A method for predicting and inhibiting cavitation of a valve under high-temperature working conditions

Abstract

This invention discloses a method for predicting and suppressing valve cavitation under high-temperature conditions, belonging to the field of fluid machinery and control technology. This method addresses the problem of inaccurate numerical simulation of valve cavitation under high-temperature conditions by introducing temperature corrections for the interface capture model, cavitation model, and working fluid properties during simulation. This accurately reflects the changes in the working fluid's properties in the actual high-temperature environment, improving the simulation accuracy of the cavitation flow field. Based on this, the entropy-pressure synergy criterion is applied to analyze the cavitation region, and the valve body structure is specifically optimized based on the analysis results. This invention effectively solves the problem of inaccurate numerical simulation of cavitation phenomena in valves under high-temperature conditions, and can provide precise guidance for the reliable design and performance optimization of valves in high-temperature conditions such as metallurgy.

Description

Technical Field

[0001] This application relates to the field of fluid machinery and control technology, and in particular to a method for predicting and suppressing valve cavitation under high-temperature conditions. Background Technology

[0002] As core components of fluid transmission and control in chemical processes, energy power, and aerospace, valves' performance reliability directly determines the operational stability of the entire equipment. In high-temperature industrial scenarios such as continuous casting in metallurgy, hydraulic systems face severe thermal conditions for extended periods. For example, in the billet guide section of a continuous casting machine or the descaling system of a hot rolling mill, ambient radiant heat and process heat load can keep the hydraulic oil temperature above 60°C, and even briefly exceed 80°C. Under such high-temperature conditions, cavitation is more likely to occur in valves due to the throttling effect—when the local pressure of the flow field is lower than the saturated vapor pressure corresponding to the current oil temperature, the liquid vaporizes violently, generating cavitation bubbles. These bubbles move with the fluid to the high-pressure area and collapse, generating microjet streams and shock waves that drastically exacerbate cavitation wear of the valve core and valve body materials, causing high-frequency vibration and noise in the system, seriously threatening the continuity and safety of production.

[0003] Currently, research methods for valve cavitation mainly fall into two categories: experimental studies and numerical simulations. However, experimental studies face significant challenges in high-temperature industrial environments such as metallurgy: the high-temperature, high-pressure, and closed-loop conditions make flow field visualization extremely difficult, resulting in high experimental costs, long cycles, and difficulty in capturing transient flow field details. While numerical simulation methods based on computational fluid dynamics (CFD) can compensate for these shortcomings, their accuracy still depends on the setting of physical property parameters. Existing numerical analysis methods fail to fully consider the decisive influence of key parameters such as the saturated vapor pressure, surface tension coefficient, and viscosity of hydraulic oil on cavitation dynamics under high-temperature conditions. This leads to deviations between simulation results and actual high-temperature conditions, failing to provide effective guidance for valve cavitation suppression and structural optimization, and has become a technical bottleneck restricting the performance improvement of high-heat-load equipment in metallurgy and other industries. Summary of the Invention

[0004] In view of this, the present application provides a method for predicting and suppressing valve cavitation under high temperature conditions, aiming to solve the problem that the numerical simulation results of cavitation in the prior art have large deviations from the actual results due to insufficient consideration of the influence of temperature on the physical properties of hydraulic oil.

[0005] According to an embodiment of this application, a method for predicting and suppressing valve cavitation under high-temperature conditions is provided, including:

[0006] S1: Construct the flow field model of the valve;

[0007] S2: The flow field model is meshed and refined to obtain a flow field mesh model;

[0008] S3: Perform simulation calculations on the flow field mesh model to obtain simulation results. The simulation requires setting up a turbulence model, an interface capture model, and a cavitation model, as well as adjusting the boundary conditions and hydraulic oil physical parameters according to the actual working conditions. The interface capture model, cavitation model, and hydraulic oil physical parameters are also corrected for temperature changes under high-temperature conditions.

[0009] S4: Process the simulation results to obtain the total gas volume in the flow field, as well as the pressure cloud map and the entropy yield distribution cloud map.

[0010] S5: The pressure cloud map and entropy yield distribution cloud map of the flow field are analyzed using the entropy-pressure synergy criterion to evaluate the cavitation phenomenon. The entropy-pressure synergy criterion divides the cavitation region into high, medium, and low entropy yield regions based on the ratio of local entropy yield to peak entropy yield in the entropy yield distribution cloud map. At the same time, a pressure safety margin is introduced, which is defined as the ratio of the minimum pressure of the flow field to the saturated vapor pressure of the working fluid at the current temperature. The region in the pressure cloud map with a pressure safety margin of less than 1 is defined as the low-pressure region where cavitation begins.

[0011] S6: Based on the analysis results of the entropy-pressure synergy criterion, optimize the high-entropy yield region and the low-pressure region, using the total gas volume in the flow field as the calculation basis, until the cavitation suppression coefficient is greater than or equal to the set threshold.

[0012] Optionally, a flow field model of the valve is constructed, including:

[0013] Based on the valve's structural parameters, a 3D modeling software is used to create a model. Boolean operations, volume extraction, or filling methods are then used to process the valve's geometric model to obtain the valve's flow field model.

[0014] Optionally, the flow field model is meshed and refined to obtain a flow field mesh model, including:

[0015] The flow field model is initially meshed, and then the mesh near the valve throttling orifice is locally refined; based on this, the locally refined mesh model is globally refined to generate the flow field mesh model.

[0016] Optionally, modifications to the interface capture model include:

[0017] Taking into account the influence of surface tension on the evolution of the cavitation interface, the surface tension effect is equivalent to a volume force source term acting on the momentum equation. The definition is as follows:

[0018] ;

[0019] In the formula, The surface tension coefficient of hydraulic oil; For interface curvature; The phase fraction gradient;

[0020] The surface tension coefficient of hydraulic oil Due to temperature variations, the following correction formula should be used for calculation:

[0021] ;

[0022] In the formula, 𝜎0 is the surface tension coefficient at the reference temperature; is the temperature coefficient of surface tension; T0 is the selected reference temperature; T is the temperature.

[0023] Optionally, modifications to the cavitation model include:

[0024] To characterize the temperature dependence of saturated vapor pressure, the saturated vapor pressures involved in the evaporation and condensation source terms in the cavitation model are corrected using the following functional relationship:

[0025] ;

[0026] In the formula, Where is the saturated vapor pressure; T is the temperature; A, B, and C are constants that are related to the saturated vapor pressure and temperature of the hydraulic oil.

[0027] Optionally, the correction of hydraulic oil physical properties includes:

[0028] When setting the physical properties of hydraulic oil, the influence of its viscosity on cavitation phenomena due to temperature changes must be considered. To accurately characterize this dependence, the following formula is used to correct the dynamic viscosity of hydraulic oil at different temperatures:

[0029] ;

[0030] In the formula, is the dynamic viscosity of the working fluid; T is the temperature; a and b are constants obtained from the viscosity-temperature curve of the hydraulic oil.

[0031] Optionally, the pressure safety margin is defined as the ratio of the minimum pressure of the flow field to the saturated vapor pressure of the hydraulic oil at the current temperature.

[0032] Optionally, based on the analysis results of the entropy-pressure synergy criterion, the high-entropy yield region and the low-pressure region are optimized, using the total gas phase volume in the flow field as the calculation basis, until the cavitation suppression coefficient is greater than or equal to a set threshold, including:

[0033] S61: Calculate the total volume of the first gas phase in the flow field mesh model before optimization;

[0034] S62: Based on the analysis results of the entropy-pressure synergy criterion, the high-entropy yield region and the low-pressure region are optimized;

[0035] S63: Calculate the total volume of the second gas phase in the optimized flow field mesh model;

[0036] S64: Calculate the cavitation suppression coefficient based on the first gas phase total volume and the second gas phase total volume. If the cavitation suppression coefficient is greater than or equal to the set threshold, it is determined that the cavitation suppression meets the requirements and the process ends; otherwise, return to S62 to continue the iteration.

[0037] Optionally, the expression for the cavitation suppression coefficient is as follows:

[0038] ;

[0039] In the formula, This is the cavitation suppression coefficient; The first gas phase total volume in the flow field mesh model before optimization; This represents the total volume of the second gas phase in the optimized flow field mesh model.

[0040] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0041] As can be seen from the above embodiments, this application adopts adaptive mesh refinement technology, which is a technical means of implementing fine mesh division in key flow field areas such as valve orifices. This overcomes the technical difficulties of low computational efficiency and difficulty in accurately capturing local cavitation flow details of traditional uniform meshes. As a result, it achieves the technical effect of significantly improving analysis efficiency and greatly reducing computational costs while ensuring computational accuracy.

[0042] This invention employs a temperature correlation equation to correct the interface capture model, cavitation model, and working fluid properties based on temperature changes. This overcomes the technical challenge of distorted cavitation numerical simulation caused by insufficient consideration of the temperature-dependent changes in physical properties under high-temperature conditions. As a result, the simulation results accurately reflect the true cavitation characteristics of the valve under actual high-temperature conditions.

[0043] This invention employs the entropy-pressure synergy criterion to analyze cavitation phenomena in valves, thereby locating high-entropy and low-pressure regions in the flow field. This overcomes the technical challenge of lacking reliable evidence for cavitation suppression, providing clear optimization guidance for cavitation suppression. Through targeted structural optimization, it effectively reduces the total volume of cavitation bubbles, ultimately significantly improving the service life and reliability of valves under high-temperature conditions.

[0044] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] Figure 1 This is a flowchart illustrating a valve cavitation prediction and suppression method under high-temperature operating conditions, according to an exemplary embodiment.

[0047] Figure 2 This is a valve body model shown according to an exemplary embodiment.

[0048] Figure 3 This is a flow field model illustrated according to an exemplary embodiment.

[0049] Figure 4 This is a grid number independence verification illustrated according to an exemplary embodiment.

[0050] Figure 5 This is a flow field pressure contour map illustrated according to an exemplary embodiment.

[0051] Figure 6 This is a flow field gas phase volume fraction cloud map illustrated according to an exemplary embodiment.

[0052] Figure 7 This is a cloud map illustrating the entropy yield distribution of a flow field according to an exemplary embodiment.

[0053] Figure 8 This is a flowchart illustrating cavitation suppression according to an exemplary embodiment. Detailed Implementation

[0054] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0055] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0056] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0057] Figure 1 This is a flowchart illustrating a valve cavitation prediction and suppression method under high-temperature operating conditions, according to an exemplary embodiment. Figure 1 As shown, this method, used in the flow channel of a labyrinth pressure-reducing valve, may include the following steps:

[0058] S1: Construct the flow field model of the valve;

[0059] Specifically, in 3D modeling software such as Solidworks or UG, the valve is modeled according to the relevant dimensions of the target valve and its components. Sharp edges or protrusions in the valve's geometric model are processed, such as chamfering or deletion. The valve is then assembled according to its working principle. The assembled model is saved as a .x_t file or other common file type. The model in this embodiment is as follows: Figure 2 As shown. In Ansys Workbench software, create a Fluent module, import the model file into the Design Modeler module, and use the edge surface function in the concept to create surfaces at the valve inlet and outlet respectively. Then, use the fill function in the tools to extract the flow field region model, or use software such as Space Claim or Discovery to extract the flow field region model. Since the valve geometry does not participate in the simulation calculation, physical suppression is applied to it. Name the generated labyrinthine pressure-reducing flow channel region model accordingly, such as naming the flow channel inlet as Inlet, the fluid outlet as Outlet, and the remaining surfaces as wall. The generated flow field model is as follows. Figure 3 As shown. This provides a realistic geometric basis for cavitation simulation, ensuring the accuracy and computational reliability of the simulation model as a whole.

[0060] S2: The flow field model is meshed and refined to obtain a flow field mesh model;

[0061] Specifically, the mesh module in Fluent is opened. In this embodiment, Meshing software is used for mesh generation, but Fluent Meshing, ICEM, and other software can also be used. First, a preliminary mesh generation is performed on the flow field model. The overall flow field model uses a hexahedral mesh structure with a size of 0.5 mm. For locations where cavitation needs to be captured, such as the corner region at the last stage of the flow channel, local mesh refinement is applied with a size of 0.1 mm. Simultaneously, boundary layers are added to the entire maze flow channel; in this embodiment, three boundary layers are used, each with a thickness of 50 μm. Based on this, global refinement is applied to the locally refined mesh model, thereby generating a series of models with different mesh counts. The independence of the flow field mesh count is verified as follows: Figure 4 To eliminate the potential impact of mesh size on simulation results, simulations were performed on flow field mesh models with different numbers of globally refined meshes under the same boundary conditions and operating conditions. By comparing the steam mass flow rate and pressure drop calculated from two adjacent mesh models, the mesh independence condition was considered satisfied when the error between the two was less than 1%, and the mesh model with the largest number of meshes was selected as the flow field mesh model for calculation. Verification ultimately determined that a mesh size of 269w was used for simulation calculations. This mesh generation scheme, combining overall structured meshing with local refinement, effectively controls the mesh size while ensuring computational accuracy, improves the ability to capture near-wall flow separation and cavitation phase change processes, and achieves an optimal balance between computational accuracy and efficiency.

[0062] S3: Perform simulation calculations on the flow field mesh model to obtain simulation results. The simulation requires setting up a turbulence model, an interface capture model, and a cavitation model, as well as adjusting the boundary conditions and hydraulic oil physical parameters according to the actual working conditions. The interface capture model, cavitation model, and hydraulic oil physical parameters are also corrected for temperature changes under high-temperature conditions.

[0063] Specifically, in the Fluent module settings, select and set the relevant models and parameters. In the general tab under the settings pane in the left overview view, select Transient Solution Settings and check the Gravity option. Set the y-axis value to -9.81. In the Model tab, check the Energy Equation, select SST k-ω for the Viscous Model, and select the VOF Multiphase Flow Model in the Multiphase Flow Model section, checking Coupled Level Set +VOF. Level-set function equations:

[0064]

[0065] In the formula, The phase field variable is t; time is t. Represents the velocity vector field of the fluid; This is the mobility coefficient; For interface thickness parameters; Find the gradient for the Nabla operator; This represents the rate of change of the phase field variable over time; This indicates a convection term.

[0066] Calculate the interface curvature based on the Level-set function equation. :

[0067]

[0068] The VOF volume fraction equation transforms the Level-set function into a volume fraction through the Heaviside function to ensure current mass conservation. The coupling relationship is as follows:

[0069]

[0070] In the formula, It is a constant, taken as 3.14159.

[0071] The Level-Set function can accurately capture the cavitation boundary, avoiding the interface blurring problem of the single VOF method. The VOF method, through real-time quality correction, makes up for the quality loss defect of the single Level-Set function. Through the coupling of VOF and Level-Set functions, the strict conservation of liquid volume fraction is ensured, and high-precision calculation of interface curvature is achieved.

[0072] Since the thermodynamic properties of hydraulic oil directly affect its surface tension, to quantify the impact of surface tension changes on the evolution behavior of the cavitation interface, the surface tension effect is equivalent to a volume force, and a corresponding volume force source term is introduced into the momentum control equation. The expression for this term is as follows:

[0073]

[0074] In the formula, It is the curvature of the interface; It is the liquid volume fraction; It is the surface tension coefficient, which is affected by temperature, and is calculated using the following correction formula:

[0075]

[0076] in, The surface tension coefficient at the reference temperature; The temperature coefficient of surface tension; For temperature; The selected reference temperature; for the phosphate ester synthetic hydraulic oil used in this embodiment under high-temperature conditions, Take 0.037, Take 0.0098, Take 293.15K.

[0077] By employing a continuous surface force model to transform surface tension into volume force, numerical oscillations that may occur when directly calculating interface curvature are avoided, thus enhancing the convergence of multiphase flow calculations. This improvement makes the predicted evolution behavior of cavitation interfaces under high-temperature environments more consistent with physical reality, significantly improving the simulation accuracy of cavitation models under variable temperature conditions.

[0078] In the phase settings interface, hydraulic-oil is set as the Primary Phase, and hydraulic-oil-vapor is set as the Secondary Phase. In the interphase interaction interface, the surface tension coefficient of the interphase interaction force is calculated using a modified formula. The phase change process is the transformation of hydraulic oil from the liquid phase to the gas phase. Therefore, in the heat, mass, and reaction interface, the mass transfer mechanism quantity is set to 1. From hydraulic-oil to hydraulic-oil-vapor, the mechanism is cavitation. The cavitation model is the Schnerr-Sauer model, which describes the cavitation phase change process occurring in the valve. The evaporation source term and condensation source term of this model are as follows:

[0079]

[0080]

[0081] in, and These are the densities of the liquid phase and the gas phase, respectively. It is the saturated vapor pressure; For pressure; It represents the liquid volume fraction; The bubble number density is set to 10. 13 .

[0082] Given the characteristic that the saturated vapor pressure of hydraulic oil changes with temperature, the saturated vapor pressure is calculated using the following formula using User-defined functions. Calculation:

[0083]

[0084] Where T is temperature; A, B, and C are constants related to the substance, fitted by the hydraulic oil saturated vapor pressure and temperature curve; for the phosphate ester synthetic hydraulic oil used in this embodiment under high temperature conditions, A is 93, B is 121401, and C is 1725.

[0085] In the Boundary Conditions tab, set the inlet velocity to 10 m / s, the working medium temperature to 345 K, the mixture horizontal set function flux to -0.1, the hydraulic-oil-vapor volume fraction to 0, and the outlet pressure to atmospheric pressure (101325 Pa). In the Materials tab, set the required working medium parameters. When setting the hydraulic oil properties, consider the effect of viscosity changes with temperature on cavitation; use the following formula to correct the dynamic viscosity of the hydraulic oil at different temperatures:

[0086]

[0087] in, The dynamic viscosity of the working fluid; For temperature; , b α is a constant, fitted using the viscosity-temperature curve of the hydraulic oil; for the phosphate ester synthetic hydraulic oil used in this embodiment under high-temperature conditions, α is taken as 2.5 × 10⁻⁶. -5 Pa·s, b is 2613K.

[0088] The physical property parameters determined based on real physical property data enable the model to accurately characterize the real behavior of specific hydraulic oils under high-temperature conditions. This dynamic correction mechanism of physical property parameters significantly improves the predictive reliability of cavitation models under variable temperature conditions, providing a theoretical basis for the precise design and optimization of high-temperature hydraulic systems.

[0089] The parameters for hydraulic oil and hydraulic oil vapor are shown in Table 1 below:

[0090] Table 1: Working Medium Properties Table;

[0091]

[0092] The solution settings were configured, and the pressure-velocity coupling algorithm was set to the PISO algorithm. The gradient term was discretized using a least-squares-based scheme, the pressure term using the PRESTO scheme, and the momentum, turbulence, energy, and composition equations were all discretized using a first-order upwind scheme. The hybrid initialization method was selected in the initialization tab for computational initialization, and the simulation results were obtained after running the calculation. By modifying the model, the distortion of physical parameters caused by neglecting temperature effects in traditional simulations was effectively solved, significantly improving the simulation accuracy of cavitation phase transition processes and interface evolution behavior under high-temperature conditions, making the simulation results more closely resemble the actual performance of the valve under real high-temperature conditions.

[0093] S4: Process the simulation results to obtain the total gas volume in the flow field, as well as the pressure cloud map and the entropy yield distribution cloud map.

[0094] Specifically, first create a new observation plane located on the XY Plane. Then, in the Graphics tab of the Results panel, create a contour plot, setting the coloring variable to Phases-Volume fraction and the phase to hydraulic-oil-vapor. Display the contour plot on the newly created observation plane, keeping the rest as default. Set the transient calculation data saving frequency to once per time step for subsequent flow animation generation and analysis. The storage type is In Memory, and the animation object is contour-1. After setting this, in the Run Calculation tab, set the time step to 10. -6 Then start the calculation. Open the Results module in Fluent, use Tecplot for post-processing, select Insert, then click Plane in Location. Keep the default plane name, select XY Plane for Method, set the Z position to 0, and keep the default Plane Bounds and Plane Type, but adjust them as needed. Finally, click Apply. Select the Contour option in Insert, name the contour plot "Pressure," select Plane 1 for Locations, select Pressure for Variable, and adjust the names of the rest as needed. Finally, click Apply to generate the pressure contour plot, as shown below. Figure 5 As shown, recreate the cloud map and name it Cavitation Volume Fraction. Select Plane 1 for Locations and hydraulic-oil-vapor. Volume Fraction for Variable. Adjust the rest as needed. Finally, click Apply to generate the gas phase volume fraction cloud map. Figure 6 As shown, the total gas phase volume in the flow field region can be calculated using the Function Calculator in the Calculator. However, the entropy yield distribution needs to be determined using the User-Defined function in Define. Select Interpreted in Functions to import the entropy yield calculation method. The entropy yield calculation method is as follows:

[0095]

[0096]

[0097]

[0098] in, For local entropy production rate, The entropy production rate caused by time-averaged motion. The entropy production rate caused by velocity fluctuations For energy transfer rate, For temperature, Viscosity, , , For velocity components, A constant of 0.09 For density, For turbulent dissipation rate, It is turbulent energy.

[0099] The rest follows the same generation method as described above, which can generate an entropy yield distribution cloud map, such as... Figure 7 As shown, this provides a basis for subsequent suppression of cavitation phenomena.

[0100] S5: The pressure cloud map and entropy yield distribution cloud map of the flow field are analyzed using the entropy-pressure synergy criterion to evaluate the cavitation phenomenon. The entropy-pressure synergy criterion is to divide the cavitation region into high, medium and low entropy yield regions based on the ratio of local entropy yield to peak entropy yield in the entropy yield distribution cloud map. At the same time, a pressure safety margin is introduced, and the region in the pressure cloud map with a pressure safety margin of less than 1 is defined as the low-pressure region where cavitation begins.

[0101] Specifically, the entropy-pressure synergy criterion is an analytical method that evaluates low-pressure regions and high-entropy-producing regions in the current flow field. The entropy-pressure synergy criterion is applied to the pressure contour map and entropy production rate distribution contour map of the flow field to analyze cavitation phenomena. In this embodiment, when cavitation occurs, the entropy production rate at a certain point in the flow field is defined as... The peak entropy yield is ,definition The region is a high-entropy productivity region. This is a region with medium entropy yield. It is a low-entropy production region.

[0102] Meanwhile, to quantify the impact of local pressure state on cavitation, a pressure safety margin is introduced. As a criterion, it is defined as the ratio of the minimum pressure in the flow field to the saturated vapor pressure of the hydraulic oil at the current temperature, i.e. ,in, This represents the minimum pressure value in the flow field. Given the saturated vapor pressure, based on this definition, The area is identified as a low-pressure zone, which is the primary location for the initial formation of cavitation.

[0103] S6: Based on the analysis results of the entropy-pressure synergy criterion, optimize the high-entropy yield region and the low-pressure region, using the total gas volume in the flow field as the calculation basis, until the cavitation suppression coefficient is greater than or equal to the set threshold; this step includes the following sub-steps, the specific process is as follows: Figure 8 As shown:

[0104] S61: Calculate the total volume of the first gas phase in the flow field mesh model before optimization;

[0105] Specifically, by using the Calculator function in Tecplot, specifically the FunctionCalculator, the total gas volume in the flow field region is calculated to obtain the first total gas volume in the flow field mesh model before optimization. 2086.4mm 3 .

[0106] S62: Based on the analysis results of the entropy-pressure synergy criterion, the high-entropy yield region and the low-pressure region are optimized;

[0107] Specifically, structural optimization is performed on the identified key areas, including but not limited to modifying the sharp edge structure at the valve core throttling orifice into a rounded transition with a radius R = 0.5 mm, to improve streamlines, reduce eddies and local pressure losses, and increase the minimum pressure in the flow field. Additionally, a micro-dimple array (0.2 mm diameter, 0.1 mm depth, and 0.3 mm spacing) is created on the inner wall of the valve seat corresponding to the high-entropy productivity region to generate stable micro-vortices, thereby dispersing energy, reducing turbulent dissipation, and further reducing the high-entropy productivity region in the flow field. This optimization method effectively improves the streamline morphology, reduces local pressure losses, and effectively disperses energy.

[0108] S63: Calculate the total volume of the second gas phase in the optimized flow field mesh model;

[0109] Specifically, by using the Calculator function in Tecplot, specifically the FunctionCalculator, the total gas volume in the flow field region is calculated to obtain the second total gas volume in the optimized flow field mesh model. 1002.3mm 3 .

[0110] S64: Calculate the cavitation suppression coefficient based on the first gas phase total volume and the second gas phase total volume. If the cavitation suppression coefficient is greater than or equal to the set threshold, it is determined that the cavitation suppression meets the requirements and the process ends; otherwise, return to S62 to continue the iteration.

[0111] Specifically, based on the cavitation suppression coefficient definition:

[0112]

[0113] Easy to know The value ranges from 0 to 1, and When the threshold is close to 0, the cavitation suppression effect is poor; when it is equal to 1, the cavitation phenomenon in the flow field is completely suppressed. The threshold can be set according to actual needs. In this embodiment, a cavitation suppression coefficient is set. =0.5, meaning the cavitation suppression coefficient is calculated with the goal of suppressing half the cavitation volume in the flow field. =0.52, which is greater than the currently set cavitation suppression coefficient. Therefore, the suppression of cavitation in the current valve meets the requirements, and the optimization process ends.

[0114] This method, combining structural optimization with quantitative assessment, can identify the initial risk region of cavitation from the perspective of thermodynamic potential energy, and locate the core area of ​​energy loss from the perspective of energy conversion. This dual-criteria system overcomes the limitations of single-parameter analysis, providing both early warning of cavitation initiation and assessment of cavitation intensity. It offers a clear optimization target area and theoretical basis for cavitation suppression, forming a complete closed-loop optimization process, and significantly improving the accuracy of cavitation prediction and optimization effect of valves under high-temperature conditions.

[0115] As can be seen from the above embodiments, this application completely solves the technical problem of predicting cavitation phenomena in valves under high-temperature conditions such as metallurgy through innovative methods such as cavitation model correction, and achieves significant cavitation suppression effects through targeted optimization based on the analysis results of the entropy-pressure synergy criterion. Specifically, after modeling the valve under actual working conditions, numerical simulation is used to obtain the total gas volume in the flow field, as well as the pressure cloud map and entropy production rate distribution cloud map. Based on the entropy-pressure synergy criterion, the flow field is analyzed to accurately locate the high entropy production region and low pressure region in the valve. Based on this, targeted structural optimization design is implemented, and the optimal structure is determined by simulation verification of the structurally optimized valve, thereby achieving effective suppression of cavitation phenomena.

[0116] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0117] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for predicting and suppressing valve cavitation under high-temperature operating conditions, characterized in that, include: S1: Construct the flow field model of the valve; S2: The flow field model is meshed and refined to obtain a flow field mesh model; S3: Perform simulation calculations on the flow field mesh model to obtain simulation results. The simulation requires setting up a turbulence model, an interface capturing model, and a cavitation model, as well as adjusting the boundary conditions and working fluid properties according to the actual working conditions. The interface capturing model, cavitation model, and working fluid properties are also corrected for temperature changes under high-temperature conditions. S4: Process the simulation results to obtain the total gas volume in the flow field, as well as the pressure cloud map and the entropy yield distribution cloud map. S5: The pressure cloud map and entropy yield distribution cloud map of the flow field are analyzed using the entropy-pressure synergy criterion to evaluate the cavitation phenomenon. The entropy-pressure synergy criterion divides the cavitation region into high, medium, and low entropy yield regions based on the ratio of local entropy yield to peak entropy yield in the entropy yield distribution cloud map. At the same time, a pressure safety margin is introduced, which is defined as the ratio of the minimum pressure of the flow field to the saturated vapor pressure of the working fluid at the current temperature. The region in the pressure cloud map with a pressure safety margin of less than 1 is defined as the low-pressure region where cavitation begins. S6: Based on the analysis results of the entropy-pressure synergy criterion, the high-entropy yield region and the low-pressure region in the valve flow channel are optimized, using the total volume of the gas phase in the flow field as the calculation basis, until the cavitation suppression coefficient is greater than or equal to the set threshold.

2. The method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1, characterized in that, Constructing the flow field model of the valve includes: Based on the valve's structural parameters, a 3D modeling software is used to create a model. Boolean operations, volume extraction, or filling methods are then used to process the valve's geometric model to obtain the valve's flow field model.

3. The method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1, characterized in that, The flow field model is meshed and refined to obtain a flow field mesh model, including: The flow field model is initially meshed, and then the mesh near the valve throttle orifice or the throat of the flow channel is locally refined; based on this, the locally refined mesh model is globally refined to generate the flow field mesh model.

4. The method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1, characterized in that, The modifications to the interface capture model include: Taking into account the influence of surface tension on the evolution of the cavitation interface, the surface tension effect is equivalent to a volume force source term acting on the momentum equation. The definition is as follows: ； In the formula, The surface tension coefficient of the working fluid; For interface curvature; The phase fraction gradient; The surface tension coefficient of the working fluid Due to temperature variations, the following correction formula should be used for calculation: ； In the formula, 𝜎0 is the surface tension coefficient at the reference temperature; is the temperature coefficient of surface tension; T0 is the selected reference temperature; T is the temperature.

5. The method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1, characterized in that, The modifications to the cavitation model include: To characterize the temperature dependence of saturated vapor pressure, the saturated vapor pressures involved in the evaporation and condensation source terms in the cavitation model are corrected using the following functional relationship: ； In the formula, Where is the saturated vapor pressure; T is the temperature; A, B, and C are constants that are related to the saturated vapor pressure and temperature of the working fluid.

6. The method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1, characterized in that, The corrections to the working fluid's physical properties include: When setting the physical properties of the working fluid, the influence of its viscosity on cavitation phenomena as a function of temperature must be considered. To accurately characterize this dependence, the following formula is used to correct the dynamic viscosity of the working fluid at different temperatures: ； In the formula, denoted as νk, where νk is the dynamic viscosity of the working fluid; T is the temperature; and a and b are constants.

7. The method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1, characterized in that, Based on the analysis results of the entropy-pressure synergy criterion, optimization is performed on the high-entropy yield region and the low-pressure region, using the total gas volume in the flow field as the calculation basis, until the cavitation suppression coefficient is greater than or equal to a set threshold, including: S61: Calculate the total volume of the first gas phase in the flow field mesh model before optimization; S62: Based on the analysis results of the entropy-pressure synergy criterion, the high-entropy yield region and the low-pressure region are optimized; S63: Calculate the total volume of the second gas phase in the optimized flow field mesh model; S64: Calculate the cavitation suppression coefficient based on the first gas phase total volume and the second gas phase total volume. If the cavitation suppression coefficient is greater than or equal to the set threshold, it is determined that the cavitation suppression meets the requirements and the process ends; otherwise, return to S62 to continue the iteration.

8. A method for predicting and suppressing valve cavitation under high-temperature conditions according to claim 1 or 7, characterized in that, The expression for the cavitation suppression coefficient is as follows: ； In the formula, This is the cavitation suppression coefficient; The first gas phase total volume in the flow field mesh model before optimization; This represents the total volume of the second gas phase in the optimized flow field mesh model.

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