Numerical calculation method of hydrofoil cavitation dynamics evolution induced energy release mechanism

Abstract

The invention discloses a numerical calculation method for a hydrofoil cavitation dynamics evolution induced energy release mechanism. The numerical calculation method comprises the following steps: constructing a hydrofoil streaming flow field calculation domain; dividing grids for the computational domain, and importing the grids of the computational domain into computational fluid mechanics simulation software; setting a boundary condition and a solution algorithm of hydrofoil cavitation calculation, selecting a discrete phase model, and injecting multiple particles into the head of the hydrofoil; through cavitation flow field calculation, motion characteristics of cavitation bubbles in a cavitation flow field are obtained based on the motion data of the particles; and constructing a multi-cavitation energy numerical model considering the cavitation aggregation effect, and coupling the multi-cavitation energy numerical model with the cavitation kinetic equation to obtain the cavitation radius, the internal pressure, the energy distribution rule and the release mechanism in the cavitation flow. By means of the method, reliable calculation of cavitation characteristic changes of the hydrofoil surface cavitation flow in different forms is achieved, theoretical reference is provided for revealing cavitation dynamics evolution induced energy release, and meanwhile prediction means of energy conversion in the hydraulic machinery cavitation flow with the airfoil section as a basic blade unit are enriched.

Description

Technical Field

[0001] This invention belongs to the field of cavitation energy detection, specifically relating to a numerical calculation method for the energy release mechanism induced by the cavitation dynamic evolution of a hydrofoil. Background Technology

[0002] Cavitation is a phase change phenomenon that occurs when the local pressure in a liquid falls below the saturated vapor pressure at the ambient temperature, typically in high-speed flowing liquids. Liquids in low-pressure cavitation zones carry numerous air bubbles, forming a two-phase flow that disrupts the macroscopic continuity of the liquid. These air bubbles collapse as they flow through areas of higher pressure. Therefore, cavitation encompasses various unsteady processes, including bubble formation, growth, contraction, collapse, and disappearance. Cavitation is most common in hydraulic machinery, which uses liquid as its working medium. The intense shock waves generated by the continuous collapse of air bubbles can cause cavitation erosion damage to the surfaces of hydraulic machinery components, affecting their service life and overall performance. Therefore, accurately predicting the structural changes in cavitation flow, analyzing the dynamic behavior during bubble collapse, calculating the energy impact of bubble collapse, and resolving the transformation mechanisms between air bubbles are crucial for understanding and controlling cavitation.

[0003] Due to the unsteady spatiotemporal evolution of cavitation bubbles in actual cavitation flow fields, the diversity of their existence forms, and the complexity of their interactions, current predictions of cavitation energy mostly rely on experimental methods such as high-speed photography, miniature pressure sensors, and hydrophones to capture data on kinetic energy and shock wave energy within the flow field. However, purely experimental methods are insufficient to obtain complete and detailed flow field data and are highly susceptible to interference from external factors. Therefore, numerical simulation methods are necessary for further research. Researchers have established a theoretical model of cavitation energy conversion based on the Rayleigh-Plesset equations for spherical cavitation collapse to obtain specific values ​​for energy conversion, including cavitation potential energy, flow field kinetic energy, and pressure wave energy. However, research on the influence of cavitation evolution dynamics on cavitation energy at different levels is still in its early stages, especially regarding the energy release from cavitation bubbles in multi-cavitation scenarios, which requires further in-depth investigation.

[0004] Therefore, this invention studies a numerical model of multi-cavitation energy, providing important theoretical support for improving the prediction accuracy of cavitation release energy. Summary of the Invention

[0005] The purpose of this invention is to address the aforementioned problems by proposing a numerical calculation method for the energy release mechanism induced by the cavitation dynamics evolution of hydrofoils. This method is based on an accurate simulation of the spatiotemporal evolution of cavitation in unstable hydrofoils. By obtaining the instantaneous pressure at the location of the cavitation bubble in the flow field, and coupling the cavitation dynamics equation and energy equation, instantaneous change data such as the internal pressure and radius of the cavitation bubble are obtained, thereby calculating the energy contained in and released by a single cavitation bubble during collapse. Furthermore, a numerical model of multi-cavitation energy is provided to obtain the energy conversion and release mechanism during the entire cavitation group evolution process in actual multi-cavitation scenarios. This provides an effective and feasible numerical model for predicting the energy induced by cavitation in hydraulic machinery with airfoils as the basic blade unit, improving the accuracy of cavitation energy prediction in actual multi-cavitation scenarios.

[0006] The technical solution of this invention is a numerical calculation method for the energy release mechanism induced by the cavitation dynamics evolution of a hydrofoil, comprising the following steps: Step 1: Construct the computational domain for the flow field around the hydrofoil; Step 2: Mesh the computational domain and define the inlet and outlet boundaries and solid wall conditions of the computational domain; Step 3: Import the computational domain mesh obtained in Step 2 into the fluid dynamics simulation software; Step 4: Set the boundary conditions and solution algorithm for hydrofoil cavitation calculation, select the discrete phase model, and inject multiple particles into the hydrofoil head; Step 5: Obtain the data of the particle through cavitation flow field simulation calculation, and solve the cavitation dynamics equation to obtain the internal pressure and radius data of the cavitation at the particle's location; Step 6: Based on the internal pressure and radius data of the cavitation bubble, solve the energy equation for the spherical single cavitation bubble; Considering the cavitation aggregation effect, a multi-cavitation energy numerical model is established to modify the energy equation of a spherical single cavitation, thereby obtaining the energy distribution characteristics of cavitation on the hydrofoil surface and the energy released by the cavitation cluster.

[0007] Preferably, in step 1, the calculation domain for the hydrofoil cavitation flow field is constructed by using the drawing software Solidworks to model the external fluid region of the hydrofoil.

[0008] Preferably, step 2 includes the following sub-steps: Step 2.1: Import the computational domain file from Step 1 into the network partitioning software ICEM CFD, and name the boundaries of the computational domain; Step 2.2: Construct the initial topological block structure of the mesh. By appropriately dividing the block structure of the hydrofoil surface into independent blocks and performing "O"-shaped partitioning, the number of mesh nodes is set according to the line length on the computational domain. The "O"-shaped blocks are set with a sufficiently dense mesh along their normal direction so that the body-fitting mesh is located within the boundary layer.

[0009] Preferably, in step 3, the computational domain mesh file obtained in step 2 is read using the fluid dynamics simulation software ANSYS FLUENT, and reduced to 1 / 1000 of its original size, and the mesh quality is checked to see if it meets the computational requirements.

[0010] Preferably, step 4 specifically includes the following sub-steps: Step 4.1: Set the solver to unsteady mode, set the turbulence model to mixed turbulence model, and the cavitation model to Schnerr-Sauer cavitation model; Step 4.2: Set the working fluid to liquid water and cavitation, set the main properties of liquid water and cavitation, set the computational domain inlet to the velocity inlet boundary, set the computational domain outlet to the pressure outlet boundary, and set the hydrofoil surface and upper and lower boundaries to be free, slip-free walls. Step 4.3: Set the pressure-velocity coupling mode, and select a high-order format for the interpolation of gradient, pressure, momentum, and volume fraction; Step 4.4: Open the discrete phase model, select the massless particle type, inject multiple particles into the hydrofoil head, and activate the discrete phase random motion model.

[0011] Preferably, in step 5, the CFD-POST post-processing module is used to obtain data on the cloud cavitation evolution process and mechanical properties within one cycle, and this data is compared with experimental results obtained by high-speed imaging under the same operating conditions of the hydrofoil to ensure the reliability and accuracy of the hydrofoil cavitation flow field data. Using MATLAB software, the pressure along the cavitation flow field experienced by the injected particles is used as the driving pressure at each time point to solve the cavitation dynamics equation, thereby obtaining the internal pressure and radius values ​​of the cavitation bubble.

[0012] Preferably, in step 6, the mathematical expression of the multi-cavitation numerical model is: ; In the formula, λ Distance The expected value of having no other cavitation events; N core The cavitation nucleus number density; Indicates the number of cavitation bubbles. k ! is the factorial of the number of other cavitation events that occur; R Indicates the initial radius r The instantaneous radius of the cavitation nucleus of 0; R 1. R 2 represents the initial radius. r The maximum and minimum radii that a cavitation nucleus of size 1 can achieve without disturbance; Represents the probability density function. This represents the maximum radius of the cavitation bubble during the cavitation growth stage. This represents the energy of an isolated single cavitation bubble. This represents the corrected single-cavitation energy. Indicates the distance between cavitation nuclei. This is the spatial distribution function of cavitation.

[0013] Compared with the prior art, the beneficial effects of the present invention include: 1) The numerical calculation method for the energy release mechanism induced by the cavitation dynamics evolution of hydrofoils provided by this invention realizes high-precision prediction of cavitation energy release induced by cavitation dynamics evolution under multi-cavitation scenarios, provides theoretical support for revealing the energy conversion and release mechanism of cavitation swarms under the influence of cavitation aggregation effect, and enriches the prediction means of cavitation energy problems of hydraulic machinery with airfoils as the basic blade unit.

[0014] 2) It pioneered a multi-cavitation aggregation effect correction mechanism, breaking through the limitations of the traditional single-cavitation model, and proposed a multi-cavitation energy coupling algorithm based on the cavitation spatial distribution probability function and the cavitation interaction correction equation; it quantified the impact of "cavitation-cavitation" interaction on collapse energy in the evolution of cavitation groups, and solved the industry problem of large energy prediction deviation in multi-cavitation scenarios.

[0015] 3) This invention provides a multi-scale cavitation energy analysis mechanism: at the micro level, the energy ratio of the collapse shock wave is revealed by the explicit separation calculation method of the potential energy and kinetic energy of a single cavitation bubble; at the meso level, the energy of the cavitation bubble population is corrected by the cavitation core density to quantify the energy accumulation effect of the cavitation bubble accumulation area; at the macro level, the cavitation energy distribution cloud map of the hydrofoil surface is used to locate high-risk areas of cavitation erosion.

[0016] 4) This invention employs a hybrid turbulence model and the Schnerr-Sauer model to capture the periodic cavitation evolution and instantaneous lift coefficient of the hydrofoil surface, achieving high computational accuracy. It provides reliable data on the instantaneous changes in flow field parameters such as pressure and cavitation volume fraction for cavitation energy calculation. Through a multi-cavitation energy coupling algorithm and a high-precision cross-scale solver, it achieves full-link quantitative prediction from "microscopic energy of single cavitation collapse" to "macroscopic cavitation damage of hydraulic machinery." It establishes significant technical advantages in three dimensions: prediction accuracy, engineering applicability, and cross-domain scalability, providing a new generation of theoretical tools for cavitation protection design of high-end equipment.

[0017] 5) Based on the Gilmore-NASG cavitation dynamics equation, the liquid phase multivariate index is introduced to accurately characterize the liquid compressibility, and a thermodynamic correction term is introduced to make up for the insufficient prediction of gas phase heat capacity. A high-precision cavitation dynamics solution system is constructed, which can be applied to high driving pressure scenarios and the error is significantly reduced compared with the traditional model.

[0018] 6) The discrete phase particle tracking method is coupled with the instantaneous pressure of cavitation to achieve dynamic mapping of cavitation trajectory and collapse energy; the O-type meshing combined with the boundary layer densification mesh strategy greatly improves the boundary layer resolution and the accuracy of cavitation fall-off capture. Attached Figure Description

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Figure 1 This is a schematic diagram of the hydrofoil cavitation energy prediction process according to an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of the hydrofoil cavitation calculation domain according to an embodiment of the present invention.

[0022] Figure 3 This is a schematic diagram of the hydrofoil cavitation computational domain mesh division according to an embodiment of the present invention.

[0023] Figure 4 This is a schematic diagram of the mechanism of the numerical calculation model of multi-cavitation energy on the hydrofoil cavitation surface in an embodiment of the present invention.

[0024] Figure 5 This is a comparison chart of the calculated results and experimental results of cavitation evolution and instantaneous lift coefficient changes during the cavitation cycle of this invention.

[0025] Figure 6 This is a schematic diagram of the predicted results of the single-cavitation dynamic characteristics of the hydrofoil surface according to an embodiment of the present invention.

[0026] Figure 7 This is a schematic diagram of the predicted results of the multi-cavitation energy characteristics of the hydrofoil surface according to an embodiment of the present invention. Detailed Implementation

[0027] In this embodiment, the chord length of the hydrofoil is c =0.07m, angle of attack is α =8°.

[0028] like Figure 1 As shown, the numerical calculation method for the energy release mechanism induced by the cavitation dynamics evolution of a hydrofoil includes the following steps: Step 1: Construct the computational domain for the flow field around the hydrofoil; A hydrofoil cavitation computational domain is constructed, with an overall rectangular shape, and the hydrofoil located inside it, as follows: Figure 2 As shown. The length and width of the computational domain are set to 10 respectively. c and 2.7 c The distance from the top to the leading edge of the hydrofoil is 1.35. c The distance from the outlet to the leading edge of the hydrofoil is 7. c , cThis represents the chord length of the hydrofoil. The external flow field of the hydrofoil was modeled using the Solidworks drawing tool, and the computational domain was saved as a step format transfer file.

[0029] Step 2: Mesh the computational domain from Step 1, and define the inlet and outlet boundaries and solid wall conditions of the computational domain. The meshed computational domain is as follows: Figure 3 As shown.

[0030] Step 2.1: Import the computational domain file from Step 1 into the mesh generation software ICEM CFD. Referring to the water flow direction, define the inlet boundary, outlet boundary, upper and lower walls, and hydrofoil surface of the computational domain, and complete the boundary naming of the computational domain. Step 2.2: Create the initial topological block structure of the mesh. Independently divide the block structure of the hydrofoil surface through appropriate partitioning and perform an "O"-shaped mesh. Then, set the number of mesh nodes according to the line length in the computational domain. Set a sufficiently dense mesh along the normal direction for the "O"-shaped blocks, and set the thickness of the first boundary layer to 3×10⁻⁶. -6 m, with a growth rate of 1.12, outputs a .msh file.

[0031] Step 3: Import the mesh file obtained in Step 2 into the computational fluid dynamics simulation software, check the mesh quality and scale it.

[0032] Use ANSYS FLUENT software to read the mesh file obtained in step 2, scale it down to 1 / 1000 of its original size using the Scale Factor command, and use the Check command to check the mesh quality to determine whether it meets the calculation requirements.

[0033] Step 4: Set the boundary conditions and solution algorithm for hydrofoil cavitation calculation, and select the discrete phase model.

[0034] Step 4.1: Select the unsteady mode as the solver, set the turbulence model to the Filter-Based Density Correction Model (FBDCM), and the cavitation model to the Schnerr-Sauer (SS) cavitation model.

[0035] Step 4.2: Set the working fluid to liquid water and cavitation. The density and viscosity of the liquid water are respectively... ρ l =1000 kg / m 3 , μ l =1.139×10 -3 Pa.s; the density and viscosity of the cavitation bubbles are respectively ρ v =0.02308kg / m3 , μ v =9.8626×10 -6 Pas. The computational domain inlet boundary is set as a velocity condition, with a velocity magnitude of... U =10 m / s; the outlet boundary is under pressure conditions, and the outlet pressure value is calculated based on the cavitation number. Sheet-like, cloud-like, and hypercavitated forms ( σ The corresponding outlet pressures at (= 0.4, 0.8, 1.4) are 23152.8MPa, 43136.6MPa, and 73112.3MPa, respectively. The top, bottom, and hydrofoil surfaces of the computational domain are solid, non-slip walls.

[0036] Step 4.3: Set the pressure-velocity coupling mode to SIMPLE format, the gradient interpolation to Least Squares Cell Based format, the pressure interpolation to Pressure Staggering Option (PRESTO!) format, the momentum interpolation to Bounded Central Differencing format, and the volume fraction to QUICK format. Set the convergence residual standard for all physical quantities to 1×10⁻⁶. -6 To improve calculation accuracy.

[0037] Step 4.4: Open the discrete phase model, select the massless particle type, select group as the jet source type, inject 100 particles at the vertical normal position of the hydrofoil head, and activate the discrete phase random motion model.

[0038] Step 5: Obtain the injected particle data through cavitation flow field calculation, solve the cavitation dynamics equation, and obtain data such as the radius and internal pressure of the cavitation at the particle location.

[0039] The Gilmore-NASG cavitation dynamics equation is an equation suitable for solving cavitation problems under high driving pressures and overcomes the shortcomings of traditional methods in predicting liquid heat capacity. The mathematical expression of the cavitation dynamics equation is as follows: ; In the formula, the subscript l and v These represent the physical parameters in liquid water and gas phases, respectively; subscripts ref Reference values ​​representing physical parameters; R Where is the cavitation radius, A reference value representing the cavitation radius; C l The velocity of sound of liquid water at the wall of the cavitation bubble; H This represents the difference in enthalpy between liquid water at the cavitation wall and at infinity. express H The derivative; p ∞ Indicates far-field pressure; Indicates environmental pressure; p a Indicates driving pressure; Indicates the pressure of the air bubble. This indicates the pressure of the vapor inside the bubble. ; Indicates reference pressure. Indicates the reference pressure for cavitation; b v The volume is the same as the volume of gas molecules; ρ Indicates the density of each phase; B The pressure constant related to the material; Γ Indicates multiple indices, The multivariate index of liquid water; γ It is the surface tension coefficient; Indicates the pressure of liquid water. This represents the density of the cavitation bubble. This represents the density of liquid water. This represents the density of the liquid phase in the undisturbed far field. This represents the reference value for cavitation density. , These represent the pressure constants of liquid water and air bubbles, respectively. Let be the viscosity coefficient of liquid water, and t represent time. T This indicates the gas phase temperature inside the cavitation bubble. Indicates reference temperature. Indicates the radial velocity of the cavitation bubble. This represents the radial acceleration of the cavitation bubble.

[0040] Cloud cavitation is obtained through CFD-POST post-processing. σ = 0.8) The calculation results of the periodic cavitation evolution and instantaneous lift coefficient of the hydrofoil surface under the operating condition are compared with the experimental values, such as Figure 5 As shown, Figure 5 China T b This represents the cavitation period. The pressure along the path of the injected particles in the flow field is obtained and used as the driving pressure in the cavitation dynamics equations. The cavitation radius and internal pressure data at the particle's position are then calculated, such as... Figure 6 As shown.

[0041] Step 6: Based on the data such as the internal pressure and radius of the cavitation bubble, solve the energy equation of the spherical single cavitation bubble, and then construct a multi-cavitation energy numerical model that considers the cavitation bubble aggregation effect. Modify the energy equation of the single cavitation bubble to obtain the energy distribution characteristics of cavitation on the hydrofoil surface and the energy release mechanism of the cavitation bubble cluster.

[0042] The numerical model of multi-cavitation energy is a numerical model that calculates the energy equation of multi-cavitation based on solving the energy equation of a single-cavitation bubble. The energy equation of a microscopic single-cavitation bubble assumes that the cavitation bubble collapses spherically and treats the flow field as an infinitely distant domain. The mathematical expression is as follows: ; In the formula, U r The velocity of the cavitation bubble; ρ The flow field density; μ The viscosity coefficient of the fluid; F For surface forces; R Where is the cavitation radius; γ The tension coefficient at the surface of the cavitation bubble. For cavitation parameters, r Indicates the cavitation core radius, This represents the potential energy of a single cavitation bubble. Represents the kinetic energy density of a infinitesimal element. This represents the total kinetic energy of the flow field. This represents the rate of change of the radial velocity of the cavitation bubble with time. This represents a differential operator.

[0043] The modified multi-cavitation energy equation is a calculation method that considers the cavitation nucleus density and cavitation aggregation effect. It is a distribution function of cavitation number density as a function of radius, derived by combining the distribution function of cavitation radius and cavitation nucleation density. Its mathematical expression is as follows: ; In the formula, λ Distance The expected value of having no other cavitation events; N core The cavitation nucleus number density; Indicates the number of cavitation bubbles. k ! is the factorial of the number of other cavitation events that occur; R Indicates the initial radius r The instantaneous radius of the cavitation nucleus of 0; R 1. R 2 represents the initial radius. r The maximum and minimum radii that a cavitation nucleus of size 1 can achieve without disturbance; Represents the probability density function. This represents the maximum radius of the cavitation bubble during the cavitation growth stage. This represents the energy of an isolated single cavitation bubble. This represents the corrected single-cavitation energy. Indicates the distance between cavitation nuclei. This is the spatial distribution function of cavitation.

[0044] The mechanism of the constructed multi-cavitation numerical calculation model is as follows: Figure 4 As shown, when the distance between cavitation bubbles is sufficiently large—that is, the distance between the centers of two adjacent cavitation bubbles is much greater than the sum of the peak radii of the two cavitation bubbles—each cavitation bubble develops and collapses independently. Conversely, when cavitation bubbles approach each other, the energy inside the outer cavitation bubble is mainly transferred to the inner cavitation bubble, and finally, evolution and energy conversion occur in the form of a single cavitation bubble. For an initial radius of... r 0 cavitation nuclei a The initial radius of the adjacent ones is r 1 cavitation nucleus b Its maximum radius that can be achieved during the cavitation growth stage is from L ( r ) indicates that when a and b The distance between them exceeds L(r 0)+ L ( r 1) At that time, cavitation nuclei a The entire cavitation process can be completed without interference from other bubbles. Based on the above mechanism, the cavitation energy is calculated and corrected to obtain the energy distribution of multiple cavitation bubbles on the hydrofoil surface, as shown below. Figure 7 As shown.

[0045] The system for numerical calculation of the above-mentioned hydrofoil cavitation energy release mechanism includes: Cavitation dynamics equation solving module: used to solve the cavitation dynamics equation to obtain the internal pressure and radius data of the cavitation in the flow field around the hydrofoil; Single-cavitation bubble energy solution module: Based on the internal pressure and radius data of the cavitation bubble output by the cavitation dynamics equation solution module, the energy equation of the spherical single-cavitation bubble is solved to obtain the energy characteristic data of the cavitation bubble; Multi-cavitation energy solution module: Based on the multi-cavitation energy numerical model, the energy characteristic data of the single cavity output by the single cavity energy solution module is corrected to obtain the multi-cavitation energy distribution characteristic data of the hydrofoil surface.

[0046] The above detailed description further illustrates the purpose, technical solution, and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the numerical algorithm and principle of the present invention should be included within the scope of protection of the present invention.

Claims

1. A numerical calculation method for the energy release mechanism induced by the cavitation dynamics evolution of a hydrofoil, characterized in that, Includes the following steps: Step 1: Construct the computational domain for the flow field around the hydrofoil; Step 2: Mesh the computational domain and define the inlet and outlet boundaries and solid wall conditions of the computational domain; Step 3: Import the computational domain mesh obtained in Step 2 into the fluid dynamics simulation software; Step 4: Set the boundary conditions and solution algorithm for hydrofoil cavitation calculation, select the discrete phase model, and inject multiple particles into the hydrofoil head; Step 5: Obtain the data of the particle through cavitation flow field calculation, and solve the cavitation dynamics equation to obtain the internal pressure and radius data of the cavitation at the particle's location; Step 6: Based on the internal pressure and radius data of the cavitation bubble, solve the energy equation for a spherical single cavitation bubble; Considering the cavitation aggregation effect, a multi-cavitation energy numerical model is established to modify the energy equation of a spherical single cavitation, thereby obtaining the energy distribution characteristics of cavitation on the hydrofoil surface and the energy released by the cavitation cluster.

2. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 1, characterized in that, In step 1, the calculation domain for the hydrofoil cavitation flow field is constructed by using the drawing software Solidworks to model the external fluid region of the hydrofoil.

3. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 1, characterized in that, Step 2 specifically includes the following sub-steps: Step 2.1: Import the hydrofoil flow field calculation domain file obtained in Step 1 into the network partitioning software ICEM CFD, and name the boundary of the calculation domain; Step 2.2: Construct the initial topological block structure of the mesh, and divide the block structure into "O" shaped blocks. Then, set the number of mesh nodes according to the line length on the computation domain, and set a dense mesh for the "O" shaped blocks along their normal direction so that the body-fitting mesh is located within the boundary layer.

4. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 3, characterized in that, In step 3, the computational domain mesh file obtained in step 2 is read using the fluid dynamics simulation software ANSYS FLUENT, and it is reduced to 1 / 1000 of its original size. The mesh quality is then checked to see if it meets the computational requirements.

5. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 4, characterized in that, Step 4 specifically includes the following sub-steps: Step 4.1: Set the solver to unsteady mode, set the turbulence model to mixed turbulence model, and the cavitation model to Schnerr-Sauer cavitation model; Step 4.2: Set the working fluid to liquid water and cavitation, set the main properties of liquid water and cavitation, set the computational domain inlet to the velocity inlet boundary, set the computational domain outlet to the pressure outlet boundary, and set the hydrofoil surface and upper and lower boundaries to be free, slip-free walls. Step 4.3: Set the pressure-velocity coupling mode, and select a high-order format for the interpolation of gradient, pressure, momentum, and volume fraction; Step 4.4: Open the discrete phase model, select the massless particle type, inject multiple particles into the hydrofoil head, and activate the discrete phase random motion model.

6. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 5, characterized in that, In step 4.3, the convergence residual standard for all physical quantities is set to 1×10⁻⁶. -6 .

7. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 5, characterized in that, In step 5, the CFD-POST post-processing module is used to obtain data on cloud cavitation evolution and mechanical properties within one cycle, and the data is compared with experimental results obtained by high-speed camera method under the same operating conditions of hydrofoil to ensure the reliability and accuracy of hydrofoil cavitation flow field data. Using MATLAB software, the pressure along the cavitation flow field experienced by the injected particles is used as the driving pressure at each time point to solve the cavitation dynamics equation, thereby obtaining the internal pressure and radius values ​​of the cavitation bubble.

8. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to any one of claims 1-7, characterized in that, In step 5, the mathematical expression of the cavitation dynamics equation is as follows: ； In the formula, the subscript l and v These represent the physical parameters in liquid water and gas phase, respectively. R Where is the cavitation radius, A reference value representing the cavitation radius; C l The velocity of sound of liquid water at the wall of the cavitation bubble; H This represents the difference in enthalpy between liquid water at the cavitation wall and at infinity. express H The derivative; p ∞ Indicates far-field pressure; Indicates environmental pressure; p a Indicates driving pressure; Indicates the pressure of the air bubble. This indicates the pressure of the vapor inside the bubble. ; Indicates reference pressure. Indicates the reference pressure for cavitation; b v The volume is the same as the volume of gas molecules; ρ Indicates the density of each phase; B The pressure constant related to the material; Γ Indicates multiple indices, The multivariate index of liquid water; γ It is the surface tension coefficient; Indicates the pressure of liquid water. This represents the density of the cavitation bubble. This represents the density of liquid water. This represents the density of the liquid phase in the undisturbed far field. This represents the reference value for cavitation density. , These represent the pressure constants of liquid water and air bubbles, respectively. Let be the viscosity coefficient of liquid water, and t represent time. T This indicates the gas phase temperature inside the cavitation bubble. Indicates reference temperature. Indicates the radial velocity of the cavitation bubble. This represents the radial acceleration of the cavitation bubble.

9. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 8, characterized in that, In step 6, the expression for the energy equation of the spherical single cavitation bubble is: ； In the formula, U r The velocity of the cavitation bubble; ρ The flow field density; μ The viscosity coefficient of the fluid; F For surface forces; R Where is the cavitation radius; γ The tension coefficient at the surface of the cavitation bubble. For cavitation parameters, r Indicates the cavitation core radius, This represents the potential energy of a single cavitation bubble. Represents the kinetic energy density of a infinitesimal element. This represents the total kinetic energy of the flow field. This represents the rate of change of the radial velocity of the cavitation bubble with time. This represents a differential operator.

10. The numerical calculation method for the hydrofoil cavitation energy release mechanism according to claim 9, characterized in that, In step 6, the mathematical expression of the multi-cavitation numerical model is: ； In the formula, Represents pi (π). λ Distance The expected value of having no other cavitation events; N core The cavitation nucleus number density; Indicates the number of cavitation bubbles. k ! is the factorial of the number of other cavitation events that occur; R Indicates the initial radius r The instantaneous radius of the cavitation nucleus of 0; R 1. R 2 represents the initial radius. r The maximum and minimum radii that a cavitation nucleus of size 1 can achieve without disturbance; Represents the probability density function. This represents the maximum radius of the cavitation bubble during the cavitation growth stage. This represents the energy of an isolated single cavitation bubble. This represents the corrected single-cavitation energy. Indicates the distance between cavitation nuclei. This is the spatial distribution function of cavitation.

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