthermore, numerical simulation can provide detailed parameter variations, offering strong support for design optimization and performance improvement. Currently, most research on hydraulic turbine cavitation calculations focuses on homogeneous flow simulations due to their simplicity and good convergence. Because these factors are not considered, stable results can be achieved quickly. However, this neglect results in relatively low simulation accuracy, requiring continuous adjustments through experimentation and trial and error. Therefore, the application of three-dimensional cavitation models that consider surface tension and density gradients is essential. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is: how to simulate a hydropower station using a hydropower station cavitation simulation prediction method, and at the same time conduct a comprehensive analysis and evaluation of the internal flow field, impeller performance and cavitation characteristics of the turbine.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a cavitation simulation and prediction method for hydropower stations, comprising the following steps: constructing a geometric model computational domain based on the structural parameters of the entire flow channel of the turbine in the hydropower station; processing the geometric model computational domain to obtain a geometric file; importing the geometric file into a preset mesh generation software for processing to obtain a mesh file; according to the operating conditions of the turbine, encoding and compiling the code into simulation software to obtain a simulation program; importing the mesh file into the simulation software and associating it with the simulation program to obtain a solution model; processing the solution model using the simulation software, and outputting the result when the processing result meets the convergence condition.

[0007] As a preferred embodiment of the cavitation simulation and prediction method for hydropower stations described in this invention, the step of obtaining the geometric file includes: constructing a geometric model calculation domain based on the structural parameters of the turbine's entire flow channel in the power station; defining the geometric model calculation domain; and converting the defined geometric model calculation domain into an adaptive format according to a preset mesh generation software type to generate the geometric file.

[0008] As a preferred embodiment of the hydropower station cavitation simulation and prediction method described in this invention, the step of obtaining the mesh file includes: importing the geometric file into the mesh generation software, the mesh generation software sending a structured mesh generation instruction, and using structured mesh generation to perform mesh generation on the turbine full-channel structural parameters corresponding to the geometric file; wherein, structured mesh generation includes mesh refinement or boundary layer generation.

[0009] As a preferred embodiment of the hydropower station cavitation simulation and prediction method described in this invention, the step of constructing code based on the turbine's operating conditions includes: constructing Y simulation programs based on the pressure distribution boundary conditions, surface tension, and density under the actual operating conditions of the turbine; and performing syntax verification on each simulation program to complete the code construction. The beneficial effects of this preferred technical solution are that by using the pressure distribution boundary conditions, surface tension, and density under the actual operating conditions of the turbine as the core basis for code construction, it avoids the defects caused by neglecting the gas-liquid interphase interaction or high density gradient in traditional homogeneous flow simulation, making the simulation model more closely resemble the actual operating state of the turbine and reducing cavitation prediction deviations caused by parameters deviating from reality; simultaneously, syntax verification ensures that the code can be compiled normally in the preset simulation software.

[0010] As a preferred embodiment of the hydropower station cavitation simulation and prediction method described in this invention, the step of obtaining the solution model includes: importing the mesh file into the simulation software; configuring the mesh file according to the solver and preset model in the simulation software; importing the code into the simulation software for compilation; and matching the compiled simulation program with the configured mesh file to obtain the solution model. The beneficial effects of this preferred embodiment are that importing the mesh file into the simulation software and configuring it according to the solver and preset model in the software ensures that the mesh file is compatible with the simulation environment; importing the code into the simulation software for compilation and matching it with the configured mesh file enables the code and mesh file to work together in the simulation system; and by combining the operating parameters in the code with the flow channel structure of the mesh file, the constructed solution model better meets the cavitation simulation requirements of the hydropower turbine.

[0011] As a preferred embodiment of the hydropower station cavitation simulation and prediction method of the present invention, the step of processing the solution model using the simulation software includes: initializing the solution model with water flow data when the turbine operating state does not exceed the deviation threshold.

[0012] As a preferred embodiment of the hydropower station cavitation simulation and prediction method described in this invention, the step of outputting the solution model after the processing result meets the convergence condition includes: setting a calculation step size according to the actual rotational speed of the turbine based on the simulation software; monitoring the calculation results of the solution model based on the step size; and outputting the solution model of the current state when the result is within the error threshold and the result meets the convergence condition. The beneficial effects of this preferred embodiment are that the actual rotational speed of the turbine is set by the simulation software using a calculation step size, providing a reasonable time interval for monitoring the calculation results; monitoring the calculation results of the solution model based on this step size allows for orderly tracking of changes in the turbine flow field and cavitation-related parameters, avoiding monitoring confusion; and determining that the result meets the convergence condition and outputting the solution model of the current state when the result is within the error threshold ensures that the cavitation-related state reflected by the output solution model meets the accuracy requirements, avoiding inaccurate results due to premature output and preventing wasted computational resources.

[0013] This invention provides a cavitation simulation and prediction system for hydropower stations.

[0014] To address the aforementioned technical problems, the present invention further provides the following technical solution: a hydropower station cavitation simulation and prediction system, comprising: a model construction module for constructing a geometric model computational domain based on the structural parameters of the turbine's entire flow channel in the hydropower station; a geometric file configuration module for processing the geometric model computational domain to obtain a geometric file; a mesh file configuration module for importing the geometric file into a preset mesh generation software for processing to obtain a mesh file; a code construction module for encoding the turbine's operating conditions and compiling it into simulation software to obtain a simulation program; a solution model construction module for importing the mesh file into the simulation software and associating it with the simulation program to obtain a solution model; and a simulation result output module for processing the solution model using the simulation software and outputting the result when the processing result meets the convergence condition.

[0015] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer, and the processor executes the steps of the aforementioned hydropower station cavitation simulation and prediction method when the computer is used.

[0016] The present invention provides a computer-readable storage medium having a computer stored thereon, characterized in that, when the computer is executed by a processor, it implements the steps of the aforementioned hydropower station cavitation simulation and prediction method.

[0017] The beneficial effects of this invention are as follows: By constructing a geometric model computational domain using the structural parameters of the entire flow channel of the turbine in a hydropower station, a model for the flow channel range required for turbine cavitation simulation is established. By processing the geometric model computational domain to obtain geometric files, the geometric data is adapted to subsequent mesh generation software. By importing the geometric files into a pre-set mesh generation software for processing to obtain mesh files, mesh construction meeting computational accuracy requirements is achieved. Based on the turbine's operating conditions, code is generated through a pre-set simulation program and imported into the simulation software for compilation, achieving computational logic matching the actual operating conditions of the turbine and ensuring simulation parameters closely match actual operating conditions. By importing the mesh files into the simulation software and associating them with the compiled code to obtain the solution model, the synergy between mesh data and computational logic is achieved, constructing a complete model usable for cavitation simulation. By processing the solution model using simulation software and outputting the processing results after meeting convergence conditions, accurate prediction and result output of turbine cavitation characteristics are achieved, providing effective data support for analyzing cavitation impacts. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 The above is a flowchart of a hydropower station cavitation simulation and prediction method provided in one embodiment of the present invention. Detailed Implementation

[0020] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0021] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a method for cavitation simulation and prediction of hydropower stations, including: S100: The calculation domain of the geometric model is constructed based on the structural parameters of the entire flow channel of the turbine in the hydropower station; S200: Processes the computational domain of the geometric model to obtain the geometric file; S300: Import the geometry file into the preset mesh generation software for processing to obtain the mesh file; S400: Build code based on the operating conditions of the water turbine, input the code into the simulation software to complete the compilation, and obtain the simulation program; S500: Import the mesh file into the simulation software and associate it with the simulation program to obtain the solution model; S600: Uses simulation software to process the solution model and outputs the result when the processing condition is met.

[0022] It should be noted that existing technologies for turbine cavitation calculations mostly focus on homogeneous flow simulations. Although these models have good convergence due to their simplicity and can quickly achieve stable results, they neglect the gas-liquid interphase interaction forces and high-density gradients, resulting in low simulation accuracy. They can only be continuously adjusted through experiments and trial and error. Furthermore, the turbine's entire flow system has not been constructed for three-dimensional numerical simulation, making it difficult to comprehensively analyze the internal flow field, impeller performance, and cavitation characteristics. This makes it impossible to intuitively explore the impact of cavitation development on unit operation and to accurately predict the occurrence and development of cavitation.

[0023] Therefore, to address the issue of low simulation accuracy and inability to predict cavitation in existing technologies, a cavitation simulation and prediction method for hydropower stations is established through steps S100-S600. First, a geometric model computational domain is constructed based on the structural parameters of the turbine's entire flow channel in the hydropower station, and this domain is processed to obtain a geometric file. Second, the geometric file is imported into a pre-defined mesh generation software for processing to obtain a mesh file. Next, based on the turbine's operating conditions, code is constructed and input into the simulation software for compilation to obtain a simulation program. Then, the mesh file is imported into the simulation software and associated with the compiled code to obtain a solution model. Finally, the solution model is processed using the simulation software, and the result is output when the processing condition is met.

[0024] Example 2, refer to Figure 1 This is the second embodiment of the present invention, which provides a method for cavitation simulation and prediction of hydropower stations.

[0025] In the implementation steps of this invention, step S100 involves constructing a geometric model calculation domain based on the structural parameters of the entire flow channel of the turbine in the hydropower station.

[0026] Specifically, the structural parameters of the turbine's entire flow channel in the hydropower station are obtained based on the power station design drawings. These parameters include the dimensions of the inlet, guide vanes, runner, and tailrace, the morphological parameters of the guide vanes and runner blades, and the clearance parameters between the runner and the flow channel.

[0027] Furthermore, using UG, AutoCAD, Creo, or Solidworks modeling software, based on the obtained full flow channel structural parameters, a three-dimensional geometric model calculation domain covering the turbine's entire flow system, including the inlet, guide vanes, runner, and tailrace pipe, is constructed to ensure that the model calculation domain is consistent with the actual full flow channel structure of the turbine.

[0028] In the implementation steps of this invention, step S200 processes the geometric model computation domain to obtain a geometric file. Specifically, the computational domain of the geometric model is defined, and the defined computational domain is converted into an adapted format according to the preset mesh generation software type to generate a geometric file.

[0029] It should be noted that the geometry file is a geometric data file adapted to the requirements of the mesh generation software. The geometry file defines the geometric parameters and topological relationships of the key areas of the turbine's entire flow channel, including the inlet, guide vanes, runner, and draft tube.

[0030] One method to limit the computational domain of the geometric model is to trim the structure outside the turbine's flow passage during modeling, while retaining the flow passage from the inlet to the tailrace pipe.

[0031] Furthermore, the computational domain of the geometric model is defined, and the boundary range of the key areas of the entire flow channel of the turbine, including the inlet, guide vanes, runner, and tailrace tube, is clarified to ensure that the computational domain focuses on the core flow channel area where cavitation may occur.

[0032] In one possible implementation, the computational domain of the geometric model can be limited through Boolean operations and boundary naming in the modeling software. Using a pre-set geometric modeling software, a preliminary geometric model of the entire flow channel of the turbine is first imported. Through the Boolean difference function of the software, non-flow structures unrelated to cavitation simulation are removed from the model, leaving only the complete flow channel consisting of the inlet, guide vanes, runner, and tailrace pipe. Then, through the boundary naming function of the software, key boundaries such as the inlet section, the transition section between the guide vanes and the runner, the connection section between the runner and the tailrace pipe, and the tailrace pipe outlet section are given custom names, while invalid geometric elements outside the flow channel are deleted.

[0033] In another possible implementation, the calculation domain of the geometric model can be limited by dimensional constraints and region trimming. Based on the key dimensional parameters of the turbine's entire flow channel marked in the power plant design drawings, the geometric dimensions of the inlet, guide vanes, runner, and tailrace pipe are locked to the design values ​​using the dimensional constraint function in the modeling software. Then, the region trimming tool is used to trim the extended sections in the flow channel that exceed the simulation requirements, with the cavitation-prone area as the core.

[0034] It should be noted that the default meshing software is ANSYSICEM, ANSYSTurboGrid, or Fluentmeshing. According to the format requirements of the selected meshing software, the defined geometric model computation domain is converted into an adaptable format that the software can recognize, ensuring that the geometric file can be successfully imported into the meshing software.

[0035] In the implementation steps of this invention, in step S300, the geometric file is imported into a preset mesh generation software for processing to obtain a mesh file.

[0036] Specifically, the geometry file is imported into the mesh generation software, which then sends a structured mesh generation command to generate a mesh based on the structural parameters of the turbine's entire flow channel corresponding to the geometry file.

[0037] It should be noted that structural partitioning includes mesh refinement or boundary layer partitioning.

[0038] Among them, the mesh refinement improves the local mesh resolution by reducing the size of the mesh cells and increasing the number of mesh cells in the gap area between the guide vane wall, the runner blade surface and the flow channel in the entire flow channel of the turbine, according to the preset mesh density standard.

[0039] The boundary layer is defined by the area in the turbine's flow channel where the fluid comes into contact with the solid wall, such as the guide vane wall and the runner blade surface. According to the preset boundary layer grid number and grid stretching ratio, a grid layer is generated near the wall to simulate the viscous flow characteristics of the fluid near the wall.

[0040] In one possible implementation, structural partitioning can also be achieved through the block structured meshing function of ANSYSICEM. After importing the full flow channel geometry file of the turbine into ANSYSICEM, the topology of the computational domain of the geometric model is first cleaned and repaired. Then, the block structured meshing module is started to decompose the complex full flow channel into multiple regular sub-blocks. Then, the basic mesh size parameters are set for each sub-block. Finally, the mesh generation command is executed, and the software automatically generates a structured mesh in each sub-block.

[0041] In another possible implementation, structural division can also be achieved through Fluentmeshing's automatic structured mesh. After importing the geometry file into Fluentmeshing, the software automatically identifies the geometric boundaries of the turbine's entire flow channel by setting mesh quality control parameters and generates a preliminary structured mesh based on preset parameters. In local mesh control, after setting parameters, mesh generation and quality checks are performed to ensure that the mesh quality meets the standards.

[0042] In the implementation steps of this invention, step S400 involves constructing code based on the operating conditions of the turbine and inputting the code into simulation software to complete compilation and obtain the simulation program, including the following steps A1~A2: It should be noted that the simulation software specifically refers to Fluent software.

[0043] A1: Based on the pressure distribution boundary conditions, surface tension, and density under the actual operating conditions of the water turbine, construct Y simulation programs.

[0044] Specifically, Y in this invention has a value of 4, and the simulation program is a segmented Fluent program for key parameters of turbine cavitation simulation. Each simulation program is constructed collaboratively based on actual operating condition parameters.

[0045] Furthermore, the first simulation program is coded based on the pressure distribution boundary conditions of the upstream inlet submersion depth. Based on the actual pressure monitoring data of the turbine inlet section, such as the pressure distribution curve of the inlet section, the pressure boundary conditions of the inlet are defined through the DEFINE_PROFILE macro in the UDF, and the pressure value is associated with the coordinates of the inlet position of the flow channel to achieve accurate assignment of non-uniform pressure distribution.

[0046] Furthermore, the second simulation program encodes the pressure distribution boundary conditions based on the downstream outlet flooding depth, and combines the operating conditions of the outlet section, such as the pressure value corresponding to the tailwater level, to set the outlet pressure boundary conditions using the DEFINE_PROFILE macro, ensuring that the upstream and downstream pressure gradients of the flow field are consistent with the actual operating conditions.

[0047] In one implementation, the macro-defined inlet pressure boundary condition can also be achieved through the non-uniform pressure import in the boundary conditions panel of the Fluent software. By selecting the turbine inlet boundary in Fluent's boundary conditions, setting the boundary type to pressure inlet, selecting user-defined data in the pressure distribution option, and importing a data file generated in advance based on the pressure distribution curve of the inlet section, the file contains the actual pressure monitoring values ​​corresponding to different position coordinates of the flow channel inlet; the software automatically reads the data and binds the pressure values ​​with the corresponding position coordinates.

[0048] In another possible implementation, the macro-defined inlet pressure boundary condition can also be achieved through Fluent's tail correlation calculation function. Input the water density and gravitational acceleration parameters in Fluent's operating conditions panel, select pressure outlet in the outlet boundary condition settings, enable the static pressure calculation function, and input the actual tailwater level height; the software automatically calculates the static pressure value at the outlet and automatically adjusts the outlet pressure to match the upstream and downstream pressure gradient in actual operation.

[0049] Furthermore, the third simulation program is encoded based on the momentum equation of surface tension, introduces the surface tension coefficient of water at the working temperature, and quantifies the influence of surface tension on the formation and development of cavitation bubbles by defining the surface tension action model of the gas-liquid interface through the DEFINE_PROPERTY macro definition.

[0050] Specifically, the momentum equation is expressed as follows: ; In the formula, Let σ be the surface tension phase, κ be the surface tension coefficient, and κ be the surface curvature of the interface. For mixed density, , Let be the components of the fluid velocity in the i and j directions of the Cartesian coordinate system. For time, , The coordinates are in the Cartesian coordinate system. The effective viscosity of the laminar portion in a multiphase flow. ϕ is the effective viscosity coefficient, n is the normal vector, and ϕ is the LevelSet function.

[0051] Specifically, the LevelSet function ϕ is defined as the distance from the computational unit to the interface, so the gas-liquid interface can be represented by the LevelSet function ϕ.

[0052] The interface S1 between water vapor and water can be represented as: ; The interface S2 between the air and water can be represented as: ; In the formula, d1 and d2 represent the minimum distance between the calculation point and the interface, respectively; x represents the position coordinates, and the coordinates determine whether the point is located in the aqueous phase region or the water vapor phase.

[0053] Specifically, using the LevelSet function, the surface tension phase in the momentum equation can be written as: ; In the formula: σκδ(ϕ)n is the surface tension phase, σ is the surface tension coefficient, δ(ϕ) is the DiracDelta function, and ϕ is the LevelSet function.

[0054] It should be noted that the physical properties of the mixed medium in the flow field are defined as follows: ; ; In the formula: subscripts a, v, l represent the three phases of air, water vapor, and water, respectively; ρ is the density; μ is the dynamic viscosity, such as ρa is the air density and μa is the air dynamic viscosity; ρm and μm are the equivalent density and equivalent dynamic viscosity of the mixed medium, respectively; H(ϕ) is the smoothed Heaviside step function, defined as follows; ε is the interface thickness smoothing parameter; others are other points far from the interface region.

[0055] Furthermore, the fourth simulation program is coded based on a density-adaptive cavitation model. It constructs a density-pressure correlation model based on the cavitation mechanism and updates the density field through the DEFINE_PROPERTY macro. When the local pressure is lower than the saturated vapor pressure, the fluid density in that region is adjusted to reflect the cavitation state. When the local pressure is higher than the saturated vapor pressure, the normal density value is restored.

[0056] In one possible implementation, the density field can also be updated using a user-defined scalar. By defining a user-defined scalar in the simulation software and associating it with the local pressure of each grid cell in the flow field, a corresponding calculation simulation program can be written to allow the scalar to read and determine the relationship between the local pressure and the saturated vapor pressure at the corresponding temperature in real time.

[0057] In another possible implementation, the density field can also be updated by calculating the volume fraction of a multiphase flow model. The volume fraction method multiphase flow model is enabled in the simulation software. This model tracks the changes in the volume fraction of water vapor and water phases in the flow field in real time. When the local pressure is lower than the saturated vapor pressure, the model automatically increases the volume fraction of water vapor phase and calculates a lower mixing density to reflect cavitation. When the pressure is higher than the saturated vapor pressure, the volume fraction of water vapor phase decreases and the mixing density automatically approaches the normal density of water.

[0058] A2: Perform syntax checks on the simulation program to complete the code construction.

[0059] Specifically, the code of the simulation program is verified by an encoder, and the actual use of each line of code is debugged to complete the code construction.

[0060] In the implementation steps of this invention, step S500 involves importing the mesh file into the simulation software and associating it with the simulation program to obtain the solution model, including the following steps B1~B2: B1: Import the mesh file into the simulation software and configure the mesh file according to the solver and preset model in the simulation software.

[0061] Specifically, import the mesh file into the preset simulation software Fluent, enter the software's operation condition settings interface, and start the gravity model.

[0062] It should be noted that the gravity model simulates the effect of gravity on the hydrostatic pressure of the fluid in the entire flow channel of the turbine, ensuring that the distribution of hydrostatic pressure at different heights in the flow channel conforms to actual physical laws.

[0063] Furthermore, in the solution method settings, the SIMPLEC solver is selected to solve for various physical quantities of the flow field in the entire turbine channel. At the same time, in the Models module of the software, the multiphase flow model and the cavitation model are opened. The density gradient of the cavitation model can be adaptively adjusted according to the pressure gradient, thereby completing the adaptation configuration of the mesh file.

[0064] B2: Match the four simulation programs with the configured mesh file to obtain the solution model.

[0065] Specifically, the code is imported into the Fluent simulation software, and the compilation is completed according to the software compilation process to ensure that the simulation program has no syntax errors.

[0066] Furthermore, in the BoundaryConditions interface of the software, the compiled upstream inlet and downstream outlet pressure distribution boundary condition UDF simulation program is associated with the inlet and outlet boundaries of the configured mesh file; in the SolutionMethods page, the momentum equation UDF simulation program considering surface tension is matched with the momentum calculation module of the mesh file; in the MassTransfer page, the density cavitation model UDF simulation program is matched with the cavitation calculation module of the mesh file. Through parameter transfer between modules, the compiled simulation program and the mesh file are adapted. The adapted simulation program and the mesh file are then combined to obtain the solution model.

[0067] In the implementation steps of this invention, step S600 involves processing the solution model using simulation software, and outputting the result after the processing meets the convergence condition, including the following steps C1~C4: C1: Initialize the solution model with water flow data when the turbine's operating status does not exceed the deviation threshold.

[0068] Specifically, key parameters such as the pressure value corresponding to the upstream inlet submersion depth, the pressure value corresponding to the downstream outlet submersion depth, the rated operating flow rate, and the rated speed of the turbine runner are collected to ensure that the deviation of these data from the actual operating state of the turbine is controlled within 3% of the deviation threshold.

[0069] Furthermore, these flow data that meet the deviation requirements are imported into the simulation software, and the solution model is initialized in the form of a steady-state initial field so that the initial state of the model is consistent with the actual stable operating state of the turbine.

[0070] C2: Based on the simulation software, the calculation step size is set according to the actual speed of the turbine by solving the model.

[0071] Specifically, the actual rotational speed of the turbine is obtained, and the time taken for the runner to rotate 3° is calculated based on this speed. This time is then set as the calculation step size for the simulation software.

[0072] C3: Calculation results based on the step size monitoring solution model.

[0073] Specifically, after each calculation step is completed, the calculation results of the solution model are automatically extracted, including the pressure data of each grid cell in the entire flow channel of the turbine, the equivalent density data of the mixed medium, the volume fraction of the gas and liquid phases, as well as the pressure gradient and flow velocity distribution on the guide vane wall and the runner blade surface. Furthermore, real-time tracking of key indicator changes is conducted to monitor whether local pressures fall below the saturated vapor pressure at the corresponding water temperature, and whether the density adjusts with pressure changes.

[0074] C4: When the result is within the error threshold, if the result satisfies the convergence condition, output the solution model of the current state.

[0075] Specifically, based on the physical quantities of the turbine cavitation simulation, error thresholds are established, including the following: the average pressure change rate of the entire flow channel between adjacent calculation steps ≤1%, the equivalent density change rate of the mixed medium ≤2%, and the water vapor volume fraction change rate ≤3%.

[0076] Furthermore, when the results are within the error threshold, the output includes various physical quantities of the flow field.

[0077] In summary, this invention constructs a geometric model computational domain using the structural parameters of the entire flow channel of a hydropower turbine, thus establishing a model for the flow channel range required for cavitation simulation of the turbine. By processing the computational domain of the geometric model to obtain geometric files, the geometric data is adapted to subsequent mesh generation software. By importing the geometric files into a pre-defined mesh generation software for processing to obtain mesh files, mesh construction meeting computational accuracy requirements is achieved. Based on the turbine's operating conditions, code is constructed and input into the simulation software for compilation, resulting in a simulation program. This achieves computational logic matching the actual operating conditions of the turbine, ensuring simulation parameters closely match real-world operation. Importing the mesh files into the simulation software and associating them with the simulation program to obtain the solution model demonstrates the synergy between mesh data and computational logic, constructing a complete model suitable for cavitation simulation. Finally, by processing the solution model using simulation software and outputting the results when convergence conditions are met, accurate prediction and output of turbine cavitation characteristics are achieved, providing effective data support for analyzing cavitation impacts.

[0078] Example 3 is the third embodiment of the present invention. This embodiment provides a hydropower station cavitation simulation and prediction system, including...

[0079] The model construction module constructs a geometric model computational domain based on the structural parameters of the entire flow channel of the turbine in the hydropower station.

[0080] The geometry file configuration module processes the computational domain of the geometric model to obtain the geometry file.

[0081] The mesh file configuration module imports geometric files into preset mesh generation software for processing to obtain mesh files.

[0082] The code construction module constructs code based on the operating conditions of the turbine, and then inputs the code into the simulation software to complete the compilation and obtain the simulation program.

[0083] The solution model construction module imports the mesh file into the simulation software and associates it with the simulation program to obtain the solution model.

[0084] The simulation result output module uses simulation software to process the solved model and outputs the results when the processing results meet the convergence conditions.

[0085] Example 4, the fourth embodiment of the present invention, differs from the previous three embodiments in that: if the function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0086] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0087] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0088] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination of all three. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0089] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for cavitation simulation and prediction in hydropower stations, characterized in that: include, A geometric model computational domain is constructed based on the structural parameters of the entire flow channel of the turbine in a hydropower station. The computational domain of the geometric model is processed to obtain a geometric file; The geometric file is imported into a preset mesh generation software for processing to obtain a mesh file; The operating condition code of the water turbine is constructed, and the code is input into the simulation software to complete the compilation and obtain the simulation program; The mesh file is imported into the simulation software and associated with the simulation program to obtain the solution model; The simulation software is used to process the solution model, and the result is output when the processing condition is met.

2. The cavitation simulation and prediction method for hydropower stations as described in claim 1, characterized in that: The steps to obtain the geometry file include: A geometric model computational domain is constructed based on the structural parameters of the entire flow channel of the turbine in the power station. The computational domain of the geometric model is defined, and the defined computational domain is converted into an adaptive format according to the preset mesh generation software type to generate the geometric file.

3. The cavitation simulation and prediction method for hydropower stations as described in claim 2, characterized in that: The steps to obtain a grid file include: The geometry file is imported into the mesh generation software, which then sends a structured mesh generation command to perform mesh generation on the turbine full-flow channel structure parameters corresponding to the geometry file using the structured mesh generation. The structural partitioning includes mesh refinement or boundary layer partitioning.

4. The cavitation simulation and prediction method for hydropower stations as described in claim 3, characterized in that: The steps for constructing the code based on the operating conditions of the water turbine include: Based on the pressure distribution boundary conditions, surface tension and density under the actual operating conditions of the water turbine, a Y-segment code is constructed, and the Y-segment code is input into the simulation software for compilation to obtain the simulation program. The simulation program is then subjected to syntax verification to complete the construction of the code.

5. The cavitation simulation and prediction method for hydropower stations as described in claim 4, characterized in that: The steps to obtain the solution model include: The mesh file is imported into the simulation software, and the mesh file is configured according to the solver and preset model in the simulation software. The code is imported into the simulation software for compilation. The compiled simulation program is then matched with the configured mesh file to obtain the solution model.

6. The cavitation simulation and prediction method for hydropower stations as described in claim 5, characterized in that: The steps of processing the solution model using the simulation software include: The water flow data when the turbine's operating state does not exceed the deviation threshold is used to initialize the solution model.

7. The cavitation simulation and prediction method for hydropower stations as described in claim 6, characterized in that: The steps for outputting the result after the processing meets the convergence condition include: The simulation software sets the calculation step size according to the actual rotational speed of the water turbine. The calculation results of the solution model are monitored based on the step size; When the result is within the error threshold, and the result satisfies the convergence condition, the solution model of the current state is output.

8. A hydropower station cavitation simulation and prediction system, employing the hydropower station cavitation simulation and prediction method as described in any one of claims 1 to 7, characterized in that, include: The model construction module constructs a geometric model computational domain based on the structural parameters of the entire flow channel of the turbine in the hydropower station. The geometry file configuration module processes the computational domain of the geometry model to obtain the geometry file; The mesh file configuration module imports the geometry file into a preset mesh generation software for processing to obtain the mesh file. The code construction module, based on the operating conditions of the water turbine, encodes the data and inputs it into the simulation software to complete the compilation and obtain the simulation program; The solution model construction module imports the mesh file into the simulation software and associates it with the simulation program to obtain the solution model; The simulation result output module processes the solution model using the simulation software and outputs the result when the processing result meets the convergence condition.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the hydropower station cavitation simulation and prediction method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the hydropower station cavitation simulation and prediction method according to any one of claims 1 to 7.

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